Abstract: The present invention discloses a packaging box that displays different images when open and closed, which comprises an outer box body and an inner box body. A display window is provided on the upper face of the outer box body. Different images are displayed in the display window on the unfolded surface or the closed surface. The unfolded surface is fixed in the display window. Opening and closing the inner box body drives the lateral movement of the closed surface to display the image on the unfolded surface or the image on the closed surface in the display window. The invention also discloses a preparation method and application of the packaging box.

Abstract: Apparatuses, systems, and techniques to obtain one or more captions for a video using machine learning. In at least one embodiment, at least one machine learning process is used to generate at least one output caption using at least one image-level caption, at least one video-level caption, and/or at least one motion caption. In at least one embodiment, the video-level caption(s) is/are generated by one or more second machine learning processes using the video, and the image-level caption(s) is/are generated by one or more third machine learning processes using one or more images sampled from the video.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for recurrence in a transformer architecture. In one aspect, a method includes receiving input embeddings representing a sequence of words as input; generating as output attention vectors for each of the words, the attention vectors for each word indicating an importance of the word in the sequence relative to other words in the sequence; generating first and second linear transformations X1 and X2 of the attention vectors; determining, in a recurrent neural network, a hidden state corresponding to each attention vector using only element wise operations on the first linear transformation of the attention vectors during a recurrent step; and generating a set of output vectors using a multiplicative gating function in combination with the second linear transformation.

Abstract: Apparatuses, systems, and techniques for enhancing autonomous driving systems. In at least one embodiment, visual input corresponding to an observable environment is tokenized into object-level knowledge and provided to a large language model (LLM). Object-level tokens are processed by the LLM to enhance autonomous vehicle route-planning, reducing trajectory error and decreasing collision rates.

Abstract: The described aspects and implementations enable training and deploying of accurate one-shot models capable of predicting trajectories of vehicles and other objects in driving environments. The disclosed techniques include, in one implementation, obtaining training data that includes a training input representative of a driving environment of a vehicle and one or more ground truth trajectories associated with a forecasted motion of the vehicle within the driving environment. The one or more ground truth trajectories are generated by a teacher model using the training input. The techniques further include training, using the training data, a student model to predict one or more trajectories of the vehicle and/or objects in the driving environment of the vehicle.

Abstract: Systems and methods for incorporating latent states into robotic planning are provided. In one embodiment, the method includes identifying an agent team including at least one robotic agent and at least one human agent. The method also includes receiving sensor data associated with relative physical parameters between the at least one robotic agent and the at least one human agent. The method further includes modeling the latent states of the at least one human agent as a behavior model. The latent states describe cognition of the at least one human agent. The method includes calculating a first belief state based on the relative physical parameters and the behavior model. The method yet further includes predicting future probabilities of future observations at a second the future probabilities.

Abstract: Systems and methods for curiosity development in an agent located in an uncertain environment are provided. In one embodiment, the system includes a goal state module, a curiosity module, and a planning module. The goal module is configured to calculate a goal state of a goal associated with the environment. The curiosity module is configured to determine an uncertainty value for the environment and calculate a curiosity reward based on the uncertainty value. The planning module is configured to update a motion plan based on the goal state and the curiosity reward.

Abstract: Systems and methods for curiosity development in an agent located in an uncertain environment are provided. In one embodiment, the system includes a goal state module, a curiosity module, and a planning module. The goal module is configured to calculate a goal state of a goal associated with the environment. The curiosity module is configured to determine an uncertainty value for the environment and calculate a curiosity reward based on the uncertainty value. The planning module is configured to update a motion plan based on the goal state and the curiosity reward.

Abstract: Systems and methods for incorporating latent states into robotic planning are provided. In one embodiment, the method includes identifying an agent team including at least one robotic agent and at least one human agent. The method also includes receiving sensor data associated with relative physical parameters between the at least one robotic agent and the at least one human agent. The method further includes modeling the latent states of the at least one human agent as a behavior model. The latent states describe cognition of the at least one human agent. The method includes calculating a first belief state based on the relative physical parameters and the behavior model. The method yet further includes predicting future probabilities of future observations at a second the future probabilities.

