Abstract: Various embodiments of the present technology generally relate to robotic devices and artificial intelligence. More specifically, some embodiments relate to an artificial neural network training method that does not require extensive training data or time expenditure. The few-shot training model disclosed herein includes attempting to pick up items and, in response to a failed pick up attempt, transferring and generalizing information to similar regions to improve probability of success in future attempts. In some implementations, the training method is used to robotic device for picking items from a bin and perturbing items in a bin. When no picking strategies with high probability of success exist, the robotic device may perturb the contents of the bin to create new available pick-up points. In some implementations, the device may include one or more Computer-vision systems.

Abstract: The present invention relates to n-type conjugated polymers and blends, which is made from aromatic diketone with active methylene or an enolic transformation product thereof, and is obtained directly by polymerization reaction in the presence of an oxidant. The reaction described does not require precious metal catalysis and is insensitive to a reaction atmosphere. A process is simple and inexpensive and suitable for commercial applications. Meanwhile, the modulation of the conductivity of the n-type conjugated polymers can be achieved by ionic modification. The n-type conjugated polymers can be applied to an organic optoelectronic device to achieve an excellent photovoltaic effect.

Abstract: Provided are compounds of the Formula (I), or a pharmaceutically acceptable salt thereof: wherein W, X, Y, Z, x, R1, R2, R3, x and n are defined in the specification. The compounds are inhibitors of lysyl oxidase (LOX) and lysyl oxidase-like (LOXL) family members (LOXL1, LOXL2, LOXL3, LOXL4) and are useful in therapy, particularly in the treatment of cancer. Also disclosed are LOX inhibitors for use in the treatment of a cancer associated with EGFR and biomarkers that predict responsiveness to a LOX inhibitor.

Abstract: Provided are compounds of the Formula (I), or a pharmaceutically acceptable salt thereof: wherein W, X, Y, Z, x, R1, R2, R3, x and n are defined in the specification. The compounds are inhibitors of lysyl oxidase (LOX) and lysyl oxidase-like (LOXL) family members (LOXL1, LOXL2, LOXL3, LOXL4) and are useful in therapy, particularly in the treatment of cancer. Also disclosed are LOX inhibitors for use in the treatment of a cancer associated with EGFR and biomarkers that predict responsiveness to a LOX inhibitor.

Abstract: This invention relates to compounds useful as lysyl oxidase (LOX) and lysyl oxidase-like (LOXL) family member (LOXL1, LOXL2, LOXL3, LOXL4) inhibitors. In addition there are contemplated pharmaceutical compositions comprising the compounds and the use of the compounds in the treatment of conditions mediated by LOX and LOXL, for example cancer. In particular a LOX inhibitor such as the present compounds may be for use in the treatment of a cancer associated with EGFR. The present invention also contemplates the identification of biomarkers that predict responsiveness to a LOX inhibitor.

Abstract: This invention relates to compounds useful as lysyl oxidase (LOX) and lysyl oxidase-like (LOXL) family member (LOXL1, LOXL2, LOXL3, LOXL4) inhibitors. In addition there are contemplated pharmaceutical compositions comprising the compounds and the use of the compounds in the treatment of conditions mediated by LOX and LOXL, for example cancer. In particular a LOX inhibitor such as the present compounds may be for use in the treatment of a cancer associated with EGFR. The present invention also contemplates the identification of biomarkers that predict responsiveness to a LOX inhibitor.

Abstract: Various embodiments of the technology described herein generally relate to systems and methods for trajectory optimization with machine learning techniques. More specifically, certain embodiments relate to using neural networks to quickly predict optimized robotic arm trajectories in a variety of scenarios. Systems and methods described herein use deep neural networks to quickly predict optimized robotic arm trajectories according to certain constraints. Optimization, in accordance with some embodiments of the present technology, may include optimizing trajectory geometry and dynamics while satisfying a number of constraints, including staying collision-free, and minimizing the time it takes to complete the task.

Abstract: Various embodiments of the technology described herein generally relate to systems and methods for trajectory optimization with machine learning techniques. More specifically, certain embodiments relate to using neural networks to quickly predict optimized robotic arm trajectories in a variety of scenarios. Systems and methods described herein use deep neural networks to quickly predict optimized robotic arm trajectories according to certain constraints. Optimization, in accordance with some embodiments of the present technology, may include optimizing trajectory geometry and dynamics while satisfying a number of constraints, including staying collision-free and minimizing the time it takes to complete the task.

