Abstract: Target characteristic data may be predicted using an apparatus including a processor and one or more computer readable mediums collectively including instructions. When executed by the processor, the instructions cause the processor to obtain a plurality of physical structure data and a plurality of characteristic data, estimate at least one structural similarity between at least two physical structures that correspond with physical structure data among the plurality of physical structure data, and generate an estimation model for estimating a target characteristic data from a target physical structure data by using at least one characteristic data and corresponding at least one structural similarity between the target physical structure data and each of the plurality of the physical structure data.

Abstract: Systems and methods are provided for associating items based at least in part on physical location information that includes a physical location of at least two items. By associating items based at least in part on physical location information, associations among items may be identified that would otherwise be difficult to determine without usage of physical location information. In one embodiment, physical location information of various items may be collected by electronically recording the physical location of the items in a physical retail store. A degree of association may be derived from an analysis of the physical proximity between the items. The determined association information may later be used to recommend items to a user or for other purposes.

Abstract: The method aims at obtaining from waste and more particularly from municipal solid waste (MSW) the energy contained therein at the highest level for industrial use by means of natural technologies and with low environmental impact. The method, denoted by the acronym NEW (Natural Energy from Waste) operates through the following process phases: a) aerobic digestion of the putrescible biological part to produce stabilized waste which is easy to handle, b) separation of a fraction rich in materials with a high heat value, c) storage of the residue, rich in biodegradable and inert substances, compacted into appropriate geometrical shapes in bioreactors which can be activated and sealed, d) activation of the bioreactors with water and their service in time during anaerobic digestion to supply biogas to be used for the production of energy, e) bio-stabilization and dehydration of the residual material of the anaerobic treatment with air, f) possible recovery of the materials produced in this way.

Abstract: A method for measuring a degree of association (58) between, and for selectively creating a grouping (40) of, n plurality of spatially referenced physical events (22) of a predetermined physical characteristic. The method includes the steps of assembling n plurality of physical events (26), assembling a universe of possible sample locations (36), determining a reference distribution (54), determining a restricted distribution (56), and determining the degree of association (58) between the n plurality of physical events. Specifically, the physical events each have an indicia of location and a physical characteristic above a threshold. The step (54) of determining a reference distribution is conducted by calculating a test statistic (78) for each of n? plurality of random allocations (74) of the n plurality of physical events over the selected n plurality of sample locations.

Abstract: A method for measuring a degree of association (58) between, and for selectively creating a grouping (40) of, n plurality of spatially referenced physical events (22) of a predetermined physical characteristic. The method includes the steps of assembling n plurality of physical events (26), assembling a universe of possible sample locations (36), determining a reference distribution (54), determining a restricted distribution (56), and determining the degree of association (58) between the n plurality of physical events. Specifically, the physical events each have an indicia of location and a physical characteristic above a threshold. The step (54) of determining a reference distribution is conducted by calculating a test statistic (78) for each of n′ plurality of random allocations (74) of the n plurality of physical events over the selected n plurality of sample locations.

Abstract: A method for measuring a degree of association (58) between, and for selectively creating a grouping (40) of, n plurality of spatially referenced physical events (22) of a predetermined physical characteristic. The method includes the steps of assembling n plurality of physical events (26), assembling a universe of possible sample locations (36), determining a reference distribution (54), determining a restricted distribution (56), and determining the degree of association (58) between the n plurality of physical events. Specifically, the physical events each have an indicia of location and a physical characteristic above a threshold. The step (54) of determining a reference distribution is conducted by calculating a test statistic (78) for each of n′ plurality of random allocations (74) of the n plurality of physical events over the selected n plurality of sample locations.

Abstract: A method for measuring a degree of association between, and for selectively creating a grouping of, n plurality of spatially referenced physical events of a predetermined physical characteristic. The method includes the steps assembling n plurality of physical events, assembling a universe of possible sample locations, determining a reference distribution, determining a restricted distribution, and determining the degree of association between the n pluralities of physical events. Specifically, the physical events each have an indicia of location and a physical characteristic above a threshold. The step of determining a reference distribution of conducted by calculating a test statistic for each of n′ plurality of random allocations of the n plurality of physical events over the selected n plurality of sample locations.

Abstract: Butanol and acetone are major end products of a bacterial fermentation process carried out by anaerobic saccharolytic clostridia such as Clostridium acetobutylicum. However, these organisms degenerate upon repeated subculture of growing cells, thereby losing their capacity to produce solvents and to develop into spores. A novel class of degeneration-resistant mutants of C. acetobutylicum, generated by transposon insertion mutagenesis, has been produced employing a novel selection procedure. Upon subculture the mutant cells survive significantly longer than the parental cells without altered solventogenic characteristics. The mutant organism, the technique for its isolation and its use are provided.