Abstract: A computing system may create an anomaly detection model to detect anomalies in multivariate data originating from a given data source by extracting a model object for the anomaly detection model using a first set of training data originating from the given data source, establishing starting values of a set of anomaly thresholds for the anomaly detection model using the extracted model object and a second set of training data originating from the given data source, and refining the starting values of the set of anomaly thresholds for at least a subset of the variables included in the multivariate data using the extracted model object and a set of test data. In turn, the computing system may use the anomaly detection model to monitor for anomalies in observation data originating from the given data source.

Abstract: A computing system may create an anomaly detection model to detect anomalies in multivariate data originating from a given data source by extracting a model object for the anomaly detection model using a first set of training data originating from the given data source, establishing starting values of a set of anomaly thresholds for the anomaly detection model using the extracted model object and a second set of training data originating from the given data source, and refining the starting values of the set of anomaly thresholds for at least a subset of the variables included in the multivariate data using the extracted model object and a set of test data. In turn, the computing system may use the anomaly detection model to monitor for anomalies in observation data originating from the given data source.

Abstract: A computing system may operate in a first mode during which it calculates a set of training metrics on a running basis as a stream of multivariate data points originating from a data source is being received. While operating in the first mode, the computing system may determine that the set of training metrics has reached a threshold level of stability. In response, the computing system may transition to a second mode during which its extracts a model object and calculates a set of model parameters for an anomaly detection model. While operating in the second mode, the computing system may determine that the set of model parameters has reached a threshold level of stability. In response, the computing system may transition to a third mode during which it uses the anomaly detection model to monitor for anomalies in the stream of multivariate data points originating from the data source.

Abstract: A method including receiving data including first searchable data segments and non-searchable data segments, identifying the non-searchable data segments within the data, determining coordinates for the non-searchable data segments relative to the first searchable data segments, extracting the non-searchable data segments, processing the non-searchable data segments, the processing including converting the non-searchable data segments into second searchable data segments, overlaying the second searchable data segments at the determined coordinates relative to the first searchable data segments and exporting the first searchable data segments and the second searchable data segments.

Abstract: A portable cooling system for use with a semiconductor fabrication system having a heating block is provided. A portable cooling system, consistent with one embodiment of the invention, includes a support structure removably mountable on part of the semiconductor fabrication system and near the heating block of the fabrication system. Disposed on the support structure are one or more fans for blowing air over the heating block. In one embodiment, the support structure includes a plate and a plurality of legs which extend down from the plate for mounting on the heating block. In another embodiment, the support structure includes a plate and means for mounting the plate on one or more walls of the semiconductor fabrication system. The portable cooling system facilitates the cooling of the heating block of the fabrication system and can, for example, significantly reduce the time spent cleaning the semiconductor fabrication system as compared to conventional cleaning techniques.

Abstract: The present invention provides a recombinant combination strain which is capable of over-expressing at least two different genes under two separate promoters in filamentous fungi. The genes encode phytase and pH 2.5 acid phosphatase. Mixtures containing desired ratios of the two enzymes are prepared by recombinant DNA techniques. The enzyme mixtures show a cooperative effect in the degradation of phytic acid and its salts. The preferred ratios of the two enzymes are from about 3:1 to about 16:1.

Abstract: The present invention provides a nucleic acid molecule encoding a phytase. The present invention also provides a nucleic acid molecule encoding a pH 2.5 acid phosphatase. Also provided are vectors, host cells, and a method of overexpressing phytate degrading enzymes.

Abstract: A highly efficient overexpression system for phytase and pH 2.5 acid phosphatase in Trichoderma is described. This system results in enzyme compositions that are especially useful in the animal feed industry.

Abstract: A process for preparing bovine interleukin-2 (bIL-2) by culturing a microbial host transformed by a vector containing a DNA sequence encoding bIL-2 under conditions suitable for the expression of bIL-2 and recovering bIL-2.

Abstract: A chemically-synthesized oligonucleotide composing a portion of the nucleotide sequence of the human IL-2 is employed as a probe to isolate the gene coding for human IL-2. The human IL-2 gene is selected from a cDNA library prepared from RNA produced by mitogen-stimulated Jurkat cells. Double-stranded cDNA is prepared from polyadenylated RNA extracted from bovine cells thought to produce interleukin-2. Such cDNA is inserted within a plasmid vector and the recombinant plasmid employed to transform hosts. Plasmid DNA, prepared from pools of the transformed hosts, is hybridized with a probe composed of a large portion of the coding sequence of the human IL-2 gene. Pools of host cells that provide signal to the human cDNA probe are identified, subdivided, and rescreened until a single positive colony is identified. Bovine plasmid cDNA is prepared from this colony, and the bIL-2 gene is sequenced.