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Fluorescence microscopy can provide valuable information about cell interior dynamics. Particularly, mean squared displacement (MSD) analysis is widely used to characterize proteins and sub-cellular structures' mobility providing the laws of molecular diffusion. The MSD curve is traditionally extracted from individual trajectories recorded by single-particle tracking-based techniques. More recently, image correlation methods like iMSD have been shown capable of providing averaged dynamic information directly from images, without the need for isolation and localization of individual particles. iMSD is a powerful technique that has been successfully applied to many different biological problems, over a wide spatial and temporal scales. The aim of this work is to review and compare these two well-established methodologies and their performance in different situations, to give an insight on how to make the most out of their unique characteristics. We show the analysis of the same datasets by the two methods. Regardless of the experimental differences in the input data for MSD or iMSD analysis, our results show that the two approaches can address equivalent questions for free diffusing systems. We focused on studying a range of diffusion coefficients between D = 0.001μm2s-1and D = 0.1μm2s-1, where we verified that the equivalence is maintained even for the case of isolated particles. This opens new opportunities for studying intracellular dynamics using equipment commonly available in any biophysical laboratory.

A new diagnostic method is proposed that allows us, under conditions of direct operation, to carry out an express assessment of the tendency of steels and alloys toward stress corrosion cracking (delayed destruction) by analyzing the microhardness of their structural components. It is shown that the convergence of the results obtained during experimental studies is maximum for steels and alloys prone to stress corrosion cracking. The limitations of the proposed method of accelerated testing of metal structures for assessing their crack resistance in terms of application to steels and alloys prone to the development of crack-like defects are established. [ABSTRACT FROM AUTHOR]

Aluminum alloys are widely used in various industries due to their as low density, high strength-to-weight ratio, and good corrosion resistance. However, their wear resistance is often inadequate for certain applications. Utilization of industrial waste materials, such as iron slag, as reinforcement in aluminum alloy matrix composites offers a sustainable approach to material development and waste management. The utilization of industrial waste materials for aluminum alloy matrix composite fabrication offers a waste utilization to material development. The loading of this reinforcement varied from 0 to 15 wt.% and different particle size range (220-140, 140-70, and 70-0 µm). A microscopic analysis indicated that the iron slag particles are spread uniformly inside the metallic matrix. There is also a reduction in the size of primary silicon, as well as morphological changes (acicular to globular shape). The wear behavior was calculated using a pin-on-disk wear set up in accordance with ASTM G99 standard. The composites were employed to dry sliding wear test under various operating conditions such as applied pressure (0.2–1.4 MPa), and sliding distance (0–3000 m). The 15F composite outperformed all other composite samples in terms of wear rate under all working conditions. When compared to the base alloy, it demonstrated a remarkable 67% drop in steady state wear rate. The enhancements in wear performance for the 15F composite were attributed to the effects of Fe slag reinforcement. The inclusion of iron slag particles induced strong interfacial bonding between matrix and reinforcement particles improving the durability of the mechanical mixed layer developed during relative motion. Importantly, the wear rate parameters of the 15F composite were similar to those of the brake drum material used in commercial applications. This emphasizes the composite suitability for usage in a variety of automobile components. [ABSTRACT FROM AUTHOR]

We report the smectic layer reorientation process in a surface-stabilized ferroelectric liquid crystal subject to the surface mode dominance at certain temperature and application of the controlled measuring field strength. The process is investigated by dielectric spectroscopy and optical textures analysis simultaneously in heating and cooling cycle. First the smectic layers are reoriented just 1–2 oC below Tc by applying a bias of 0.5 V as the material is soft here and cooled the sample to room temperature in absence of bias field which we call this a treated cell. In second type, the cell was taken to just above the Tc and taken the measurement in cooling cycle which we call an untreated cell. We have observed that there is a distinct molecular dynamic in the heating and cooling cycles of the material due to reoriented smectic layering and surface effect which assists the reorientation. It has also been observed that in heating cycles, the surface effect phenomenon is dominant, and in cooling cycles, it is weaker. Sometimes, the heating and cooling of the sample under electric field has been found affecting the optical performance of sample due to the readjustment of smectic layers. This study may clarify the control over the layer reorientation by surface effect and may open the possible application in displays and optical communication devices. [ABSTRACT FROM AUTHOR]

Wire arc additive manufacturing (WAAM) has increasingly been recognized as a cost-effective method for fabricating intricate metallic parts, especially from nickel-based superalloys. This review covers key aspects of WAAM, including its versatile heat sources (GTAW, GMAW, CMT, and PAW) with unique advantages and limitations for customization. Design for Additive Manufacturing (DfAM) principles are highlighted, enabling intricate geometries and addressing support structures, distortion control, and orientation. Several nickel-based superalloys (e.g., Inconel 718, Inconel 625, Inconel 617, Hastelloy C276, Hastelloy X, Haynes 282) are rigorously evaluated for WAAM suitability due to their hightemperatureature strength, corrosion resistance, and mechanical properties. The review analyzes process parameters like arc current, wire feed rate, and deposition path. It explores defect detection and prevention strategies and emphasizes post-processing methods (heat treatment, rolling, hot isostatic pressing) in enhancing microstructural characteristics and mechanical properties. Microstructural characterization techniques (optical microscopy and XRD) provide insights into grain structure, phase composition, and defect presence. In conclusion, this review underscores the paramount suitability of WAAM for producing defect-free and complex structures in nickel-based superalloys. Ongoing research and advancements in WAAM will undoubtedly improve its competitiveness and unlock its full potential in the field of additive manufacturing. [ABSTRACT FROM AUTHOR]

