Research in the field of underwater (UW) robotic applications is rapidly developing. The emergence of coupling the newest technologies on submersibles, different types of telecommunication devices, sensors, and soft robots is transforming the rigid approach to robotic design by providing solutions that bridge the gap between accuracy and adaptability in an environment where there is so much fluctuation in object targeting and environmental conditions. In this paper, we represent a review of the history, development, recent research endeavors, and projected outlook for the area of soft robotics technology pertaining to its use with tactile sensing in the UW environment.

Objective: The present study investigates viscoelastic properties of human autopsy brain tissue via nanoindentation to find feasible biomarkers for Alzheimer's disease (AD) in ex vivo condition and to understand the mechanics of the human brain better, especially on the difference before and after progression of AD. Methods: Viscoelastic properties of paraformaldehyde-fixed, paraffinembedded thin (8 μm) sectioned normal and AD affected human autopsy brain tissue samples are investigated via nanoindentation with a combined loading profile of a linear preloading and a sinusoidal loading at various loading frequencies from 0.01 to 10 Hz. In 1200 indentation tests for ten human autopsy brain tissue samples from ten different subjects (five AD cases and five normal controls), viscoelastic properties such as Young's modulus, storage modulus, loss modulus, and loss factor of both gray and white matter brain tissues samples from normal and AD affected tissues were measured experimentally. Results: We found that the normal brain tissues have higher Young's modulus values than the AD affected brain tissues by 23.5% and 27.9% on average for gray and white matter, respectively, with statistically significant differences (p <; 0.0001) between the normal and AD affected brain tissues. Additionally, the AD affected brain tissues have much higher loss factor than the normal brain tissues on lower loading frequencies. Significance: AD is one of the leading causes of death in America and continues to affect a growing population. The challenges of recognizing the early pathological changes in brain tissue due to AD and diagnosing a patient has led to much research focused on finding biomarkers for the disease. In this regard, understanding the mechanics of brain tissues is increasingly recognized to play an important role in diagnosing brain diseases.

Achieving a novel drug delivery system needs site-specificity along with dosage control. Many physical, chemical, mechanical, and biological signals are used for developing these systems, out of which light has been used predominantly in the past decade. Light responsive drug delivery systems have tremendous potential, and their exploration is crucial in developing a precise and controlled delivery system. Spatio-temporal and intensity control of light allows better manipulation of drug delivery vehicles than mechanical, chemical, and biological signals. The use of ultraviolet (UV) and near-infrared (NIR) light has helped in upgrading therapeutic functionalities, while the use of up-conversion nanoparticles (UCNPs) has delivered an extension into theranostic tools. Biomaterials incorporated with photosensitizers can readily respond to changes in light and are vital in achieving clinical success via translational research. Further, the inclusion of biological macromolecules for the transportation of drugs, genes, and proteins has seen a broader application of light-controlled systems. The key objective of this review paper is to summarise the evolution of light-activated targeted drug delivery systems and the importance of biomaterials in developing one.

Tactile information is crucial for recognizing physical interactions, manipulation of an object, and motion planning for a robotic gripper; however, concurrent tactile technologies have certain limitations over directional force sensing. In particular, they are expensive, difficult to fabricate, and mostly unsuitable for underwater use. Here, we present a facile and cost-effective synthesis technique of a flexible multi-directional force sensing system, which is also favorable to be utilized in underwater environments. We made use of four flex sensors within a silicone-made hemispherical shell structure. Each sensor was placed 90${}^{°}$ apart and aligned with the curve of the hemispherical shape. If the force is applied on the top of the hemisphere, all the flex sensors would bend uniformly and yield nearly identical readings. When force is applied from a different direction, a set of flex sensors would characterize distinctive output patterns to localize the point of contact as well as the direction and magnitude of the force. The deformation of the fabricated soft sensor due to applied force was simulated numerically and compared with the experimental results. The fabricated sensor was experimentally calibrated and tested for characterization including an underwater demonstration. This study would widen the scope of identification of multi-directional force sensing, especially for underwater soft robotic applications.

Goal: This research aims to validate a new biomarker of breast cancer by introducing electromechanical coupling factor of breast tissue samples as a possible additional indicator of breast cancer. Since collagen fibril exhibits a structural organization that gives rise to a piezoelectric effect, the difference in collagen density between normal and cancerous tissue can be captured by identifying the corresponding electromechanical coupling factor. Methods: The design of a portable diagnostic tool and a microelectromechanical systems (MEMS)-based biochip, which is integrated with a piezoresistive sensing layer for measuring the reaction force as well as a microheater for temperature control, is introduced. To verify that electromechanical coupling factor can be used as a biomarker for breast cancer, the piezoelectric model for breast tissue is described with preliminary experimental results on five sets of normal and invasive ductal carcinoma (IDC) samples in the 25-45 °C temperature range. Conclusion: While the stiffness of breast tissues can be captured as a representative mechanical signature which allows one to discriminate among tissue types especially in the higher strain region, the electromechanical coupling factor shows more distinct differences between the normal and IDC groups over the entire strain region than the mechanical signature. From the two-sample t-test, the electromechanical coupling factor under compression shows statistically significant differences (p ≤ 0.0039) between the two groups. Significance: The increase in collagen density in breast tissue is an objective and reproducible characteristic of breast cancer. Although characterization of mechanical tissue property has been shown to be useful for differentiating cancerous tissue from normal tissue, using a single parameter may not be sufficient for practical usage due to inherent variation among biological samples. The portable breast cancer diagnostic tool reported in this manuscript shows the feasibility of measuring multiple parameters of breast tissue allowing for practical application.