Cryo-EM Map Anisotropy Can Be Attenuated by Map Post-Processing and a New Method for Its Estimation

One of the most important challenges in cryogenic electron microscopy (cryo-EM) is the substantial number of samples that exhibit preferred orientations, which leads to an uneven coverage of the projection sphere. As a result, the overall quality of the reconstructed maps can be severely affected, as manifested by the presence of anisotropy in the map resolution. Several methods have been proposed to measure the directional resolution of maps in tandem with experimental protocols to address the problem of preferential orientations in cryo-EM. Following these works, in this manuscript we identified one potential limitation that may affect most of the existing methods and we proposed an alternative approach to evaluate the presence of preferential orientations in cryo-EM reconstructions. In addition, we also showed that some of the most recently proposed cryo-EM map post-processing algorithms can attenuate map anisotropy, thus offering alternative visualization opportunities for cases affected by moderate levels of preferential orientations.

Fluid suppression in amide proton transfer-weighted (APTw) CEST imaging: New theoretical insights and clinical benefits

PURPOSE

Amide proton transfer-weighted (APTw) MRI at 3T provides a unique contrast for brain tumor imaging. However, APTw imaging suffers from hyperintensities in liquid compartments such as cystic or necrotic structures and provides a distorted APTw signal intensity. Recently, it has been shown that heuristically motivated fluid suppression can remove such artifacts and significantly improve the readability of APTw imaging.

THEORY AND METHODS

In this work, we show that the fluid suppression can actually be understood by the known concept of spillover dilution, which itself can be derived from the Bloch-McConnell equations in comparison to the heuristic approach. Therefore, we derive a novel post-processing formula that efficiently removes fluid artifact, and explains previous approaches. We demonstrate the utility of this APTw assessment in silico, in vitro, and in vivo in brain tumor patients acquired at MR scanners from different vendors.

RESULTS

Our results show a reduction of the CEST signals from fluid environments while keeping the APTw-CEST signal intensity almost unchanged for semi-solid tissue structures such as the contralateral normal appearing white matter. This further allows us to use the same color bar settings as for conventional APTw imaging.

CONCLUSION

Fluid suppression has considerable value in improving the readability of APTw maps in the neuro-oncological field. In this work, we derive a novel post-processing formula from the underlying Bloch-McConnell equations that efficiently removes fluid artifact, and explains previous approaches which justify the derivation of this metric from a theoretical point of view, to reassure the scientific and medical field about its use.

Surface Finishing and Coating Parameters Impact on Additively Manufactured Binder-Jetted Steel-Bronze Composites

In this paper, electroless nickel plating is explored for the protection of binder-jetting-based additively manufactured (AM) composite materials. Electroless nickel plating was attempted on binder-jetted composites composed of stainless steel and bronze, resulting in differences in the physicochemical properties. We investigated the impact of surface finishing, plating solution chemistry, and plating parameters to attain a wide range of surface morphologies and roughness levels. We employed the Keyence microscope to quantitatively evaluate dramatically different surface properties before and after the coating of AM composites. Scanning electron microscopy revealed a wide range of microstructural properties in relation to each combination of surface finishing and coating parameters. We studied chempolishing, plasma cleaning, and organic cleaning as the surface preparation methods prior to coating. We found that surface preparation dictated the surface roughness. Taguchi statistical analysis was performed to investigate the relative strength of experimental factors and interconnectedness among process parameters to attain optimum coating qualities. The quantitative impacts of phosphorous level, temperature, surface preparation, and time factor on the roughness of the nickel-plated surface were 17.95%, 8.2%, 50.02%, and 13.21%, respectively. On the other hand, the quantitative impacts of phosphorous level, temperature, surface preparation, and time factor on the thickness of nickel plating were 35.12%, 41.40%, 3.87%, and 18.24%, respectively. The optimum combination of the factors' level projected the lowest roughness of Ra at 7.76 µm. The optimum combination of the factors' level projected the maximum achievable thickness of ~149 µm. This paper provides insights into coating process for overcoming the sensitivity of AM composites in hazardous application spaces via robust coating.

