Correction: Automated code development based on genetic programming in graphical programming language: A pilot study.

[This corrects the article DOI: 10.1371/journal.pone.0299456.].

Automated code development based on genetic programming in graphical programming language: A pilot study.

Continual technological advances associated with the recent automation revolution have tremendously increased the impact of computer technology in the industry. Software development and testing are time-consuming processes, and the current market faces a lack of specialized experts. Introducing automation to this field could, therefore, improve software engineers' common workflow and decrease the time to market. Even though many code-generating algorithms have been proposed in textual-based programming languages, to the best of the authors' knowledge, none of the studies deals with the implementation of such algorithms in graphical programming environments, especially LabVIEW. Due to this fact, the main goal of this study is to conduct a proof-of-concept for a requirement-based automated code-developing system within the graphical programming environment LabVIEW. The proposed framework was evaluated on four basic benchmark problems, encompassing a string model, a numeric model, a boolean model and a mixed-type problem model, which covers fundamental programming scenarios. In all tested cases, the algorithm demonstrated an ability to create satisfying functional and errorless solutions that met all user-defined requirements. Even though the generated programs were burdened with redundant objects and were much more complex compared to programmer-developed codes, this fact has no effect on the code's execution speed or accuracy. Based on the achieved results, we can conclude that this pilot study not only proved the feasibility and viability of the proposed concept, but also showed promising results in solving linear and binary programming tasks. Furthermore, the results revealed that with further research, this poorly explored field could become a powerful tool not only for application developers but also for non-programmers and low-skilled users.

Explorative Image Analysis of Methylene Blue Interactions with Gelatin in Polypropylene Nonwoven Fabric Membranes: A Potential Future Tool for the Characterization of the Diffusion Process.

This manuscript explores the interaction between methylene blue dye and gelatin within a membrane using spectroscopy and image analysis. Emphasis is placed on methylene blue's unique properties, specifically its ability to oscillate between two distinct resonance states, each with unique light absorption characteristics. Image analysis serves as a tool for examining dye diffusion and absorption. The results indicate a correlation between dye concentrations and membrane thickness. Thinner layers exhibit a consistent dye concentration, implying an even distribution of the dye during the diffusion process. However, thicker layers display varying concentrations at different edges, suggesting the establishment of a diffusion gradient. Moreover, the authors observe an increased concentration of gelatin at the peripheries rather than at the center, possibly due to the swelling of the dried sample and a potential water concentration gradient. The manuscript concludes by suggesting image analysis as a practical alternative to spectral analysis, particularly for detecting whether methylene blue has been adsorbed onto the macromolecular network. These findings significantly enhance the understanding of the complex interactions between methylene blue and gelatin in a membrane and lay a solid foundation for future research in this field.

Antidurotaxis Droplet Motion onto Gradient Brush Substrates.

Durotaxis motion is a spectacular phenomenon manifesting itself by the autonomous motion of a nano-object between parts of a substrate with different stiffness. This motion usually takes place along a stiffness gradient from softer to stiffer parts of the substrate. Here, we propose a new design of a polymer brush substrate that demonstrates antidurotaxis droplet motion, that is, droplet motion from stiffer to softer parts of the substrate. By carrying out extensive molecular dynamics simulation of a coarse-grained model, we find that antidurotaxis is solely controlled by the gradient in the grafting density of the brush and is favorable for fluids with a strong attraction to the substrate (low surface energy). The driving force of the antidurotaxial motion is the minimization of the droplet-substrate interfacial energy, which is attributed to the penetration of the droplet into the brush. Thus, we anticipate that the proposed substrate design offers a new understanding and possibilities in the area of autonomous motion of droplets for applications in microfluidics, energy conservation, and biology.

A high-resolution large-scale dataset of pathological and normal white blood cells.

Microscopic examination plays a significant role in the initial screening for a variety of hematological, as well as non-hematological, diagnoses. Microscopic blood smear examination that is considered a key diagnostic technique, is in recent clinical practice still performed manually, which is not only time consuming, but can lead to human errors. Although automated and semi-automated systems have been developed in recent years, their high purchasing and maintenance costs make them unaffordable for many medical institutions. Even though much research has been conducted lately to explore more accurate and feasible solutions, most researchers had to deal with a lack of medical data. To address the lack of large-scale databases in this field, we created a high-resolution dataset containing a total of 16027 annotated white blood cells. Moreover, the dataset covers overall 9 types of white blood cells, including clinically significant pathological findings. Since we used high-quality acquisition equipment, the dataset provides one of the highest quality images of blood cells, achieving an approximate resolution of 42 pixels per 1 µm.

