Methods, systems, and computer program products for determining a property of construction material. According to one aspect, a material property gauge operable to determine a property of construction material is disclosed. The gauge may include an electromagnetic sensor operable to measure a response of construction material to an electromagnetic field. Further, the electromagnetic sensor may be operable to produce a signal representing the measured response by the construction material to the electromagnetic field. An acoustic detector may be operable to detect a response of the construction material to the acoustical energy. Further, the acoustic detector may be operable to produce a signal representing the detected response by the construction material to the acoustical energy. A material property calculation function may be configured to calculate a property value associated with the construction material based upon the signals produced by the electromagnetic sensor and the acoustic detector.

A method is provided for characterizing a sample, by estimating a plurality of characteristic thicknesses, each being associated with a calibration material. The method includes acquiring an energy spectrum transmitted through the sample, located in an X and/or gamma spectral band; for each spectrum of a plurality of calibration spectra, calculating a likelihood from said calibration spectrum, and from the spectrum transmitted through the sample, each calibration spectrum corresponding to the energy spectrum transmitted through a stack of gauge blocks, each formed of a known thickness of a calibration material; and estimating the characteristic thicknesses associated with the sample according to the criterion of maximum likelihood.

A method is provided for characterizing a sample, by estimating a plurality of characteristic thicknesses, each being associated with a calibration material. The method includes acquiring an energy spectrum transmitted through the sample, located in an X and/or gamma spectral band; for each spectrum of a plurality of calibration spectra, calculating a likelihood from said calibration spectrum, and from the spectrum transmitted through the sample, each calibration spectrum corresponding to the energy spectrum transmitted through a stack of gauge blocks, each formed of a known thickness of a calibration material; and estimating the characteristic thicknesses associated with the sample according to the criterion of maximum likelihood.

The present inventions provides drug-drug conjugates, drug-porphyrin conjugates, nanoparticles of the conjugates, as well as modified nanoparticles having PEGylated exteriors or encapsulated by red blood cell vesicles. The conjugates, nanoparticles and nanocarriers are useful for treating cancers and other diseases, as well as for imaging diseased tissue or organs.

The present inventions provides drug-drug conjugates, drug-porphyrin conjugates, nanoparticles of the conjugates, as well as modified nanoparticles having PEGylated exteriors or encapsulated by red blood cell vesicles. The conjugates, nanoparticles and nanocarriers are useful for treating cancers and other diseases, as well as for imaging diseased tissue or organs.

Techniques including methods, apparatus and computer program products are disclosed. These techniques include computer instructions that are encoded on computer storage media for determining wettability. The techniques use a numerical aging computation process to provide a representation of a wettability alteration of a physical rock sample in the presence of at least two fluids is disclosed. The techniques include retrieving a representation of a physical rock sample, the representation including pore space and grain space data corresponding to the physical rock sample, calculating local curvature for each surface in the pore space, determining from the calculated local curvature whether water-film breakage will occur, and classifying the wettability of the physical rock based on the determination of water-film breakage.

Techniques including methods, apparatus and computer program products are disclosed. These techniques include computer instructions that are encoded on computer storage media for determining wettability. The techniques use a numerical aging computation process to provide a representation of a wettability alteration of a physical rock sample in the presence of at least two fluids is disclosed. The techniques include retrieving a representation of a physical rock sample, the representation including pore space and grain space data corresponding to the physical rock sample, calculating local curvature for each surface in the pore space, determining from the calculated local curvature whether water-film breakage will occur, and classifying the wettability of the physical rock based on the determination of water-film breakage.

A device for the contactless determination of at least one property of a metal product during the metallurgical production of the metal product comprises a housing and at least one measuring device comprising a transmitting unit and a receiving unit. An electromagnetic field is generated by the transmitting unit and directed onto the metal product, thereby inducing a physical interaction in the material of the metal product, and a remaining and/or resulting part of this physical interaction is subsequently received by the receiving unit. At least one component of the measuring device comprising the transmitting unit and/or the receiving unit can be moved relative to the housing or the metal product moving therein, in order to thereby set or selectively change a predetermined distance to the metal product for the transmitting unit and/or the receiving unit.

Devices, systems, and methods for material characterization can include detecting definitional data from material samples that are positionally encoded according to know attributes as operational data, characterizing at least some of the samples as training data, and processing the training data via a machine learning model to train the model and/or to characterize the remaining samples based on the training data.

Devices, systems, and methods for material characterization can include detecting definitional data from material samples that are positionally encoded according to know attributes as operational data, characterizing at least some of the samples as training data, and processing the training data via a machine learning model to train the model and/or to characterize the remaining samples based on the training data.