Additive manufacturing based on arc welding (=DED-Arc) has already established itself in the world of additive manufacturing. Recent process optimizations show the increased use in a hybrid process by irradiating an additional laser beam into the active arc zone. Numerous publications can be found in the literature for steel, aluminum, or bronze, in which, among other things, a strength-enhancing effect or an improved wall surface during this hybrid process is reported. The way in which the laser beam impacts the arc, at what distance, at what angle and with what spot size or focusing appears to be random in the publications and is always chosen differently in the literature. In order to close this knowledge gap, a corresponding holder for a DED-Arc torch and laser optic is developed, which allows these geometric factors to be systematically changed and also enables the titanium alloy Ti-6Al-4V to be processed in a hybrid process. By welding individual tracks and walls with different angles, distances and spot sizes of the two energy sources, a fundamental understanding of the laser-arc hybrid process is created. The results are analyzed using a high-speed camera and evaluated on the basis of surface measurements, micrographs, and power source values. This showed that the distance between the laser and the arc has the greatest effect on the additive process stability and the arc power sources values. In the range of 2–6 mm, there are, in some cases, strong fluctuations in the wire deposition and the arc voltage, so that this range should be avoided. It also showed that a wider spot sizes range of 360–600 μm can be used, whereby different ranges are recommended depending on the target size of uniform wall height or thickness. For the laser incidence angle, the most uniform walls across all tests are achieved at 20°. As the angle of incidence becomes flatter, the walls become more irregular, although there is no linear relationship or areas that should be avoided at all. [ABSTRACT FROM AUTHOR]

The orientation of fibers or filaments in nonwovens is critical in determining their mechanical characteristics. Image processing techniques, prized for their minimal human intervention and rapid processing speed, are widely utilized in nonwoven fiber orientation measurement. However, these techniques often face substantial challenges, such as low accuracy in corner detection, errors in fiber segmentation, and inefficiencies in fiber orientation calculation. Addressing these concerns, this study introduces a novel, enhanced method accompanied by two innovative optimization algorithms to enhance accuracy. The first innovation involves the development of a newly developed fiber corner detection algorithm, dubbed the T-detector, specifically tailored for the unique characteristics of fiber images, enabling efficient corner point detection and removal. Subsequently, we introduce and employ a fiber length restriction algorithm to further segment the processed longer fibers into the remaining fiber fragments and utilize a skeleton projection algorithm to calculate the fiber orientation. These algorithms overcome the existing technology's inherent shortcomings, thereby heightening measurement accuracy. The results illustrate an improvement in measurement precision over other orientation distribution measurement algorithms, with the fiber information retention (covering ratio) reaching an impressive 95%. Our proposed method not only calculates fiber orientation distribution in nonwovens with remarkable accuracy and efficiency, but its innovative approach also stands to provide a theoretical foundation for the design of three-dimensional filtering models with specific fiber orientation. [ABSTRACT FROM AUTHOR]

Transverse corner cracks are among the most common defects in high carbon and high carbon micro-alloyed grade slab casting. Calculation and analysis were done to minimize the negative strip time of mold oscillation, which is responsible for reducing the depth of the oscillation mark formed on the slab surface. The value of negative strip time decreases with an increase in the frequency of mold oscillation. Based on the trial results, it was suggested that the oscillation proportionality be adjusted from 1.2 to either 1.25 or 1.3. This adjustment will reduce the depth of oscillation marks and the tendency to form transverse cracks. The transverse crack on the narrow face of the slab was examined for crack analysis and compositional analysis. Microstructural analysis revealed that the crack has no branching and consists of an iron scale inside it. Furthermore, it is observed that the crack propagates across the allotriomorphic ferrite grains. [ABSTRACT FROM AUTHOR]

While tire wear particles (TWP) have been estimated to represent more than 90% of the total microplastic (MP) emitted in European countries and may have environmental health effects, only few data about TWP concentrations and characteristics are available today. The lack of data stems from the fact that no standardized, cost efficient or accessible extraction and identification method is available yet. We present a method allowing the extraction of TWP from soil, performing analysis with a conventional optical microscope and a machine learning approach to identify TWP in soil based on their colour. The lowest size of TWP which could be measured reliably with an acceptable recovery using our experimental set-up was 35 µm. Further improvements would be possible given more advanced technical infrastructure (higher optical magnification and image quality). Our method showed a mean recovery of 85% in the 35–2000 µm particle size range and no blank contamination. We tested for possible interference from charcoal (as another black soil component with similar properties) in the soils and found a reduction of the interference from charcoal by 92% during extraction. We applied our method to a highway adjacent soil at 1 m, 2 m, 5 m, and 10 m and detected TWP in all samples with a tendency to higher concentrations at 1 m and 2 m from the road compared to 10 m from the road. The observed TWP concentrations were in the same order of magnitude as what was previously reported in literature in highway adjacent soils. These results demonstrate the potential of the method to provide quantitative data on the occurrence and characteristics of TWP in the environment. The method can be easily implemented in many labs, and help to address our knowledge gap regarding TWP concentrations in soils. [ABSTRACT FROM AUTHOR]

Glass vials are the most widely used primary containers for the packaging of parenteral products due to their optical clarity, general inertness, and hermetic properties, but under certain circumstances, they can pose safety concerns. Most of these issues are related to the potential formation of glass particulates through delamination or precipitation, resulting from the chemical interaction between the drug product and the inner surface of the glass vial. Hence, it is imperative for pharmaceutical companies to conduct product-vial compatibility studies to determine the appropriate packaging/container closure system. To support this development activity, scientists need to develop analytical methods to detect subvisible glass particulates in parenteral products, along with the appropriate positive controls, to facilitate detection and identification. This paper outlines the utilization of coaxial/episcopic and oblique illumination microscopy, combined with spectroscopic techniques, to detect thin glass particulates generated from a modified procedure. It also showcases the importance of angle-dependent lighting in visualizing positive control samples containing thin glass particulates. The analytical microscopy techniques discussed in this paper can assist scientists in selecting suitable container closure systems for developing parenteral products. [ABSTRACT FROM AUTHOR]

The utilization of natural lignocellulosic fibers as reinforcements in polymer composites has become increasingly popular in recent years. This research focuses on investigating the potential of Derris scandens (Roxb.) benth root fiber (DSBFs) as a reinforcing material in thermosetting polymer composites. The study begins by analyzing the properties and composition of DSBFs, using standardized testing methods. The single fiber tensile strength of DSBFs is determined to be 423 Pa at a strain rate of 4.01%, and they exhibit a Young's modulus of 79.45 GPa. Chemical analysis reveals that DSBFs are composed of helically coiled cellulose microfibrils, constituting 72.59 wt.%, held together by an amorphous lignin matrix and contain 9.69 wt.% hemicellulose and a low wax content of 0.3 wt.%. Thermal stability (TGA) analysis demonstrates that the fibers exhibit stability up to 340 °C, with a mass loss of 43.78%. X-ray diffraction analysis confirms the crystalline index of 18.16 nm and a crystalline size of 49.28%. 13C (CP-MAS) NMR spectroscopy yields the evidence for the presence of cellulose, hemicellulose, and lignin in DSBFs. Fourier-transform infrared spectroscopy (FTIR) identify functional groups and elemental composition of DSBFs. Surface morphology is analysed by atomic force microscopy (AFM) and optical microscopy. These findings suggest that DSBFs can find applications beyond their traditional use in Thai medicine. [ABSTRACT FROM AUTHOR]

