OBJECTIVE To assess the influence of genetic polymorphisms and non-genetic factors on warfarin maintenance dose variations in order to provide guidance for personalized use of warfarin. METHODS Two ...hundred patients from outpatient and inpatient with stable international normalized ratio(INR) were recruited. Clinical data and blood samples were collected. Genotypes of 4 genes involved in warfarin metabolic pathways were determined with Sanger sequencing. Based on statistical analysis of warfarin maintenance dosage, a mathematical model was established. RESULTS Among non-genetic factors, the age and height have significant influence in warfarin dosage. The dosage is negatively correlated with age but positively correlated with height. The difference in dosage for between the 20-year-old group and 60-year-old group has reached 1.81 mg/day, and that for between the 140 cm in height and 180 cm in height groups has reached 1.06 mg/day. VKORC1 -1639G/A, CYP2C9 430C/T, CYP2C9 1075A/C and CYP4F2 V433M polymorphisms ha
The absorption spectra of Tm3+:K2YF5 crystal was measured at room temperature (RT). Based on the Judd-Ofelt theory, the intensity parameters of Tm3+ in K2YF5 crystal were determined, Omega2 = 5.02 X ...10-20 cm2, Omega4 = 3.40 X 10-20 cm2 and Omega6 = 0.38 X 10-20 cm2, and then the values of the radiative transition probabilities, branching ratios, integrated emission cross-sections and radiative lifetimes of excited states of Tm3+ in K2YF5 crystal were calculated. The stimulated emission cross-sections were also evaluated for the 1D2 - > 3F4 and 1D2 - > 3H6 transitions. In comparison with other Tm3+-doped laser crystals, Tm3+:K2YF5 crystal has potential as a promising laser crystal.
Recent works on generalizable NeRFs have shown promising results on novel view synthesis from single or few images. However, such models have rarely been applied on other downstream tasks beyond ...synthesis such as semantic understanding and parsing. In this paper, we propose a novel framework named FeatureNeRF to learn generalizable NeRFs by distilling pre-trained vision foundation models (e.g., DINO, Latent Diffusion). FeatureNeRF leverages 2D pre-trained foundation models to 3D space via neural rendering, and then extract deep features for 3D query points from NeRF MLPs. Consequently, it allows to map 2D images to continuous 3D semantic feature volumes, which can be used for various downstream tasks. We evaluate FeatureNeRF on tasks of 2D/3D semantic keypoint transfer and 2D/3D object part segmentation. Our extensive experiments demonstrate the effectiveness of FeatureNeRF as a generalizable 3D semantic feature extractor. Our project page is available at https://jianglongye.com/featurenerf/ .
The spectroscopy of the adsorbed silane coupling agent on micro-sized silica particles was observed by
1H solid state NMR (SSNMR) under fast magic angle spinning (MAS). We found that this is a fast ...and effective way to characterize the structure and dynamics of the thin layer of coupling agent on the surface of micro-sized silica. Compared with conventional
29Si NMR spectroscopy and other methods, the present proton solid state NMR is a promising method to characterize the adsorbed layer on micro-sized silica.
Zero-shot novel view synthesis (NVS) from a single image is an essential problem in 3D object understanding. While recent approaches that leverage pre-trained generative models can synthesize ...high-quality novel views from in-the-wild inputs, they still struggle to maintain 3D consistency across different views. In this paper, we present Consistent-1-to-3, which is a generative framework that significantly mitigates this issue. Specifically, we decompose the NVS task into two stages: (i) transforming observed regions to a novel view, and (ii) hallucinating unseen regions. We design a scene representation transformer and view-conditioned diffusion model for performing these two stages respectively. Inside the models, to enforce 3D consistency, we propose to employ epipolor-guided attention to incorporate geometry constraints, and multi-view attention to better aggregate multi-view information. Finally, we design a hierarchy generation paradigm to generate long sequences of consistent views, allowing a full 360-degree observation of the provided object image. Qualitative and quantitative evaluation over multiple datasets demonstrates the effectiveness of the proposed mechanisms against state-of-the-art approaches. Our project page is at https://jianglongye.com/consistent123/
The spectroscopy of the adsorbed silane coupling agent on micro-sized silica particles was observed by 1H solid state NMR (SSNMR) under fast magic angle spinning (MAS). We found that this is a fast ...and effective way to characterize the structure and dynamics of the thin layer of coupling agent on the surface of micro-sized silica. Compared with conventional 29Si NMR spectroscopy and other methods, the present proton solid state NMR is a promising method to characterize the adsorbed layer on micro-sized silica.
Thermodynamic analysis of the correlation of H_2S and COS has been carried out at the temperature range of 400-650 ℃ at which high temperature desulfurization of coal gas is usually performed. The ...correlation of the two sulfur species is mainly through the reaction H_2S+CO→COS+H_2. Simulated coal gas with the following composition CO 32.69%, H_2 39.58%, CO_2 18.27%, N2 8.92% and H_2S 0.47% was used in this study, and the equilibrium concentrations of the two species at different temperatures were calculated. The results of Fe-based sorbents during sulfidation were compared with calculations. It is concluded that the above reaction may reach equilibrium concentration in the presence of the Fe-based sorbents, which means the Fe-based sorbents may effectively catalyze the reaction between H_2S and CO. Because of the correlation of the two sulfur species, both can be effectively removed at high temperatures simultaneously, offering high temperature desulfurization some advantages over low temperature desulfurization processes. KCI Citation Count: 13
We propose to learn to generate grasping motion for manipulation with a dexterous hand using implicit functions. With continuous time inputs, the model can generate a continuous and smooth grasping ...plan. We name the proposed model Continuous Grasping Function (CGF). CGF is learned via generative modeling with a Conditional Variational Autoencoder using 3D human demonstrations. We will first convert the large-scale human-object interaction trajectories to robot demonstrations via motion retargeting, and then use these demonstrations to train CGF. During inference, we perform sampling with CGF to generate different grasping plans in the simulator and select the successful ones to transfer to the real robot. By training on diverse human data, our CGF allows generalization to manipulate multiple objects. Compared to previous planning algorithms, CGF is more efficient and achieves significant improvement on success rate when transferred to grasping with the real Allegro Hand. Our project page is available at https://jianglongye.com/cgf .
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