Abstract: Compositions, devices, methods and systems are provided for differential functionalization of a surface of a structure to support biopolymer synthesis. Provided herein are processes which include use of lamps, lasers, and/or microcontact printing to add functional groups to surfaces for the efficient and uniform synthesis of oligonucleic acids.

Abstract: Methods, systems and platforms for digital imaging of multiple regions of an array, and detection and counting of the labeled features thereon, are described.

Abstract: Compositions and methods for creating plants exhibiting enhanced resistance to abiotic stresses, especially cold stress are disclosed.

Abstract: Methods, systems and platforms for digital imaging of multiple regions of an array, and detection and counting of the labeled features thereon, are described.

Abstract: Certain embodiments of the present invention provide an improved method for using an intraoperative imaging system. The method includes acquiring an image using an intraoperative imaging system, labeling the image by associating the image with a label, and storing the image and the label.

Abstract: Disclosed herein are devices and systems comprising a) a substrate comprising at least 100 microwells and a plurality of beads, wherein a plurality of the at least 100 microwells each contain a single bead, and wherein the ratio of the average diameter of the microwells to the diameter of the beads ranges from about 1.2 to about 1.8; b) a flow cell in fluid communication with the substrate; and c) at least one inlet port and at least one outlet port, wherein the at least one inlet port and at least one outlet port are capable of directing a flow of a fluid through the flow cell, thereby contacting the microwells with the fluid.

Abstract: Methods, systems and platforms for digital imaging of multiple regions of an array, and detection and counting of the labeled features thereon, are described.

Abstract: A wireless sensor for indicating a physical state within an environment includes a housing defining a hermetically sealed cavity. A structure located within the cavity of the housing has elements providing capacitance, the elements being arranged such that the distance and thereby the capacitance of the structure changes when a physical state of the environment changes. The structure has a resonant frequency based at least in part on the capacitance of the structure when in the presence of a fluctuating electromagnetic field. When the sensor is positioned within an environment and is subjected to a fluctuating electromagnetic field, the resonant frequency indicates the physical state of the environment.

Abstract: One or more techniques and/or systems are disclosed for predicting propagation of a message on a social network. A predictive model is trained to determine a probability of propagation of information on the social network using both positive and negative information propagation feedback, which may be collected while monitoring the social network over a desired period of time for information propagation. A particular message can be input to the predictive model, which can determine a probability of propagation of the message on the social network, such as how many connections may receive at least a portion of the message and/or a likelihood of at least a portion of the message reaching respective connections in the social network.

Abstract: One or more techniques and/or systems are disclosed for predicting propagation of a message on a social network. A predictive model is trained to determine a probability of propagation of information on the social network using both positive and negative information propagation feedback, which may be collected while monitoring the social network over a desired period of time for information propagation. A particular message can be input to the predictive model, which can determine a probability of propagation of the message on the social network, such as how many connections may receive at least a portion of the message and/or a likelihood of at least a portion of the message reaching respective connections in the social network.

Abstract: One or more techniques and/or systems are disclosed for predicting propagation of a message on a social network. A predictive model is trained to determine a probability of propagation of information on the social network using both positive and negative information propagation feedback, which may be collected while monitoring the social network over a desired period of time for information propagation. A particular message can be input to the predictive model, which can determine a probability of propagation of the message on the social network, such as how many connections may receive at least a portion of the message and/or a likelihood of at least a portion of the message reaching respective connections in the social network.

Abstract: A recommender system may he used to predict a user behavior that a user will give in relation to an item. In an embodiment such predictions are used to enable items to be recommended to users. For example, products may be recommended to customers, potential friends may be recommended to users of a social networking tool, organizations may be recommended to automated users or other items may be recommended to users. In an embodiment a memory stores a data structure specifying a bi-linear collaborative filtering model of user behaviors. In the embodiment an automated inference process may be applied to the data structure in order to predict a user behavior given information about a user and information about an item. For example, the user information comprises user features as well as a unique user identifier.

