The Announcement Effect of Monetary Policy on the Corporate Bond Markets

This study investigates the impact of the central bank’s monetary policy announcements on the perceptions of yield spread in corporate bond markets under the event of extreme events. These results highlight that the coronavirus pandemic has caused a market panic in the global economy. This caused investors to withdraw their money from bond markets, which caused a liquidity crisis in bond markets. The Fed announcements caused statistically significant tightening on US and global investment grades and high-yield corporate bond spreads. The Euro investment grade and high-yield corporate bond spread narrowed when the Fed took additional actions to provide more funds and expanded the buying scope to support market liquidity. These results suggest that forward guidance that emphasizes the Fed’s monetary policy causes stronger information effects

Rapid Determination of Saponins in the Honey-Fried Processing of Rhizoma Cimicifugae by Near Infrared Diffuse Reflectance Spectroscopy.

ObjectiveA model of Near Infrared Diffuse Reflectance Spectroscopy (NIR-DRS) was established for the first time to determine the content of Shengmaxinside I in the honey-fried processing of Rhizoma Cimicifugae.MethodsShengmaxinside I content was determined by high-performance liquid chromatography (HPLC), and the data of the honey-fried processing of Rhizoma Cimicifugae samples from different batches of different origins by NIR-DRS were collected by TQ Analyst 8.0. Partial Least Squares (PLS) analysis was used to establish a near-infrared quantitative model.ResultsThe determination coefficient R² was 0.9878. The Cross-Validation Root Mean Square Error (RMSECV) was 0.0193%, validating the model with a validation set. The Root Mean Square Error of Prediction (RMSEP) was 0.1064%. The ratio of the standard deviation for the validation samples to the standard error of prediction (RPD) was 5.5130.ConclusionThis method is convenient and efficient, and the experimentally established model has good prediction ability, and can be used for the rapid determination of Shengmaxinside I content in the honey-fried processing of Rhizoma Cimicifugae

Dual-View Visual Contextualization for Web Navigation

Automatic web navigation aims to build a web agent that can follow language instructions to execute complex and diverse tasks on real-world websites. Existing work primarily takes HTML documents as input, which define the contents and action spaces (i.e., actionable elements and operations) of webpages. Nevertheless, HTML documents may not provide a clear task-related context for each element, making it hard to select the right (sequence of) actions. In this paper, we propose to contextualize HTML elements through their "dual views" in webpage screenshots: each HTML element has its corresponding bounding box and visual content in the screenshot. We build upon the insight -- web developers tend to arrange task-related elements nearby on webpages to enhance user experiences -- and propose to contextualize each element with its neighbor elements, using both textual and visual features. The resulting representations of HTML elements are more informative for the agent to take action. We validate our method on the recently released Mind2Web dataset, which features diverse navigation domains and tasks on real-world websites. Our method consistently outperforms the baseline in all the scenarios, including cross-task, cross-website, and cross-domain ones.Comment: Accepted to CVPR 202

MAAIG: Motion Analysis And Instruction Generation

Many people engage in self-directed sports training at home but lack the real-time guidance of professional coaches, making them susceptible to injuries or the development of incorrect habits. In this paper, we propose a novel application framework called MAAIG(Motion Analysis And Instruction Generation). It can generate embedding vectors for each frame based on user-provided sports action videos. These embedding vectors are associated with the 3D skeleton of each frame and are further input into a pretrained T5 model. Ultimately, our model utilizes this information to generate specific sports instructions. It has the capability to identify potential issues and provide real-time guidance in a manner akin to professional coaches, helping users improve their sports skills and avoid injuries.Comment: Accepted to the ACM Multimedia Asia 2023 Workshop on Intelligent Sports Technologies (WIST

Long Non Coding RNA MALAT1 Promotes Tumor Growth and Metastasis by Inducing Epithelial-Mesenchymal Transition in Oral Squamous Cell Carcinoma

The prognosis of advanced oral squamous cell carcinoma (OSCC) patients remains dismal, and a better understanding of the underlying mechanisms is critical for identifying effective targets with therapeutic potential to improve the survival of patients with OSCC. This study aims to clarify the clinical and biological significance of metastasis-associated long non-coding RNA, metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) in OSCC. We found that MALAT1 is overexpressed in OSCC tissues compared to normal oral mucosa by real-time PCR. MALAT1 served as a new prognostic factor in OSCC patients. When knockdown by small interfering RNA (siRNA) in OSCC cell lines TSCCA and Tca8113, MALAT1 was shown to be required for maintaining epithelial-mesenchymal transition (EMT) mediated cell migration and invasion. Western blot and immunofluorescence staining showed that MALAT1 knockdown significantly suppressed N-cadherin and Vimentin expression but induced E-cadherin expression in vitro. Meanwhile, both nucleus and cytoplasm levels of β-catenin and NF-κB were attenuated, while elevated MALAT1 level triggered the expression of β-catenin and NF-κB. More importantly, targeting MALAT1 inhibited TSCCA cell-induced xenograft tumor growth in vivo. Therefore, these findings provide mechanistic insight into the role of MALAT1 in regulating OSCC metastasis, suggesting that MALAT1 is an important prognostic factor and therapeutic target for OSCC

Reduction of Monocyte Chemoattractant Protein-1 and Interleukin-8 Levels by Ticlopidine in TNF-α Stimulated Human Umbilical Vein Endothelial Cells