Efficient Integration of Rate-Adaptive Reconciliation with Syndrome-Based Error Estimation and Subblock Confirmation for Quantum Key Distribution

An effective post-processing algorithm is essential for achieving high rates of secret key generation in quantum key distribution. This work introduces an approach to quantum key distribution post-processing by integrating the three main steps into a unified procedure: syndrome-based error estimation, rate-adaptive reconciliation, and subblock confirmation. The proposed scheme employs low-density parity-check codes to estimate the quantum bit error rate using the syndrome information, and to optimize the channel coding rates based on the Slepian-Wolf coding scheme for the rate-adaptive method. Additionally, this scheme incorporates polynomial-based hash verification in the subblock confirmation process. The numerical results show that the syndrome-based estimation significantly enhances the accuracy and consistency of the estimated quantum bit error rate, enabling effective code rate optimization for rate-adaptive reconciliation. The unified approach, which integrates rate-adaptive reconciliation with syndrome-based estimation and subblock confirmation, exhibits superior efficiency, minimizes practical information leakage, reduces communication rounds, and guarantees convergence to the identical key. Furthermore, the simulations indicate that the secret key throughput of this approach achieves the theoretical limit in the context of a BB84 quantum key distribution system.

Image processing setting adaptions according to image dose and radiologist preference can improve image quality in computed radiography of the equine distal limb: A cadaveric study

Image processing (IP) in digital radiography has been steadily refined to improve image quality. Adaptable settings enable users to adjust systems to their specific requirements. This prospective, analytical study aimed to investigate the influence of different IP settings and dose reductions on image quality. Included were 20 cadaveric equine limb specimens distal to the metacarpophalangeal and metatarsophalangeal joints. Images were processed with the Dynamic Visualization II system (Fujifilm) using five different IP settings including multiobjective frequency processing, flexible noise control (FNC), and virtual grid processing (VGP). Seven criteria were assessed by three veterinary radiology Diplomates and one veterinary radiology resident in a blinded study using a scoring system. Algorithm comparison was performed using an absolute visual grading analysis. The rating of bone structures was improved by VGP at full dose (P < .05; AUCVGC  = 0.45). Überschwinger artifact perception was enhanced by VGP (P < .001; AUCVGC  = 0.66), whereas image noise perception was suppressed by FNC (P < .001; AUCVGC  = 0.29). The ratings of bone structures were improved by FNC at 50% dose (P < .05; AUCVGC  = 0.44), and 25% dose (P < .001; AUCVGC  = 0.32), and clinically acceptable image quality was maintained at 50% dose (mean rating 2.16; 95.8% ratings sufficient or better). The favored IP setting varied among observers, with higher agreement at lower dose levels. These findings supported using individualized IP settings based on the radiologist's preferences and situational image requirements, rather than using default settings.

Domain independent post-processing with graph U-nets: applications to electrical impedance tomographic imaging⋆

Objective.To extend the highly successful U-Net Convolutional Neural Network architecture, which is limited to rectangular pixel/voxel domains, to a graph-based equivalent that works flexibly on irregular meshes; and demonstrate the effectiveness on electrical impedance tomography (EIT).Approach.By interpreting the irregular mesh as a graph, we develop a graph U-Net with new cluster pooling and unpooling layers that mimic the classic neighborhood based max-pooling important for imaging applications.Mainresults.The proposed graph U-Net is shown to be flexible and effective for improving early iterate total variation (TV) reconstructions from EIT measurements, using as little as the first iteration. The performance is evaluated for simulated data, and on experimental data from three measurement devices with different measurement geometries and instrumentations. We successfully show that such networks can be trained with a simple two-dimensional simulated training set, and generalize to very different domains, including measurements from a three-dimensional device and subsequent 3D reconstructions.Significance.As many inverse problems are solved on irregular (e.g. finite element) meshes, the proposed graph U-Net and pooling layers provide the added flexibility to process directly on the computational mesh. Post-processing an early iterate reconstruction greatly reduces the computational cost which can become prohibitive in higher dimensions with dense meshes. As the graph structure is independent of 'dimension', the flexibility to extend networks trained on 2D domains to 3D domains offers a possibility to further reduce computational cost in training.

