Abstract: An implant for fusing a joint between first and second bone portions. The implant includes a screw member, and a washer polyaxially rotatable relative to the screw member. The screw member includes a head, a lag zone, and a threaded engagement zone. The implant includes a fusion zone for joint compression, extending from the washer to the proximal end of the engagement zone. Fenestrations may be present in the fusion zone. The length of the fusion zone ranges from about 10 mm to about 37 mm. Different surface finishes including roughened and non-roughened may be applied selectively to selected portions of the implant. In an embodiment, the joint is a sacro-iliac joint, and upon implantation the implant extends from the exterior of the ilium, across the joint and into the sacral vertebral body. Instrumentation and methods for preparing the joint and implanting the implant are disclosed.

Abstract: Dynamic data dissemination is provided. A resolved data subject identifier corresponding to a data subject is selected from a set of resolved data subject identifiers existing in rows of a data asset. In response to determining that the resolved data subject identifier does not correspond to a right to forget list, it is determined that the resolved data subject identifier corresponds to a data subject request list. The rows are transformed to anonymize existing pseudo and personal identifiers in cells of the rows that are tied to columns associated with data classes for which specific consent dimensions have been indicated as revoked by the data subject.

Abstract: Techniques for data evaluation are provided. A plurality of data records is received, and a first comparison vector is generated by comparing a first and a second data record of the plurality of data records, where the first comparison vector indicates differences between the first and second data records. A machine learning model is trained based at least in part on the first comparison vector. The plurality of data records is evaluated using the machine learning model, and at least two of the plurality of data records are linked based on the evaluation.

Abstract: Provided is a method, computer program product, and system for automatically predicting unknown semantic data types in a rectangular dataset using a holistic knowledge of said dataset. A processor may receive one or more rectangular datasets, the one or more rectangular datasets comprising a plurality of columns having a set of known semantic data types. The processor may extract a set of features from the plurality of columns, where the set of features is used to determine a relationship among each column of the plurality of columns. The processor may construct a set of training data based on the extracted set of features. Using the training data, the processor may train a machine learning model to predict a semantic data type of a target column in a rectangular dataset having an unknown semantic data type.

Abstract: Dynamic data dissemination is provided. A resolved data subject identifier corresponding to a data subject is selected from a set of resolved data subject identifiers existing in rows of a data asset. In response to determining that the resolved data subject identifier does not correspond to a right to forget list, it is determined that the resolved data subject identifier corresponds to a data subject request list. The rows are transformed to anonymize existing pseudo and personal identifiers in cells of the rows that are tied to columns associated with data classes for which specific consent dimensions have been indicated as revoked by the data subject.

Abstract: An apparatus and related method defend against adversarial queries. A policy enforcement hypergraph is constructed to express a set of security policies. Then, the hypergraph is repeatedly traversed to determine whether a user behavior is changing over time. The user behavior is measured by reference to a vertex or an edge in the hypergraph. If it is determined that the user behavior has changed over time an enforcement action is taken based on a security policy.

Abstract: Provided is a method, computer program product, and system for automatically predicting unknown semantic data types in a rectangular dataset using a holistic knowledge of said dataset. A processor may receive one or more rectangular datasets, the one or more rectangular datasets comprising a plurality of columns having a set of known semantic data types. The processor may extract a set of features from the plurality of columns, where the set of features is used to determine a relationship among each column of the plurality of columns. The processor may construct a set of training data based on the extracted set of features. Using the training data, the processor may train a machine learning model to predict a semantic data type of a target column in a rectangular dataset having an unknown semantic data type.

Abstract: Enforcement of policies for tabular data access as a collection of columns over a plurality of different information assets is provided. In an enforcement knowledge graph, information asset-assigned terms are found that correspond to information assets in a virtual information asset that references a set of tabular data. Transitive closures of the information asset-assigned terms are found in a business glossary to form a table of business glossary terms. Term intersection is determined between a hash table of any column-assigned terms and the table of business glossary terms. The information assets are assigned to the virtual information asset when the term intersection is not empty. A set of policy rules associated with the set of tabular data and a context of a user making a data access request to the set of tabular data is applied to the virtual information asset to determine an access enforcement decision.

Abstract: Predicting access impact of a plurality of rule changes on a corpus of information assets is provided. A set of affected rules in a new rule space for controlling access to the corpus of information assets is received. The set of affected rules is shredded to identify right-hand side terms contained in predication blocks of the set of affected rules. An enforcement knowledge graph is traversed to identify a set of hot information assets having same terms as the right-hand side terms of the set of affected rules. The set of hot information assets having the same terms as the right-hand side terms of the set of affected rules is added to a hash table of hot information assets.

Abstract: Candidate data record prioritization for match processing includes identifying candidate records for use in match processing to determine records that match to an incoming record. The candidates are grouped into buckets according to bucket roles, with each bucket correlating to a bucket role, and with each bucket role being defined by a unique record attribute set. The method obtains an effectiveness score for each of the bucket roles. The scores are measures of effectiveness of the bucket roles in identifying candidates that match to incoming data records. The method establishes an order of priority in which to process the candidates by prioritizing the buckets into an order based on the effectiveness scores for the bucket roles. The process then commences match processing to process the candidates in the established order of priority where the match processing processes candidates of a higher priority bucket before processing candidates of lower priority buckets.

