Private Art Museum backed by Hong Kong Invetment - Wan Fung Art Musem as an Example

The rapid development of private art museums in the world can be regarded as the epitome of global economic development. The Chinese government has given unprecedented support to the development of culture and art. As the world\u27s second largest economy, China\u27s middle class has been increasing year by year. The hot art market has attracted European and American auction giants, and famous galleries have entered the Chinese market. Since the birth of the first private art museum in China at the end of the 20th century, Chinese scholars have been constantly exploring the direction of development. From copying the European and American models in the past to independent innovation now, the operation mode of China\u27s private art museum has become more and more diversified. Wan Fung Art Museum backed by Hong Kong Investment is such an innovator. This paper is an essay about Wan Fung Art Museum backed by Hong Kong Investment operations exploratory, primarily through the discussion on the mode of private art museum backed by Hong Kong Investment. the concrete analysis in Wan Fung Art Museum, for example, comparing with other Chinese Private Art Museums, found that at present the plight of, combing the existing model, attempts to give a solution. Finally, the operation mode of Private Art Museum backed by Hong Kong Investment is confirmed: At the same time, we see the feasibility and development direction from practice. This paper is a supplement and improvement to the research of China\u27s existing art museums, which is helpful for scholars to further study

Coordinated Multipoint Communications In Heterogeneous Networks

As users' demands on cellular service escalate rapidly, operators are required to deploy technologies with wider and more sophisticated techniques. In order to meet the future service needs, the standardization body 3rd Generation Partnership Project (3GPP) has standardized Long Term Evolution (LTE) and it has been working on enhancement of LTE and LTE-Advanced. The two key enabling technologies of LTE-Advanced are Heterogeneous Networks (HetNets) and Coordinated Multipoint (CoMP) communications. The former is aimed to improve inconsistent user experience and its basic feature is standardized in 3GPP release 11. The latter one where small cells are deployed within macro-cellular networks has been considered to enhance coverage and capacity. This thesis presents a concise literature survey of cooperative communications and CoMP technologies. Furthermore, a detailed Matlab-based simulation study on CoMP between macro and small cells in HetNets is presented. Comparative analyses and evaluations are also made for different CoMP schemes under different deployed scenarios. At the same time, a new CoMP UE selection criterion is proposed to fit the modified round robin scheduling deployed in simulation and optimize the resource allocation among CoMP and non-CoMP UEs

Keypoint-GraspNet: Keypoint-based 6-DoF Grasp Generation from the Monocular RGB-D input

Great success has been achieved in the 6-DoF grasp learning from the point cloud input, yet the computational cost due to the point set orderlessness remains a concern. Alternatively, we explore the grasp generation from the RGB-D input in this paper. The proposed solution, Keypoint-GraspNet, detects the projection of the gripper keypoints in the image space and then recover the SE(3) poses with a PnP algorithm. A synthetic dataset based on the primitive shape and the grasp family is constructed to examine our idea. Metric-based evaluation reveals that our method outperforms the baselines in terms of the grasp proposal accuracy, diversity, and the time cost. Finally, robot experiments show high success rate, demonstrating the potential of the idea in the real-world applications.Comment: Submitted to ICRA202

WDiscOOD: Out-of-Distribution Detection via Whitened Linear Discriminant Analysis

Deep neural networks are susceptible to generating overconfident yet erroneous predictions when presented with data beyond known concepts. This challenge underscores the importance of detecting out-of-distribution (OOD) samples in the open world. In this work, we propose a novel feature-space OOD detection score based on class-specific and class-agnostic information. Specifically, the approach utilizes Whitened Linear Discriminant Analysis to project features into two subspaces - the discriminative and residual subspaces - for which the in-distribution (ID) classes are maximally separated and closely clustered, respectively. The OOD score is then determined by combining the deviation from the input data to the ID pattern in both subspaces. The efficacy of our method, named WDiscOOD, is verified on the large-scale ImageNet-1k benchmark, with six OOD datasets that cover a variety of distribution shifts. WDiscOOD demonstrates superior performance on deep classifiers with diverse backbone architectures, including CNN and vision transformer. Furthermore, we also show that WDiscOOD more effectively detects novel concepts in representation spaces trained with contrastive objectives, including supervised contrastive loss and multi-modality contrastive loss.Comment: Accepted by ICCV 2023. Code is available at: https://github.com/ivalab/WDiscOOD.gi

Planning with Sequence Models through Iterative Energy Minimization

Recent works have shown that sequence modeling can be effectively used to train reinforcement learning (RL) policies. However, the success of applying existing sequence models to planning, in which we wish to obtain a trajectory of actions to reach some goal, is less straightforward. The typical autoregressive generation procedures of sequence models preclude sequential refinement of earlier steps, which limits the effectiveness of a predicted plan. In this paper, we suggest an approach towards integrating planning with sequence models based on the idea of iterative energy minimization, and illustrate how such a procedure leads to improved RL performance across different tasks. We train a masked language model to capture an implicit energy function over trajectories of actions, and formulate planning as finding a trajectory of actions with minimum energy. We illustrate how this procedure enables improved performance over recent approaches across BabyAI and Atari environments. We further demonstrate unique benefits of our iterative optimization procedure, involving new task generalization, test-time constraints adaptation, and the ability to compose plans together. Project website: https://hychen-naza.github.io/projects/LEAPComment: Accepted by ICLR2023. Project page: https://hychen-naza.github.io/projects/LEAP/index.htm