Unidirectional Droplet Propulsion onto Gradient Brushes without External Energy Supply.

Using extensive molecular dynamics simulation of a coarse-grained model, we demonstrate the possibility of sustained unidirectional motion (durotaxis) of droplets without external energy supply when placed on a polymer brush substrate with stiffness gradient in a certain direction. The governing key parameters for the specific substrate design studied, which determine the durotaxis efficiency, are found to be the grafting density of the brush and the droplet adhesion to the brush surface, whereas the strength of the stiffness gradient, the viscosity of the droplet, or the length of the polymer chains of the brush have only a minor effect on the process. It is shown that this durotaxial motion is driven by the steady increase of the interfacial energy between droplet and brush as the droplet moves from softer to stiffer parts of the substrate whereby the mean driving force gradually declines with decreasing roughness of the brush surface. We anticipate that our findings indicate further possibilities in the area of nanoscale motion without external energy supply.

Deformation of Gels with Spherical Auxetic Inclusions.

Auxetic metamaterials possess unnatural properties, such as a negative Poisson's ratio, which offers interesting features when combined with traditional materials. This paper describes the deformation behavior of a gel consisting of spherical auxetic inclusions when embedded in a conventional matrix. The auxetic inclusions and conventional matrix were modeled as spherical objects with a controlled pore shape. The auxetic particle had a reentrant honeycomb, and the conventional phase contained honeycomb-shaped pores. The deformation behavior was simulated using various existing models based on continuum mechanics. For the continuum mechanics models-the simplest of which are the Mori-Tanaka theory and self-consistent field mechanics models-the auxetic particle was homogenized as a solid element with Young's modulus and Poisson's ratio and compared with the common composite gel filled with rigid spheres. The finite element analysis simulations using these models were performed for two cases: (1) a detailed model of one particle and its surroundings in which the structure included the design of both the reentrant and conventional honeycombs; and (2) a multiparticle face-centered cubic lattice where both the classic matrix and auxetic particle were homogenized. Our results suggest that auxetic inclusion-filled gels provide an unsurpassed balance of low density and enhanced stiffness.

Ex-vivo biomechanical testing of pig femur diaphysis B type fracture fixed by novel biodegradable bone glue.

AIMS: The aim of this study was to answer the question whether our newly developed injectable biodegradable "self-setting" polymer-composite as a bone adhesive is a good "bone-glue" candidate to efficiently fix comminuted fractures of pig femoral bones used as an ex-vivo experimental model. METHODS: Mechanical properties of adhesive prepared from α-tricalcium phosphate (TCP) powder and thermogelling copolymer were optimized by selecting the appropriate composition with adhesion enhancers based on dopamine and sodium iodinate. Setting time and injectability were controlled by rheology. Ex-vivo experiments of fixed pig bones were provided in terms of either the three-point bending test of bending wedge type fractured pig femurs (with LCP) or the axial compression test of 45° oblique fractured femurs (without LCP) in physiological saline solution at 37 °C. Fractured bones treated with optimized adhesive before and after bending tests were imaged by X-ray microtomography (µCT). RESULTS: Based on the rheological measurement, the adhesive modified with both dopamine and sodium iodinate exhibited optimal thixotropic properties required for injection via thin 22 G needle. This optimal adhesive composition showed an 8 min lag phase (processing time) followed by fast increase in storage modulus at 37 °C up to 1 GPa within 110 min. Self-setting of dopamine/iodinate modified adhesive was completed in 48 h exhibiting the maximum strength at compression of 7.98 MPa ± 1.39 MPa. Whereas unmodified adhesive failed in glue-to-bone adhesion, dopamine and dopamine/iodinate modified adhesive used for 45° oblique fracture fixation showed good and similar strength at compression (3.05 and 2.79 MPa, respectively). However, significantly higher elasticity of about 250% exhibited adhesive with iodinate enhancer. Moreover, mechanical properties of B2 fractures fixed with both LCP and dopamine/iodinate adhesive were approaching closely to the properties of original bone. Excellent adhesion between the adhesive and the bone fragments was proved by µCT. CONCLUSION: The polymer-composite bone adhesive modified with dopamine/iodinate exhibited very good fixation ability of femoral artificial comminuted fractures in an experimental model.

