Abstract: A frequency-tunable film bulk acoustic resonator and a preparation method therefor are provided. The resonator includes a substrate, an air gap, a sandwiched structure formed by electrodes and piezoelectric layers, and an electrode lead-out layer, wherein the substrate is connected to the sandwiched structure formed by the electrodes and the piezoelectric layers, and a connection face of the substrate and the sandwiched structure formed by the electrodes and the piezoelectric layers is recessed towards inside of the substrate to form the air gap; and the electrode lead-out layer is connected to the sandwiched structure formed by the electrodes and the piezoelectric layers. The sandwiched structure formed by the electrodes and the piezoelectric layers includes a bottom electrode, piezoelectric layers, intermediate electrodes, and a top electrode, wherein the electrodes and the piezoelectric layers are alternately arranged to form the sandwiched structure.

Abstract: The present invention provides anti-A2aR antigen binding molecules, including antibodies and the antigen binding fragment thereof, and methods for using the same for treating a variety of diseases associated with aberrant adenosine signaling, including cancers, chronic diseases, chronic infections, autoimmune diseases, inflammatory diseases, neurodegenerative diseases, and fibrotic diseases.

Abstract: Systems and methods for training a machine-learning model for named-entity recognition. A rule graph is constructed including a plurality of nodes each corresponding to a different labeling rule of a set of labeling rules (including a set of seeding rules of known labeling accuracy and a plurality of candidate rules of unknown labeling accuracy). The nodes are coupled to other nodes based on which rules exhibit the highest sematic similarity. A labeling accuracy metric is estimated for each candidate rule by propagating a labeling confidence metric through the rule graph from the seeding rules to each candidate rule. A subset of labeling rules is then identified by ranking the rules by their labeling confidence metric. The identified subset of labeling rules is applied to unlabeled data to generate a set of weakly labeled named entities and the machine-learning model is trained based on the set of weakly labeled named entities.

Abstract: The present invention relates to antibodies with specificity for FGFR1. More particularly, the invention relates to monoclonal antibodies that bind specifically to and neutralize human, macaque and mouse forms of FGFR1 with high affinity. The invention also relates to nucleic acids encoding said antibodies, vectors for expression of these nucleic acids, and host cells for producing said antibodies. Further, the invention relates to the use of said antibodies in the diagnosis and/or treatment of cancers.

Abstract: An antibody or antigen-binding fragment specifically binds to human programmed cell death ligand-1 (PD-L1). The antibody or antigen-binding fragment is able to enhance the function of T cells and upregulate a T cell-mediated immune response. The antibody or the antigen-binding fragment is useful for the treatment of diseases, e.g. tumor, associated with aberrant expression of PD-L1 and/or dysfunction of T cells.

Abstract: The present application relates to anti-TIGIT antibodies or antigen binding fragments thereof, nucleic acid encoding the same, therapeutic compositions thereof, and their use to enhance T-cell function to upregulate cell-mediated immune responses and for the treatment of T cell dysfunctional disorders, such as tumor immunity, for the treatment of infectious diseases and cancer.

Abstract: Systems and methods for training a machine-learning model for named-entity recognition. A rule graph is constructed including a plurality of nodes each corresponding to a different labeling rule of a set of labeling rules (including a set of seeding rules of known labeling accuracy and a plurality of candidate rules of unknown labeling accuracy). The nodes are coupled to other nodes based on which rules exhibit the highest sematic similarity. A labeling accuracy metric is estimated for each candidate rule by propagating a labeling confidence metric through the rule graph from the seeding rules to each candidate rule. A subset of labeling rules is then identified by ranking the rules by their labeling confidence metric. The identified subset of labeling rules is applied to unlabeled data to generate a set of weakly labeled named entities and the machine-learning model is trained based on the set of weakly labeled named entities.

Abstract: Methods and systems for performing semantic entity recognition. The method includes accessing a document stored in a memory and selecting from a general knowledge data repository, target domain information based on a specified target domain. The method also includes generating a plurality of weak annotators for the document based upon the selected target domain information and expert knowledge from a domain-specific expert knowledge data repository and applying the plurality of weak annotators to the document to generate a plurality of weak labels. The method further includes selecting at least one weak label from the plurality of weak labels as training data and training a semantic entity prediction model using the training data.

Abstract: The invention is based, in part, upon the discovery of a family of antibodies that specifically bind human T Cell Immunoglobulin and Mucin Domain-3 (TIM-3). The antibodies contain TIM-3 binding sites based on the CDRs of the antibodies. The antibodies can be used as therapeutic agents as a monotherapy or in combination with another therapeutic agent. When used as therapeutic agents, the antibodies can be optimized, e.g., affinity-matured, to improve biochemical and/or biophysical properties and/or to reduce or eliminate immunogenicity, when administered to a human patient. The antibodies inhibit TIM-3 from binding to TIM-3 ligands, e.g., galectin-9, phosphatidylserine (PtdSer) and carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1). The disclosed antibodies can be used to inhibit the proliferation of tumor cells in vitro or in vivo. When administered to a human cancer patient or an animal model, the antibodies inhibit or reduce tumor growth in the human patient or animal model.

Abstract: The invention is based, in part, upon the discovery of a family of antibodies that specifically bind human T Cell Immunoglobulin and Mucin Domain-3 (TIM-3). More specifically, this invention relates to a method of treating cancer by administering an anti-TIM-3 antibody in combination with an anti-PD-L1/TGF? Trap fusion protein. When administered to a human cancer patient or an animal model, the antibodies inhibit or reduce tumor growth in the human patient or animal model.

Abstract: An antibody or an antigen-binding fragment thereof capable of specifically binding to TNFR2, the antibody or the antigen-binding fragment thereof is capable of regulating the function of immune cells and may be used as a medicament to treat diseases related to immune-related disorders, such as tumors.

Abstract: Methods and systems for performing semantic entity recognition. The method includes accessing a document stored in a memory and selecting from a general knowledge data repository, target domain information based on a specified target domain. The method also includes generating a plurality of weak annotators for the document based upon the selected target domain information and expert knowledge from a domain-specific expert knowledge data repository and applying the plurality of weak annotators to the document to generate a plurality of weak labels. The method further includes selecting at least one weak label from the plurality of weak labels as training data and training a semantic entity prediction model using the training data.

Abstract: The present invention relates to antibodies with specificity for FGFR1. More particularly, the invention relates to monoclonal antibodies that bind specifically to and neutralize human, macaque and mouse forms of FGFR1 with high affinity. The invention also relates to nucleic acids encoding said antibodies, vectors for expression of these nucleic acids, and host cells for producing said antibodies. Further, the invention relates to the use of said antibodies in the diagnosis and/or treatment of cancers.

Abstract: An electrically conductive pin comprising a pin stem and a pin head attached to the pin stem. The pin head is adapted to be mounted onto a surface of a microelectronic substrate to support the pin stem. The pin head defines at least one slot therein, the at least one slot being configured to allow gases to escape therethrough from a region at an underside of the pin head.