XCP-D: A Robust Pipeline for the post-processing of fMRI data

Functional neuroimaging is an essential tool for neuroscience research. Pre-processing pipelines produce standardized, minimally pre-processed data to support a range of potential analyses. However, post-processing is not similarly standardized. While several options for post-processing exist, they tend not to support output from disparate pre-processing pipelines, may have limited documentation, and may not follow BIDS best practices. Here we present XCP-D, which presents a solution to these issues. XCP-D is a collaborative effort between PennLINC at the University of Pennsylvania and the DCAN lab at the University at Minnesota. XCP-D uses an open development model on GitHub and incorporates continuous integration testing; it is distributed as a Docker container or Singularity image. XCP-D generates denoised BOLD images and functional derivatives from resting-state data in either NifTI or CIFTI files, following pre-processing with fMRIPrep, HCP, and ABCD-BIDS pipelines. Even prior to its official release, XCP-D has been downloaded >3,000 times from DockerHub. Together, XCP-D facilitates robust, scalable, and reproducible post-processing of fMRI data.

Influence of Particle Size on the Mechanical Performance and Sintering Quality of Peanut Husk Powder/PES Composites Fabricated through Selective Laser Sintering

This study intends to enhance the mechanical strength of wood-plastic composite selective laser sintering (SLS) parts by using a sustainable composite, peanut husk powder (PHP)/poly ether sulfone (PES) (PHPC). The study aims to address agricultural waste pollution by encouraging the eco-friendly utilization of such waste in SLS technology. To ensure the sintering quality and mechanical properties and prevent deformation and warping during sintering, the thermo-physical properties of PHP and PES powders were analyzed to determine a suitable preheating temperature for PHPC. Single-layer sintering tests were conducted to assess the formability of PHPC specimens with varying PHP particle sizes. The study showed the effects of different PHP particle sizes on the mechanical performance of PHPC parts. The evaluation covered various aspects of PHPC SLS parts, including mechanical strength, density, residual ash content, dimensional accuracy (DA), and surface roughness, with different PHP particle sizes. The mechanical analysis showed that PHPC parts made from PHP particles of ≤0.125 mm were the strongest. Specifically, the density bending strength, residual ash content, tensile, and impact strength were measured as 1.1825 g/cm3, 14.1 MPa, 1.2%, 6.076 MPa, and 2.12 kJ/cm2, respectively. Notably, these parameters showed significant improvement after the wax infiltration treatment. SEM was used to examine the PHP and PES powder particles, PHPC specimen microstructure, and PHPC SLS parts before and after the mechanical tests and waxing. Consequently, SEM analysis wholly confirmed the mechanical test results.

Iodine-Based Sensitization of Copper Alloys to Enable Self-Terminating Etching for Support Removal and Surface Improvements of Additively Manufactured Components

Advances in selective laser melting (SLM) of metals in the past two decades have made metals additive manufacturing more accessible for industrial adoption. Despite printing process improvements, post-processing of SLM components has not improved much, resulting in considerable costs, delay, and design limitations. Building upon recent advances in sensitization-based self-terminating etching processes, this work details a new set iodine-based sensitization and etching chemistries that simplify the post-processing of copper (Cu) alloy components fabricated using SLM. This work demonstrates that iodine can be used to "sensitize" the surface of copper alloy components to form soluble copper iodide salt that can be then dissolved in common solvents, such as acetonitrile. This process removes a predefined amount of material from all interior and exterior surfaces in a self-terminating manner, enabling facile removal of internal and external supports, removal of any trapped powder, and the smoothing of interior and exterior surfaces. We demonstrate this process on GRCop (Cu-chromium-niobium) alloys due to their widespread use by the rocket propulsion industry along with a demonstration in copper (110) for applications in heat exchangers and electromagnetic transmitters/receivers. Our results provide the first systematic study on the effect of iodization temperature and duration on the thickness of the iodide region in GRCop-84 components. Additionally, the surface roughness before and after each iodization-dissolution was also quantified for GRCop-84 and showed 70% reduction in Ra roughness from a high of 10 μm as-printed to a low of 3 μm after four iodization-dissolution cycles.

