Thermal-electric model for piezoelectric ZnO nanowires

A Proof of Concept Combined Using Mixed Reality for Personalized Neurorehabilitation of Cerebellar Ataxic Patients

BACKGROUND

Guidelines for degenerative cerebellar ataxia neurorehabilitation suggest intensive coordinative training based on physiotherapeutic exercises. Scientific studies demonstrate virtual exergaming therapeutic value. However, patient-based personalization, post processing analyses and specific audio-visual feedbacks are not provided. This paper presents a wearable motion tracking system with recording and playback features. This system has been specifically designed for ataxic patients, for upper limbs coordination studies with the aim to retrain movement in a neurorehabilitation setting. Suggestions from neurologists and ataxia patients were considered to overcome the shortcomings of virtual systems and implement exergaming.

METHODS

The system consists of the mixed-reality headset Hololens2 and a proprietary exergaming implemented in Unity. Hololens2 can track and save upper limb parameters, head position and gaze direction in runtime.

RESULTS

Data collected from a healthy subject are reported to demonstrate features and outputs of the system.

CONCLUSIONS

Although further improvements and validations are needed, the system meets the needs of a dynamic patient-based exergaming for patients with cerebellar ataxia. Compared with existing solutions, the mixed-reality system is designed to provide an effective and safe therapeutic exergaming that supports both primary and secondary goals of an exergaming: what a patient should do and how patient actions should be performed.

Fundamentals and Applications of ZnO-Nanowire-Based Piezotronics and Piezo-Phototronics

The piezotronic effect is a coupling effect of semiconductor and piezoelectric properties. The piezoelectric potential is used to adjust the p-n junction barrier width and Schottky barrier height to control carrier transportation. At present, it has been applied in the fields of sensors, human-machine interaction, and active flexible electronic devices. The piezo-phototronic effect is a three-field coupling effect of semiconductor, photoexcitation, and piezoelectric properties. The piezoelectric potential generated by the applied strain in the piezoelectric semiconductor controls the generation, transport, separation, and recombination of carriers at the metal-semiconductor contact or p-n junction interface, thereby improving optoelectronic devices performance, such as photodetectors, solar cells, and light-emitting diodes (LED). Since then, the piezotronics and piezo-phototronic effects have attracted vast research interest due to their ability to remarkably enhance the performance of electronic and optoelectronic devices. Meanwhile, ZnO has become an ideal material for studying the piezotronic and piezo-phototronic effects due to its simple preparation process and better biocompatibility. In this review, first, the preparation methods and structural characteristics of ZnO nanowires (NWs) with different doping types were summarized. Then, the theoretical basis of the piezotronic effect and its application in the fields of sensors, biochemistry, energy harvesting, and logic operations (based on piezoelectric transistors) were reviewed. Next, the piezo-phototronic effect in the performance of photodetectors, solar cells, and LEDs was also summarized and analyzed. In addition, modulation of the piezotronic and piezo-phototronic effects was compared and summarized for different materials, structural designs, performance characteristics, and working mechanisms' analysis. This comprehensive review provides fundamental theoretical and applied guidance for future research directions in piezotronics and piezo-phototronics for optoelectronic devices and energy harvesting.

A Comparative Study on a Novel Quality Assessment Protocol Based on Image Analysis Methods for Color Doppler Ultrasound Diagnostic Systems

Color Doppler (CD) imaging is widely used in diagnostics since it allows real-time detection and display of blood flow superimposed on the B-mode image. Nevertheless, to date, a shared worldwide standard on Doppler equipment testing is still lacking. In this context, the study herein proposed would give a contribution focusing on the combination of five test parameters to be included in a novel Quality Assessment (QA) protocol for CD systems testing. A first approach involving the use of the Kiviat diagram was investigated, assuming the diagram area, normalized with respect to one of the gold standards, as an index of the overall Doppler system performance. The QA parameters were obtained from the post-processing of CD data through the implementation of custom-written image analysis methods and procedures, here applied to three brand-new high-technology-level ultrasound systems. Experimental data were collected through phased and convex array probes, in two configuration settings, by means of a Doppler flow phantom set at different flow rate regimes. The outcomes confirmed that the Kiviat diagram might be a promising tool applied to quality controls of Doppler equipment, although further investigations should be performed to assess the sensitivity and specificity of the proposed approach.

Artificial Intelligence in Thyroid Field-A Comprehensive Review

Simple Summary

The incidence of thyroid pathologies has been increasing worldwide. Historically, the detection of thyroid neoplasms relies on medical imaging analysis, depending mainly on the experience of clinicians. The advent of artificial intelligence (AI) techniques led to a remarkable progress in image-recognition tasks. AI represents a powerful tool that may facilitate understanding of thyroid pathologies, but actually, the diagnostic accuracy is uncertain. This article aims to provide an overview of the basic aspects, limitations and open issues of the AI methods applied to thyroid images. Medical experts should be familiar with the workflow of AI techniques in order to avoid misleading outcomes.

