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In this study, a lumped parameter model which includes systemic circulation, cerebral blood vessels, systemic arteriolar resistance control, heart rate control, cerebral autoregulation mechanisms and cerebral CO2 reactivity was developed to simulate healthy and heart failure conditions. In the healthy cardiovascular system model, the results were obtained with all control mechanisms connected to the model. Whilst heart failure cases were simulated, all control mechanisms were removed from the model. Then, cerebral autoregulation and cerebral CO2 reactivity mechanisms were connected to the model. Lastly, systemic arteriolar resistance and heart rate control mechanisms were connected to the model. Also, Monte Carlo Analysis was performed to determine the range of parameters controlled for simulations of healthy and heart failure conditions. The results showed that blood flow rate in cerebral circulation can be simulated more accurately by modeling interaction among autoregulatory mechanisms rather than studying separately. [ABSTRACT FROM AUTHOR]

With respect to the ever‐increasing performance needs in communication technologies, the need for accurate and computational efficient design optimization methods for high‐end microwave designs are also increased. Many studies had been proposed for the last decades for creating numerical modeling methods for having high accurate, stable, and computation efficient solutions suitable to be used in the design optimization process. Ensemble learning is a technique that the models are strategically created and combined to solve a specific computer intelligence challenge and primarily employed to boost the efficiency of a model or to lower the risk of a weak learner collection. Herein, XGBoosting‐based ensemble learning had been used for having surrogate models for three different microwave designs. In the first and second study cases, two microwave designs from the literature are taken into consideration for testing the performance of the proposed model with existing methods. Furthermore, a novel antenna design had been studied as a third study case with sparse training samples, to test the performance of the proposed modeling technique. As a result, the proposed method had achieved a remarkable performance for all the mentioned study cases both based on its own performance measures and its comparison with the counterpart algorithms. [ABSTRACT FROM AUTHOR]

In this work, a high-performance voltage and current output instrumentation amplifier circuit is proposed. The proposed circuit also has voltage-mode (VM) and transadmittance-mode (TAM) outputs at a time. It employs a single current backward transconductance amplifier (CBTA) and a grounded resistor. It has the advantage of having low input and high output impedances which makes it easy for cascadability. The presented circuit has electronically tunable property due to the bias current of the CBTA. The validity of the proposed circuit is demonstrated by PSPICE simulations using a 0.18 μ m CMOS process with ± 0. 9 V supply voltage. Simulation results show that the proposed circuit has a high common mode rejection ratio (CMRR), wide bandwidth, low offset and high gain properties. [ABSTRACT FROM AUTHOR]

In this article, a new active building component with electronically tunable transresistive block, voltage difference transresistance amplifier, and its floating frequency dependent negative resistor simulator circuit application is presented. The simulator circuit is shown to operate using single active building block with two grounded passive components, to be electronically tunable over its value which is controlled by an independent current source, not to require any conditions of component matching and to have good sensitivity performance with respect to tracking errors. To examine functionality of the design, a CRD band-pass filter example is given. Numerous simulation program with integrated circuit emphasis (SPICE) simulations are performed and depicted through the article to verify validity of the study. Taiwan semiconductor manufacturing company (TSMC) 0.18 µm complementary metal oxide semiconductor technology parameters are used through simulations. [ABSTRACT FROM AUTHOR]

The aim of this paper is proposing an alternative method to Gorski-Popiel Technique in realization of synthetic transformers. A new synthetic floating transformer (FT) circuit is also given. The proposed synthetic transformer circuit uses two current backward transconductance amplifiers (CBTAs), three resistors, and two grounded capacitors. The primary self-inductance, the secondary self-inductance, and the mutual inductance can be independently controlled and can be tuned electronically by changing the biasing current of the employed CBTAs. It has a good sensitivity performance with respect to tracking errors. A band-pass filter is also realized to test the performance of the proposed synthetic transformer circuit. The validity of the proposed synthetic transformer circuit is demonstrated by PSPICE simulations and experimental results. [ABSTRACT FROM AUTHOR]

This study presents the design of current‐mode full‐wave rectifier circuits using single active component. The first proposed circuit uses only one operational transconductance amplifier (OTA), two diodes and two resistors. Its current gain can be electronically controlled using the transconductance gain of the OTA. The second proposed circuit uses only one differential voltage current conveyor (DVCC), two diodes and three resistors. Using the complementary metal‐oxide semiconductor structure of both OTA and DVCC, the behaviours of the proposed structures have been verified by HSPICE simulations. In addition, both of the proposed circuits are tested practically using commercially available components, such as AD844 and LM13700. [ABSTRACT FROM AUTHOR]

Current-mode (CM) and voltage-mode (VM) multiphase sinusoidal oscillator (MSO) structures using current backward transconductance amplifier (CBTA) are proposed. The proposed oscillators can generate n current or voltage signals (n being even or odd) equally spaced in phase, n+1 CBTAs, n grounded capacitor and a grounded resistor are used for nth-state oscillator. The oscillation frequency can be independently controlled through trans-conductance (g,,) of the CBTAs which are adjustable via their bias currents. The effects caused by the non-ideality of the CBTA on the oscillation frequency and condition have been analyzed. The performance of the proposed circuits is demonstrated on third-stage and fifth-stage MSOs by using PSPICE simulations based on the 0.25 µum TSMC level-7 CMOS technology parameters. [ABSTRACT FROM AUTHOR]