A Review of the Residual Stress Generation in Metal Additive Manufacturing: Analysis of Cause, Measurement, Effects, and Prevention

Metal additive manufacturing (AM) is capable of producing complex parts, using a wide range of functional metals that are otherwise very difficult to make and involve multiple manufacturing processes. However, because of the involvement of thermal energy in the fabrication of metallic AM parts, residual stress remains one of the major concerns in metal AM. This residual stress has negative effects on part quality, dimensional accuracy, and part performance. This study aims to carry out a comprehensive review and analysis of different aspects of residual stress, including the causes and mechanisms behind the generation of residual stress during metal AM, the state-of-the-art measurement techniques for measuring residual stress, various factors influencing residual stress, its effect on part quality and performance, and ways of minimizing or overcoming residual stress in metal AM parts. Residual stress formation mechanisms vary, based on the layer-by-layer deposition mechanism of the 3D printing process. For example, the residual stress formation for wire-arc additive manufacturing is different from that of selective laser sintering, direct energy deposition, and powder bed fusion processes. Residual stress formation mechanisms also vary based on the scale (i.e., macro, micro, etc.) at which the printing is performed. In addition, there are correlations between printing parameters and the formation of residual stress. For example, the printing direction, layer thickness, internal structure, etc., influence both the formation mechanism and quantitative values of residual stress. The major effect residual stress has on the quality of a printed part is in the distortion of the part. In addition, the dimensional accuracy, surface finish, and fatigue performance of printed parts are influenced by residual stress. This review paper provides a qualitative and quantitative analysis of the formation, distribution, and evolution of residual stress for different metal AM processes. This paper also discusses and analyzes both in situ and ex situ measurement techniques for measuring residual stress. Microstructural evolution and its effect on the formation of residual stress are analyzed. Various pre- and post-processing techniques used to countermeasure residual stress are discussed in detail. Finally, this study aims to present both a qualitative and quantitative analysis of the existing data and techniques in the literature related to residual stress, as well as to provide a critical analysis and guidelines for future research directions, to prevent or overcome residual stress formation in metal AM processes.

Laser Powder Bed Fusion of Inconel 718 Tools for Cold Deep Drawing Applications: Optimization of Printing and Post-Processing Parameters

Inconel 718 (IN 718) powder is used for a laser powder bed fusion (LPBF) printer, but the mechanical properties of the as-built object are not suited to cold deep drawing applications. This study uses the Taguchi method to design experimental groups to determine the effect of various factors on the mechanical properties of as-built objects produced using an LPBF printer. The optimal printing parameters are defined using the result for the factor response to produce an as-built object with the greatest ultimate tensile strength (UTS), and this is used to produce a specimen for post-processing, including heat treatment (HT) and surface finishing. The HT parameter value that gives the maximum UTS is the optimal HT parameter. The optimal printing and HT parameter values are used to manufacture a die and a punch to verify the suitability of the manufactured tool for deep drawing applications. The experimental results show that the greatest UTS is 1091.33 MPa. The optimal printing parameters include a laser power of 190 W, a scanning speed of 600 mm/s, a hatch space of 0.105 mm and a layer thickness of 40 μm, which give a UTS of 1122.88 MPa. The UTS for the post-processed specimen increases to 1511.9 MPa. The optimal parameter values for HT are heating to 720 °C and maintaining this temperature for 8 h, decreasing the temperature to 620 °C and maintaining this temperature for 8 h, and cooling to room temperature in the furnace. Surface finishing increases the hardness to HRC 55. Tools, including a punch and a die, are manufactured using these optimized parameter values. The deep drawing experiment demonstrates that the manufactured tools that are produced using these values form a round cup of Aluminum alloy 6061. The parameter values that are defined can be used to manufacture IN 718 tools with a UTS of more than 1500 MPa and a hardness of more than 50 HRC, so these tools are suited to cold deep drawing specifications.

Biomass 3D Printing: Principles, Materials, Post-Processing and Applications

Under the background of green and low-carbon era, efficiently utilization of renewable biomass materials is one of the important choices to promote ecologically sustainable development. Accordingly, 3D printing is an advanced manufacturing technology with low energy consumption, high efficiency, and easy customization. Biomass 3D printing technology has attracted more and more attentions recently in materials area. This paper mainly reviewed six common 3D printing technologies for biomass additive manufacturing, including Fused Filament Fabrication (FFF), Direct Ink Writing (DIW), Stereo Lithography Appearance (SLA), Selective Laser Sintering (SLS), Laminated Object Manufacturing (LOM) and Liquid Deposition Molding (LDM). A systematic summary and detailed discussion were conducted on the printing principles, common materials, technical progress, post-processing and related applications of typical biomass 3D printing technologies. Expanding the availability of biomass resources, enriching the printing technology and promoting its application was proposed to be the main developing directions of biomass 3D printing in the future. It is believed that the combination of abundant biomass feedstocks and advanced 3D printing technology will provide a green, low-carbon and efficient way for the sustainable development of materials manufacturing industry.