Abstract: Provided are compounds of the Formula (I), or a pharmaceutically acceptable salt thereof: wherein W, X, Y, Z, x, R1, R2, R3, x and n are defined in the specification. The compounds are inhibitors of lysyl oxidase (LOX) and lysyl oxidase-like (LOXL) family members (LOXL1, LOXL2, LOXL3, LOXL4) and are useful in therapy, particularly in the treatment of cancer. Also disclosed are LOX inhibitors for use in the treatment of a cancer associated with EGFR and biomarkers that predict responsiveness to a LOX inhibitor.

Abstract: Various embodiments of the present technology generally relate to robotic devices and artificial intelligence. More specifically, some embodiments relate to an artificial neural network training method that does not require extensive training data or time expenditure. The few-shot training model disclosed herein includes attempting to pick up items and, in response to a failed pick up attempt, transferring and generalizing information to similar regions to improve probability of success in future attempts. In some implementations, the training method is used to robotic device for picking items from a bin and perturbing items in a bin. When no picking strategies with high probability of success exist, the robotic device may perturb the contents of the bin to create new available pick-up points. In some implementations, the device may include one or more Computer-vision systems.

Abstract: Various embodiments of the present technology generally relate to robotic devices and artificial intelligence. More specifically, some embodiments relate to a robotic device for picking items from a bin and perturbing items in a bin. In some implementations, the device may include one or more computer-vision systems. A computer-vision system, in accordance with the present technology, may use at least two two-dimensional images to generate three-dimensional (3D) information about the bin and items in the bin. Based on the 3D information, a strategy for picking up items from the bin is determined. When no strategies with high probability of success exist, the robotic device may perturb the contents of the bin to create new available pick-up points and re-attempt to pick up an item.

Abstract: Provided are compounds of the Formula (I), or a pharmaceutically acceptable salt thereof: wherein W, X, Y, Z, x, R1, R2, R3, x and n are defined in the specification. The compounds are inhibitors of lysyl oxidase (LOX) and lysyl oxidase-like (LOXL) family members (LOXL1, LOXL2, LOXL3, LOXL4) and are useful in therapy, particularly in the treatment of cancer. Also disclosed are LOX inhibitors for use in the treatment of a cancer associated with EGFR and biomarkers that predict responsiveness to a LOX inhibitor.

Abstract: This invention relates to compounds useful as lysyl oxidase (LOX) and lysyl oxidase-like (LOXL) family member (LOXL1, LOXL2, LOXL3, LOXL4) inhibitors. In addition there are contemplated pharmaceutical compositions comprising the compounds and the use of the compounds in the treatment of conditions mediated by LOX and LOXL, for example cancer. In particular a LOX inhibitor such as the present compounds may be for use in the treatment of a cancer associated with EGFR. The present invention also contemplates the identification of biomarkers that predict responsiveness to a LOX inhibitor.

Abstract: Provided are compounds of the Formula (I), or a pharmaceutically acceptable salt thereof: wherein W, X, Y, Z, x, R1, R2, R3, x and n are defined in the specification. The compounds are inhibitors of lysyl oxidase (LOX) and lysyl oxidase-like (LOXL) family members (LOXL1, LOXL2, LOXL3, LOXL4) and are useful in therapy, particularly in the treatment of cancer. Also disclosed are LOX inhibitors for use in the treatment of a cancer associated with EGFR and biomarkers that predict responsiveness to a LOX inhibitor.

Abstract: Provided are compounds of the Formula (I), or a pharmaceutically acceptable salt thereof: wherein W, X, Y, Z, x, R1, R2, R3, x and n are defined in the specification. The compounds are inhibitors of lysyl oxidase (LOX) and lysyl oxidase-like (LOXL) family members (LOXL1, LOXL2, LOXL3, LOXL4) and are useful in therapy, particularly in the treatment of cancer. Also disclosed are LOX inhibitors for use in the treatment of a cancer associated with EGFR and biomarkers that predict responsiveness to a LOX inhibitor.