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Background: Indobufen is a drug that hinders the aggregation of platelets by reversibly repressing the cyclooxygenase enzyme, further bringing about diminished thromboxane production. During quality control of indobufen tablets, an unknown impurity was detected. Objective: To characterize an unknown impurity in indobufen tablets. Methods: A new method compatible with mass spectrometry detection was set up. A C18 column at 35 °C with a mobile phase consisting of aqueous buffer (including ammonium formate) and methanol (35: 65, v/v) was used at a flow rate of 1.0 mL/min at 228 nm. High-performance liquid chromatography quadrupole time-of-flight mass spectrometry mass spectrometry (HPLC-Q-TOF MS) was used to identify the impurity with the electrospray ionization (ESI) source in the positive ionization mode. Results: The results of HPLC-Q-TOF MS analysis indicated that the protonated molecule ions [M + H]+ of the unknown impurity was at m/z 312. Preparative LC method was put into practice with a Prep- C18 column with a mobile phase consisting of water and methanol (20: 80, v/v) at a flow rate of 20.0 mL/min at 228 nm. The assignment of the 1D and 2D NMR signals was performed for the unknown impurity. In addition, possible formation of the novel impurity was also studied. Conclusion: An unknown impurity in indobufen tablets was characterized. The impurity was assigned as 2-(4-(1-hydroxy-3-oxoisoindolin-2-yl) phenyl) butanoic acid.

Background: Clarithromycin is widely used for infections of helicobacter pylori. Clarithromycin belongs to polymorphic drug. Crystalline state changes of clarithromycin in sustained release tablets were found. Objective: The aim of this study was to find the influential factor of the crystal transition of clarithromycin in preparation process of sustained-release tablets and to investigate the possible interactions between the clarithromycin and pharmaceutical excipients. Methods and Results: The crystal transition of active pharmaceuticals ingredients from form II to form I in portion in clarithromycin sustained release tablets were confirmed by x-ray powder diffraction. The techniques including differential scanning calorimetry and infrared spectroscopy, x-ray powder diffraction were used for assessing the compatibility between clarithromycin and several excipients as magnesium stearate, lactose, sodium carboxymethyl cellulose, polyvinyl-pyrrolidone K-30 and microcrystalline cellulose. All of these methods showed compatibilities between clarithromycin and the selected excipients. Alcohol prescription simulation was also done, which showed incompatibility between clarithromycin and concentration alcohol. Conclusion: It was confirmed that the reason for the incompatibility of clarithromycin with high concentration of alcohol was crystal transition.

Recently, Masked Image Modeling (MIM) achieves great success in self-supervised visual recognition. However, as a reconstruction-based framework, it is still an open question to understand how MIM works, since MIM appears very different from previous well-studied siamese approaches such as contrastive learning. In this paper, we propose a new viewpoint: MIM implicitly learns occlusion-invariant features, which is analogous to other siamese methods while the latter learns other invariance. By relaxing MIM formulation into an equivalent siamese form, MIM methods can be interpreted in a unified framework with conventional methods, among which only a) data transformations, i.e. what invariance to learn, and b) similarity measurements are different. Furthermore, taking MAE (He et al.) as a representative example of MIM, we empirically find the success of MIM models relates a little to the choice of similarity functions, but the learned occlusion invariant feature introduced by masked image -- it turns out to be a favored initialization for vision transformers, even though the learned feature could be less semantic. We hope our findings could inspire researchers to develop more powerful self-supervised methods in computer vision community.

We propose a new neural network design paradigm Reversible Column Network (RevCol). The main body of RevCol is composed of multiple copies of subnetworks, named columns respectively, between which multi-level reversible connections are employed. Such architectural scheme attributes RevCol very different behavior from conventional networks: during forward propagation, features in RevCol are learned to be gradually disentangled when passing through each column, whose total information is maintained rather than compressed or discarded as other network does. Our experiments suggest that CNN-style RevCol models can achieve very competitive performances on multiple computer vision tasks such as image classification, object detection and semantic segmentation, especially with large parameter budget and large dataset. For example, after ImageNet-22K pre-training, RevCol-XL obtains 88.2% ImageNet-1K accuracy. Given more pre-training data, our largest model RevCol-H reaches 90.0% on ImageNet-1K, 63.8% APbox on COCO detection minival set, 61.0% mIoU on ADE20k segmentation. To our knowledge, it is the best COCO detection and ADE20k segmentation result among pure (static) CNN models. Moreover, as a general macro architecture fashion, RevCol can also be introduced into transformers or other neural networks, which is demonstrated to improve the performances in both computer vision and NLP tasks. We release code and models at https://github.com/megvii-research/RevCol, Comment: Accepted by ICLR 2023

Interest has spread to potential unconventional shale reservoirs in the last decades, and they have become an increasingly important source of hydrocarbon. Importantly, pore structure of shale has considerable effects on the storage, seepage and output of the fluids in shale reservoirs so that reliable fractal characteristics are essential. To better understand the evolution characteristics of pore structure for a shale gas condensate reservoir and their influence on liquid hydrocarbon occurrences and reservoir physical properties, we conducted high-pressure mercury intrusion tests (HPMIs), field emission scanning electron microscopies (FESEM), total organic carbon (TOC), Rock-Eval pyrolysis and saturation measurements on samples from the Duvernay formation. Furthermore, the fractal theory is applied to calculate the fractal dimension of the capillary pressure curves, and three fractal dimensions D1, D2 and D3 are obtained. The relationships among the characteristics of the Duvernay shale (TOC, organic matter maturity, fluid saturation), the pore structure parameters (permeability, porosity, median pore size), and the fractal dimensions were investigated. The results show that the fractal dimension D1 ranges from 2.44 to 2.85, D2 ranges from 2.09 to 2.15 and D3 ranges from 2.35 to 2.48. D2 and D3 have a good positive correlation. The pore system studied mainly consists of organic pores and microfractures, with the percentage of micropores being 50.38%. TOC has a positive relationship with porosity and D3 due to the development of organic pores. D3 has a positive correlation with gas saturation. With increased D3, median pore size shows a decreasing trend and an increase in permeability and porosity, demonstrating that D3 has a large effect on pore size distribution and the heterogeneity of pore size. In general, D3 has a better correlation with petrophysical and petrochemical parameters. Fractal theory can be applied to better understand the pore evolution, pore size distribution and fluid storage capacity of shale reservoirs.