In this study, a novel floating frequency dependent negative resistor (FDNR), floating inductor, floating capacitor and floating resistor simulator circuit employing two CBTAs and three passive components is proposed. The presented circuit can realize floating FDNR, inductor, capacitor or resistor depending on the passive component selection. Since the passive elements are all grounded, this circuit is suitable for fully integrated circuit design. The circuit does not require any component matching conditions, and it has a good sensitivity performance with respect to tracking errors. Moreover, the proposed FDNR, inductance, capacitor and resistor simulator can be tuned electronically by changing the biasing current of the CBTA or can be controlled through the grounded resistor or capacitor. The high-order frequency dependent element simulator circuit is also presented. Depending on the passive component selection, it realizes high-order floating circuit defining as V(s) = snAI(s) or V(s) = s-nBI (s). The proposed floating FDNR simulator circuit and floating high-order frequency dependent element simulator circuit are demonstrated by using SPICE simulation for 0.25 µm, level 7, TSMC CMOS technology parameters. [ABSTRACT FROM AUTHOR]

Objective: Myelin is essential for a healthy nervous system. Myelin formed by oligodendrocytes, accelerates impulse propagation and supports neuronal survival. Demyelination leads to neurodegeneration. In multiple sclerosis (MS) immune attack results in demyelination. Our goal is to dissect interactions among oligodendrocytes, neurons, and immune cells to improve our understanding of myelination and the demyelinating diseases. We aim to discover new targets for remyelination therapies. Methods: We are building tools for analyzing protein-protein and cell-to-cell interactions. To identify genes involved in myelination and MS, we developed a bioinformatics-based strategy, interactome analysis, which combines proteome and gene expression methodologies. Identified genes are evaluated in peripheral blood of MS patients and in mouse models. To accelerate drug discovery, 23 machine learning-based methodologies were assessed for myelin identification in fluorescent microscopy images. Results: Interactome analysis identified hundreds of proteinprotein interactions between pairs of oligodendrocytes, neurons, macrophages, microglia, and T cells. Most significant interactions are further analyzed in vivo and in vitro. Our customizedconvolutional neural network and Boosted Tree methods segmented myelin at over 98% accuracy. Identified myelin can be quantified and visualized in 3D. Conclusion: The interactome analysis yielded novel genes that are likely to be linked to MS. Machine learning-based methodologies are very effective in accelerating myelin quantification and thus, drug screens against demyelinating diseases such as MS. Overall, our innovative analysis strategies employing computer assistance produced novel avenues of exploration for myelination and demyelinating diseases. This study was supported TUBITAK (218S495,316S026), Istanbul Medipol University (BAP2018/06), and Turkish Academy of Sciences (GEBIP). [ABSTRACT FROM AUTHOR]

Diffuse optical tomography (DOT) is an optical imaging technique using near-infrared spectroscopy (NIRS). Because the NIR light is highly scattered in biological tissue, the photon density drops rapidly with increasing depth. This makes the measurement accuracy of DOT in deep tissue significantly lower than in superficial tissue. Classical Regularized Least Square (RLS) based regularization methods with different penalty term (l1-norm, l2-norm, LASSO, Ridge, and Elastic Net etc.) come up short in finding the inclusions when the inclusion number is increased or one of the inclusion located on the upper surface and the other one located on the deeper surface of the tissue. This is the depth problem encountered in DOT. In this paper, a new least square based regularization method is proposed. Within the scope of the proposed method, both the weight matrix and penalty terms are modified in order to solve this problem. In this process, firstly, the A matrix is changed using the diagonal value of A A T based on DCA (Depth Compensation Algorithm). Then, a new penalty term using modified A matrix is added. It has been observed that when the noise level increases, proposed method give higher accuracy and more robust according to other RLS Method on synthetic data. Experimental results on synthetic data show that the new method improves inversion accuracy, reduces errors, and the lowers inversion instability compared to the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Myelin is an essential component of the nervous system and myelin damage causes demyelination diseases. Myelin is a sheet of oligodendrocyte membrane wrapped around the neuronal axon. In the fluorescent images, experts manually identify myelin by co-localization of oligodendrocyte and axonal membranes that fit certain shape and size criteria. Because myelin wriggles along x-y-z axes, machine learning is ideal for its segmentation. However, machine-learning methods, especially convolutional neural networks (CNNs), require a high number of annotated images, which necessitate expert labor. To facilitate myelin annotation, we developed a workflow and software for myelin ground truth extraction from multi-spectral fluorescent images. Additionally, to the best of our knowledge, for the first time, a set of annotated myelin ground truths for machine learning applications were shared with the community., Competing Interests: No competing interests were disclosed., (Copyright: © 2023 Çapar A et al.)