Advanced optical imaging techniques enhance our ability to investigate various intracellular biomolecular condensates that form through phase separation. Biomolecular condensates demonstrate diverse organizations and dynamics, serving as the physical infrastructure that enables the execution of biological processes. The physicochemical properties of condensates dictate the rules governing their multilayered ultrastructure. Intracellular biomolecular condensates, which form via phase separation, display a highly organized ultrastructure and complex properties. Recent advances in optical imaging techniques, including super-resolution microscopy and innovative microscopic methods that leverage the intrinsic properties of the molecules observed, have transcended the limitations of conventional microscopies. These advances facilitate the exploration of condensates at finer scales and in greater detail. The deployment of these emerging but sophisticated imaging tools allows for precise observations of the multiphasic organization and physicochemical properties of these condensates, shedding light on their functions in cellular processes. In this review, we highlight recent progress in methodological innovations and their profound implications for understanding the organization and dynamics of intracellular biomolecular condensates. [ABSTRACT FROM AUTHOR]

Analysis of microplastics in drinking water is often challenging due to smaller particle size and low particle count. In this study, we used a low cost and an easy to assemble smartphone microscopic system for imaging and quantitating microplastic particles as small as 20 μm. The system consisted of a spherical sapphire ball lens of 4 mm diameter attached to a smartphone camera as a major imaging component. It also involved pre‐concentration of the sample using ZnCl2 solution. The spike recovery and limit of detection of the method in filtered distilled and deionized water samples (n = 9) were 55.6% ± 9.7% and 34 particles/L, respectively. Imaging performance of the microscopic system was similar to a commercial bright field microscopic system. The method was further implemented to examine microplastic particles in commercial bottled and jar water samples (n = 20). The particles count in bottled and jar water samples ranged from 0–91 particles/L to 0–130 particles/L, respectively. In both sample types, particles of diverse shape and size were observed. The particles collected from water samples were further confirmed by FTIR spectra (n = 36), which found 97% of the particles tested were made of plastic material. These findings suggested that the smartphone microscopic system can be implemented as a low‐cost alternative for preliminary screening of microplastic in drinking water samples. Research Highlights: Ball lens based smartphone microscopic method was used for microplastic analysis.Particles of diverse shape and size were found in bottle and jar water samples. [ABSTRACT FROM AUTHOR]

The effect of different concentrations of fly ash aluminosilicate cenospheres on the structure and properties of elastomeric composites is studied. Composite materials based on ethylene–propylene–diene rubber (EPDM-40) with different mass fractions of fly ash (10, 20, 30%) are obtained using laboratory rollers. The microstructure of mixtures of EPDM and aluminosilicate cenospheres is studied by optical microscopy. It is shown that the concentration of the filler of more than 30 wt % increases the concentration of larger cenosphere agglomerates in the structure, which indicates interfacial separation in the mixtures, which is probably associated with the fact that mechanical mixing on mixing equipment does not make it possible to achieve uniform distribution of the filler throughout the elastomeric matrix. The appearance of new absorption bands in the region of 1400–800 cm–1 that correspond to the stretching vibrations of Si–O–Si present in aluminosilicate cenospheres is detected in the IR spectra. According to the thermogravimetry data of the compositions under study, the introduction of aluminosilicate cenospheres promotes a slight increase in the thermal stability of the composition under study with the concentration of cenospheres of more than 30%. The influence of the concentration of aluminosilicate cenospheres on the resistance of the composites to aggressive media is analyzed, and it is found that the introduction of a cenosphere filler in the amount of 10 to 30 wt % into mixtures based on EPDM can increase the oil and petrol resistance of the materials. [ABSTRACT FROM AUTHOR]

Plasmonic gratings provide an advantageous platform for fluorescence sensing due to their compatibility with functionalization techniques, imaging detection, and the potential for signal enhancement. Among traditional fluorescence detection methods, microscopes are commonly used tools. The interaction between dye fluorescence processes and the plasmonic modes of the grating strongly depends on the measurement configuration and is influenced by the dispersion and spectral characteristics of the plasmonic modes. In our study, we investigated the angular behavior of the fluorescence emission from ATTO700 dye by varying the collection angle using a standard optical microscope coupled with a spectrometer. Our results show a clear dependence of fluorescence emission in terms of spectral shape on the collection angle that can be attributed to plasmonic mode dispersion. [ABSTRACT FROM AUTHOR]

Asbestos research, identification, and quantification have been performed over the years, and the relationship between fiber inhalation and lung disease development is well defined. The same cannot be said for the gastroenteric system: the International Agency for Research on Cancer (IARC) believes that colorectal cancer (CRC) could be associated with asbestos exposure, but research has not demonstrated a casual nexus between exposure and CRC, despite highlighting an association tendency. The combination of scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS) is the most applied technique in asbestos fiber identification in tissues and intestinal mucosa. In this study, SEM/EDS was applied to evaluate the presence of asbestos fibers and bodies (ABs) inside the tissue of eleven patients affected by CRC who had undergone environmental exposure due to living in an asbestos-polluted area where an Eternit plant had been active in the past. This technique was coupled with optical microscopy (OM) to verify whether the latter could be applied to evaluate the presence of these mineral phases, with the goal of understanding its suitability for identifying fibers and ABs in colon tissues. In addition to verifying the presence of fibers, this study allowed us to identify the deposition site of said fibers within the sample and possibly detect associated tissue reactions using OM, over a shorter time and at lower costs. Despite being a preliminary and descriptive work, the obtained results allowed us to propose a method involving first-sample OM observation to identify regulated (fibers with a length ≥ 5 μm, a thickness ≤ 3 μm, and a length/thickness ratio > 3) asbestos phases and ABs in the extra-respiratory system. In fact, OM and SEM/EDS provided similar information: no asbestiform morphology or ABs were found, but phyllosilicates and other inorganic materials were identified. This research needs to be continued using higher-resolution techniques to definitively rule out the presence of these fibers inside tissues whilst also increasing the number of patients involved. [ABSTRACT FROM AUTHOR]

