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We propose Composite Parallel Coordinates, a novel parallel coordinates technique to effectively represent the interplay of component alternatives in a system. It builds upon a dedicated data model that formally describes the interaction of components. Parallel coordinates can help decision-makers identify the most preferred solution among a number of alternatives. Multi-component systems require one such multi-attribute choice for each component. Each of these choices might have side effects on the system's operability and performance, making them co-dependent. Common approaches employ complex multi-component models or involve back-and-forth iterations between single components until an acceptable compromise is reached. A simultaneous visual exploration across independently modeled but connected components is needed to make system design more efficient. Using dedicated layout and interaction strategies, our Composite Parallel Coordinates allow analysts to explore both individual properties of components as well as their interoperability and joint performance. We showcase the effectiveness of Composite Parallel Coordinates for co-dependent multi-attribute choices by means of three real-world scenarios from distinct application areas. In addition to the case studies, we reflect on observing two domain experts collaboratively working with the proposed technique and communicating along the way.Nowadays, photonics-based techniques are used extensively in various applications, including functional clinical diagnosis, progress monitoring in treatment, and provision of metrological control. In fact, in the frame of practical implementation of optical methods, such as laser Doppler flowmetry (LDF), the qualitative interpretation and quantitative assessment of the detected signal remains vital and urgently required. In the conventional LDF approach, the key measured parameters, index of microcirculation and perfusion rate, are proportional to an averaged concentration of red blood cells (RBC) and their average velocity within a diagnostic volume. These quantities compose mixed signals from different vascular beds with a range of blood flow velocities and are typically expressed in relative units. In the current paper we introduce a new signal processing approach for the decomposition of LDF power spectra in terms of ranging blood flow distribution by frequency series. The developed approach was validated in standard occlusion tests conducted on healthy volunteers, and applied to investigate the influence of local pressure rendered by a probe on the surface of the skin. Finally, in limited clinical trials, we demonstrate that the approach can significantly improve the diagnostic accuracy of detection of microvascular changes in the skin of the feet in patients with Diabetes Mellitus type 2, as well as age-specific changes. The results obtained show that the developed approach of LDF signal decomposition provides essential new information about blood flow and blood microcirculation and has great potential in the diagnosis of vascular complications associated with various diseases.
Quantitative technique based on In-line phase-contrast computed tomography with single scanning attracts more attention in application due to the flexibility of the implementation. However, the quantitative results usually suffer from artifacts and noise since the phase retrieval and reconstruction are independent ("two-step") without feedback from the original data. The work aims to investigate a method for material quantitation to improve the image quality of In-line tomography within single scanning.

An iterative method based Fresnel diffraction imaging model is developed in this work, which directly reconstructs the refractive index decrement δ and imaginary β of the object from observed data ("one-step"). Moreover, high-quality material decomposition results are obtained by using a linear approximation in the iterative process.

Compared with the existing methods, Our method shows a higher peak signal-to-noise ratio and structural similarity in numerical experimental results. Additionally, the quantitation accuracy of the proposed method is greater than 97.2 % by calculating the equivalent atomic number of the decomposed basic material in the real experiment.

We demonstrate that this one-step method greatly reduces noise and improves quantitative reconstruction and decomposition results.