Atherosclerosis and its associated complications represent major causes of morbidity and mortality in the industrialized or Western countries. Monocyte chemoattractant protein-1 (MCP-1) is critical for the initiating and developing of atherosclerotic lesions. Interleukin-8 (IL-8), a CXC chemokine, stimulates neutrophil chemotaxis. Ticlopidine is one of the antiplatelet drugs used to prevent thrombus formation relevant to the pathophysiology of atherothrombosis. In this study, we found that ticlopidine dose-dependently decreased the mRNA and protein levels of TNF-α-stimulated MCP-1, IL-8, and vascular cell adhesion molecule-1 (VCAM-1) in human umbilical vein endothelial cells (HUVECs). Ticlopidine declined U937 cells adhesion and chemotaxis as compared to TNF-α stimulated alone. Furthermore, the inhibitory effects were neither due to decreased HUVEC viability, nor through NF-kB inhibition. These results suggest that ticlopidine decreased TNF-α induced MCP-1, IL-8, and VCAM-1 levels in HUVECs, and monocyte adhesion. Therefore, the data provide additional therapeutic machinery of ticlopidine in treatment and prevention of atherosclerosis

Differential Expression and Functional Analysis of the Tristetraprolin Family during Early Differentiation of 3T3-L1 Preadipocytes

The tristetraprolin (TTP) family comprises zinc finger-containing AU-rich element (ARE)-binding proteins consisting of three major members: TTP, ZFP36L1, and ZFP36L2. The present study generated specific antibodies against each TTP member to evaluate its expression during differentiation of 3T3-L1 preadipocytes. In contrast to the inducible expression of TTP, results indicated constitutive expression of ZFP36L1 and ZFP36L2 in 3T3-L1 preadipocytes and their phosphorylation in response to differentiation signals. Physical RNA pull-down and functional luciferase assays revealed that ZFP36L1 and ZFP36L2 bound to the 3′ untranslated region (UTR) of MAPK phosphatase-1 (MKP-1) mRNA and downregulated Mkp-1 3′UTR-mediated luciferase activity. Mkp-1 is an immediate early gene for which the mRNA is transiently expressed in response to differentiation signals. The half-life of Mkp-1 mRNA was longer at 30 min of induction than at 1 h and 2 h of induction. Knockdown of TTP or ZFP36L2 increased the Mkp-1 mRNA half-life at 1 h of induction. Knockdown of ZFP36L1, but not ZFP36L2, increased Mkp-1 mRNA basal levels via mRNA stabilization and downregulated ERK activation. Differentiation induced phosphorylation of ZFP36L1 through ERK and AKT signals. Phosphorylated ZFP36L1 then interacted with 14-3-3, which might decrease its mRNA destabilizing activity. Inhibition of adipogenesis also occurred in ZFP36L1 and TTP knockdown cells. The findings indicate that the differential expression of TTP family members regulates immediate early gene expression and modulates adipogenesis

Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data

We propose a learning problem involving adapting a pre-trained source model to the target domain for classifying all classes that appeared in the source data, using target data that covers only a partial label space. This problem is practical, as it is unrealistic for the target end-users to collect data for all classes prior to adaptation. However, it has received limited attention in the literature. To shed light on this issue, we construct benchmark datasets and conduct extensive experiments to uncover the inherent challenges. We found a dilemma -- on the one hand, adapting to the new target domain is important to claim better performance; on the other hand, we observe that preserving the classification accuracy of classes missing in the target adaptation data is highly challenging, let alone improving them. To tackle this, we identify two key directions: 1) disentangling domain gradients from classification gradients, and 2) preserving class relationships. We present several effective solutions that maintain the accuracy of the missing classes and enhance the overall performance, establishing solid baselines for holistic transfer of pre-trained models with partial target data.Comment: Accepted to NeurIPS 2023 main trac

Adaptive OCR coordination in distribution system with distributed energy resources contribution

More and more distributed energy resources (DERs) are being added to the medium-voltage (MV) or low-voltage (LV) radial distribution networks (RDNs). These distributed power sources will cause the redistribution of power flow and fault current, bringing new challenges to the coordination of power system protection. An adaptive protection coordination strategy is proposed in this paper. It will trace the connectivity of the system structure to determine the set of relay numbers as a tracking path. According to the topology of the system structure, the tracking path can be divided into two categories: the main feeder path and the branch path. The time multiplier setting (TMS) of each relay can be used to evaluate the operation time of the over-current relay (OCR), and the operation time of the relay can be used to evaluate the fitness of the TMS setting combination. Furthermore, the relay protection coordination problem can be modeled to minimize the accumulated summation of all primary and backup relay operation time (OT) subject to the coordination time interval (CTI) limitation. A modified particle swarm optimization (MPSO) algorithm with adaptive self-cognition and society operation scheme (ASSOS) was proposed and utilized to determine TMS for each relay on the tracking path. A 16-bus test MV system with distributed generators (DGs) will be applied to test the adaptive protection coordination approach proposed in this paper. The results show that the proposed MPSO algorithm reduces the overall OT and relieves the impact on protection coordination settings after DG joins the system. The paper also tests and compares the proposed MPSO with other metaheuristic intelligence-based random search algorithms to prove that MPSO possesses with increased efficiency and performance