The discrimination of five subtypes of regenerated cellulose fibers, i.e., viscose, bamboo, lyocell, modal, and cupro, from both men's and women's clothing available on the prevalent apparel market was described. The examinations were conducted using optical microscopy (in transmitted white light and polarized light), scanning electron microscopy coupled with energy dispersive X-ray spectrometry (SEM–EDX), and Fourier Transform Infrared Spectroscopy (FTIR). The microscopic methods revealed characteristic features of the morphological structure of the examined fibers, enabling the identification of differences between the subtypes. As a result, the microscopic methods were found to be the most effective for identifying and distinguishing between the types of examined fibers. Although the FTIR technique did not allow for distinguishing between the fiber subcategories, it contributed to the enlargement of the IR spectra databases for regenerated cellulose fibers. Based on the findings, a general scheme of the procedure for identifying the tested fibers was proposed. [ABSTRACT FROM AUTHOR]

Wire arc additive manufacturing (WAAM) has increasingly been recognized as a cost-effective method for fabricating intricate metallic parts, especially from nickel-based superalloys. This review covers key aspects of WAAM, including its versatile heat sources (GTAW, GMAW, CMT, and PAW) with unique advantages and limitations for customization. Design for Additive Manufacturing (DfAM) principles are highlighted, enabling intricate geometries and addressing support structures, distortion control, and orientation. Several nickel-based superalloys (e.g., Inconel 718, Inconel 625, Inconel 617, Hastelloy C276, Hastelloy X, Haynes 282) are rigorously evaluated for WAAM suitability due to their high-temperatureature strength, corrosion resistance, and mechanical properties. The review analyzes process parameters like arc current, wire feed rate, and deposition path. It explores defect detection and prevention strategies and emphasizes post-processing methods (heat treatment, rolling, hot isostatic pressing) in enhancing microstructural characteristics and mechanical properties. Microstructural characterization techniques (optical microscopy and XRD) provide insights into grain structure, phase composition, and defect presence. In conclusion, this review underscores the paramount suitability of WAAM for producing defect-free and complex structures in nickel-based superalloys. Ongoing research and advancements in WAAM will undoubtedly improve its competitiveness and unlock its full potential in the field of additive manufacturing.

The article presents an experimental study on the corrosion resistance of the 3003 Aluminium alloy Friction Stir Welded (FSW) joint in different working environments. Three types of corrosive media at different temperatures were tested to see how they affected the FSW joint mechanical properties. The media were sodium chloride, hydrogen chloride, and ethylene glycol. In parallel with the study of the effect of temperature, static tensile tests were carried out on specimens taken perpendicular to the welding direction. Also, micro-hardness profiles were used to determine the influence of the parameters studied on the various weld zones. Finally, the effect of the most aggressive corrosive medium, temperature, and the inclusion of ethylene glycol on the crack propagation resistance of an FSW joint were studied. Fatigue-propagation tests at constant stress amplitude were carried out to understand what affects the fatigue crack propagation of welded joints after corrosive attack. The results showed that uniform and pitting corrosion were combined to cause FSW joint surface degradation. Corrosion damage does not appear to alter yield strength and ultimate stress values. However, FSW joints show a significant degradation in mechanical properties with increasing temperature and with the aggressiveness of the corrosive medium. The inclusion of ethylene glycol was found to delay the rate of crack propagation during testing, leading to an improvement in the service life of pre-corroded FSW joints.

Abstract While tire wear particles (TWP) have been estimated to represent more than 90% of the total microplastic (MP) emitted in European countries and may have environmental health effects, only few data about TWP concentrations and characteristics are available today. The lack of data stems from the fact that no standardized, cost efficient or accessible extraction and identification method is available yet. We present a method allowing the extraction of TWP from soil, performing analysis with a conventional optical microscope and a machine learning approach to identify TWP in soil based on their colour. The lowest size of TWP which could be measured reliably with an acceptable recovery using our experimental set-up was 35 µm. Further improvements would be possible given more advanced technical infrastructure (higher optical magnification and image quality). Our method showed a mean recovery of 85% in the 35–2000 µm particle size range and no blank contamination. We tested for possible interference from charcoal (as another black soil component with similar properties) in the soils and found a reduction of the interference from charcoal by 92% during extraction. We applied our method to a highway adjacent soil at 1 m, 2 m, 5 m, and 10 m and detected TWP in all samples with a tendency to higher concentrations at 1 m and 2 m from the road compared to 10 m from the road. The observed TWP concentrations were in the same order of magnitude as what was previously reported in literature in highway adjacent soils. These results demonstrate the potential of the method to provide quantitative data on the occurrence and characteristics of TWP in the environment. The method can be easily implemented in many labs, and help to address our knowledge gap regarding TWP concentrations in soils.

Abstract Glass vials are the most widely used primary containers for the packaging of parenteral products due to their optical clarity, general inertness, and hermetic properties, but under certain circumstances, they can pose safety concerns. Most of these issues are related to the potential formation of glass particulates through delamination or precipitation, resulting from the chemical interaction between the drug product and the inner surface of the glass vial. Hence, it is imperative for pharmaceutical companies to conduct product-vial compatibility studies to determine the appropriate packaging/container closure system. To support this development activity, scientists need to develop analytical methods to detect subvisible glass particulates in parenteral products, along with the appropriate positive controls, to facilitate detection and identification. This paper outlines the utilization of coaxial/episcopic and oblique illumination microscopy, combined with spectroscopic techniques, to detect thin glass particulates generated from a modified procedure. It also showcases the importance of angle-dependent lighting in visualizing positive control samples containing thin glass particulates. The analytical microscopy techniques discussed in this paper can assist scientists in selecting suitable container closure systems for developing parenteral products.

