Evaluation of Volatility Models: Evidence from Chinese Equity Markets

This thesis aims to find the most appropriate model to estimate and forecast volatility in Chinese stock markets, and to investigate the differences between simple historical models and GARCH-type models. The studied model collection includes seven models: Random Walk, RiskMetrics EWMA, GARCH, GARCH-in-mean, EGARCH, TGARCH and APARCH. The forecast performances of those models are then evaluated in seven different criteria including symmetric loss functions and asymmetric loss functions. Other measurements such as the forecast encompassing test is conducted to check whether GARCH-type models carry additional information than simple historical models. The whole evaluation process is conducted with two Chinese stock markets’ indices, namely the SSE composite index and the SZSE component index. The selected sample period with updated data spans from 04 March 2006 through 30 December 2016. The empirical evidence shows that the Random Walk model has the worst performance among all studied models. Model Performance is highly sensitive to the choice of forecast error statistics. The asymmetric loss function suggests systematically over-prediction exists in the forecasts which might be caused by the choice of forecast period. GARCH models carry more information than the Random Walk model. But no significant evidence is found in this study to support that GARCH models carry additional information than the RiskMetrics EWMA model.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Design and optimization of an advanced time-of-flight neutron spectrometer for deuterium plasmas of the large helical device

A time-of-flight neutron spectrometer based on the Time-Of-Flight Enhanced Diagnostic (TOFED) concept has been designed and is under development for the Large Helical Device (LHD). It will be the first advanced neutron spectrometer to measure the 2.45 MeV D–D neutrons (DDNs) from helical/stellarator plasmas. The main mission of the new TOFED is to study the supra-thermal deuterons generated from the auxiliary heating systems in helical plasmas by measuring the time-of-flight spectra of DDN. It will also measure the triton burnup neutrons (TBNs) from the d+t reactions, unlike the original TOFED in the EAST tokamak. Its capability of diagnosing the TBN ratios is evaluated in this work. This new TOFED is expected to be installed in the basement under the LHD hall and shares the collimator with one channel of the vertical neutron camera to define its line of sight. The distance from its primary scintillators to the equatorial plane of LHD plasmas is about 15.5 m. Based on Monte Carlo simulation by a GEANT4 model, the resolution of the DDN energy spectra is 6.6%. When projected onto the neutron rates that are typically obtained in LHD deuterium plasmas (an order of 1015 n/s with neutral beam injection), we expect to obtain the DDN and TBN counting rates of about 2.5 · 105 counts/s and 250 counts/s, respectively. This will allow us to analyze the DDN time-of-flight spectra on time scales of 0.1 s and diagnose the TBN emission rates in several seconds with one instrument, for the first time in helical/stellarator plasmas

Enhanced Water Sorption Performance of Polyacrylamide & Glass Fiber Paper Composites: Investigation and Comparison of Application in Desiccant Wheels

The water sorption and desorption properties of solid adsorbent materials are crucial in rotary dehumidification systems. Metal organic frameworks (MOFs) and hydrogels are mostly at the laboratory stage due to factors like the synthesis process and yield. In this study, we utilized an eco-friendly and large-scale synthesis method to prepare polyacrylamide (PAM) hydrogels (yielding approximately 500 mL from a single polymerization). Subsequently, PAM was then coated onto glass fiber paper (GFP), which serves as a commonly employed substrate in desiccant wheels. By incorporating the hygroscopic salt LiCl and optimizing the content of each component, the water sorption performance of the composite was notably improved. The water sorption and desorption performances, as well as cycling stability, were evaluated and compared with composites containing aluminum fumarate, LiCl, and GFP (AlFum-LiCl&GFP). The results revealed that PAM-LiCl&GFP outperformed AlFum-LiCl&GFP in terms of sorption capacity throughout various relative humidity (RH) levels. It achieved a water uptake of 1.06 g·g−1 at 25 °C and 30% RH, corresponding to a water sorption rate coefficient K of 15.32 × 10−4 s−1. Furthermore, the lower desorption temperature (60 °C) resulting in a desorption ratio of 82.6%, along with the excellent cycling stability and effective performance as a desiccant wheel module, provide evidence for the potential application of PAM-LiCl&GFP in desiccant wheels

Optimizing Salt Leakage Mitigation and Comparing Sorption–Desorption Characteristics of Polyacrylamide-Based Hydrogels

