Abstract: An electrosurgical instrument capable of performing both thermal ablation and electroporation in a minimally invasive manner. The instrument is dimensioned to fit within an instrument channel of an endoscope to enable non-percutaneous insertion. The instrument comprises a radiating tip mounted at a distal end of a coaxial transmission line to receive microwave EM energy from the coaxial transmission line and emit it as a field around the radiating tip. The instrument further comprises an auxiliary transmission line arranged to convey electromagnetic energy having an electroporation waveform to a microelectrode array mounted on the radiating tip. The electroporation waveform may be a radiofrequency or low frequency electromagnetic (EM) signal. The microelectrode array may comprise a plurality of nanoscale conductive electrode elements.

Abstract: The disclosure relates to a sterilization apparatus which uses thermal or non-thermal plasma to disinfect surgical scoping devices such as endoscopes, gastroscopes, laparoscopes and the like. Aspect of the disclosure provide: (i) an apparatus for sterilizing inside an instrument channel formed with an insertion tube of a surgical scoping device, (ii) a whole-device sterilization apparatus for treating the entire exterior surface of a surgical scoping device, and (iii) an apparatus for cleaning and sterilizing a distal end face of an insertion tube of a surgical scoping device.

Abstract: A treatment apparatus which uses thermal or non-thermal plasma to treat urinary tract infections (UTIs) by destroying bacteria. The apparatus comprises an elongate probe that includes a coaxial cable for conveying radiofrequency (RF) electromagnetic (EM) energy and/or microwave EM energy, a probe tip connected at the distal end of the coaxial cable for receiving the RF and/or microwave EM energy, and a gas conduit for conveying gas to the probe tip. The probe tip comprises a first electrode connected to the inner conductor of the coaxial cable, and a second electrode connected to the outer conductor of the coaxial cable, and wherein the first electrode and second electrode are arranged to produce an electric field from the received RF and/or microwave EM energy across a flow path of gas received from the gas conduit to produce a thermal or a non-thermal plasma.

Abstract: The invention relates to processes for preparing isoindolin-1-one derivatives, and in particular processes for preparing (2S,3S)-3-(4-chlorophenyl)-3-[(1R)-1-(4-chlorophenyl)-7-fluoro-5-[(1S)-1-hydroxy-1-(oxan-4-yl)propyl]-1-methoxy-3-oxo-2,3-dihydro-1H-isoindol-2-yl]-2-methylpropanoic acid. The invention also relates to crystalline forms of the compound (2S,3S)-3-(4-chlorophenyl)-3-[(1R)-1-(4-chlorophenyl)-7-fluoro-5-[(1S)-1-hydroxy-1-(oxan-4-yl)propyl]-1-methoxy-3-oxo-2,3-dihydro-1H-isoindol-2-yl]-2-methylpropanoic acid and its salts.

Abstract: The invention relates to processes for preparing isoindolin-1-one derivatives, and in particular processes for preparing (2S,3S)-3-(4-chlorophenyl)-3-[(1R)-1-(4-chlorophenyl)-7-fluoro-5-[(1S)-1-hydroxy-1-(oxan-4-yl)propyl]-1-methoxy-3-oxo-2,3-dihydro-1H-isoindol-2-yl]-2-methylpropanoic acid. The invention also relates to crystalline forms of the compound (2S,3S)-3-(4-chlorophenyl)-3-[(1R)-1-(4-chlorophenyl)-7-fluoro-5-[(1S)-1-hydroxy-1-(oxan-4-yl)propyl]-1-methoxy-3-oxo-2,3-dihydro-1H-isoindol-2-yl]-2-methylpropanoic acid and its salts.

Abstract: The invention relates to processes for preparing isoindolin-1-one derivatives, and in particular processes for preparing (2S,3S)-3-(4-chlorophenyl)-3-[(1R)-1-(4-chlorophenyl)-7-fluoro-5-[(1S)-1-hydroxy-1-(oxan-4-yl)propyl]-1-methoxy-3-oxo-2,3-dihydro-1H-isoindol-2-yl]-2-methylpropanoic acid. The invention also relates to crystalline forms of the compound (2S,3S)-3-(4-chlorophenyl)-3-[(1R)-1-(4-chlorophenyl)-7-fluoro-5-[(1S)-1-hydroxy-1-(oxan-4-yl)propyl]-1-methoxy-3-oxo-2,3-dihydro-1H-isoindol-2-yl]-2-methylpropanoic acid and its salts.

Abstract: An enhanced multi object potting fixture for exposure to a curing modality that sets an adhesive includes a fixture housing supporting a plurality of objects, the fixture housing having a wall defining a plurality of bonding wells with each the bonding well receiving a first portion of one of the objects, each the bonding well including an aperture in the wall proximate the first portion wherein each bonding well includes a target zone for selective cure of the adhesive to inhibit the adhesive from exiting the aperture; and a fixture enhancement structure integrated into the wall concentrating the curing modality in each the target zone.

Abstract: A system and method for generating frequency-multiplexed synthetic sound-speech stimuli and for detecting and analyzing electrical brain activity of a subject in response to the stimuli. Frequency-multiplexing of speech copora and synthetic sounds helps the composite sound to blend into a single auditory object. The synthetic sounds are temporally aligned with the utterances of the speech corpus. Frequency multiplexing may include splitting the frequency axis into alternating bands of speech and synthetic sound to minimize the disruptive interaction between the speech and synthetic sounds along the basilar membrane and in their neural representations. The generated stimuli can be used with both traditional and advanced techniques to analyze electrical brain activity and provides a rapid, synoptic view into the functional health of the early auditory system, including how speech is processed at different levels and how these levels interact.