Digital in-line holographic microscopy (DIHM) is a widely used interference technique for real-time reconstruction of living cells’ morphological information with large space-bandwidth product and compact setup. However, the need for a larger pixel size of detector to improve imaging photosensitivity, field-of-view, and signal-to-noise ratio often leads to the loss of sub-pixel information and limited pixel resolution. Additionally, the twin-image appearing in the reconstruction severely degrades the quality of the reconstructed image. The deep learning (DL) approach has emerged as a powerful tool for phase retrieval in DIHM, effectively addressing these challenges. However, most DL-based strategies are data-driven or end-to-end net approaches, suffering from excessive data dependency and limited generalization ability. Herein, a novel multi-prior physics-enhanced neural network with pixel super-resolution (MPPN-PSR) for phase retrieval of DIHM is proposed. It encapsulates the physical model prior, sparsity prior and deep image prior in an untrained deep neural network. The effectiveness and feasibility of MPPN-PSR are demonstrated by comparing it with other traditional and learning-based phase retrieval methods. With the capabilities of pixel super-resolution, twin-image elimination and high-throughput jointly from a single-shot intensity measurement, the proposed DIHM approach is expected to be widely adopted in biomedical workflow and industrial measurement.

Abstract Purpose Wood comprises different cell types, such as fibers, tracheids and vessels, defining its properties. Studying cells’ shape, size, and arrangement in microscopy images is crucial for understanding wood characteristics. Typically, this involves macerating (soaking) samples in a solution to separate cells, then spreading them on slides for imaging with a microscope that covers a wide area, capturing thousands of cells. However, these cells often cluster and overlap in images, making the segmentation difficult and time-consuming using standard image-processing methods. Results In this work, we developed an automatic deep learning segmentation approach that utilizes the one-stage YOLOv8 model for fast and accurate segmentation and characterization of macerated fiber and vessel form aspen trees in microscopy images. The model can analyze 32,640 x 25,920 pixels images and demonstrate effective cell detection and segmentation, achieving a $$\hbox {mAP}_{0.5-0.95}$$ mAP 0.5 - 0.95 of 78 %. To assess the model’s robustness, we examined fibers from a genetically modified tree line known for longer fibers. The outcomes were comparable to previous manual measurements. Additionally, we created a user-friendly web application for image analysis and provided the code for use on Google Colab. Conclusion By leveraging YOLOv8’s advances, this work provides a deep learning solution to enable efficient quantification and analysis of wood cells suitable for practical applications.

Abstract A product class characterization was requested on some plastic granular waste samples, already reduced in fine form with particles

This study investigates the hygrothermal aging effect on the tensile and impact behavior of flax/PLA biocomposites. Specimens underwent up to four weeks of conditioning at 40°C in a climate chamber with water. Analysis covered porosity, moisture diffusibility, and transversal microstructure, enabling assessment of tensile strength, tensile modulus, and impact performance in relation to moisture uptake and fiber orientation. The study of tensile properties revealed that at approximately 12% moisture content, stiffness and yield stress decrease, while strength remains constant. Moisture diffusivity is higher in warp and weft yarn directions than the out‐of‐plane direction. Tensile testing at environmental equilibrium moisture reveals greater stiffness in the weft direction, correlated with lower crimp percentage and yarn angle. The main contribution of the paper is the study of the influence of moisture on the impact behavior, the results show that energy absorption capability of flax/PLA biocomposite increases with moisture content. Highlights: Fully biodegradable composite material by heat‐compression molding subjected to hygrothermal aging conditions for up to four weeks.The moisture diffusivity in both the warp and weft yarn directions registered higher values in comparison to the out‐of‐plane direction.Tensile testing at environmental equilibrium moisture revealed that the stiffness in the weft direction presented higher values.At 12% of moisture uptake, the stiffness and yield stress reached their lowest values, while strength remained constant.However, the low‐velocity impact properties of the composites exhibited improvement with moisture. [ABSTRACT FROM AUTHOR]

The spacer layer imaging method (SLIM) is widely used to measure the thickness of additive and lubricant films, in lubricant development and evaluation, and for fundamental research into elastohydrodynamic lubrication and tribofilm formation mechanisms. The film thickness measurement, as implemented on several popular tribometers, provides powerful, non-destructive in-situ mapping of film topography with nanometre-scale height sensitivity. However, the results can be highly sensitive to experimental procedure, machine condition, and image analysis, in some cases reporting unphysical film thickness trends. The prevailing image analysis techniques make it challenging to interrogate these errors, often hiding their multivariate nonlinear behaviour from the user by spatial averaging. Herein, several common ‘silent errors’ in the SLIM measurement, including colour matching to incorrect fringe orders, and colour drift due to the optical properties of the system or film itself, are discussed, with examples. A robust suite of novel a priori and a posteriori methods to address these issues, and to improve the accuracy and reliability of the measurement, are also presented, including a novel, computationally inexpensive circle-finding algorithm for automated image processing. In combination, these methods allow reliable mapping of films up to at least 800 nm in thickness, representing a significant milestone for the utility of SLIM applied to elastohydrodynamic contact. [ABSTRACT FROM AUTHOR]

Diatom communities preserved in sediment samples are valuable indicators for understanding the past and present dynamics of phytoplankton communities, and their response to environmental changes. These studies are traditionally achieved by counting methods using optical microscopy, a time‐consuming process that requires taxonomic expertise. With the advent of automated image acquisition workflows, large image data sets can now be acquired, but require efficient preprocessing methods. Detecting diatom frustules on microscope images is a challenge due to their low relief, diverse shapes, and tendency to aggregate, which prevent the use of traditional thresholding techniques. Deep learning algorithms have the potential to resolve these challenges, more particularly for the task of object detection. Here we explore the use of a Faster Region‐based Convolutional Neural Network model to detect siliceous biominerals, including diatoms, in microscope images of a sediment trap series from the Mediterranean Sea. Our workflow demonstrates promising results, achieving a precision score of 0.72 and a recall score of 0.74 when applied to a test set of Mediterranean diatom images. Our model performance decreases when used to detect fragments of these microfossils; it also decreases when particles are aggregated or when images are out of focus. Microfossil detection remains high when the model is used on a microscope image set of sediments from a different oceanic basin, demonstrating its potential for application in a wide range of contemporary and paleoenvironmental studies. This automated method provides a valuable tool for analyzing complex samples, particularly for rare species under‐represented in training data sets. Plain Language Summary: Microfossils preserved in ocean sediments are studied to explore the impact of climate change on planktonic communities. The usual way to count these microfossils is slow and requires an expert to identify them on microscope images. In this study, we explore how artificial intelligence can be used on microscope images to detect the microfossils produced by one particular group, diatoms. Our results show that models can be trained to identify these objects, including the ones that were not specifically shown to the model during the training phase. However, the quality of the microscope image, and of the sample preparation beforehand, can affect how well the model works. This new protocol has good potential to be used on diatom images differing in age and geographical origins. Adopting this method could make it possible to rapidly increase the temporal resolution and spatial extent of existing data on diatom diversity, which could thus improve our knowledge of plankton resilience to climate change. Key Points: Faster Region‐based Convolutional Neural Network models are efficient at detecting marine diatom frustules on microscope slide imagesThese models can be applied to detect the diatoms on images from a diverse array of environmental conditionsAdequate sample preparation and image quality enhance model results [ABSTRACT FROM AUTHOR]

