The disclosure provides methods of managing opioid therapy, particularly, for pain management. The methods comprise determining in a subject, for example, a subject who has received an opioid treatment, pupillary unrest in ambient light (PUAL). Low values of PUAL can be used to identify patients at risk for opioid side-effects, such as opioid-related respiratory depression (OIRD), and who warrant attention to prevent such side effects. Accordingly, the methods include monitoring the patients having low values of PUAL for signs of adverse side-effects and/or limiting or avoiding administration of opioids.

The disclosure provides methods of managing opioid therapy, particularly, for pain management. The methods comprise determining in a subject, for example, a subject who has received an opioid treatment, pupillary unrest in ambient light (PUAL). Low values of PUAL can be used to identify patients at risk for opioid side-effects, such as opioid-related respiratory depression (OIRD), and who warrant attention to prevent such side effects. Accordingly, the methods include monitoring the patients having low values of PUAL for signs of adverse side-effects and/or limiting or avoiding administration of opioids.

In an example, a thermal imaging test article comprises a block configured to be attached to a blackbody on a back side of the block, the block having a variable thickness to represent facial features of a human face, the block including a cutout to allow a thermal imaging device to see the blackbody behind the block through the cutout, and one or more heaters thermally coupled to the block to produce heat to heat the block. The variable thickness of the block and the heat produced by the one or more heaters are selected to simulate thermally the human face on a front side of the block.

In an example, a thermal imaging test article comprises a block configured to be attached to a blackbody on a back side of the block, the block having a variable thickness to represent facial features of a human face, the block including a cutout to allow a thermal imaging device to see the blackbody behind the block through the cutout, and one or more heaters thermally coupled to the block to produce heat to heat the block. The variable thickness of the block and the heat produced by the one or more heaters are selected to simulate thermally the human face on a front side of the block.

A fault state detection apparatus includes an input unit and a processing unit. The input unit receives condition monitoring data. The processing unit implements a trained machine learning algorithm to analyze the received condition monitoring data to determine if the received condition monitoring data is associated with a fault state. The trained machine learning algorithm was trained on the basis of a plurality of non-fault state condition monitoring data and associated ground truth information and on the basis of a plurality of fault state condition monitoring data and associated ground truth information. A subset of the plurality of fault state condition monitoring data was generated from one or more non-fault state condition monitoring data. Generation of fault state conditioning monitoring data in the subset of the plurality of fault state condition monitoring data comprises a transformation of non-fault state condition monitoring data to fault state condition monitoring data.

A fault state detection apparatus includes an input unit and a processing unit. The input unit receives condition monitoring data. The processing unit implements a trained machine learning algorithm to analyze the received condition monitoring data to determine if the received condition monitoring data is associated with a fault state. The trained machine learning algorithm was trained on the basis of a plurality of non-fault state condition monitoring data and associated ground truth information and on the basis of a plurality of fault state condition monitoring data and associated ground truth information. A subset of the plurality of fault state condition monitoring data was generated from one or more non-fault state condition monitoring data. Generation of fault state conditioning monitoring data in the subset of the plurality of fault state condition monitoring data comprises a transformation of non-fault state condition monitoring data to fault state condition monitoring data.

A light detection device includes a Fabry-Perot interference filter, a light detector, a spacer that has a placement surface on which a portion outside a light transmission region in a bottom surface of the interference filter is placed, and an adhesive member that adheres the interference filter and the spacer to each other. Elastic modulus of the adhesive member is smaller than elastic modulus of the spacer. At least a part of a lateral surface of the interference filter is located on the placement surface such that a part of the placement surface of the spacer is disposed outside the lateral surface. The adhesive member is disposed in a corner portion formed by the lateral surface of the interference filter and the part of the placement surface of the spacer and contacts each of the lateral surface and the part of the placement surface.

A light detection device includes a Fabry-Perot interference filter, a light detector, a spacer that has a placement surface on which a portion outside a light transmission region in a bottom surface of the interference filter is placed, and an adhesive member that adheres the interference filter and the spacer to each other. Elastic modulus of the adhesive member is smaller than elastic modulus of the spacer. At least a part of a lateral surface of the interference filter is located on the placement surface such that a part of the placement surface of the spacer is disposed outside the lateral surface. The adhesive member is disposed in a corner portion formed by the lateral surface of the interference filter and the part of the placement surface of the spacer and contacts each of the lateral surface and the part of the placement surface.

Disclosed is a method for capturing images that makes it possible to correct at least partially a memory effect of sensitive elements of a matrix used to capture the images. A corrected image is formed by subtracting, from a captured new raw image, a part of a prior raw image that was captured before the new raw image. The method is particularly suitable for sensitive elements with a first-order transfer function with respect to time, such as bolometers or microbolometers. Correction of the memory effect makes it possible to improve the transfer function and/or reduce a tail effect that is present in the images when scene elements move.

Disclosed is a method for capturing images that makes it possible to correct at least partially a memory effect of sensitive elements of a matrix used to capture the images. A corrected image is formed by subtracting, from a captured new raw image, a part of a prior raw image that was captured before the new raw image. The method is particularly suitable for sensitive elements with a first-order transfer function with respect to time, such as bolometers or microbolometers. Correction of the memory effect makes it possible to improve the transfer function and/or reduce a tail effect that is present in the images when scene elements move.