Abstract: Provided herein are methods and compositions for the identification of modulators of LILRB3 activation. Also provided herein are methods of treating cancer comprising the administration of an inhibitor LILRB3 activation. Also provided are methods of treating autoimmune disease or inhibiting the onset of transplant rejection or treating an inflammatory disorder comprising administering an agonist of LILRB3 activation to a subject.

Abstract: A multifunctional portable tool is provided, which includes a housing; a motor received in the housing and having a first output end; a pump head movably received in the housing and having a driven shaft that is connectable with the first output end; and a first reset mechanism disposed between the motor and the pump head. The multifunctional portable tool has a first working state in which the driven shaft of the pump head is connected with the first output end of the motor so that the pump head and the motor together function as a pump, and a second working state in which the pump head is driven by the first reset mechanism to move away from the motor until the driven shaft of the pump head is disconnected with the first output end of the motor.

Abstract: A method and system for calculating emotional indicators based on pupil-wave are provided. The operation of calculating emotional indicators based on a pupil-wave may include the following operations. A pupil-wave is collected when a subject is in a calm state and set as a standard pupil-wave; Obtaining emotional indicators and corresponding emotions used to measure a mental state. The pupil-wave of the subject in each emotional state is collected and set as an emotional pupil-wave; According to the standard pupil-wave, a bandwidth and differential pupil-wave corresponding to each emotion are calculated; The standard, emotional, bandwidth and differential pupil-wave are input into a pre-trained deep convolutional neural network to obtain index values of emotional indicators.

Abstract: Provided is a modified Fc region. The Fc region has at least one amino acid mutation with respect to a parent Fc region. The modified Fc region has improved affinity to Fc?RIIB with respect to the affinity of the parent Fc region to Fc?RIIB Also provided is an antibody containing the modified Fc region, especially an agonistic antibody. The modified Fc region has significant use for optimizing the agonistic activity of the antibody.

Abstract: A lockable storage case mechanism for electronic device includes a case and a fixing mechanism connected to the case, the case includes a front cover and a rear cover, the front cover is provided with a film, a middle portion of the rear cover is provided with a placing portion for an electronic device, the front cover and the rear cover are connected by a pressing mechanism, and the fixing mechanism includes a connecting member which is configured to be a disc with a notch; when the case is rotated so that the notch corresponds to the pressing mechanism, the pressing mechanism is unlocked; when the notch leaves from the pressing mechanism, the disc is inserted into the pressing mechanism, and the pressing mechanism is locked. The present disclosure utilizes the rotating of the case to lock or unlock the pressing mechanism, and is convenient to use.

Abstract: The present invention provides a keratin BD-11, an encoding nucleic acid molecule, an expression vector, a host cell, a preparation method thereof, and a pharmaceutical composition containing the keratin. The keratin BD-11 can be used in the preparation of medicamnet for antipyretic, analgesic, antitussive, expectorant, anticonvulsant, antiepileptic, anti-hypertension, anti-inflammatory, and antiviral.

Abstract: The present invention provides a keratin BD-10, an encoding nucleic acid molecule, an expression vector, a host cell thereof, a preparation method for BD-10, and a pharmaceutical composition containing the keratin BD-10. Also provides the use of the keratin BD-10, nucleic acid molecule, expression vector, host cell or pharmaceutical composition in the preparation of medicament for antipyretic, analgesic, antitussive, expectorant, anticonvulsant, antiepileptic, anti-hypertension, anti-inflammatory, and antiviral.

Abstract: A method for preparing a bisphenol phosphate hydroxyl aluminum salt nucleating agent is provided, which adopts organic aluminum alcoholate as raw materials to prepare bisphenol phosphate hydroxyl aluminum salt. In prior art, a neutralization reaction of bisphenol phosphate and sodium hydroxide is firstly performed, so as to prepare bisphenol phosphate sodium salt; then a double decomposition reaction of sodium salt and inorganic aluminum salt is performed to prepare the bisphenol phosphate hydroxyl aluminum salt. The present invention combines the two-step reaction in prior art into the one-step reaction of phosphate and organic aluminum alcoholate for synthesizing the bisphenol phosphate hydroxyl aluminum salt, thereby simplifying the production process, improving the production efficiency, shortening the reaction time, and improving the product quality.

Abstract: A system may perform speech enhancement of audio data in real-time by suppressing noise components that are present in the audio data while preserving speech components. The system may include an in-ear module and a separate signal processing module that is wirelessly communicatively coupled to the in-ear module. The system may include non-negative matrix factorization (NMF) dictionaries capable of identifying frequency band components associated with speech and frequency band components associated with noise. The NMF dictionaries may be trained using voice samples and noise samples. The NMF dictionaries may be applied to noisy speech data to produce an NMF representation of the speech data which may then be applied using a dynamic mask to the noisy speech data in order to suppress the noise components of the noisy speech data and produce speech enhanced data.

Abstract: A method of operating a demand side platform (DSP) includes determining a current state of the DSP, wherein the current state of the DSP is based on a remaining bid budget and remaining number of opportunities, receiving, at the DSP, a bid request for one or more advertisement impressions, and determining an uncertainty of a predicted user response probability. The method further includes determining a risk tendency value based on the current state of the DSP, determining an adjusted value of the one or more advertisement impressions based on the uncertainty and risk tendency, determining a bid price for each of the one or more advertisement impressions based on the adjusted value of the one or more advertisement impressions, transmitting the bid price to an exchange platform to participate in an auction, receiving an auction result and updating the current state of the DSP based on the auction result.