SNAP: a structure-based neuron morphology reconstruction automatic pruning pipeline

Background

Neuron morphology analysis is an essential component of neuron cell-type definition. Morphology reconstruction represents a bottleneck in high-throughput morphology analysis workflow, and erroneous extra reconstruction owing to noise and entanglements in dense neuron regions restricts the usability of automated reconstruction results. We propose SNAP, a structure-based neuron morphology reconstruction pruning pipeline, to improve the usability of results by reducing erroneous extra reconstruction and splitting entangled neurons.

Methods

For the four different types of erroneous extra segments in reconstruction (caused by noise in the background, entanglement with dendrites of close-by neurons, entanglement with axons of other neurons, and entanglement within the same neuron), SNAP incorporates specific statistical structure information into rules for erroneous extra segment detection and achieves pruning and multiple dendrite splitting.

Results

Experimental results show that this pipeline accomplishes pruning with satisfactory precision and recall. It also demonstrates good multiple neuron-splitting performance. As an effective tool for post-processing reconstruction, SNAP can facilitate neuron morphology analysis.

Influence of Different Build Orientations and Heat Treatments on the Creep Properties of Inconel 718 Produced by PBF-LB

Inconel 718 is a nickel-based superalloy with excellent creep properties and good tensile and fatigue strength. In the field of additive manufacturing, it is a versatile and widely used alloy due to its good processability in the powder bed fusion with laser beam (PBF-LB) process. The microstructure and mechanical properties of the alloy produced by PBF-LB have already been studied in detail. However, there are fewer studies on the creep resistance of additively manufactured Inconel 718, especially when the focus is on the build direction dependence and post-treatment by hot isostatic pressing (HIP). Creep resistance is a crucial mechanical property for high-temperature applications. In this study, the creep behavior of additively manufactured Inconel 718 was investigated in different build orientations and after two different heat treatments. The two heat treatment conditions are, first, solution annealing at 980 °C followed by aging and, second, HIP with rapid cooling followed by aging. The creep tests were performed at 760 °C and at four different stress levels between 130 MPa and 250 MPa. A slight influence of the build direction on the creep properties was detected, but a more significant influence was shown for the different heat treatments. The specimens after HIP heat treatment show much better creep resistance than the specimens subjected to solution annealing at 980 °C with subsequent aging.

Post-acquisition water-signal removal in 3D water-unsuppressed 1 H-MR spectroscopic imaging of the prostate

PURPOSE

To develop a robust processing procedure of raw signals from water-unsuppressed MRSI of the prostate for the mapping of absolute tissue concentrations of metabolites.

METHODS

Water-unsuppressed 3D MRSI data were acquired from a phantom, from healthy volunteers, and a patient with prostate cancer. Signal processing included sequential computation of the modulus of the FID to remove water sidebands, a Hilbert transformation, and k-space Hamming filtering. For the removal of the water signal, we compared Löwner tensor-based blind source separation (BSS) and Hankel Lanczos singular value decomposition techniques. Absolute metabolite levels were quantified with LCModel and the results were statistically analyzed to compare the water removal methods and conventional water-suppressed MRSI.

RESULTS

The post-processing algorithms successfully removed the water signal and its sidebands without affecting metabolite signals. The best water removal performance was achieved by Löwner tensor-based BSS. Absolute tissue concentrations of citrate in the peripheral zone derived from water-suppressed and unsuppressed ¹ H MRSI were the same and as expected from the known physiology of the healthy prostate. Maps for citrate and choline from water-unsuppressed 3D ¹ H-MRSI of the prostate showed expected spatial variations in metabolite levels.

CONCLUSION

We developed a robust relatively simple post-processing method of water-unsuppressed MRSI of the prostate to remove the water signal. Absolute quantification using the water signal, originating from the same location as the metabolite signals, avoids the acquisition of additional reference data.

