Design, Synthesis, Characterization, And Applications Of Matrix Free Polymer Nanocomposites

This dissertation focuses on the design, synthesis, characterization and application of matrix free polymer nanocomposites. Reversible addition-fragmentation chain transfer (RAFT) polymerization was used to synthesize block copolymers and polymer grafted silica nanoparticles with precise control over architectures. In the first chapter, thermoplastic elastomer (TPE) grafted nanoparticles were prepared by grafting block copolymer poly(styrene-block-(n-butyl acrylate)) onto silica nanoparticles (NPs) (~15nm) via surface initiated RAFT polymerization. The effects of polymer chain length and graft density on the mechanical properties were investigated using films made solely from the grafted NPs. The ultimate tensile stress and elastic modulus increased with the increase of PS chain length. The dispersion of silica NPs and the microphase separation of block copolymers in the matrix-free polymer nanocomposite were investigated using small angle X-ray scattering (SAXS), transmission electron microscopy (TEM), differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA). The higher polymer graft density TPEs exhibited better microphase separation of block copolymers and more uniform silica NP dispersion than lower polymer graft density TPEs with similar polymer chain length and compositions. In the following chapter, we investigated the application of matrix-free polymer nanocomposites in the gas separation area. Polymer membranes have wide applications in gas separation. Poly(methyl acrylate) (PMA) and poly(methyl methacrylate) (PMMA) grafted silica NPs were synthesized by surface initiated RAFT polymerization. A versatile protocol was developed to remove ungrafted PMA from PMA grafted silica NPs from RAFT polymerization, which was implemented in place of a traditional ultracentrifuge procedure. The membranes from neat polymer grafted silica NPs exhibited an enhanced gas permeability over neat polymers, which was related to the increased free volume. The permeability can also be tuned by the grafted polymer molecular weight, which showed a “volcano plot” in permeability versus molecular weight. There was no aging effect on the membranes from polymer grafted NPs in the experimental measurement time line, which is important for practical applications in designing stable gas separation membranes. Finally, the synthesis and applications of matrix free polymer grafted silica nanoplatelets as photonic crystals were investigated. One-dimensional photonic crystals can be formed by self-assembly of block copolymers, which typically need large molecular weight polymers. A new strategy for two different photonic crystals was constructed with different solvent responses and reflecting colors from the films of a single block copolymer. Initially, films made from poly(3-(triethoxysilyl)propyl methacrylate)-block-poly(stearyl methacrylate) with moderate molecular weight (PTEPM666-b-PSMA553 film) were responsive to alcohol with an observed stop band change from 365 nm (dry film) to 458 nm (film in ethanol), displaying a blue color. After conversion of the PTEPM domain to form SiO2 nanoplatelets, the PSMA553-g-SiO2 nanoplatelet film showed a larger stop band change from 365 nm (dry film) to 591 nm (film in THF), which reflected a bright orange color

The Knowledge Graph for Macroeconomic Analysis with Alternative Big Data

The current knowledge system of macroeconomics is built on interactions among a small number of variables, since traditional macroeconomic models can mostly handle a handful of inputs. Recent work using big data suggests that a much larger number of variables are active in driving the dynamics of the aggregate economy. In this paper, we introduce a knowledge graph (KG) that consists of not only linkages between traditional economic variables but also new alternative big data variables. We extract these new variables and the linkages by applying advanced natural language processing (NLP) tools on the massive textual data of academic literature and research reports. As an example of potential applications, we use it as the prior knowledge to select variables for economic forecasting models in macroeconomics. Compared to statistical variable selection methods, KG-based methods achieve significantly higher forecasting accuracy, especially for long run forecasts

Worse outcome in breast cancer with higher tumor-infiltrating FOXP3+ Tregs : a systematic review and meta-analysis

Table S1. Characteristics of the included studies. (DOCX 39 kb

DASTSiam: Spatio-Temporal Fusion and Discriminative Augmentation for Improved Siamese Tracking

Tracking tasks based on deep neural networks have greatly improved with the emergence of Siamese trackers. However, the appearance of targets often changes during tracking, which can reduce the robustness of the tracker when facing challenges such as aspect ratio change, occlusion, and scale variation. In addition, cluttered backgrounds can lead to multiple high response points in the response map, leading to incorrect target positioning. In this paper, we introduce two transformer-based modules to improve Siamese tracking called DASTSiam: the spatio-temporal (ST) fusion module and the Discriminative Augmentation (DA) module. The ST module uses cross-attention based accumulation of historical cues to improve robustness against object appearance changes, while the DA module associates semantic information between the template and search region to improve target discrimination. Moreover, Modifying the label assignment of anchors also improves the reliability of the object location. Our modules can be used with all Siamese trackers and show improved performance on several public datasets through comparative and ablation experiments

