Study on Axial Compression Stability of Q345 Large-Section Angle Steel Columns

With the growing demand for the bearing capacity of columns, large-section angle steel (LAS) columns have been widely adopted. Q345 is the most commonly used steel, but research on the axial compression stability of LAS columns mainly focuses on steels with 420 MPa and above. In order to study the buckling behavior of Q345 LAS columns, a total of 96 specimens are subjected to axial compression tests. The test results are compared with the specification and analyzed. Based on test data, an accurate finite element model of the Q345 LAS column is established, and the parametric analysis is carried out through the model. The results show that the buckling mode of Q345 LAS columns is flexural buckling, and local buckling is not observed. The axial compression stability coefficient of Q345 LAS short columns is significantly higher than the result of the specification. The reasons come from the constitutive model and the buckling mode, and the influence of section size can be ignored. The curve a in GB50017-2017 and Eurocode 3 can be used to calculate the axial compression stability of Q345 LAS columns. Finally, a new column curve is proposed to calculate the axial compression stability of Q345 LAS columns

Harnessing jump component for crude oil volatility forecasting in the presence of extreme shocks

Oil markets are subject to extreme shocks (e.g. Iraq’s invasion of Kuwait), causing the oil market price exhibits extreme movements, called jumps (or spikes). These jumps pose challenges on oil market volatility forecasting using conventional volatility dynamic models (e.g. GARCH model). This paper characterizes dynamics of jumps in oil market price using high frequency data from three perspectives: the probability (or intensity) of jump occurrence, the sign (e.g. positive or negative) of jumps, and the concurrence with stock market jumps. And then, the paper exploits predictive ability of these jump-related information for oil market volatility forecasting under the mixed data sampling (MIDAS) modeling framework. Our empirical results show that augmenting standard MIDAS model using the three jump-related information significantly improves the accuracy of oil market volatility forecasting. The jump intensity and negative jump size are particularly useful for predicting future oil volatility. These results are widely consistent across a variety of robustness tests. This work provides new insights on how to forecast oil market volatility in the presence of extreme shocks

A two degree-of-freedom rotary-linear machine with transverse-flux structure

This paper proposes a two-degree-of-freedom rotary-linear machine with transverse-flux structure. In the proposed machine, the rotary flux and linear flux are naturally decoupled, hence its linear force and rotary torque can be controlled independently. Unlike the conventional rotary-linear machines with 3D-flux pattern, the proposed machine with transverse-flux structure can employ circumferentially laminated steel sheets to provide outstanding electromagnetic performance. The topology and operation principle of the proposed machine are introduced, while the naturally decoupled-flux feature is explained by analytical modelling and 3D finite-element method. A parametric study of pole-pair numbers combination is conducted to obtain the optimal pole-pair numbers in both axial and circumferential directions. The optimal electromagnetic performances are quantitatively compared with other two conventional rotary-linear machines, while an experimental prototype is manufactured to verify the proposed concepts.Ministry of Education (MOE)National Research Foundation (NRF)Submitted/Accepted versionThis work was supported by National Research Foundation (NRF) Singapore under its NRF Fellowship Grant NRF-NRFF12-2020-0003, and the Ministry of Education, Singapore, under its Academic Research Fund (AcRF) Tier 1 Program under Grant 2019-T1-002-064

Analysis of contra-rotating brushless integrated flux-modulation machine with open-slot structure for wind power generation

This paper presents a contra-rotating (CR) brushless integrated flux-modulation (BIFM) machine with open-slot structure for wind power generation, termed CR-BIFM machine. The presented machine employs two contra-rotating rotors coupled with two sets of wind turbine blades, thus being able to capture more wind energy than conventional single-rotor wind turbines. Due to the dual flux-modulation effect and flux-bridge effect, the presented machine exhibits high torque/power density, making it suitable for direct-drive wind power generation without issues related to mechanical gearboxes. As two sets of windings share the same stator slots in the presented machine, the decoupling design of windings is systematically investigated from the perspective of air-gap modulated magnetic field, considering the influence of both stator and rotors. The advantages of the presented machine are comprehensively evaluated compared to the baseline machine, showing that the presented machine exhibits higher torque/power density, higher efficiency, higher power factor, higher PM utilization, and better vibration performance. Finally, a prototype is fabricated and tested to validate the analysis.National Research Foundation (NRF)Submitted/Accepted versionThis work was supported by the National Research Foundation (NRF) Singapore under its NRF Fellowship Grant NRF-NRFF12-2020-0003