Solid hygroscopic materials are extensively utilized in diverse fields, including adsorption heat transfer, adsorption heat storage, atmospheric water harvesting (AWH), and air conditioning dehumidification. The efficacy and energy efficiency of these materials in practical applications are significantly influenced by their adsorption and desorption properties. Yet, the introduction of inorganic salts to boost adsorption performance can result in issues like salt leakage. In this research, we prepared a polyacrylamide hydrogel through free radical polymerization, and its water-absorbing capabilities were improved by incorporating the hygroscopic salt lithium chloride. We compared it to a salt-based porous adsorbent, AlFum-LiCl, which also exhibited strong water adsorption properties and the potential for large-scale production. While AlFum-LiCl suffered from limited pores and salt leakage during high water uptake, the optimized PAM-LiCl displayed superior water sorption capabilities, showing no salt leakage even at water uptake of up to 3.5 g/g. At 25 °C, PAM-LiCl achieved equilibrium water uptake of 1.26 g/g at 30% RH and 3.15 g/g at 75% RH. In this context, utilizing 20 g of PAM-LiCl for the AWH experiment yielded daily water outputs of 8.34 L/kg at 30% RH and 16.86 L/kg at 75% RH. The salt-optimized PAM-LiCl hydrogel offers the benefit of application in higher relative humidity environments without the risk of deliquescence, underscoring its promise for atmospheric water harvesting

A Novel Framework for Multimodal Named Entity Recognition with Multi-level Alignments

Mining structured knowledge from tweets using named entity recognition (NER) can be beneficial for many downstream applications such as recommendation and intention under standing. With tweet posts tending to be multimodal, multimodal named entity recognition (MNER) has attracted more attention. In this paper, we propose a novel approach, which can dynamically align the image and text sequence and achieve the multi-level cross-modal learning to augment textual word representation for MNER improvement. To be specific, our framework can be split into three main stages: the first stage focuses on intra-modality representation learning to derive the implicit global and local knowledge of each modality, the second evaluates the relevance between the text and its accompanying image and integrates different grained visual information based on the relevance, the third enforces semantic refinement via iterative cross-modal interactions and co-attention. We conduct experiments on two open datasets, and the results and detailed analysis demonstrate the advantage of our model

An optical fiber-based data-driven method for human skin temperature 3-D mapping

Human skin temperature mapping provides abundant information of physiological conditions of human body, which provides supplementary or alternative indicators for disease monitoring or diagnosis. The existing models of temperature mapping or temperature field distribution of human skin are generally established by finite element method. Due to the complexity of biological systems, it is challenging to achieve high accuracy mathematical models of temperature field of human skin. The goal of this study is to establish human skin temperature three-dimensional (3-D) mapping platform by integrating optical fibers and improved genetic algorithm-back propagation (GA-BP) neural network. The proposed data-driven method is capable of acquiring entire human skin temperature 3-D mapping by simply measuring a few points on human skin. Multiple experiments were conducted to validate the proposed method on different areas of human skin in different ambient environments. In each experiment setting, the measured data and the model output data were compared. The mean absolute error in all the validation experiments is 0.11 °C, which is lower than that in the state of the art using physical modeling for skin temperature prediction and more close to clinical accuracy. The results show that the proposed approach is accurate and reliable, which may provide a platform technology for human skin temperature mapping that can be used in both medical and scientific studies as well as home monitoring

Evolution of CD8+ T Cell Receptor (TCR) Engineered Therapies for the Treatment of Cancer

Engineered T cell receptor T (TCR-T) cell therapy has facilitated the generation of increasingly reliable tumor antigen-specific adaptable cellular products for the treatment of human cancer. TCR-T cell therapies were initially focused on targeting shared tumor-associated peptide targets, including melanoma differentiation and cancer-testis antigens. With recent technological developments, it has become feasible to target neoantigens derived from tumor somatic mutations, which represents a highly personalized therapy, since most neoantigens are patient-specific and are rarely shared between patients. TCR-T therapies have been tested for clinical efficacy in treating solid tumors in many preclinical studies and clinical trials all over the world. However, the efficacy of TCR-T therapy for the treatment of solid tumors has been limited by a number of factors, including low TCR avidity, off-target toxicities, and target antigen loss leading to tumor escape. In this review, we discuss the process of deriving tumor antigen-specific TCRs, including the identification of appropriate tumor antigen targets, expansion of antigen-specific T cells, and TCR cloning and validation, including techniques and tools for TCR-T cell vector construction and expression. We highlight the achievements of recent clinical trials of engineered TCR-T cell therapies and discuss the current challenges and potential solutions for improving their safety and efficacy, insights that may help guide future TCR-T studies in cancer

Excitation of Surface Plasmon Resonance in Composite Structures Based on Single-Layer Superaligned Carbon Nanotube Films

Surface-enhanced Raman scattering (SERS) provides valuable information on the vibrational modes of molecules and the physical mechanism of surface plasmon resonance (SPR). In this paper we study the localized SPR process in Ag- or Ag/oxide-coated single-layer superaligned carbon nanotube (SACNT) films. Because of the unidirectional alignment of the carbon nanotubes in these films, the Raman signal is higher when the laser is polarized parallel to the aligned direction than when perpendicular to it. We investigated the polarization-dependent transmittance and Raman spectra for various Ag particle sizes and different oxide medium layers to study the localized SPR in these composite structures. These results systematically characterize the properties of SACNT film-based SERS substrates and clarify the origin of transmittance peaks