Tethered TGF-β1 in a Hyaluronic Acid-Based Bioink for Bioprinting Cartilaginous Tissues

In 3D bioprinting for cartilage regeneration, bioinks that support chondrogenic development are of key importance. Growth factors covalently bound in non-printable hydrogels have been shown to effectively promote chondrogenesis. However, studies that investigate the functionality of tethered growth factors within 3D printable bioinks are still lacking. Therefore, in this study, we established a dual-stage crosslinked hyaluronic acid-based bioink that enabled covalent tethering of transforming growth factor-beta 1 (TGF‑β1). Bone marrow-derived mesenchymal stromal cells (MSCs) were cultured over three weeks in vitro, and chondrogenic differentiation of MSCs within bioink constructs with tethered TGF‑β1 was markedly enhanced, as compared to constructs with non-covalently incorporated TGF‑β1. This was substantiated with regard to early TGF‑β1 signaling, chondrogenic gene expression, qualitative and quantitative ECM deposition and distribution, and resulting construct stiffness. Furthermore, it was successfully demonstrated, in a comparative analysis of cast and printed bioinks, that covalently tethered TGF‑β1 maintained its functionality after 3D printing. Taken together, the presented ink composition enabled the generation of high-quality cartilaginous tissues without the need for continuous exogenous growth factor supply and, thus, bears great potential for future investigation towards cartilage regeneration. Furthermore, growth factor tethering within bioinks, potentially leading to superior tissue development, may also be explored for other biofabrication applications.

High-bandwidth controller design for dual-stage actuator system in hard disk drives

Large-capacity hard disk drives are important for the development of an information society. The capacities of hard disk drives depend on the positioning accuracy of magnetic heads, which read and write digital data, in disk-positioning control systems. Therefore, it is necessary to improve positioning accuracy to develop hard disk drives with large capacities. Hard disk drives employ dual-stage actuator systems to accurately control the magnetic heads. A dual-stage actuator system consists of a voice coil motor and micro-actuator. In micro-actuators, there is a trade-off between head-positioning accuracy and stroke limitation. In particular, in a conventional controller design, the micro-actuator is required to actuate such that it compensates for low-frequency vibration. To overcome this trade-off, this study proposes a high-bandwidth controller design for the micro-actuator in a dual-stage actuator system. The proposed method can reduce the required stroke of the micro-actuator by increasing the gain of the feedback controller of the voice coil motor at low frequencies. Although the voice coil motor control loop becomes unstable, the micro-actuator stabilizes the entire feedback loop at high frequencies. As a result, the control system improves the positioning accuracy compared to that achieved by conventional control methods, and the required micro-actuator stroke is reduced.

Equivalent Input Disturbance-Based Control Design for Three Phase Dual-Stage Grid-Tied Photovoltaic System Considering Dead Time Effect

Grid-tied inverter is the prominent component of the three-phase dual-stage photovoltaic (PV) grid-tied power generation system. However, the disturbances caused by dead time effect will pose the reduction of grid-tied current quality and even cause the imbalance of inverter itself or other circuit devices. In this paper, a current control strategy is proposed to damp dead time effect for the three-phase dual-stage PV grid-tied inverter system, and its design, stability analysis, and implementation are carried out. First, the inverter model is modified by regarding the dq reference frame coupling terms, uncertainties, and external and internal disturbances as an unknown lumped disturbance. Then, a current control scheme based on compensation of equivalent input disturbance is introduced, and it estimates and compensates the unknown lumped disturbance, which effectively realizes the inverter model decoupling and comprehensive disturbance rejection. Last, simulation results demonstrate the effectiveness and superiority of the proposed current controller.

A Dual-Stage Vocabulary of Features (VoF)-Based Technique for COVID-19 Variants’ Classification

Novel coronavirus, known as COVID-19, is a very dangerous virus. Initially detected in China, it has since spread all over the world causing many deaths. There are several variants of COVID-19, which have been categorized into two major groups. These groups are variants of concern and variants of interest. Variants of concern are more dangerous, and there is a need to develop a system that can detect and classify COVID-19 and its variants without touching an infected person. In this paper, we propose a dual-stage-based deep learning framework to detect and classify COVID-19 and its variants. CT scans and chest X-ray images are used. Initially, the detection is done through a convolutional neural network, and then spatial features are extracted with deep convolutional models, while handcrafted features are extracted from several handcrafted descriptors. Both spatial and handcrafted features are combined to make a feature vector. This feature vector is called the vocabulary of features (VoF), as it contains spatial and handcrafted features. This feature vector is fed as an input to the classifier to classify different variants. The proposed model is evaluated based on accuracy, F1-score, specificity, sensitivity, specificity, Cohen’s kappa, and classification error. The experimental results show that the proposed method outperforms all the existing state-of-the-art methods.

Thermodynamic Analysis and Optimization of a Novel Power-Water Cogeneration System for Waste Heat Recovery of Gas Turbine

A power-water cogeneration system based on a supercritical carbon dioxide Brayton cycle (SCBC) and reverse osmosis (RO) unit is proposed and analyzed in this paper to recover the waste heat of a gas turbine. In order to improve the system performance, the power generated by SCBC is used to drive the RO unit and the waste heat of SCBC is used to preheat the feed seawater of the RO unit. In particular, a dual-stage cooler is employed to elevate the preheating temperature as much as possible. The proposed system is simulated and discussed based on the detailed thermodynamic models. According to the results of parametric analysis, the exergy efficiency of SCBC first increases and then decreases as the turbine inlet temperature and split ratio increase. The performance of the RO unit is improved as the preheating temperature rises. Finally, an optimal exergy efficiency of 52.88% can be achieved according to the single-objective optimization results.