Abstract: Certain aspects involve optimizing neural networks or other models for assessing risks and generating explanatory data regarding predictor variables used in the model. In one example, a system identifies predictor variables. The system generates a neural network for determining a relationship between each predictor variable and a risk indicator. The system performs a factor analysis on the predictor variables to determine common factors. The system iteratively adjusts the neural network so that (i) a monotonic relationship exists between each common factor and the risk indicator and (ii) a respective variance inflation factor for each common factor is sufficiently low. Each variance inflation factor indicates multicollinearity among the common factors. The adjusted neural network can be used to generate explanatory indicating relationships between (i) changes in the risk indicator and (ii) changes in at least some common factors.

Abstract: A method protects a daemon in an operating system of a host computer. The operating system detects that there is an access of a plist file of a daemon by a process in the computer. If so, then it executes a callback function registered for the plist file. The callback function sends to a kernel extension a notification of the attempted access. The kernel extension returns a value to the operating system indicating that the access should be denied. The operating system denies access to the plist file of the daemon by the process. The extension may also notify an application which prompts the user for instruction. The kernel extension also protects itself by executing its exit function when a command is given to unload the extension, and the exit function determines whether or not the command is invoked by an authorized application, such as by checking a flag.

Abstract: Certain aspects involve optimizing neural networks or other models for assessing risks and generating explanatory data regarding predictor variables used in the model. In one example, a system identifies predictor variables. The system generates a neural network for determining a relationship between each predictor variable and a risk indicator. The system performs a factor analysis on the predictor variables to determine common factors. The system iteratively adjusts the neural network so that (i) a monotonic relationship exists between each common factor and the risk indicator and (ii) a respective variance inflation factor for each common factor is sufficiently low. Each variance inflation factor indicates multicollinearity among the common factors. The adjusted neural network can be used to generate explanatory indicating relationships between (i) changes in the risk indicator and (ii) changes in at least some common factors.

Abstract: Certain aspects involve optimizing neural networks or other models for assessing risks and generating explanatory data regarding predictor variables used in the model. In one example, a system identifies predictor variables. The system generates a neural network for determining a relationship between each predictor variable and a risk indicator. The system performs a factor analysis on the predictor variables to determine common factors. The system iteratively adjusts the neural network so that (i) a monotonic relationship exists between each common factor and the risk indicator and (ii) a respective variance inflation factor for each common factor is sufficiently low. Each variance inflation factor indicates multicollinearity among the common factors. The adjusted neural network can be used to generate explanatory indicating relationships between (i) changes in the risk indicator and (ii) changes in at least some common factors.

Abstract: Certain aspects involve optimizing neural networks or other models for assessing risks and generating explanatory data regarding predictor variables used in the model. In one example, a system identifies predictor variables compliant with certain monotonicity constraints. The system generates a neural network for determining a relationship between each predictor variable and a risk indicator. The system performs a factor analysis on the predictor variables to determine common factors. The system iteratively adjusts the neural network so that (i) a monotonic relationship exists between each common factor and the risk indicator and (ii) a respective variance inflation factor for each common factor is sufficiently low. Each variance inflation factor indicates multicollinearity among a subset of the predictor variables corresponding to a common factor.

Abstract: Certain aspects involve optimizing neural networks or other models for assessing risks and generating explanatory data regarding predictor variables used in the model. In one example, a system identifies predictor variables compliant with certain monotonicity constraints. The system generates a neural network for determining a relationship between each predictor variable and a risk indicator. The system performs a factor analysis on the predictor variables to determine common factors. The system iteratively adjusts the neural network so that (i) a monotonic relationship exists between each common factor and the risk indicator and (ii) a respective variance inflation factor for each common factor is sufficiently low. Each variance inflation factor indicates multicollinearity among a subset of the predictor variables corresponding to a common factor.

Abstract: The present invention relates to methods for the design and/or production of a probe or primer that is capable of hybridizing to a plurality of sites in a sample comprising nucleic acid. Furthermore, the present invention provides methods for detecting and amplifying nucleic acid using such a probe or primer, for example, for identification of a strain, species or genera. Probe or primer sequences are determined by reference to codon usage bias of a target nucleic acid. In addition, the present invention provides methods for determining codon distribution and/or base pair distance between codons in a nucleic acid.

Abstract: Compositions having carbon nanotubes and two or more graphene sheets are disclosed. The carbon nanotubes can be interposed between the graphene sheets within the composition. Applicants have surprisingly found that, in some embodiments, these compositions exhibit superior absorbent and/or electrical properties. The present application also includes methods of making and using these compositions, and capacitors including these compositions.

Abstract: Methods are disclosed for manufacturing carbon rods from lignin scrap and for using such lignin-derived carbon rods for manufacturing carbon nanotubes in an arc discharge process.

Abstract: Compositions having carbon nanotubes and two or more graphene sheets are disclosed. The carbon nanotubes can be interposed between the graphene sheets within the composition. Applicants have surprisingly found that, in some embodiments, these compositions exhibit superior absorbent and/or electrical properties. The present application also includes methods of making and using these compositions, and capacitors including these compositions.

Abstract: Methods are disclosed for manufacturing carbon rods from lignin scrap and for using such lignin-derived carbon rods for manufacturing carbon nanotubes in an arc discharge process.

Abstract: The present application relates to methods of making a chemical sensor including dispersing mesoporous silica structures, an organic solvent, and water to form a composition; and combining one or more chemical sensing molecules with the composition. In some embodiments, the composition includes not more than about 0.6 g of water relative to about 1 g of the mesoporous silica structures. In some embodiments, the chemical sensing molecules include a silane coupling group coupled to a chemical sensing group. Also discloses herein are chemical sensors and methods of using the chemical sensors. The chemical sensors may, in some embodiments, exhibit superior detection of one or more analytes.