Monotonic Neural Ordinary Differential Equation: Time-series Forecasting for Cumulative Data

Time-Series Forecasting based on Cumulative Data (TSFCD) is a crucial problem in decision-making across various industrial scenarios. However, existing time-series forecasting methods often overlook two important characteristics of cumulative data, namely monotonicity and irregularity, which limit their practical applicability. To address this limitation, we propose a principled approach called Monotonic neural Ordinary Differential Equation (MODE) within the framework of neural ordinary differential equations. By leveraging MODE, we are able to effectively capture and represent the monotonicity and irregularity in practical cumulative data. Through extensive experiments conducted in a bonus allocation scenario, we demonstrate that MODE outperforms state-of-the-art methods, showcasing its ability to handle both monotonicity and irregularity in cumulative data and delivering superior forecasting performance.Comment: Accepted as CIKM'23 Applied Research Trac

COMPARISON AND ANALYSIS OF APPLICATION EFFECT OF TRADITIONAL PAPER OPERATION METHOD AND DIGITAL INFORMATION SYSTEM IN HEMODIALYSIS

Objective To investigate the effect of traditional paper operation methods and digital information systems on improving clinical work efficiency. Methodology A number of clinical controlled studies and questionnaire surveys were conducted to evaluate the operation of the hemodialysis information electronic management system, its impact on dialysis work efficiency and dialysis quality, and the satisfaction of doctors and patients, and achieved hemodialysis centers. Electronic information management can save costs and control operating expenses while liberating people and improving work efficiency. Results The information electronic management system helps improve the safety of hemodialysis treatment. With the use of electronic information management, the integrity of the records of hemodialysis medical records has been significantly improved, and the authenticity has been better guaranteed. The implementation rate of doctor’s orders reaches 100%, and medical errors are reduced, making it easier for traceability and quality control. Conclusion The use of digital information system in hemodialysis can improve the work quality and work efficiency of the hemodialysis room and improve the satisfaction of doctors and patients as a whole. Therefore, digital information systems have positive application value in hemodialysis

Prompt Pool based Class-Incremental Continual Learning for Dialog State Tracking

Continual learning is crucial for dialog state tracking (DST) in dialog systems, since requirements from users for new functionalities are often encountered. However, most of existing continual learning methods for DST require task identities during testing, which is a severe limit in real-world applications. In this paper, we aim to address continual learning of DST in the class-incremental scenario (namely the task identity is unknown in testing). Inspired by the recently emerging prompt tuning method that performs well on dialog systems, we propose to use the prompt pool method, where we maintain a pool of key-value paired prompts and select prompts from the pool according to the distance between the dialog history and the prompt keys. The proposed method can automatically identify tasks and select appropriate prompts during testing. We conduct experiments on Schema-Guided Dialog dataset (SGD) and another dataset collected from a real-world dialog application. Experiment results show that the prompt pool method achieves much higher joint goal accuracy than the baseline. After combining with a rehearsal buffer, the model performance can be further improved

Research on Design Method of Long-life Asphalt Pavement

In recent years, the problem of early damage of asphalt pavement has been basically solved, and the service performance has been improved, but there are still some deficiencies in design life and service life. This paper investigates the long-life asphalt pavement structure, analyzes the design method of asphalt mixture, and summarizes the pavement design theory and related software. The long-life asphalt pavement with semi-rigid base, flexible base and combined base structure has been designed by four method, including typical load, Per-Road, D50-2006 and D50-2017. Four methods were compared by designing long-life pavements with semi-rigid base and flexible base. The results show that the proposed asphalt pavement structure can meet the requirements of Per-Road, typical load design and D50-2006. However, D50-2017 has higher requirements for the bending and tensile fatigue life of the base layer and requires a thicker base layer. When d50-2017 is used to design flexible base pavement, the fatigue life of asphalt layer should be the main control index, and the fatigue life of sub base course should be the main control index in other pavement de-sign. It remains to be seen whether the proposed highway structure can achieve the design goal of long-life asphalt pavement