Abstract: An enhanced multi object potting fixture for exposure to a curing modality that sets an adhesive includes a fixture housing supporting a plurality of objects, the fixture housing having a wall defining a plurality of bonding wells with each the bonding well receiving a first portion of one of the objects, each the bonding well including an aperture in the wall proximate the first portion wherein each bonding well includes a target zone for selective cure of the adhesive to inhibit the adhesive from exiting the aperture; and a fixture enhancement structure integrated into the wall concentrating the curing modality in each the target zone.

Abstract: An enhanced multiobject potting fixture for exposure to a curing modality that sets an adhesive includes a fixture housing supporting a plurality of objects, the fixture housing having a wall defining a plurality of bonding wells with each the bonding well receiving a first portion of one of the objects, each the bonding well including an aperture in the wall proximate the first portion wherein each bonding well includes a target zone for selective cure of the adhesive to inhibit the adhesive from exiting the aperture; and a fixture enhancement structure integrated into the wall concentrating the curing modality in each the target zone.

Abstract: An enhanced multiobject potting fixture for exposure to a curing modality that sets an adhesive includes a fixture housing supporting a plurality of objects, the fixture housing having a wall defining a plurality of bonding wells with each the bonding well receiving a first portion of one of the objects, each the bonding well including an aperture in the wall proximate the first portion wherein each bonding well includes a target zone for selective cure of the adhesive to inhibit the adhesive from exiting the aperture; and a fixture enhancement structure integrated into the wall concentrating the curing modality in each the target zone.

Abstract: The present invention relates to the synthesis of intermediates for the preparation of compounds of formula (A): wherein n is 2 or 3 and various salt forms of these compounds.

Abstract: The present invention is directed to the improved synthesis of compounds of formula (I) an intermediate compound which is useful in the synthesis of the anticancer agents known as PSA conjugates.

Abstract: A Bayesian approach to training in conditional random fields takes a prior distribution over the modeling parameters of interest. These prior distributions may be used to generate an approximate form of a posterior distribution over the parameters, which may be trained with example or training data. Automatic relevance determination (ARD) may be integrated in the training to automatically select relevant features of the training data. From the trained posterior distribution of the parameters, a posterior distribution over the parameters based on the training data and the prior distributions over parameters may be approximated to form a training model. Using the developed training model, a given image may be evaluated by integrating over the posterior distribution over parameters to obtain a marginal probability distribution over the labels given that observational data.

Abstract: A discriminative machine learning system for labels text and non-text strokes in digital ink. The learning system considers stroke features and the context of the strokes, such as temporal information about one or more strokes, in a probabilistic framework. The learning system can also consider gap features within the probabilistic framework to label associated strokes.

Abstract: It is common in distributed systems to replicate data. In many cases, this data evolves in a consistent fashion, and this evolution can be modeled. A probabilistic model of the evolution allows us to estimate the divergence of the replicas and can be used by the application to alter its behavior, for example, to control synchronization times, to determine the propagation of writes, and to convey to the user information about how much the data may have evolved. In this paper, we describe how the evolution of the data may be modeled and outline how the probabilistic model may be utilized in various applications, concentrating on a news database example.

Abstract: A Bayesian treatment of mixture models is based on individual components having Student distributions, which have heavier tails compared to the exponentially decaying tails of Gaussians. The mixture of Student distribution components is characterized by a set of modeling parameters. Tractable approximations of the posterior distributions of individual modeling parameters are optimized and used to generate a data model for a set of input data.

Abstract: A variational Relevance Vector Machine (RVM) is disclosed. The RVM is a probabilistic basis model. Sparsity is achieved through a Bayesian treatment, where a prior is introduced over the weights governed by a set of what are referred to as hyperparameters—one such hyperparameter associated with each weight. An approximation to the joint posterior distribution over weights and hyperparameters is iteratively estimated from the data. The posterior distribution of many of the weights is sharply peaked around zero, in practice. The variational RVM utilizes a variational approach to solve the model, in particular using product approximations to obtain the posterior distribution.

Abstract: Bayesian principal component analysis. In one embodiment, a computer-implemented method for performing Bayesian PCA including inputting a data model; receiving a prior distribution of the data model; determining a posterior distribution; generating output data based on the posterior distribution (such as, a data model, a plurality of principal components, and/or a distribution); and, outputting the output data. In another embodiment, a computer-implemented method including inputting a mixture of a plurality of data spaces; determining a maximum number of principal components for each of the data spaces within the mixture; and, outputting the maximum number of principal components for each of the data spaces within the mixture.

Abstract: A variational inference engine for probabilistic graphical models is disclosed. In one embodiment, a method includes inputting a specification for a model that has observable variables and unobservable variables. The specification includes a functional form for the conditional distributions of the model, and a structure for a graph of model that has nodes for each of the variables. The method determines a distribution for the unobservable variables that approximates the exact posterior distribution, based on the graph's structure and the functional form for the model's conditional distributions. The engine thus allows a user to design, implement and solve models without mathematical analysis or computer coding.