Automated Detection of Acute Lymphoblastic Leukemia From Microscopic Images Based on Human Visual Perception.

Microscopic image analysis plays a significant role in initial leukemia screening and its efficient diagnostics. Since the present conventional methodologies partly rely on manual examination, which is time consuming and depends greatly on the experience of domain experts, automated leukemia detection opens up new possibilities to minimize human intervention and provide more accurate clinical information. This paper proposes a novel approach based on conventional digital image processing techniques and machine learning algorithms to automatically identify acute lymphoblastic leukemia from peripheral blood smear images. To overcome the greatest challenges in the segmentation phase, we implemented extensive pre-processing and introduced a three-phase filtration algorithm to achieve the best segmentation results. Moreover, sixteen robust features were extracted from the images in the way that hematological experts do, which significantly increased the capability of the classifiers to recognize leukemic cells in microscopic images. To perform the classification, we applied two traditional machine learning classifiers, the artificial neural network and the support vector machine. Both methods reached a specificity of 95.31%, and the sensitivity of the support vector machine and artificial neural network reached 98.25 and 100%, respectively.

Effects of Cryopreservation on Cell Metabolic Activity and Function of Biofabricated Structures Laden with Osteoblasts.

Biofabrication and maturation of bone constructs is a long-term task that requires a high degree of specialization. This specialization falls onto the hierarchy complexity of the bone tissue that limits the transfer of this technology to the clinic. This work studied the effects of the short-term cryopreservation on biofabricated osteoblast-containing structures, with the final aim to make them steadily available in biobanks. The biological responses studied include the osteoblast post-thawing metabolic activity and the recovery of the osteoblastic function of 3D-bioprinted osteoblastic structures and beta tricalcium phosphate (ß-TCP) scaffolds infiltrated with osteoblasts encapsulated in a hydrogel. The obtained structures were cryopreserved at -80 °C for 7 days using dimethyl sulfoxide (DMSO) as cryoprotectant additive. After thawing the structures were cultured up to 14 days. The results revealed fundamental biological aspects for the successful cryopreservation of osteoblast constructs. In summary, immature osteoblasts take longer to recover than mature osteoblasts. The pre-cryopreservation culture period had an important effect on the metabolic activity and function maintain, faster recovering normal values when cryopreserved after longer-term culture (7 days). The use of ß-TCP scaffolds further improved the osteoblast survival after cryopreservation, resulting in similar levels of alkaline phosphatase activity in comparison with the non-preserved structures. These results contribute to the understanding of the biology of cryopreserved osteoblast constructs, approaching biofabrication to the clinical practice.

Effect of Porosity Gradient on Mechanical Properties of Cellular Nano-Composites.

With their hierarchical architectures incorporating gradients in composition, porosity, and orientation, natural materials have evolved optimized balance of mechanical properties. Deciphered from the structure of bamboo, we prepared cellular solids with convex and/or concave porosity gradient and investigated their static mechanical and impact properties. Non-monotonous porosity dependences of tensile, crush, and impact strength were related to the shape of porosity gradient rather than to the properties of the wall material alone. Our results provide experimental evidence, that novel mechanically robust low density additively fabricated cellular nano-composites with convex porosity gradient satisfy the structural requirements of lightweight engineering parts. Moreover, novel functions, such as reduced flammability or electrical conductivity, can easily be introduced by selecting the type and spatial organization of nanoparticles and cellular structure of the cellular micro-particles (CMPs).

Dynamic Responsive Formation of Nanostructured Fibers in a Hydrogel Network: A Molecular Dynamics Study.

In an effort to study natural fiber formation, such as, e.g., spider silk, we present a model, which is capable of forming biomimetic fibrillar nanostructure from a hydrogel micellar network. The latter consists of interacting atomic groups which form cores of micelles, and of flexible chains forming the shells of the micelles. Micelles are connected in a compact network by linearly stretched chains. The structural elements of the network can be transformed during deformation from micellar into fibrillary type and their evolution is found to depend significantly on strain rate. Our model suggests a set of conditions suitable for the formation of nanostructured fibrillar network. It demonstrates that a fibrillar structure is only formed upon sufficiently fast stretching while, in contrast, the micellar gel structure is preserved, if the material is pulled slowly. We illustrate this key aspect by a minimalistic model of only four chains as part of the whole network, which provides a detailed view on the mechanism of fibril formation. We conclude that such a simplified structure has similar functionality and is probably responsible for the formation of nano-structured molecular fibrils in natural materials.