Influence of Post-Processing on the Properties of Multi-Material Parts Obtained by Material Projection AM

The great geometric complexity that additive manufacturing allows in parts, together with the possibility of combining several materials in the same part, establishes a new design and manufacturing paradigm. Despite the interest of many leading sectors, the lack of standardization still makes it necessary to carry out characterization work to enjoy these advantages in functional parts. In many of these techniques, the process does not end with the end of the machine cycle, but different post-processing must be carried out to consider the part finished. It has been found that the type of post process applied can have a similar effect on part quality as other further studied process parameters. In this work, the material projection technique was used to manufacture multi-material parts combining resins with different mechanical properties. The influence of different post-processing on the tensile behavior of these parts was analyzed. The results show the detrimental effect of ultrasonic treatment with isopropyl alcohol in the case of the more flexible resin mixtures, being advisable to use ultrasonic with mineral oil or furnace treatment. For more rigid mixtures, the furnace is the best option, although the other post-processing techniques do not significantly deteriorate their performance.

Influence of Antibacterial Coating and Mechanical and Chemical Treatment on the Surface Properties of PA12 Parts Manufactured with SLS and MJF Techniques in the Context of Medical Applications

Additive manufacturing (AM) is a rapidly growing branch of manufacturing techniques used, among others, in the medical industry. New machines and materials and additional processing methods are improved or developed. Due to the dynamic development of post-processing and its relative novelty, it has not yet been widely described in the literature. This study focuses on the surface topography (parameters Sa, Sz, Sdq, Sds, Str, Sdr) of biocompatible polyamide 12 (PA12) samples made by selective laser sintering (SLS) and multi jet fusion (MJF). The surfaces of the samples were modified by commercial methods: four types of smoothing treatments (two mechanical and two chemical), and two antibacterial coatings. The smoothing treatment decreased the values of all analyzed topography parameters. On average, the Sa of the SLS samples was 33% higher than that of the MJF samples. After mechanical treatment, Sa decreased by 42% and after chemical treatment by 80%. The reduction in Sdq and Sdr is reflected in a higher surface gloss. One antibacterial coating did not significantly modify the surface topography. The other coating had a smoothing effect on the surface. The results of the study can help in the development of manufacturing methodologies for parts made of PA12, e.g., in the medical industry.

Evaluation of deep-learning image reconstruction for chest CT examinations at two different dose levels

AIMS

The aims of the present study were to, for both a full-dose protocol and an ultra-low dose (ULD) protocol, compare the image quality of chest CT examinations reconstructed using TrueFidelity (Standard kernel) with corresponding examinations reconstructed using ASIR-V (Lung kernel) and to evaluate if post-processing using an edge-enhancement filter affects the noise level, spatial resolution and subjective image quality of clinical images reconstructed using TrueFidelity.

METHODS

A total of 25 patients were examined with both a full-dose protocol and an ULD protocol using a GE Revolution APEX CT system (GE Healthcare, Milwaukee, USA). Three different reconstructions were included in the study: ASIR-V 40%, DLIR-H, and DLIR-H with additional post-processing using an edge-enhancement filter (DLIR-H + E2). Five observers assessed image quality in two separate visual grading characteristics (VGC) studies. The results from the studies were statistically analyzed using VGC Analyzer. Quantitative evaluations were based on determination of two-dimensional power spectrum (PS), contrast-to-noise ratio (CNR), and spatial resolution in the reconstructed patient images.

RESULTS

For both protocols, examinations reconstructed using TrueFidelity were statistically rated equal to or significantly higher than examinations reconstructed using ASIR-V 40%, but the ULD protocol benefitted more from TrueFidelity. In general, no differences in observer ratings were found between DLIR-H and DLIR-H + E2. For the three investigated image reconstruction methods, ASIR-V 40% showed highest noise and spatial resolution and DLIR-H the lowest, while the CNR was highest in DLIR-H and lowest in ASIR-V 40%.

CONCLUSION

The use of TrueFidelity for image reconstruction resulted in higher ratings on subjective image quality than ASIR-V 40%. The benefit of using TrueFidelity was larger for the ULD protocol than for the full-dose protocol. Post-processing of the TrueFidelity images using an edge-enhancement filter resulted in higher image noise and spatial resolution but did not affect the subjective image quality.