Monolayer black phosphorus (BP) holds great promise for naturally hyperbolic polaritons and correlated states in rectangular moiré superlattices. However, preparing and identifying high-quality monolayer BP are challenging due to its instability and high transparency, which limits extensive studies. In this study, we developed a method for rapidly and nondestructively identifying monolayer BP and its crystal orientation simultaneously using modified photoluminescence (PL) microscopy. The optical contrast of monolayer BP has been significantly increased by at least twenty times compared to previous reports, making it visible even on a transparent substrate. The polarization dependence of optical contrast also allows for the in situ determination of crystal orientation. Our study facilitates the identification of monolayer BP, expediting more extensive research on and potential industrial applications of this material. [ABSTRACT FROM AUTHOR]

Grain boundary segmentation is crucial for the quantitative analysis of grain structures and material optimization. However, challenges persist due to noise interference, high labeling costs, and low detection Accuracy. Therefore, we propose a semi-supervised method called Semi-SRUnet, which is based on teacher–student knowledge distillation and pseudo-label repair to achieve grain boundary detection for a small number of labels. Specifically, the method introduces SCConv (Spatial and Channel Reconstruction Convolution) and boundary regression to improve the U-Net (a convolutional neural network architecture) as a teacher network. These innovations aim to reduce spatial and channel redundancy, expand the receptive field, and effectively capture contextual information from images, thereby improving feature extraction robustness and boundary precision in noisy environments. Additionally, we designed a pseudo-label repair algorithm to enhance the Accuracy of pseudo-labels generated by the teacher network and used knowledge distillation to train a lightweight student network. The experimental results demonstrate that Semi-SRUnet achieves 88.86% mean Intersection over Union (mIoU), 96.64% mean Recall (mRecall), 91.5% mean Precision (mPrecision), and 98.77% Accuracy, surpassing state-of-the-art models and offering a novel approach for reliable grain boundary segmentation and analysis. [ABSTRACT FROM AUTHOR]

The use of low-carbon unalloyed steel with minimal silicon content is widespread in structural steel and automotive applications due to its ease of manipulation. The mechanical properties of this steel can be significantly enhanced through severe plastic deformation (SPD) techniques. Our study focuses on the practical benefits of the dual rolling equal channel extrusion (DRECE) method, which strengthens the steel and has implications for material hardness and the thickness of subsequently applied hot-dip zinc galvanizing. Furthermore, the steel's corrosion potential and current are investigated as a function of material hardness and thickness. The findings show a 20% increase in hardness HV 30 after the first run through the forming machine, with an additional 10% increase after the second run. Subsequent galvanizing leads to a further 1–12% increase in HV 30 value. Notably, the DRECE hardening demonstrates no statistically significant effect on the corrosion potential and current; however, the impact of galvanizing is as anticipated. [ABSTRACT FROM AUTHOR]

In general, patients' opinions on reaching ideal esthetics while restoring dental tissues is one of the most important part of the oral treatment. Unfortunately, discoloration of dental materials may occur due to intrinsic and extrinsic factors. The aim of the study was to evaluate the color stability of frequently used dental resin materials and determine the mechanism of their discoloration. The study used various characterization techniques (optical microscopy, Fourier-transform infrared spectroscopy, low-temperature N2 adsorption, diffuse reflectance spectroscopy, and luminescence) to understand the effect of surface defects on discoloration. The adsorption of model liquids on the surface was confirmed to be related to the increase in BET surface area. The study found that the adsorption of discolorants, such as coffee, tea, and wine, on the surface of the dental material follows the multilayer BET model. When the surface is smooth, the discoloration is usually within acceptable limits, with a maximum of ∆E = 3.3. The discoloration made by tea and demineralized water was within acceptable limits even after 7 days of exposure. [ABSTRACT FROM AUTHOR]

Recently, the demand for 3D microscopic observation of optically transparent biological cells and optical components with micro-sized structures has increased. This demand stems from the continuous development of bio-medical and precision machinery engineering. Various microscopic observation methods for phase objects, such as laser confocal fluorescence and phase contrast microscopy exist. However, these methods have some limitations. The former suffers from the problem of sample contamination by fluorescent staining, whereas the latter is faced with challenges in achieving quantitative measurements, particularly for thick samples. To address these issues, this study focuses on a common optical microscope with non-destructive, noncontact, and low-cost capabilities for both transmission and reflection observations. However, two critical problems arise during image acquisition using the common optical microscope. First, the resolution decreases owing to the diffraction limit of optics. Second, phase information is lost in the image acquired by an image sensor. Generally, a quantitative 3D measurement of the sample obtained by utilizing an optical microscope requires amplitude and phase information of light. Therefore, we propose ptychographic structured illumination microscopy (SIM). This is a combination of the SIM and ptychographic reconstruction of the phase information of light. It enables both super-resolution and phase retrieval in optical microscopic imaging. First, we designed a numerical model of the proposed ptychographic SIM and subsequently evaluated its performance through a series of numerical simulations. Next, we developed an experimental setup and successfully improved the resolution by approximately a factor of two approximately, while quantitatively recovering optical phase information as well. [ABSTRACT FROM AUTHOR]