Small-sized platinum nanoparticles in soil organic matter: Influence on water holding capacity, evaporation and structural rigidity.

Engineered and anthropogenic nanoparticles represent a new type of pollutants. Up until now, many studies have reported its adverse effect on biota, but the potential influence on the properties and functions of environmental compartments has largely been ignored. In this work, the effect of Pt nanoparticles on the functions and properties of model soil organic matter has been studied. Using differential scanning calorimetry and molecular modeling, the effect of a wide range of 3 nm Pt nanoparticles concentrations on water holding capacity, the strength of water binding, the stability of water molecule bridges and the content of aliphatic crystallites was studied. It was found that strong hydration of the nanoparticles influences the 3D water structural network and acts as kosmotropic agents (structure-forming) in water bridges and as chaotropic agents (i.e. water destructuring) in larger water volumes. Contrarily, the interaction with soil organic matter moieties partially eliminates these effects. As a result, the 3 nm Pt nanoparticles decreased the evaporation enthalpy of water in soil organic matter and supported soil desiccation. They also increased the strength of water molecule bridges and increased the soil structural rigidity even at low concentrations. Additionally, at high concentrations, they decreased the water content in soil organic matter and induced the aliphatic moieties' crystallization. It is concluded that the small-sized Pt nanoparticles, and perhaps other types as well, may affect the local physicochemical processes in soils and may consequently contribute to enhanced evapotranspiration and deterioration of soil functions.

Non-Invasive Fetal Monitoring: A Maternal Surface ECG Electrode Placement-Based Novel Approach for Optimization of Adaptive Filter Control Parameters Using the LMS and RLS Algorithms.

This paper is focused on the design, implementation and verification of a novel method for the optimization of the control parameters (such as step size µ and filter order N) of LMS and RLS adaptive filters used for noninvasive fetal monitoring. The optimization algorithm is driven by considering the ECG electrode positions on the maternal body surface in improving the performance of these adaptive filters. The main criterion for optimal parameter selection was the Signal-to-Noise Ratio (SNR). We conducted experiments using signals supplied by the latest version of our LabVIEW-Based Multi-Channel Non-Invasive Abdominal Maternal-Fetal Electrocardiogram Signal Generator, which provides the flexibility and capability of modeling the principal distribution of maternal/fetal ECGs in the human body. Our novel algorithm enabled us to find the optimal settings of the adaptive filters based on maternal surface ECG electrode placements. The experimental results further confirmed the theoretical assumption that the optimal settings of these adaptive filters are dependent on the ECG electrode positions on the maternal body, and therefore, we were able to achieve far better results than without the use of optimization. These improvements in turn could lead to a more accurate detection of fetal hypoxia. Consequently, our approach could offer the potential to be used in clinical practice to establish recommendations for standard electrode placement and find the optimal adaptive filter settings for extracting high quality fetal ECG signals for further processing. Ultimately, diagnostic-grade fetal ECG signals would ensure the reliable detection of fetal hypoxia.

The Effect of Network Solvation on the Viscoelastic Response of Polymer Hydrogels.

The majority of investigations consider the deformation response of hydrogels, fully controlled by the deformation behavior of their polymer network, neglecting the contribution caused by the presence of water. Here, we use molecular dynamics simulation in an attempt to include the effect of physically bound water via polymer chain solvation on the viscoelastic response of hydrogels. Our model allows us to control the solvation of chains as an independent variable. The solvation of the chain is independent of other factors, mainly the effect (pH) which interferes significantly in experiments. The solvation of hydrophilic chains was controlled by setting a partial charge on the chains and quantified by the Bjerrum length (BL). The BL was calculated from the partial electric charge of the solvent and macromolecular network. When the BL is short, the repulsive Van der Waals interactions are predominant in the vicinity of macromolecules and solvation is not observed. For a long BL, the water molecules in the solvation zone of network are in the same range as attractive intermolecular forces and the solvation occurs. The model also allows the consideration of molecules of water attached to two chains simultaneously, forming a temporary bridging. By elucidating the relations between solvation of the network and structural changes during the network deformation, one may predict the viscoelastic properties of hydrogels knowing the molecular structure of its polymer chains.

