Impact of Sanctions on Russian and Chinese Stock Markets : An empirical analysis based on stock data

An ongoing war in Ukraine turned out to be the biggest event of 2022. Allied nations decisively imposed series of sanctions that sent Russian economy into a turmoil. As shock and awe of the first weeks of invasions dissipated, academia began to get supplemented by new views and ideas of scholars on the consequences and prospects of war. In this paper we provide a fresh outlook on sanctions by analyzing stock prices in Russia and China. Stock prices provide multiple storylines, and thus our analysis covers topics like insider trading, medium-term outcome, market rebound and covert trades. To examine consequences of sanctions on Russia we utilized a multi-layered approach by looking into logarithmic returns, correlations, and betas of companies. We discovered compelling results that informed that Russian companies incurred severe losses, were not involved in insider trading and were the only ones that rebound in the short aftermath of war. To examine behaviour of stocks in China we applied the event study method and difference in difference empirical analysis method. Results showed that China as a neutral country is less affected by the sanctions. However, some Chinese companies benefited due to the shift of Russian economic transactions from Europe to Asia.nhhma

A Literature Review of Fault Diagnosis Based on Ensemble Learning

The accuracy of fault diagnosis is an important indicator to ensure the reliability of key equipment systems. Ensemble learning integrates different weak learning methods to obtain stronger learning and has achieved remarkable results in the field of fault diagnosis. This paper reviews the recent research on ensemble learning from both technical and field application perspectives. The paper summarizes 87 journals in recent web of science and other academic resources, with a total of 209 papers. It summarizes 78 different ensemble learning based fault diagnosis methods, involving 18 public datasets and more than 20 different equipment systems. In detail, the paper summarizes the accuracy rates, fault classification types, fault datasets, used data signals, learners (traditional machine learning or deep learning-based learners), ensemble learning methods (bagging, boosting, stacking and other ensemble models) of these fault diagnosis models. The paper uses accuracy of fault diagnosis as the main evaluation metrics supplemented by generalization and imbalanced data processing ability to evaluate the performance of those ensemble learning methods. The discussion and evaluation of these methods lead to valuable research references in identifying and developing appropriate intelligent fault diagnosis models for various equipment. This paper also discusses and explores the technical challenges, lessons learned from the review and future development directions in the field of ensemble learning based fault diagnosis and intelligent maintenance

Genetic Variants on Chromosome 8q24 and Colorectal Neoplasia Risk: A Case-Control Study in China and a Meta-Analysis of the Published Literature

Previous studies have found that common genetic variants on chromosome 8q24 are associated with the risk of developing colorectal neoplasia. We conducted a hospital-based case-control study, including 435 cases and 788 unrelated controls to investigate the associations between common variants on 8q24 and the risk of colorectal cancer in a Chinese population. We also evaluated the association of rs6983267 with colorectal neoplasia in the published literature via a meta-analysis study. We found that rs6983267 was significantly associated with the risk of colorectal cancer in the Chinese population, with an adjusted odds-ratio (OR) for the GT heterozygotes and GG homozygotes of 1.30 (95% CI  = 0.98–1.71, P = 0.069) and 1.66 (95% CI  = 1.18–2.34, P = 0.004), respectively, compared to the TT homozygotes, with a P-trend value of 0.003. No association was found for the other three loci (rs16901979, rs1447295 and rs7837688). In the meta-analysis of the published genetic association studies, the rs6983267 variant was found to be associated with an increased risk of colorectal neoplasia. The heterozygous GT carriers showed a 20% increased risk of colorectal neoplasia (OR  = 1.20, 95% CI  = 1.16–1.25; random effects model) with a summary OR for homozygous GG carriers of 1.39 (95% CI  = 1.32–1.48; random effects model) compared to the TT genotype carriers. We found no significant differences between the association of rs6983267 and colorectal cancer and colorectal adenomas. In summary, our study confirms that the variant rs6983267 is a risk factor for colorectal neoplasia in various populations, including the Chinese population