Advances in imaging tools have always been a pivotal driver for new discoveries in neuroscience. An ability to visualize neurons and subcellular structures deep within the brain of a freely behaving animal is integral to our understanding of the relationship between neural activity and higher cognitive functions. However, fast highresolution imaging is limited to sub-surface brain regions and generally requires head fixation of the animal under the microscope. Developing new approaches to address these challenges is critical. The last decades have seen rapid progress in minimally invasive endo-microscopy techniques based on bare optical fibers. A single multimode fiber can be used to penetrate deep into the brain without causing significant damage to the overlying structures and provide high-resolution imaging. Here, we discuss how the full potential of high-speed super-resolution fiber endoscopy can be realized by a holistic approach that combines fiber optics, light shaping, and advanced computational algorithms. The recent progress opens up new avenues for minimally invasive deep brain studies in freely behaving mice. [ABSTRACT FROM AUTHOR]

Purpose: Wood comprises different cell types, such as fibers, tracheids and vessels, defining its properties. Studying cells' shape, size, and arrangement in microscopy images is crucial for understanding wood characteristics. Typically, this involves macerating (soaking) samples in a solution to separate cells, then spreading them on slides for imaging with a microscope that covers a wide area, capturing thousands of cells. However, these cells often cluster and overlap in images, making the segmentation difficult and time-consuming using standard image-processing methods. Results: In this work, we developed an automatic deep learning segmentation approach that utilizes the one-stage YOLOv8 model for fast and accurate segmentation and characterization of macerated fiber and vessel form aspen trees in microscopy images. The model can analyze 32,640 x 25,920 pixels images and demonstrate effective cell detection and segmentation, achieving a mAP 0.5 - 0.95 of 78 %. To assess the model's robustness, we examined fibers from a genetically modified tree line known for longer fibers. The outcomes were comparable to previous manual measurements. Additionally, we created a user-friendly web application for image analysis and provided the code for use on Google Colab. Conclusion: By leveraging YOLOv8's advances, this work provides a deep learning solution to enable efficient quantification and analysis of wood cells suitable for practical applications. [ABSTRACT FROM AUTHOR]

Microplastic ingestion by marine organisms presents a challenge to both ecosystem functioning and human health. We characterized microplastic abundance, shape, size, and polymer types ingested by the West African mangrove oyster, Crassostrea tulipa (Lamarck, 1819) sampled from estuaries and lagoons from the Gambia, Sierra Leone, Ghana, Benin, and Nigeria using optical microscopy and Fourier transform infrared (FTIR) techniques. A total of 780 microplastics were isolated in the whole tissues of the 250 oysters (n = 50 oysters per country). The abundance and distribution of microplastics in the oysters followed the pattern: the Gambia > Ghana > Sierra Leone > Nigeria > Benin. The Tanbi wetlands in the Gambia recorded the highest average of 10.50 ± 6.69 per oyster while the Ouidah lagoon in Benin recorded the lowest average of 1.80 ± 1.90 per oyster. Overall, microplastic numbers varied significantly (p < 0.05) among the five countries. Microfibers, particularly those within 1001–5000 μm size, dominated the total microplastic count with a few fragments and films. No spherical microplastics were isolated in the oysters. In the Sierra Leone and Benin oysters, fragments and films were absent in the samples. Microplastic between the 1001 and 5000 μm size class dominated the counts, followed by 501–1000 μm, 101–500 μm, and 51–100 μm. Five polymer groups namely polyethylene, polyester, nylon, polypropylene, and polyamide were identified across the five countries, with polyethylene occurring in oysters from all five countries and polyester occurring in all but the oysters from Nigeria. This diversity of polymers suggests varied sources of microplastics ingested by the studied oysters. The absence of microspheres across the five supports findings from other studies that they are the least ingested and highly egested by the oysters. [ABSTRACT FROM AUTHOR]

Among the most alarming postharvest fungal pathogens affecting the shelf life of citrus fruits are green (Penicillium digitatum) and blue (Penicillium italicum) molds. This in vitro study was aimed to evaluate the essential oils (EOs) of Cymbopogon flexuosus (CF) and Monarda citriodora (MC) and their principal components against these fungal pathogens. The composition of selected EOs was analyzed using Gas Chromatography- Mass Spectrometry (GC-MS) and Gas Chromatography-Flame Ionization Detector (GC-FID). Citral (83.81%) and thymol (62.51%) were identified as major components and were isolated by column chromatography from CF and MC EO respectively followed by characterization using spectral techniques such as Fourier Transform Infrared Spectroscopy (FTIR), Proton Nuclear Magnetic Resonance Spectroscopy (1H-NMR) and Carbon Nuclear Magnetic Resonance Spectroscopy (13C-NMR). Among EOs and their major components, thymol displayed promising potential against both Penicillium species with MIC values of 50 and 80 mg L-1 respectively. Molecular docking studies also confirmed the stable binding interaction of both components, particularly thymol with the active sites of target proteins i.e. 14-α-demethylase and chitin synthase of P. digitatum and P. italicum with the docking scores of -5.07, -5.41 kcal/mol and -5.78, -5.23 kcal/mol respectively. Optical microscopy studies revealed hyphal thinning and fragmentation at frequent sites with contraction of cytoplasmic content indicating incipient plasmolysis. The tested principal components, citral and thymol were predicted to exhibit similar mechanism of action to that of synthetic recommended molecules as revealed by molecular docking. Therefore, these findings provide empirical support to explore thymol as a promising eco-friendly antifungal agent for postharvest application in Kinnow. [ABSTRACT FROM AUTHOR]

In this research, poly(vinyl alcohol)/polyaniline blend films were fabricated using solution casting technique with different weight ratios of PANI (2, 4, 6, 8, and 10) wt.%. The results showed that the best ratio of the polymer blend was (92% PVA/8% PANI), based on the electrical conductivity of direct current. The results showed that 8 wt.% PANI possessed the highest conductivity. Then, the composite films were prepared by adding multi-walled carbon nanotubes (MWCNT) to the optimum ratio of the polymer blend as a base material and at different weight ratios (0, 1, 3, 5, 7 wt.%). A tension device was used to examine and characterize the prepared samples. It was found that the addition of MWCNT to PVA/PANI caused an obvious decrease in elongation while there was an increase in tension strength and "Young's modulus". Optical microscopy results showed a good picture of the distribution of MWCNT particles for composites up to 1 wt.% MWCNT. But, some aggregations can be observed in films with 3, 5, and 7 wt.% MWCNT content. [ABSTRACT FROM AUTHOR]