On the Security of Offloading Post-Processing for Quantum Key Distribution

Quantum key distribution (QKD) has been researched for almost four decades and is currently making its way to commercial applications. However, deployment of the technology at scale is challenging because of the very particular nature of QKD and its physical limitations. Among other issues, QKD is computationally intensive in the post-processing phase, and devices are therefore complex and power hungry, which leads to problems in certain application scenarios. In this work, we study the possibility to offload computationally intensive parts in the QKD post-processing stack in a secure way to untrusted hardware. We show how error correction can be securely offloaded for discrete-variable QKD to a single untrusted server and that the same method cannot be used for long-distance continuous-variable QKD. Furthermore, we analyze possibilities for multi-server protocols to be used for error correction and privacy amplification. Even in cases where it is not possible to offload to an external server, being able to delegate computation to untrusted hardware components on the device itself could improve the cost and certification effort for device manufacturers.

Processive Pathways to Metastability in Block Copolymer Thin Films

Block copolymers (BCPs) self-assemble into intricate nanostructures that enhance a multitude of advanced applications in semiconductor processing, membrane science, nanopatterned coatings, nanocomposites, and battery research. Kinetics and thermodynamics of self-assembly are crucial considerations in controlling the nanostructure of BCP thin films. The equilibrium structure is governed by a molecular architecture and the chemistry of its repeat units. An enormous library of materials has been synthesized and they naturally produce a rich equilibrium phase diagram. Non-equilibrium phases could potentially broaden the structural diversity of BCPs and relax the synthetic burden of creating new molecules. Furthermore, the reliance on synthesis could be complicated by the scalability and the materials compatibility. Non-equilibrium phases in BCPs, however, are less explored, likely due to the challenges in stabilizing the metastable structures. Over the past few decades, a variety of processing techniques were introduced that influence the phase transformation of BCPs to achieve a wide range of morphologies. Nonetheless, there is a knowledge gap on how different processive pathways can induce and control the non-equilibrium phases in BCP thin films. In this review, we focus on different solvent-induced and thermally induced processive pathways, and their potential to control the non-equilibrium phases with regards to their unique aspects and advantages. Furthermore, we elucidate the limitations of these pathways and discuss the potential avenues for future investigations.

Biocompatibility enhancement via post-processing of microporous scaffolds made by optical 3D printer

Providing a 3D environment that mimics the native extracellular matrix is becoming increasingly important for various applications such as cell function studies, regenerative medicine, and drug discovery. Among the most critical parameters to consider are the scaffold's complicated micro-scale geometry and material properties. Therefore, stereolithography based on photopolymerization is an emerging technique because of its ability to selectively form volumetric structures from liquid resin through localized polymerization reactions. However, one of the most important parameters of the scaffold is biocompatibility, which depends not only on the material but also on the exposure conditions and post-processing, which is currently underestimated. To investigate this systematically, microporous scaffolds with pore sizes of 0.05 mm³ corresponding to a porosity of 16,4% were fabricated using the stereolithography printer Asiga PICO2 39 UV from the widely used resins FormLabs Clear and Flexible. The use of various polymers is usually limited for cells because, after wet chemical development, the non-negligible amount of remaining monomers intertwined in the photopolymerized structures is significantly toxic to cells. Therefore, the aim of this research was to find the best method to remove monomers from the 3D scaffold by additional UV exposure. For this purpose, a Soxhlet extractor was used for the first time, and the monomers were immersed in different alcohols. A Raman microspectroscopy was also used to investigate whether different post-processing methods affect DC (cross-linking) to find out if this specifically affects the biocompatibility of the scaffolds. Finally, mesenchymal stem cells from rat dental pulp were examined to confirm the increased biocompatibility of the scaffolds and their ability to support cell differentiation into bone tissue cells.

Manufacturing of Pure Copper with Electron Beam Melting and the Effect of Thermal and Abrasive Post-Processing on Microstructure and Electric Conductivity

Due to the increasing demand for electrification in the automotive sector, the interest in the manufacturing and processing of pure Copper (Cu; purity 99.99%) is also increasing. Laser-based technologies have proven to be challenging due to Cu's high optical reflectivity. Processing pure Cu with Electron Beam Melting (EBM) is a promising manufacturing route, allowing for high design freedom. The highest priority is to achieve outstanding thermal and electric conductivity in manufactured Cu components. Chemical contamination or manufacturing defects, such as porosity, significantly reduce the thermal and electric conductivity. The literature on post-processing (thermal and abrasive) of additively manufactured Cu is scarce. Therefore, this study discusses the correlation between as built and heat treated microstructure, as well as surface roughness on the EBM electric conductivity. EBSD analysis is performed to analyze the effect of microstructure on electric conductivity. The effect of sandblasting and vibratory finishing on surface roughness and electric conductivity is investigated. Additionally, the samples are mechanically tested in terms of hardness.