This algorithm has the potential for quantitative imaging research using In-line tomography in future biomedical applications.
This algorithm has the potential for quantitative imaging research using In-line tomography in future biomedical applications.Amphiphilic random and block copolymers were synthesized as potential inkjet inks. This study evaluated the potential of these polymers for color dispersion by examining the following factors surface tension, zeta potential, viscosity, and particle size. Mereletinib Acrylic acid and (ethoxyethoxy)ethyl acrylate were used as the hydrophilic molecular units. Styrene, butyl acrylate, and phenoxyethyl acrylate were used as hydrophobic units. Color dispersions were prepared by using organic dye and these amphiphilic polymers. The color dispersions containing random copolymers exhibited low viscosity, which is preferable for jetting, but the dye particles tended to sediment after the thermal aging test. In contrast, those containing block copolymers showed high viscosity, which was unsuitable for jetting. However, they retained their initial dispersion state after the aging test. The advantages and disadvantages of each monomer arrangement (random or block) were demonstrated, providing a future outlook on the molecular design of polymer dispersants for color dispersions.Major advances in biomedical imaging have occurred over the last 2 decades and now allow many physiological, cellular, and molecular processes to be imaged noninvasively in small animal models of cardiovascular disease. Many of these techniques can be also used in humans, providing pathophysiological context and helping to define the clinical relevance of the model. Ultrasound remains the most widely used approach, and dedicated high-frequency systems can obtain extremely detailed images in mice. Likewise, dedicated small animal tomographic systems have been developed for magnetic resonance, positron emission tomography, fluorescence imaging, and computed tomography in mice. In this article, we review the use of ultrasound and positron emission tomography in small animal models, as well as emerging contrast mechanisms in magnetic resonance such as diffusion tensor imaging, hyperpolarized magnetic resonance, chemical exchange saturation transfer imaging, magnetic resonance elastography and strain, arterial spin labeling, and molecular imaging.An ensemble of in vitro cardiac tissue models has been developed over the past several decades to aid our understanding of complex cardiovascular disorders using a reductionist approach. These approaches often rely on recapitulating single or multiple clinically relevant end points in a dish indicative of the cardiac pathophysiology. The possibility to generate disease-relevant and patient-specific human induced pluripotent stem cells has further leveraged the utility of the cardiac models as screening tools at a large scale. To elucidate biological mechanisms in the cardiac models, it is critical to integrate physiological cues in form of biochemical, biophysical, and electromechanical stimuli to achieve desired tissue-like maturity for a robust phenotyping. Here, we review the latest advances in the directed stem cell differentiation approaches to derive a wide gamut of cardiovascular cell types, to allow customization in cardiac model systems, and to study diseased states in multiple cell types. We also highlight the recent progress in the development of several cardiovascular models, such as cardiac organoids, microtissues, engineered heart tissues, and microphysiological systems. We further expand our discussion on defining the context of use for the selection of currently available cardiac tissue models. Last, we discuss the limitations and challenges with the current state-of-the-art cardiac models and highlight future directions.Cardiac arrhythmias are a significant cause of morbidity and mortality worldwide, accounting for 10% to 15% of all deaths. Although most arrhythmias are due to acquired heart disease, inherited channelopathies and cardiomyopathies disproportionately affect children and young adults. Arrhythmogenesis is complex, involving anatomic structure, ion channels and regulatory proteins, and the interplay between cells in the conduction system, cardiomyocytes, fibroblasts, and the immune system. Animal models of arrhythmia are powerful tools for studying not only molecular and cellular mechanism of arrhythmogenesis but also more complex mechanisms at the whole heart level, and for testing therapeutic interventions. This review summarizes basic and clinical arrhythmia mechanisms followed by an in-depth review of published animal models of genetic and acquired arrhythmia disorders.Acute and chronic animal models of exercise are commonly used in research. Acute exercise testing is used, often in combination with genetic, pharmacological, or other manipulations, to study the impact of these manipulations on the cardiovascular response to exercise and to detect impairments or improvements in cardiovascular function that may not be evident at rest. Chronic exercise conditioning models are used to study the cardiac phenotypic response to regular exercise training and as a platform for discovery of novel pathways mediating cardiovascular benefits conferred by exercise conditioning that could be exploited therapeutically. The cardiovascular benefits of exercise are well established, and, frequently, molecular manipulations that mimic the pathway changes induced by exercise recapitulate at least some of its benefits. This review discusses approaches for assessing cardiovascular function during an acute exercise challenge in rodents, as well as practical and conceptual considerations in the use of common rodent exercise conditioning models. The case for studying feeding in the Burmese python as a model for exercise-like physiological adaptation is also explored.Heart failure (HF) describes a heterogenous complex spectrum of pathological conditions that results in structural and functional remodeling leading to subsequent impairment of cardiac function, including either systolic dysfunction, diastolic dysfunction, or both. Several factors chronically lead to HF, including cardiac volume and pressure overload that may result from hypertension, valvular lesions, acute, or chronic ischemic injuries. Major forms of HF include hypertrophic, dilated, and restrictive cardiomyopathy. The severity of cardiomyopathy can be impacted by other comorbidities such as diabetes or obesity and external stress factors. Age is another major contributor, and the number of patients with HF is rising worldwide in part due to an increase in the aged population. HF can occur with reduced ejection fraction (HF with reduced ejection fraction), that is, the overall cardiac function is compromised, and typically the left ventricular ejection fraction is lower than 40%. In some cases of HF, the ejection fraction is preserved (HF with preserved ejection fraction).
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