Abstract: A hydrogenation method and distillate two-phase hydrogenation reactor in which the size of an upper space of the reactor is greater than that of a lower catalyst bed part. The reactor comprises 2 to 4 catalyst beds. An inner component for gas replenishment and for stripping a liquid-phase stream containing impurities is arranged between at least one adjacent catalyst bed and comprises a separator plate and exhaust pipes. The separator plate is provided with multiple downcomer through holes. The separator plate is connected with a plurality of exhaust pipes. The exhaust pipes are vertically arranged above the separator plate. The top parts of the exhaust pipes are in contact with the lower part of the upper catalyst bed.

Abstract: The present invention relates to a synthesis method for ETS-10 titanosilicate molecular sieves. The method comprises the steps of mixing a titanium oxide hydrosol, a silicon source, a sodium hydroxide, a fluorine-containing mineralizer and a water to give a gel and adjusting the pH thereof to 10.4 to 10.8; and hydrothermal crystallizing the gel at 170 to 250° C. for 10 to 100 hours to obtain the ETS-10 titanosilicate molecular sieves. In the synthesis method for ETS-10 titanosilicate molecular sieves provided by the present invention, a titanium oxide hydrosol is used as the titanium source to synthesize the ETS-10 titanosilicate molecular sieves, and the problem that conventional soluble titanium salt-based titanium sources tend to hydrolyze and the problem of poor dispersibility for the titanium source system of insoluble titanium oxide are therefore prevented. The ETS-10 titanosilicate molecular sieves synthesized has high purity and high crystallinity.

Abstract: A hydrogenation method and distillate two-phase hydrogenation reactor in which the size of an upper space of the reactor is greater than that of a lower catalyst bed part. The reactor comprises 2 to 4 catalyst beds. An inner component for gas replenishment and for stripping a liquid-phase stream containing impurities is arranged between at least one adjacent catalyst bed and comprises a separator plate and exhaust pipes. The separator plate is provided with multiple downcomer through holes. The separator plate is connected with a plurality of exhaust pipes. The exhaust pipes are vertically arranged above the separator plate. The top parts of the exhaust pipes are in contact with the lower part of the upper catalyst bed.

Abstract: Provided are a distillate oil hydrogenation deacidification catalyst containing a molecular sieve, preparation and use thereof. In this catalyst, the weight of the catalyst, on the basis of 100%, is 1-5% magnesium calculated as an oxide, 1-20% alumino-phosphate molecular sieve and/or aluminosilicate molecular sieve; 1-10% Co and/or Ni; 5-30% Mo and/or W, and the balance is aluminium oxide. The catalyst is prepared through forming, dipping and baking. The catalyst is very active in hydrogenation deacidification, and also in hydrodesulfurization and hydrodenitrogenation.

Abstract: The present invention relates to a synthesis method for ETS-10 titanosilicate molecular sieves. The method comprises the steps of mixing a titanium oxide hydrosol, a silicon source, a sodium hydroxide, a fluorine-containing mineralizer and a water to give a gel and adjusting the pH thereof to 10.4 to 10.8; and hydrothermal crystallizing the gel at 170 to 250° C. for 10 to 100 hours to obtain the ETS-10 titanosilicate molecular sieves. In the synthesis method for ETS-10 titanosilicate molecular sieves provided by the present invention, a titanium oxide hydrosol is used as the titanium source to synthesize the ETS-10 titanosilicate molecular sieves, and the problem that conventional soluble titanium salt-based titanium sources tend to hydrolyze and the problem of poor dispersibility for the titanium source system of insoluble titanium oxide are therefore prevented. The ETS-10 titanosilicate molecular sieves synthesized has high purity and high crystallinity.