Abstract: A plurality of heterogeneous microparticles can be provided, each having a shell, a payload, and a cap. The shell can define a core and an orifice in fluid communication with the core. The payload can be disposed within the core. The cap can be coupled to the shell so as to seal the orifice. The shell and cap of the microparticles can be formed by an additive manufacturing method, for example, by patterning of photomaterials using electromagnetic radiation or a particle beam. When subjected to a triggering event, at least a portion of each orifice can be exposed from the respective cap so as to release, through the exposed orifice portion, the corresponding payload from the core of the shell. The microparticles can be used in various applications, such as controlled delivery of drugs, chemicals, or biological agents, self-healing or self-lubricating materials, and failure prevention or mitigation.

Abstract: A system that is a target of health monitoring via a computational system, the computational system, and corresponding method for determining health indicators using rank correlation analysis are disclosed. The target system includes a computational system that includes a computing device that acquires data from the target system, generate at least two features from the data acquired from the target system, computes, for each feature, rank correlation of the feature with time, computes the absolute value of each rank correlation coefficient for each feature, confining the range of the absolute value rank correlation coefficients to that from 0 to 1; and chooses at least one feature with a higher relative absolute value rank correlation coefficient as a health or condition indicator for the target system. The target system or the computational system or the method may perform health or condition monitoring on the target system.

Abstract: A system that is a target of health monitoring via a computational system, the computational system, and corresponding method for determining health indicators using rank correlation analysis are disclosed. The target system includes a computational system that includes a computing device that acquires data from the target system, generate at least two features from the data acquired from the target system, computes, for each feature, rank correlation of the feature with time, computes the absolute value of each rank correlation coefficient for each feature, confining the range of the absolute value rank correlation coefficients to that from 0 to 1; and chooses at least one feature with a higher relative absolute value rank correlation coefficient as a health or condition indicator for the target system. The target system or the computational system or the method may perform health or condition monitoring on the target system.