3D Face Reconstruction from Light Field Images: A Model-free Approach

Reconstructing 3D facial geometry from a single RGB image has recently instigated wide research interest. However, it is still an ill-posed problem and most methods rely on prior models hence undermining the accuracy of the recovered 3D faces. In this paper, we exploit the Epipolar Plane Images (EPI) obtained from light field cameras and learn CNN models that recover horizontal and vertical 3D facial curves from the respective horizontal and vertical EPIs. Our 3D face reconstruction network (FaceLFnet) comprises a densely connected architecture to learn accurate 3D facial curves from low resolution EPIs. To train the proposed FaceLFnets from scratch, we synthesize photo-realistic light field images from 3D facial scans. The curve by curve 3D face estimation approach allows the networks to learn from only 14K images of 80 identities, which still comprises over 11 Million EPIs/curves. The estimated facial curves are merged into a single pointcloud to which a surface is fitted to get the final 3D face. Our method is model-free, requires only a few training samples to learn FaceLFnet and can reconstruct 3D faces with high accuracy from single light field images under varying poses, expressions and lighting conditions. Comparison on the BU-3DFE and BU-4DFE datasets show that our method reduces reconstruction errors by over 20% compared to recent state of the art

Vascular endothelial growth factor C promotes cervical cancer metastasis via up-regulation and activation of RhoA/ROCK-2/moesin cascade

<p>Abstract</p> <p>Background</p> <p>The elevated expression of vascular endothelial growth factor C (VEGF-C) is correlated with clinical cervical cancer metastasis and patient survival, which is interpreted by VEGF-C functions to stimulate angiogenesis and lymphatic genesis. However, the direct impact of VEGF-C on cervical cancer cell motility remains largely unknown.</p> <p>Methods</p> <p>In this study, we investigated the effects of VEGF-C on actin cytoskeleton remodeling and on cervical cancer cell migration and invasion and how the actin-regulatory protein, moesin regulated these effects through RhoA/ROCK-2 signaling pathway.</p> <p>Results</p> <p>On cervical carcinoma cell line SiHa cells, exposure of VEGF-C triggered remodeling of the actin cytoskeleton and the formation of membrane ruffles, which was required for cell movement. VEGF-C significantly enhanced SiHa cells horizontal migration and three-dimensional invasion into matrices. These actions were dependent on increased expression and phosphorylation of the actin-regulatory protein moesin and specific moesin siRNA severely impaired VEGF-C stimulated-cell migration. The extracellular small GTPase RhoA/ROCK-2 cascade mediated the increased moesin expression and phosphorylation, which was discovered by the use of Y-27632, a specific inhibitor of Rho kinase and by transfected constitutively active, dominant-negative RhoA as well as ROCK-2 SiRNA. Furthermore, in the surgical cervical specimen from the patients with FIGO stage at cervical intra-epithelial neoplasia and I-II cervical squamous cell carcinoma, the expression levels of moesin were found to be significantly correlated with tumor malignancy and metastasis.</p> <p>Conclusions</p> <p>These results implied that VEGF-C promoted cervical cancer metastasis by upregulation and activation of moesin protein through RhoA/ROCK-2 pathway. Our findings offer new insight into the role of VEGF-C on cervical cancer progression and may provide potential targets for cervical cancer therapy.</p

A dissection of SARS‑CoV2 with clinical implications (Review)

We are being confronted with the most consequential pandemic since the Spanish flu of 1918‑1920 to the extent that never before have 4 billion people quarantined simultaneously; to address this global challenge we bring to the forefront the options for medical treatment and summarize SARS‑CoV2 structure and functions, immune responses and known treatments. Based on literature and our own experience we propose new interventions, including the use of amiodarone, simvastatin, pioglitazone and curcumin. In mild infections (sore throat, cough) we advocate prompt local treatment for the naso‑pharynx (inhalations; aerosols; nebulizers); for moderate to severe infections we propose a tried‑and‑true treatment: the combination of arginine and ascorbate, administered orally or intravenously. The material is organized in three sections: i) Clinical aspects of COVID‑19; acute respiratory distress syndrome (ARDS); known treatments; ii) Structure and functions of SARS‑CoV2 and proposed antiviral drugs; iii) The combination of arginine‑ascorbate