To obtain a large fingerprint template from several partial fingerprints, we propose a novel partial fingerprint mosaicking scheme, which includes a coarse-to-fine alignment stage and a fusion stage, to build a synthetic template from multiple partial fingerprints. In the alignment stage, firstly, a central patch is determined after pair-wised patch matching, then the rest patches are coarsely aligned based on the central patch, thirdly, the locations of patches are optimized globally. In the feature fusion stage, not only minutiae, but also ridge sampling points are fused to increase the information in the synthetic template. The proposed algorithm is tested on two datasets of FVC2002 and the experimental results show that it can achieve a great fingerprint mosaicking performance.

To solve the problem of partial fingerprint matching difficulty caused by very small fingerprint sensors on mobile terminals, this paper presents a Cylinder Code-based partial fingerprint matching algorithm. The algorithm is inspired by the Minutia Cylinder Code (MCC) structure, and keeps the original MCC structure characteristics while reducing data redundancy. In addition, ridge points are added in the algorithm, which solve the feature loss caused by the small size of the sensors. The proposed algorithm are tested on the FVC2002 database and compared with four well-known matching algorithms. The results show the proposed method has excellent comprehensive performance and ability to apply to light architecture that other algorithms cannot match.

Los objetivos de esta tesis son analizar cómo aprenden y utilizan el pretérito indefinido y el pretérito imperfecto los alumnos sinohablantes de ELE (español como lengua extranjera); detectar cuáles son los errores que cometen en la alternancia canté/cantaba y sus motivos; y encontrar soluciones para evitarlos y mejorar su aprendizaje. En primer lugar, se expone el sistema temporal y aspectual del español para localizar las dos formas en el sistema verbal en español y describir sus valores tempo-aspectuales, así como el sistema temporal y aspectual en chino para detectar las equivalencias de las dos formas en chino. Luego se pasa al análisis contrastivo para explorar las diferencias entre las dos lenguas en la expresión del tiempo y del aspecto y establecer la correspondencia entre los dos pretéritos en español y sus equivalencias en chino. Con base en estos planteamientos teóricos, se predicen las posibles dificultades que encontrarán los estudiantes chinos en el aprendizaje de los dos pretéritos en español. A continuación, se justifica que la oposición canté/cantaba es de carácter aspectual y se analizan todos los factores que influyen en la selección de las dos formas (la interrelación entre el modo de acción y el aspecto flexivo, el tipo de oración en que se insertan, restricciones o compatibilidades entre los complementos adverbiales temporales y ambas formas, y función discursiva de los diferentes contextos en que se encuentran). Luego se elaboran unas pruebas a realizar por ochenta y cuatro alumnos universitarios chinos, residentes en China. Con estos resultados, se detectan cuáles son las dificultades y sus posibles causas en el aprendizaje de la alternancia canté/cantaba en español para los estudiantes sinohablantes. Al final, plantean sus propuestas y diseñan una unidad didáctica para progresar en el desarrollo de su interlengua. Madrid ESP

The W block shale in the study area is located at the West Canada basin and belongs to the low-porosity and ultra-low permeability gas-condensate reservoirs. The sandwiched layers in the shale are extremely important for reservoir reconstruction. As the single-layer thickness of the carbonate interbeds in the W block shale is very thin and have multi-stage superposition characteristics, the use of conventional geostatistical inversion cannot effectively and accurately predict the thin sweet spots and interbeds in the shale. This article uses three-dimensional probability constraints as pre-stack geostatistical inversion to replace traditional one-dimensional and two-dimensional face constraint inversion and achieved quantitative prediction of interbeds using well logging and 3D seismic data, so that prediction outcomes fully integrates well logging, seismic data and established a set of 3D probability constraint pre-stack geostatistical inversion process for thin interbeds and sweet spots in the shale. The process mainly includes the following crucial steps: (1) Well logging evaluation of shale reservoir parameters, analysis of shale rockphysical parameters and analysis of petrophysical characteristics of shale sweet spots and carbonate interbeds from well data, in order to evaluate and use seismic data to predict the possibility of shale sweet spots and interbeds. The characteristics of shale sweet spots is low Poisson ratio, moderate Young's modulus, high total organic content (TOC) and high brittleness. The characteristics of carbonate interbeds is high Poisson ratio, high Young's modulus, low TOC and high density. (2) Pre-stack gather optimization to establish six reliable partial sub-offset seismic data volumes. (3) Application of waveform difference simulation for prediction of shale interbeds, analysis of the vertical and horizontal variation characteristics of the interbeds based on post-stack seismic data and the three-dimensional probability volume of carbonate interbeds was estabilished according to the results of seismic waveform difference simulation and well logs. (4) High resolution 3D lithologic probability constrained pre-stack geostatistical inversion are performed and effectively predicted the spatial variation characteristics of shale thin interbeds and sweet spots.