Abstract: A quinoline derivative for treating rheumatoid arthritis and a use thereof in preparing a pharmaceutical composition for treating rheumatoid arthritis. In particular, a use of the quinoline derivative 1-[[[4-(4-Fluoro-2-methyl-1H-indol-5-yl)oxy-6-methoxyquinoline-7-yl]oxy]methyl]cyclopropanamine in treating rheumatoid arthritis.

Abstract: Apparatuses and methods are disclosed for determining artifact signals from a plurality of sample signals collected during a pre-determined time window from at least one ECG lead configured to be affixed to a patient. The apparatuses and methods select a plurality of sample points from in the sample signals, extract a plurality of features from the selected sample points, and generate a probability of the existence of the artifact signals by applying a transformation process to at least two of the plurality of features. Furthermore, the apparatuses and methods identify a plurality of QRS-complexes extract one or more features corresponding to the identified QRS-complexes. The apparatuses and methods further generate a signal quality index (“SQI”) by comparing the one or more features corresponding to the identified QRS-complexes and determine the artifact signals based on the SQI and the probability.

Abstract: Systems and methods for reading a two-dimensional matrix symbol or for determining if a two-dimensional matrix symbol is decodable are disclosed. The systems and methods can include a data reading algorithm that receives an image, locates at least a portion of the data modules within the image without using a fixed pattern, fits a model of the module positions from the image, extrapolates the model resulting in predicted module positions, determines module values from the image at the predicted module positions, and extracts a binary matrix from the module values.

Abstract: Systems and methods for reading a two-dimensional matrix symbol or for determining if a two-dimensional matrix symbol is decodable are disclosed. The systems and methods can include a data reading algorithm that receives an image, locates at least a portion of the data modules within the image without using a fixed pattern, fits a model of the module positions from the image, extrapolates the model resulting in predicted module positions, determines module values from the image at the predicted module positions, and extracts a binary matrix from the module values.

Abstract: Systems and methods for reading a two-dimensional matrix symbol or for determining if a two-dimensional matrix symbol is decodable are disclosed. The systems and methods can include a data reading algorithm that receives an image, locates at least a portion of the data modules within the image without using a fixed pattern, fits a model of the module positions from the image, extrapolates the model resulting in predicted module positions, determines module values from the image at the predicted module positions, and extracts a binary matrix from the module values.

Abstract: Systems and methods for reading a two-dimensional matrix symbol or for determining if a two-dimensional matrix symbol is decodable are disclosed. The systems and methods can include a data reading algorithm that receives an image, locates at least a portion of the data modules within the image without using a fixed pattern, fits a model of the module positions from the image, extrapolates the model resulting in predicted module positions, determines module values from the image at the predicted module positions, and extracts a binary matrix from the module values.

Abstract: Systems and methods for reading a two-dimensional matrix symbol or for determining if a two-dimensional matrix symbol is decodable are disclosed. The systems and methods can include a data reading algorithm that receives an image, locates at least a portion of the data modules within the image without using a fixed pattern, fits a model of the module positions from the image, extrapolates the model resulting in predicted module positions, determines module values from the image at the predicted module positions, and extracts a binary matrix from the module values.

Abstract: Systems and methods are described for acquiring and decoding a plurality of images. First images are acquired and then processed to attempt to decode a symbol. Contributions of the first images to the decoding attempt are identified. An updated acquisition-settings order is determined based at least partly upon the contributions of the first images to the decoding attempt. Second images are acquired or processed based at least partly upon the updated acquisition-settings order.

Abstract: Systems and methods are described for acquiring and decoding a plurality of images. First images are acquired and then processed to attempt to decode a symbol. Contributions of the first images to the decoding attempt are identified. An updated acquisition-settings order is determined based at least partly upon the contributions of the first images to the decoding attempt. Second images are acquired or processed based at least partly upon the updated acquisition-settings order.

Abstract: Systems and methods for reading a two-dimensional matrix symbol or for determining if a two-dimensional matrix symbol is decodable are disclosed. The systems and methods can include a data reading algorithm that receives an image, locates at least a portion of the data modules within the image without using a fixed pattern, fits a model of the module positions from the image, extrapolates the model resulting in predicted module positions, determines module values from the image at the predicted module positions, and extracts a binary matrix from the module values.

Abstract: Systems and methods are described for acquiring and decoding a plurality of images. First images are acquired and then processed to attempt to decode a symbol. Contributions of the first images to the decoding attempt are identified. An updated acquisition-settings order is determined based at least partly upon the contributions of the first images to the decoding attempt. Second images are acquired or processed based at least partly upon the updated acquisition-settings order.

Abstract: Systems and methods read machine readable symbols, the systems and methods capture multiple images of the symbol and can locate symbol data region(s) from an image even when the symbol data is corrupted and not decodable. Binary matrices are generated of the symbol data regions obtained from the multiple images and can be accumulated to generate a decodable image. A correspondence can be established among multiple images acquired on the same symbol when the symbol has moved from one image to the next.

Abstract: Systems and methods read machine readable symbols, the systems and methods capture multiple images of the symbol and can locate symbol data region(s) from an image even when the symbol data is corrupted and not decodable. Binary matrices are generated of the symbol data regions obtained from the multiple images and can be accumulated to generate a decodable image. A correspondence can be established among multiple images acquired on the same symbol when the symbol has moved from one image to the next.