Abstract: A sign language translation system may capture infrared images of the formation of a sign language sign or sequence of signs. The captured infrared images may be used to produce skeletal joints data that includes a temporal sequence of 3D coordinates of skeletal joints of hands and forearms that produced the sign language sign(s). A hierarchical bidirectional recurrent neural network may be used to translate the skeletal joints data into a word or sentence of a spoken language. End-to-end sentence translation may be performed using a probabilistic connectionist temporal classification based approach that may not require pre-segmentation of the sequence of signs or post-processing of the translated sentence.

Abstract: A karst channel type water inrush efficient-blocking ultra-high expansion grouting material, preparation, methods and application thereof, the grouting material includes macromolecule polymer particles A and a cross-linking solidifying fluid B, wherein the macromolecule polymer particles A are an inlaid type core-shell structure, primary macromolecule water-absorbent resin serves as an inner core, part of a gelling catalyzer is attached to an the inner core surface forming a shell, and the gelling catalyzer permeates the inner core forming an inlaid structure; before use, the macromolecule polymer particle A and the cross-linking solidifying fluid B are stirred; and then obtained mixed liquid is used as the grouting material to be injected into a fracture of a rock mass fracture zone.

Abstract: Systems and methods are disclosed which allow mobile devices, and other resource constrained applications, to more efficiently and effectively utilize deep learning neural networks using only (or primarily) local resources. These systems and methods take the dynamics of runtime resources into account to enable resource-aware, multi-tenant on-device deep learning for artificial intelligence functions for use in tasks like mobile vision systems. The multi-capacity framework enables deep learning models to offer flexible resource-accuracy trade-offs and other similar balancing of performance and resources consumed. At runtime, various systems disclosed herein may dynamically select the optimal resource-accuracy trade-off for each deep learning model to fit the model's resource demand to the system's available runtime resources and the needs of the task being performed by the model.

Abstract: Existing indoor air quality monitoring technologies focus on measuring which turn out to be effective in increasing people's awareness of air quality. However, the lack of identification of pollution sources is prone to lead to general and monotonous suggestions. In this disclosure, an indoor air quality analytics system is presented that is able to detect pollution events and identify pollution sources in real-time. The system can also forecast personal exposure to air pollution and provide actionable suggestions to help people improve indoor air quality.

Abstract: The present disclosure describes systems and methods for implementing input-adaptive neural networks. Several approaches and systems are presented for creating flexible and computationally-efficient deep neural networks that adapt their complexity based upon input data such as video streams. The approach may use fine-grained design and an automatic approach for generating optimal network architectures based on early-exit mechanisms. A neural network modified according to such principles can be implemented in various devices including mobile vision systems such as smartphones, drones, and head-mounted augmented reality devices.

Abstract: A system may perform speech enhancement of audio data in real-time by suppressing noise components that are present in the audio data while preserving speech components. The system may include an in-ear module and a separate signal processing module that is wirelessly communicatively coupled to the in-ear module. The system may include non-negative matrix factorization (NMF) dictionaries capable of identifying frequency band components associated with speech and frequency band components associated with noise. The NMF dictionaries may be trained using voice samples and noise samples. The NMF dictionaries may be applied to noisy speech data to produce an NMF representation of the speech data which may then be applied using a dynamic mask to the noisy speech data in order to suppress the noise components of the noisy speech data and produce speech enhanced data.

Abstract: A system may perform speech enhancement of audio data in real-time by suppressing noise components that are present in the audio data while preserving speech components. The system may include an in-ear module and a separate signal processing module that is wirelessly communicatively coupled to the in-ear module. The system may include non-negative matrix factorization (NMF) dictionaries capable of identifying frequency band components associated with speech and frequency band components associated with noise. The NMF dictionaries may be trained using voice samples and noise samples. The NMF dictionaries may be applied to noisy speech data to produce an NMF representation of the speech data which may then be applied using a dynamic mask to the noisy speech data in order to suppress the noise components of the noisy speech data and produce speech enhanced data.

Abstract: A system and method is provided that utilizes deep learning, including convolutional neural networks, to identify subject objects in unconstrained user images such as unknown pills. An image of, e.g., a pill, may be captured and subsequently processed using deep learning models to identify the pill. The deep learning models may be optimized to have a small footprint (in terms of computational and memory resources) suitable for a resource-limited device such as a smartphone while retaining a high object recognition accuracy. Each such model may also be run on modified versions of the unconstrained image, for example on color, greyscale, and gradient images, to focus the models on different distinguishing features of the object.

Abstract: Performance testing based on variable length segmentation and clustering of time series data is disclosed. One example is a system including a training module, a performance testing module, and an interface module. The training module generates a trained model to learn characteristics of a system of interest from training time series data by segmenting the training time series data into homogeneous windows of variable length, clustering the segments to identify patterns, and associating each cluster with a cluster score. The performance testing module analyzes system characteristics from testing time series data by receiving the testing time series data, and determining a performance metric for the testing time series data by analyzing the testing time series data based on the trained model. The interface module is communicatively linked to the performance testing module, and provides the performance metric via an interactive graphical user interface.