Abstract

Artificial intelligence (AI) uses mathematical algorithms to perform tasks that require human cognitive abilities. AI-based methodologies, e.g., machine learning and deep learning, as well as the recently developed research field of radiomics have noticeable potential to transform medical diagnostics. AI-based techniques applied to medical imaging allow to detect biological abnormalities, to diagnostic neoplasms or to predict the response to treatment. Nonetheless, the diagnostic accuracy of these methods is still a matter of debate. In this article, we first illustrate the key concepts and workflow characteristics of machine learning, deep learning and radiomics. We outline considerations regarding data input requirements, differences among these methodologies and their limitations. Subsequently, a concise overview is presented regarding the application of AI methods to the evaluation of thyroid images. We developed a critical discussion concerning limits and open challenges that should be addressed before the translation of AI techniques to the broad clinical use. Clarification of the pitfalls of AI-based techniques results crucial in order to ensure the optimal application for each patient.

3D random walk model of diffusion in human Hypo- and Hyper- mineralized collagen fibrils

Bone tissue is composed at the nanoscale of apatite minerals, collagen molecules and water that form the mineralized collagen fibril (MCF). Water has a crucial role in bone biomineralization. We developed a 3D random walk model to investigate the water diffusion process within the MCF for three different scenarios, namely low, intermediate and high mineral volume fraction. The MCF geometric model is obtained after applying 6·10⁶ translational and rotational perturbations to an ordered arrangement of mineral. Subsequently, we compute 300 random trajectories of water molecules within the MCF for each mineral volume fraction. Every trajectory is constituted of up to 500 k positions of the water particle. We determined the diffusion coefficient from the linear fit of the mean squared displacement of water molecules as a function of time. We investigate changes in the diffusivity values in relation to variation of bone mineral content. The analysis performed on the random walk data, for all mineralization conditions, leads to diffusion coefficients in good agreement with the diffusivity outcomes achieved from previous experimental studies. Thus, the 3D geometrical configuration adopted in this numerical study appears suitable for modelling the MCF with different volume fractions, from hypo- to hyper-mineralized conditions. We observed that low mineral content is associated with an increase of the water diffusion, while lower values of diffusivity are determined in hypermineralized conditions. In agreement with experimental data, our results highlight the influence of the structural alterations on the mass transport properties.

Fabrication of Pressure Sensor Using Electrospinning Method for Robotic Tactile Sensing Application

Tactile sensors are widely used by the robotics industries over decades to measure force or pressure produced by external stimuli. Piezoelectric-based pressure sensors have intensively been investigated as promising candidates for tactile sensing applications. In contrast, piezoelectric-based pressure sensors are expensive due to their high cost of manufacturing and expensive base materials. Recently, an effect similar to the piezoelectric effect has been identified in non-piezoelectric polymers such as poly(d,l-lactic acid (PDLLA), poly(methyl methacrylate) (PMMA) and polystyrene. Hence investigations were conducted on alternative materials to find their suitability. In this article, we used inexpensive atactic polystyrene (aPS) as the base polymer and fabricated functional fibers using an electrospinning method. Fiber morphologies were studied using a field-emission scanning electron microscope and proposed a unique pressure sensor fabrication method. A fabricated pressure sensor was subjected to different pressures and corresponding electrical and mechanical characteristics were analyzed. An open circuit voltage of 3.1 V was generated at 19.9 kPa applied pressure, followed by an integral output charge (ΔQ), which was measured to calculate the average apparent piezoelectric constant d_app and was found to be 12.9 ± 1.8 pC N⁻¹. A fabricated pressure sensor was attached to a commercially available robotic arm to mimic the tactile sensing.

Buckling Behavior of FG-CNT Reinforced Composite Conical Shells Subjected to a Combined Loading

The buckling behavior of functionally graded carbon nanotube reinforced composite conical shells (FG-CNTRC-CSs) is here investigated by means of the first order shear deformation theory (FSDT), under a combined axial/lateral or axial/hydrostatic loading condition. Two types of CNTRC-CSs are considered herein, namely, a uniform distribution or a functionally graded (FG) distribution of reinforcement, with a linear variation of the mechanical properties throughout the thickness. The basic equations of the problem are here derived and solved in a closed form, using the Galerkin procedure, to determine the critical combined loading for the selected structure. First, we check for the reliability of the proposed formulation and the accuracy of results with respect to the available literature. It follows a systematic investigation aimed at checking the sensitivity of the structural response to the geometry, the proportional loading parameter, the type of distribution, and volume fraction of CNTs.

Thermo-Electro-Mechanical Vibrations of Porous Functionally Graded Piezoelectric Nanoshells

In this work, we aim to study free vibration of functionally graded piezoelectric material (FGPM) cylindrical nanoshells with nano-voids. The present model incorporates the small scale effect and thermo-electro-mechanical loading. Two types of porosity distribution, namely, even and uneven distributions, are considered. Based on Love’s shell theory and the nonlocal elasticity theory, governing equations and corresponding boundary conditions are established through Hamilton’s principle. Then, natural frequencies of FGPM nanoshells with nano-voids under different boundary conditions are analyzed by employing the Navier method and the Galerkin method. The present results are verified by the comparison with the published ones. Finally, an extensive parametric study is conducted to examine the effects of the external electric potential, the nonlocal parameter, the volume fraction of nano-voids, the temperature rise on the vibration of porous FGPM cylindrical nanoshells.