Chemical composition and biological activities of the essential oil from <i>Rubus pungens</i> var. <i>oldhamii</i>

<p>This paper presents a study on chemical composition, antimicrobial, antioxidant and tyrosinase inhibitory properties of the essential oil from leaves of <i>Rubus pungens</i> var. <i>oldhamii</i> (REO). The major component of the REO is sesquiterpenes (36.04%), which consists of 1,5-Cyclooctadiene,3-(1-me thylallyl)-(8CI)(17.66%), 5,6-Diethenyl-1-methylcyclohexene (12%), (+) – γ-Elemene (10.48%) and β-Caryophyllene (8.39%).The REO is shown to be moderately active against <i>Staphylococcus</i> <i>aureus,</i> <i>Aspergillus</i> <i>niger</i> and <i>Penicillium</i> <i>glaucum</i>, and has weak antioxidant activity in 1,1-diphenyl-2-picrylhydrazyl (DPPH) assay. Furthermore, tyrosinase inhibition was investigated against monophenolase (L-tyrosine). IC₅₀ values of REO and arbutin were found 0.923 and 0.657 mg/mL, respectively. The REO exerted potential antityrosinase activity. Our test results indicated that the REO was rich in sesquiterpenes, and also exhibited good antityrosinase activity, and moderate antimicrobial activity against pathogenic micro-organisms. The REO can be used as a natural source of promising antimicrobial and tyrosinase inhibiting agent.</p

Learning In-context Learning for Named Entity Recognition

Named entity recognition in real-world applications suffers from the diversity of entity types, the emergence of new entity types, and the lack of high-quality annotations. To address the above problems, this paper proposes an in-context learning-based NER approach, which can effectively inject in-context NER ability into PLMs and recognize entities of novel types on-the-fly using only a few demonstrative instances. Specifically, we model PLMs as a meta-function $\mathcal{ \lambda_ {\text{instruction, demonstrations, text}}. M}$, and a new entity extractor can be implicitly constructed by applying new instruction and demonstrations to PLMs, i.e., $\mathcal{ (\lambda . M) }$(instruction, demonstrations) $\to$ $\mathcal{F}$ where $\mathcal{F}$ will be a new entity extractor, i.e., $\mathcal{F}$: text $\to$ entities. To inject the above in-context NER ability into PLMs, we propose a meta-function pre-training algorithm, which pre-trains PLMs by comparing the (instruction, demonstration)-initialized extractor with a surrogate golden extractor. Experimental results on 4 few-shot NER datasets show that our method can effectively inject in-context NER ability into PLMs and significantly outperforms the PLMs+fine-tuning counterparts.Comment: Accepted to ACL 2023 Main Conferenc

BMP4 promotes hepatocellular carcinoma proliferation by autophagy activation through JNK1-mediated Bcl-2 phosphorylation

Abstract Background Autophagy is a conserved catabolic process with complicated roles in tumor development. Bone morphogenetic protein 4 (BMP4), a member of the transforming growth factor (TGF-β) family of regulatory proteins, plays a crucial role in human malignancies. However, whether BMP4 contributes to the regulation of autophagy in hepatocellular carcinoma (HCC) progression remains elusive. Methods Functional analysis of BMP4 on HCC proliferation and autophagy was performed both in vitro and in vivo in HepG2 and HCCLM3 cells. Autophagic activity was estimated by Western blot for autophagic marker proteins and by transmission electron microscopy (TEM). Transfection of mRFP-GFP-LC3 adenovirus was applied to observe autophagic flux and high content screening was used for quantification. The signaling pathway of BMP4-regulated HCC proliferation and autophagy was investigated by Western blot. Results BMP4 treatment promoted HCC cells proliferation and induced autophagy. The in vivo xenograft model supported that BMP4 overexpression promoted the growth of HCC cells and autophagy induction while BMP4 knockdown exerted the opposite effect. 3-MA pre-treatment or knockdown of Beclin-1 (BECN1) blocked HCC autophagy by decreasing the expression of LC3-II and subsequently attenuated BMP4-induced autophagy and cells proliferation enhanced by BMP4 in vitro and in vivo. Mechanistic study revealed that the induction of autophagy by BMP4 was mediated through activating the JNK1/Bcl2 pathway. Furthermore, the JNK1 inhibitor and knockdown of JNK1 could attenuate autophagy induced by BMP4 and eliminated BMP4-promoted HCC cells growth. Conclusions BMP4 promoted HCC proliferation by autophagy activation through JNK1/Bcl-2 signaling