Abstract: An apparatus for synthesizing highly oriented, aligned carbon nanotubes from an alcohol includes a liquid tank for retaining an alcohol; a water cooling device for cooling the liquid tank from its outside; a condensing device for cooling and condensing vapor from the alcohol; a substrate holding device having an electrode for passing an electric current through the substrate in the alcohol; an inert gas inlet for removing air; a tank sealing device to prevent the alcohol becoming gaseous in phase; and a temperature measuring device, wherein the Si substrate with a buildup thereon of the thin film or insular particles is heated by electric current to a temperature, thereby providing a temperature gradient from the Si substrate surface toward the alcohol, wherein said thin film or insular particles is a catalyst for synthesizing carbon nanotubes, and the carbon nanotubes are synthesized.

Abstract: The present invention relates to methods for the design and/or production of a probe or primer that is capable of hybridizing to a plurality of sites in a sample comprising nucleic acid. Furthermore, the present invention provides methods for detecting and amplifying nucleic acid using such a probe or primer, for example, for identification of a strain, species or genera. Probe or primer sequences are determined by reference to codon usage bias of a target nucleic acid. In addition, the present invention provides methods for determining codon distribution and/or base pair distance between codons in a nucleic acid.

Abstract: A method is disclosed whereby a functional nanomaterial such as a monolayer carbon nanotube, a monolayer boron nitride nanotube, a monolayer silicon carbide nanotube, a multilayer carbon nanotube with the number of layers controlled, a multilayer boron nitride nanotube with the number of layers controlled, a multilayer silicon carbide nanotube with the number of layers controlled, a metal containing fullerene, and a metal containing fullerene with the number of layers controlled is produced at a high yield. According to the method, when a multilayer carbon nanotube (3) is formed by a chemical vapor deposition or a liquid phase growth process, an endothermic reaction aid (H2S) is introduced in addition to a primary reactant (CH4, H2) in the process to form a monolayer carbon nanotube (4).

Abstract: A method is disclosed whereby a functional nanomaterial such as a monolayer carbon nanotube, a monolayer boron nitride nanotube, a monolayer silicon carbide nanotube, a multilayer carbon nanotube with the number of layers controlled, a multilayer boron nitride nanotube with the number of layers controlled, a multilayer silicon carbide nanotube with the number of layers controlled, a metal containing fullerene, and a metal containing fullerene with the number of layers controlled is produced at a high yield. According to the method, when a multilayer carbon nanotube (3) is formed by a chemical vapor deposition or a liquid phase growth process, an endothermic reaction aid (H2S) is introduced in addition to a primary reactant (CH4, H2) in the process to form a monolayer carbon nanotube (4).

Abstract: A method is disclosed whereby a functional nanomaterial such as a monolayer carbon nanotube, a monolayer boron nitride nanotube, a monolayer silicon carbide nanotube, a multilayer carbon nanotube with the number of layers controlled, a multilayer boron nitride nanotube with the number of layers controlled, a multilayer silicon carbide nanotube with the number of layers controlled, a metal containing fullerene, and a metal containing fullerene with the number of layers controlled is produced at a high yield. According to the method, when a multilayer carbon nanotube (3) is formed by a chemical vapor deposition or a liquid phase growth process, an endothermic reaction aid (H2S) is introduced in addition to a primary reactant (CH4, H2) in the process to form a monolayer carbon nanotube (4).

Abstract: A method capable of synthesizing carbon nanotubes at low cost and large quantities, an apparatus usable for carrying out the method, and carbon nanotubes densely aligned on and firmly bonded to a Si substrate over, and oriented perpendicular to, an entire surface thereof are provided. Highly oriented, aligned carbon nanotubes are synthesized from an organic liquid by forming a substrate with a buildup thereon of a thin film or fine insular particles composed of at least one metallic element; exposing the substrate (3) having the buildup to a hydrogen plasma; and heating the substrate (3) exposed to the hydrogen plasma in the organic liquid (10) to a predetermined temperature.

Abstract: A method capable of synthesizing carbon nanotubes at low cost and large quantities, an apparatus usable for carrying out the method, and carbon nanotubes densely aligned on and firmly bonded to a Si substrate over, and oriented perpendicular to, an entire surface thereof are provided. Highly oriented, aligned carbon nanotubes are synthesized from an organic liquid by forming a substrate with a buildup thereon of a thin film or fine insular particles composed of at least one metallic element; exposing the substrate (3) having the buildup to a hydrogen plasma; and heating the substrate (3) exposed to the hydrogen plasma in the organic liquid (10) to a predetermined temperature.

Abstract: 3C-SiC nanowhisker and a method of synthesizing 3C-SiC nanowhisker wherein its diameter and length can be controlled. The method is safe and low cost, and the whisker can emit visible light of various wavelengths. 3C-SiC nanowhisker is formed by depositing thin film (2) made of a metal element on Si substrate (1), placing this Si substrate (1) into a plasma CVD apparatus, and holding it for predetermined time at predetermined substrate temperature in the plasma consisting of hydrogen and hydrocarbon. Si of Si substrate (1) and C in plasma dissolve at supersaturation into metal liquid particles (3), 3C-SiC nanowhisker (4) grows on the metal liquid particles (3), whisker surface is terminated with H so as to maintain the diameter constant, and the metal liquid particles (3) at whisker root take in Si from Si substrate (1) and penetrate into Si substrate (1).