Abstract: The present disclosure relates to a method for a secure storage, matching and linking of data records. The method comprises: receiving a current data record having one or more attributes, each attribute having an attribute value. For each attribute of at least part of the attributes a predefined set of variations of the attribute value of the attribute may be generated. The received attribute values may be encrypted resulting in an encrypted record and the generated sets of variations may be encrypted. The encrypted record may be stores in a storage system in association with the respective encrypted sets of variations.

Abstract: An implant for fusing a joint between first and second bone portions. The implant includes a screw member, and a washer polyaxially rotatable relative to the screw member. The screw member includes a head, a lag zone, and a threaded engagement zone. The implant includes a fusion zone for joint compression, extending from the washer to the proximal end of the engagement zone. Fenestrations may be present in the fusion zone. The length of the fusion zone ranges from about 10 mm to about 37 mm. Different surface finishes including roughened and non-roughened may be applied selectively to selected portions of the implant. In an embodiment, the joint is a sacro-iliac joint, and upon implantation the implant extends from the exterior of the ilium, across the joint and into the sacral vertebral body. Instrumentation and methods for preparing the joint and implanting the implant are disclosed.

Abstract: A method trains a neural network to recognize whether a resource is authorized to be returned to a requester. One or more processors train a neural network to traverse a policy enforcement hypergraph in order to identify a security policy to be used for a resource request and to authorize a use of a requested resource by a requester. The policy enforcement hypergraph is derived from a policy enforcement graph that expresses a set of security profiles for resources and requesters. The processor(s) receive a resource request for a requested resource from a requester, where the resource request includes a description of the requester. A system/user inputs a description of the received resource request and a description of the policy enforcement hypergraph into the trained neural network in order to selectively return the requested resource to the requester.

Abstract: Cross-matching of match indexes assigned to respective data sources can be performed. Each match index can store at least a portion of data from a subset of data records in the data source to which the match index is assigned. Such data can be stored in the match index as match index records. Responsive to identifying matches between match records of different match indexes, the data records in the data sources to which the match records correspond can be updated to add links between the respective data records.

Abstract: A method trains a neural network to recognize whether a resource is authorized to be returned to a requester. One or more processors train a neural network to traverse a policy enforcement hypergraph in order to identify a security policy to be used for a resource request and to authorize a use of a requested resource by a requester. The policy enforcement hypergraph is derived from a policy enforcement graph that expresses a set of security profiles for resources and requesters. The processor(s) receive a resource request for a requested resource from a requester, where the resource request includes a description of the requester. A system/user inputs a description of the received resource request and a description of the policy enforcement hypergraph into the trained neural network in order to selectively return the requested resource to the requester.

Abstract: An implant for fusing a joint between first and second bone portions. The implant includes a screw member, and a washer polyaxially rotatable relative to the screw member. The screw member includes a head, a lag zone, and a threaded engagement zone. The implant includes a fusion zone for joint compression, extending from the washer to the proximal end of the engagement zone. Fenestrations may be present in the fusion zone. The length of the fusion zone ranges from about 10 mm to about 37 mm. Different surface finishes including roughened and non-roughened may be applied selectively to selected portions of the implant. In an embodiment, the joint is a sacro-iliac joint, and upon implantation the implant extends from the exterior of the ilium, across the joint and into the sacral vertebral body. Instrumentation and methods for preparing the joint and implanting the implant are disclosed.

Abstract: Techniques for data evaluation are provided. A plurality of data records is received, and a first comparison vector is generated by comparing a first and a second data record of the plurality of data records, where the first comparison vector indicates differences between the first and second data records. A machine learning model is trained based at least in part on the first comparison vector. The plurality of data records is evaluated using the machine learning model, and at least two of the plurality of data records are linked based on the evaluation.

Abstract: Embodiments of the present invention provides methods, computer program products, and systems for normalizing confidence score thresholds across systems in a federated environment. Embodiments of the present invention can be used to calculate normalization factors for participating hubs in a federated environment to normalize confidence score thresholds applied by those hubs and improve search results obtained therefrom.

Abstract: Provided are a computer program product, system, and method to determine whether to perform entity resolution on vertices in an entity graph. A determination is made of pairs of records in a database having a relationship value satisfying a threshold. An entity relationship graph has a vertex for each of the records of the pairs and an edge between two vertices. Each vertex has a self-information score based on content in the record, an initial unique entity identifier, and an entity information score. For each subject vertex of the vertices, a determination is made of a target vertex directly connected to the subject vertex that has a highest entity information score and whether to set the subject vertex entity identifier and entity information score to the entity identifier and entity information score of the target vertex based on the target vertex self-information score.

Abstract: Enforcement of policies for tabular data access as a collection of columns over a plurality of different information assets is provided. In an enforcement knowledge graph, information asset-assigned terms are found that correspond to information assets in a virtual information asset that references a set of tabular data. Transitive closures of the information asset-assigned terms are found in a business glossary to form a table of business glossary terms. Term intersection is determined between a hash table of any column-assigned terms and the table of business glossary terms. The information assets are assigned to the virtual information asset when the term intersection is not empty. A set of policy rules associated with the set of tabular data and a context of a user making a data access request to the set of tabular data is applied to the virtual information asset to determine an access enforcement decision.