Optical microscopy has undergone significant changes in recent decades due to the improved diffraction limit of optical resolution and the development of high-resolution imaging techniques referred to under the common name fluorescence nanoscopy. These techniques allow researchers to observe in detail biological structures and processes at a nanoscale level to reveal previously hidden features and answer basic biological questions. The advanced methods of fluorescent nanoscopy include STED (Stimulated Emission Depletion) Microscopy, STORM (STochastic Optical Reconstruction Microscopy), PALM (Photo-activated Localization Microscopy), TIRF (Total Internal Reflection Fluorescence) microscopy, SIM (Structured Illumination Microscopy), MINFLUX (Minimal Photon Fluxes) microscopy, PAINT (Points Accumulation for Imaging in Nanoscale Topography), and RESOLFT (REversible Saturable Optical Fluorescence Transitions) microscopy, and others. Most these methods make it possible to obtain 3D images of the objects under study. In this review, we consider the principles of these methods, their advantages and disadvantages, and their application in biological research. [ABSTRACT FROM AUTHOR]

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Cold spray additively manufactured (CSAM) aluminum 6061 components are characterized by heterogeneous compressive residual stresses induced during manufacturing. This heterogeneity is further compounded by spatial variations in microstructures and mechanical properties, leading to poor inter-particle (intersplat) bonding and significant marring of overall component performance. Thermal post-processing is a keenly researched method for recovering mechanical toughness by enhancing intersplat bonding and altering highly concentrated residual stress distributions. The current work incorporates a modified microscale–mesoscale material model into a viscoplastic self-consistent simulation framework to capture material response in the as-sprayed and post-processed states. The updated model incorporates physically informed parameters emphasizing residual stresses measured experimentally through X-ray diffraction. The model calibrated using experimental tests and published literature was able to predict the stress–strain response of CSAM parts at post-heat-treated conditions. Results of the parametric study showed the significance of intersplat boundary effects on the overall yield and strain hardening of the CSAM parts. Without any information on the processing conditions of CSAM parts, the modified plasticity model predicted the deformation response using information gathered from microstructure characterization. [ABSTRACT FROM AUTHOR]

A product class characterization was requested on some plastic granular waste samples, already reduced in fine form with particles < 20 mm, derived from waste electrical wires and PC cables. The product class discrimination was worked out by visual characterization with the aid of optical stereomicroscopy and confirmation by electron scanning microscopy (SEM) and microanalysis. Characterization at a micro-scale level evidenced predominance of plastic materials with presence of metal wires, paper, textile and glass fibres at residual levels in the main fraction (0.5–4 mm). The fractions < 0.5 mm, when present, cannot easily be distinguished at sight and only approximate qualitative information can be extracted by SEM analysis. The described approach has been carried out effectively due to major shape and material differences between plastic particles and metal wires and other materials. However, this approach may not work in every case, or it may not lead to usable results with every type of waste. [ABSTRACT FROM AUTHOR]

Li redistribution processes within Si-graphite composite (SiG) electrodes are analyzed using in situ and operando X-ray diffraction (XRD), ex situ light microscopy (LM), in situ optical microscopy of cross-sectioned full cells (CS-IOM), and 3D microstructure-resolved simulations of full cells. First, the lithiation behavior of graphite and SiG full cells (Si content 20.8 wt.-%) is analyzed. The results are used as validation of the methods (XRD, LM, CS-IOM, simulation). Second, the Li redistribution between the graphite component and Si component within SiG electrodes is investigated: By operando XRD measurements during charging in comparison with relaxed cells, a higher lithiation degree in the graphite component is found during charging compared to the relaxed state, indicating Li redistribution from graphite to Si during relaxation. The Li redistribution is directly observed by in situ and ex situ optical microscopy, where the golden LiC6 phase disappears during a 24 h relaxation period. The results are supported by simulations showing the variation in the Li concentration, not only in graphite but also within the Si component. Furthermore, all methods find that the Li redistribution is more pronounced at a higher C-rate of 0.5 C, suggesting a preference for graphite lithiation over Si lithiation. [ABSTRACT FROM AUTHOR]

Two protocols for multistep grain segmentation and analysis workflow in optical microscopy images of cubic boron nitride materials were developed and compared. One is based on statistical region merging and second one on morphological segmentation of grains without high contrast borders. Judging from corresponding manual image segmentation by expert, the second method gave more accurate grain boundaries and better statistical correspondence. Then, using the morphological segmentation method and incorporating of parameter optimization into it, a grain analysis workflow was established. Deviations from the correct answer (expert segmentation) were quantified based on five geometric statistical indices, and these deviations were added together to define the overall error. Cross-validation confirmed that the morphological segmentation workflow reproduces the expert segmentation with smaller 9.4% margin of error compared to 23.9% with statistical region merging one. The automated grain segmentation of such challenging materials with high throughput image analysis is an important help for industrial development of new milling tools.

To identify morphological and structural variations in WaveOne Gold Primary® related to artificial canal instrumentation, experiments were conducted on artificial canals fabricated from Diallyl-Phthalate to identify morphological and structural variations in WaveOne-Gold-Primary (n=10) endodontic instruments. The canals were immersed in water at 38° C ± 1°C and irrigated with NaClO-5%. The instruments were examined using optical microscopy to perform Cauchy strain measurements. Lattice parameters, microstrains, and texture were determined using X-ray diffraction. Scanning electron microscopy was employed to identify shear bands and fracture characteristics. Statistical analysis was performed using analysis of variance and Bonferroni tests. Untwisting and elongation were pronounced at approximately 54 pecks; fracture occurred at 62 pecks. Mathematical models were proposed to correlate strains and texture with the number of pecks. Substantial plastic deformations caused by the torsion-adhesion mechanism and associated with ductile fracture were observed, and grain domain alterations were identified. The difference between the sample's relative intensities in X-ray diffraction demonstrated texture changes between 0 and 20 pecks and a subsequent change after 62 pecks.