MicroRNA-298 Reverses Multidrug Resistance to Antiepileptic Drugs by Suppressing MDR1/P-gp Expression in vitro

P-glycoprotein (P-gp), a critical multidrug transporter, recognizes and transports various antiepileptic drugs (AEDs) through the blood-brain barrier (BBB). This may decrease the concentrations of AEDs in brain tissues and cause multidrug resistance (MDR) in patients with refractory epilepsy. Compelling evidence indicates that microRNAs (miRNAs) modulate MDR in various cancers by regulating P-gp expression. Furthermore, a previous study showed that miR-298 mediates MDR in breast cancer cells by downregulating P-gp expression. Based on the therapeutic results obtained from tumor cells, we aimed to determine whether miR-298 reverses MDR to AEDs by regulating P-gp expression in the BBB. We first established different drug-resistant cell lines, including PHT-resistant HBMECs (human brain microvascular endothelial cells) and doxorubicin (DOX)-resistant U87-MG (human malignant glioma) cells, by inducing P-gp overexpression. Quantitative real-time PCR (qRT-PCR) analysis revealed reduced expression of miR-298 in both HBMEC/PHT and U87-MG/DOX cells, and the luciferase reporter assay identified the direct binding of miR-298 to the 3′-untranslated region (3′-UTR) of P-gp. Moreover, ectopic expression of miR-298 downregulated P-gp expression at the mRNA and protein levels, thereby increasing the intracellular accumulation of AEDs in drug-resistant HBMEC/PHT and U87-MG/DOX cells. Thus, our findings suggest that miR-298 reverses MDR to AEDs by inhibiting P-gp expression, suggesting a potential target for overcoming MDR in refractory epilepsy

Urban waterlogging prediction and risk analysis based on rainfall time series features: A case study of Shenzhen

In recent years, the frequency of extreme weather has increased, and urban waterlogging caused by sudden rainfall has occurred from time to time. With the development of urbanization, a large amount of land has been developed and the proportion of impervious area has increased, intensifying the risk of urban waterlogging. How to use the available meteorological data for accurate prediction and early warning of waterlogging hazards has become a key issue in the field of disaster prevention and risk assessment. In this paper, based on historical meteorological data, we combine domain knowledge and model parameters to experimentally extract rainfall time series related features for future waterlogging depth prediction. A novel waterlogging depth prediction model that applies only rainfall data as input is proposed by machine learning algorithms. By analyzing a large amount of historical flooding monitoring data, a “rainfall-waterlogging amplification factor” based on the geographical features of monitoring stations is constructed to quantify the mapping relationship between rainfall and waterlogging depths at different locations. After the model is trained and corrected by the measured data, the prediction error for short-time rainfall basically reaches within 2 cm. This method improves prediction performance by a factor of 2.5–3 over featureless time series methods. It effectively overcomes the limitations of small coverage of monitoring stations and insufficient historical waterlogging data, and can achieve more accurate short-term waterlogging prediction. At the same time, it can provide reference suggestions for the government to conduct waterlogging risk analysis and add new sensor stations by counting the amplification factor of other locations

The Neuroprotective Effect of Astaxanthin on Pilocarpine-Induced Status Epilepticus in Rats

Cognitive dysfunction is one of the serious complications induced by status epilepticus (SE), which has a significant negative impact on patients’ quality of life. Previous studies demonstrated that the pathophysiological changes after SE such as oxidative stress, inflammatory reaction contribute to neuronal damage. A recent study indicated that preventive astaxanthin (AST) alleviated epilepsy-induced oxidative stress and neuronal apoptosis in the brain. In the present study, rats were treated with vehicle or AST 1 h after SE onset and were injected once every other day for 2 weeks (total of seven times). The results showed that the cognitive function in SE rats was significantly impaired, and AST treatment improved cognitive function in the Morris water maze (MWM). Magnetic resonance imaging (MRI), hematoxylin-eosin (HE) staining and TdT-mediated dUTP Nick-End Labeling (TUNEL) staining showed obvious damage in the hippocampus of SE rats, and AST alleviated the damage. Subsequently, we evaluated the effect of AST on relative pathophysiology to elucidate the possible mechanisms. To evaluate the oxidative stress, the expression of malondialdehyde (MDA) and superoxide dismutase (SOD) in plasma were detected using commercially available kits. NADPH oxidase-4 (Nox-4), p22phox, NF-E2-related factor 2 (Nrf-2), heme oxygenase 1 (Ho-1) and sod1 in the parahippocampal cortex and hippocampus were detected using western blot and real-time polymerase chain reaction (RT-PCR). The levels of MDA in plasma and Nox-4 and p22phox in the brain increased in SE rats, and the levels of SOD in plasma and Nrf-2, Ho-1 and sod1 in the brain decreased. Treatment with AST alleviated these changes. We also detected the levels of inflammatory mediators like cyclooxygenase-2 (cox-2), interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α) and NF-κB phosphorylation p65 (p-p65)/p65 in the brain. The inflammatory reaction was significantly activated in the brain of SE rats, and AST alleviated neuroinflammation. We detected the levels of p-Akt, Akt, B-cell lymphoma-2 (Bcl-2), Bax, cleaved caspase-3, and caspase-3 in the parahippocampal cortex and hippocampus using western blot. The levels of p-Akt/Akt and Bcl-2 decreased in SE rats, Bax and cleaved caspase-3/caspase-3 increased, while AST alleviated these changes. The present study indicated that AST exerted an reobvious neuroprotective effect in pilocarpine-induced SE rats