Accurate micro-computed tomography imaging of pore spaces in collagen-based scaffold.

In this work we have used X-ray micro-computed tomography (µCT) as a method to observe the morphology of 3D porous pure collagen and collagen-composite scaffolds useful in tissue engineering. Two aspects of visualizations were taken into consideration: improvement of the scan and investigation of its sensitivity to the scan parameters. Due to the low material density some parts of collagen scaffolds are invisible in a µCT scan. Therefore, here we present different contrast agents, which increase the contrast of the scanned biopolymeric sample for µCT visualization. The increase of contrast of collagenous scaffolds was performed with ceramic hydroxyapatite microparticles (HAp), silver ions (Ag(+)) and silver nanoparticles (Ag-NPs). Since a relatively small change in imaging parameters (e.g. in 3D volume rendering, threshold value and µCT acquisition conditions) leads to a completely different visualized pattern, we have optimized these parameters to obtain the most realistic picture for visual and qualitative evaluation of the biopolymeric scaffold. Moreover, scaffold images were stereoscopically visualized in order to better see the 3D biopolymer composite scaffold morphology. However, the optimized visualization has some discontinuities in zoomed view, which can be problematic for further analysis of interconnected pores by commonly used numerical methods. Therefore, we applied the locally adaptive method to solve discontinuities issue. The combination of contrast agent and imaging techniques presented in this paper help us to better understand the structure and morphology of the biopolymeric scaffold that is crucial in the design of new biomaterials useful in tissue engineering.

A novel LabVIEW-based multi-channel non-invasive abdominal maternal-fetal electrocardiogram signal generator.

This paper describes the design, construction, and testing of a multi-channel fetal electrocardiogram (fECG) signal generator based on LabVIEW. Special attention is paid to the fetal heart development in relation to the fetus' anatomy, physiology, and pathology. The non-invasive signal generator enables many parameters to be set, including fetal heart rate (FHR), maternal heart rate (MHR), gestational age (GA), fECG interferences (biological and technical artifacts), as well as other fECG signal characteristics. Furthermore, based on the change in the FHR and in the T wave-to-QRS complex ratio (T/QRS), the generator enables manifestations of hypoxic states (hypoxemia, hypoxia, and asphyxia) to be monitored while complying with clinical recommendations for classifications in cardiotocography (CTG) and fECG ST segment analysis (STAN). The generator can also produce synthetic signals with defined properties for 6 input leads (4 abdominal and 2 thoracic). Such signals are well suited to the testing of new and existing methods of fECG processing and are effective in suppressing maternal ECG while non-invasively monitoring abdominal fECG. They may also contribute to the development of a new diagnostic method, which may be referred to as non-invasive trans-abdominal CTG + STAN. The functional prototype is based on virtual instrumentation using the LabVIEW developmental environment and its associated data acquisition measurement cards (DAQmx). The generator also makes it possible to create synthetic signals and measure actual fetal and maternal ECGs by means of bioelectrodes.

Dynamic behavior of acrylic acid clusters as quasi-mobile nodes in a model of hydrogel network.

Using a molecular dynamics simulation, we study the thermo-mechanical behavior of a model hydrogel subject to deformation and change in temperature. The model is found to describe qualitatively poly-lactide-glycolide hydrogels in which acrylic acid (AA)-groups are believed to play the role of quasi-mobile nodes in the formation of a network. From our extensive analysis of the structure, formation, and disintegration of the AA-groups, we are able to elucidate the relationship between structure and viscous-elastic behavior of the model hydrogel. Thus, in qualitative agreement with observations, we find a softening of the mechanical response at large deformations, which is enhanced by growing temperature. Several observables as the non-affinity parameter A and the network rearrangement parameter V indicate the existence of a (temperature-dependent) threshold degree of deformation beyond which the quasi-elastic response of the model system turns over into plastic (ductile) one. The critical stretching when the affinity of the deformation is lost can be clearly located in terms of A and V as well as by analysis of the energy density of the system. The observed stress-strain relationship matches that of known experimental systems.