Abstract: A method for a computer system includes receiving an identifier associated with a client streaming player, determining one or more attributes associated with the identifier from a data structure in response to the identifier, determining available channels from a plurality of channels that are to be made available to the client streaming player in response to the identifier, wherein available channels comprises a first channel, but not the second channel, determining a first graphical identifier associated with the first channel, providing the first graphical identifier to the client streaming player, receiving a user selection of the first graphical identifier indicating a user request to associate the first channel with the computer system, and providing an indicator of a server network address associated with the first channel to the client streaming player.

Abstract: A profile of one or more users of the online auction environment is developed. The profile of each user can be based at least in part on historical auction activity of that user. An auction of the online auction environment that is in progress is monitored. A prediction is determined as to whether the auction will be successful based at least in part on the profile of the one or more users that are participating in the auction.

Abstract: A method for a computer system includes receiving an identifier associated with a client streaming player, determining one or more attributes associated with the identifier from a data structure in response to the identifier, determining available channels from a plurality of channels that are to be made available to the client streaming player in response to the identifier, wherein available channels comprises a first channel, but not the second channel, determining a first graphical identifier associated with the first channel, providing the first graphical identifier to the client streaming player, receiving a user selection of the first graphical identifier indicating a user request to associate the first channel with the computer system, and providing an indicator of a server network address associated with the first channel to the client streaming player.

Abstract: A recommender system may be used to predict a user behavior that a user will give in relation to an item. In an embodiment such predictions are used to enable items to be recommended to users. For example, products may be recommended to customers, potential friends may be recommended to users of a social networking tool, organizations may be recommended to automated users or other items may be recommended to users. In an embodiment a memory stores a data structure specifying a bi-linear collaborative filtering model of user behaviors. In the embodiment an automated inference process may be applied to the data structure in order to predict a user behavior given information about a user and information about an item. For example, the user information comprises user features as well as a unique user identifier.

Abstract: Machine learning techniques may be used to train computing devices to understand a variety of documents (e.g., text files, web pages, articles, spreadsheets, etc.). Machine learning techniques may be used to address the issue that computing devices may lack the human intellect used to understand such documents, such as their semantic meaning. Accordingly, a topic model may be trained by sequentially processing documents and/or their features (e.g., document author, geographical location of author, creation date, social network information of author, and/or document metadata). Additionally, as provided herein, the topic model may be used to predict probabilities that words, features, documents, and/or document corpora, for example, are indicative of particular topics.

Abstract: Knowledge corroboration is described. In an embodiment many judges provide answers to many questions so that at least one answer is provided to each question and at least some of the questions have answers from more than one judge. In an example a probabilistic learning system takes features describing the judges or the questions or both and uses those features to learn an expertise of each judge. For example, the probabilistic learning system has a graphical assessment component which aggregates the answers in a manner which takes into account the learnt expertise in order to determine enhanced answers. In an example the enhanced answers are used for knowledge base clean-up or web-page classification and the learnt expertise is used to select judges for future questions. In an example the probabilistic learning system has a logical component that propagates answers according to logical relations between the questions.

Abstract: Machine learning techniques may be used to train computing devices to understand a variety of documents (e.g., text files, web pages, articles, spreadsheets, etc.). Machine learning techniques may be used to address the issue that computing devices may lack the human intellect used to understand such documents, such as their semantic meaning. Accordingly, a topic model may be trained by sequentially processing documents and/or their features (e.g., document author, geographical location of author, creation date, social network information of author, and/or document metadata). Additionally, as provided herein, the topic model may be used to predict probabilities that words, features, documents, and/or document corpora, for example, are indicative of particular topics.

Abstract: Many computing scenarios involve the classification of content items within one or more categories. The content item set may be too large for humans to classify, but an automated classifier (e.g., an artificial neural network) may not be able to classify all content items with acceptable accuracy. Instead, the automated classifier may calculate a classification confidence while classifying respective content items. Content items having a low classification confidence may be sent to a human classifier, and may be added, along with the categories identified by the human classifier, to a training set. The automated classifier may then be retrained using the training set, thereby incrementally improving the classification confidence of the automated classifier while conserving the involvement of human classifiers. Additionally, human classifiers may be rewarded for classifying the content items, and the costs of such rewards may be considered while selecting content items for the training set.