In Envelope Additive/Subtractive Manufacturing and Thermal Post-Processing of Inconel 718

This study investigated the application of an in envelope additive/subtractive (LPBF) manufacturing method (Matsuura LUMEX-Avance-25) to fabricate IN718 benchmarking coupons. The coupons were then examined comprehensively for surface finish both with and without high-speed micro-machining. The microstructure of the manufactured IN718 coupons was investigated thoroughly in the as-fabricated condition and following three different standard and one non-standard post-processing heat treatments. As built coupons revealed columnar grain morphology mainly along the <100> direction with a cellular dendritic sub-grain structure and without any strengthening precipitates. Grain size, aspect ratio, and texture were maintained after each of the applied four heat treatments. Only one of the standard heat treatments resulted in the δ phase formation. The other three heat treatments effectively dissolved the Laves phase preventing the δ formation while promoting the formation of γ′/γ″ precipitates. Despite the observed differences in their microstructures, all of the heat treatments resulted in similar yield and ultimate tensile strength values that ranged between 1103−1205 MPa and 1347−1387 MPa, respectively. These values are above the minimum requirements of 1034 MPa and 1241 MPa for the wrought material. The non-standard heat treatment provided the highest elongation of 24.0 ± 0.1% amongst all the heat-treated specimens without a significant loss in strength, while the standard heat treatment for the wrought parts resulted in the lowest elongation of 18.3 ± 0.7% due to the presence of δ phase.

The performance evaluation of the state-of-the-art EEG-based seizure prediction models

The recurrent and unpredictable nature of seizures can lead to unintentional injuries and even death. The rapid development of electroencephalogram (EEG) and Artificial Intelligence (AI) technologies has made it possible to predict seizures in real-time through brain-machine interfaces (BCI), allowing advanced intervention. To date, there is still much room for improvement in predictive seizure models constructed by EEG using machine learning (ML) and deep learning (DL). But, the most critical issue is how to improve the performance and generalization of the model, which involves some confusing conceptual and methodological issues. This review focuses on analyzing several factors affecting the performance of seizure prediction models, focusing on the aspects of post-processing, seizure occurrence period (SOP), seizure prediction horizon (SPH), and algorithms. Furthermore, this study presents some new directions and suggestions for building high-performance prediction models in the future. We aimed to clarify the concept for future research in related fields and improve the performance of prediction models to provide a theoretical basis for future applications of wearable seizure detection devices.

Reducing Surface Roughness of 3D Printed Short-Carbon Fiber Reinforced Composites

A 100 W fibre laser source was used to minimize the surface roughness of 3D-printed Onyx parts. Furthermore, this study aimed to determine the mechanism of surface finishing, the influence of the laser process parameters (laser power, pulse frequency, and laser scanning path) on the surface morphology, and the influence of the scanning path on the dimensional accuracy of the investigated Onyx 3D-printed specimens. A significant reduction in surface roughness of 91.15% was achieved on the S3 Onyx 3D-printed specimen following laser surface polishing treatment using a 50 W laser power and a frequency of 50 kHz. The laser scanning path had little influence on the surface roughness, but had a major impact on the geometrical deviation of the treated sample.

Conventional, Speed Sintering and High-Speed Sintering of Zirconia: A Systematic Review of the Current Status of Applications in Dentistry with a Focus on Precision, Mechanical and Optical Parameters

The aim of this systematic review was to provide an overview of the technical and clinical outcomes of conventional, speed sintering and high-speed sintering protocols of zirconia in the dental field. Data on precision, mechanical and optical parameters were evaluated and related to the clinical performance of zirconia ceramic. The PICOS search strategy was applied using MEDLINE to search for in vitro and in vivo studies using MeSH Terms by two reviewers. Of 66 potentially relevant studies, 5 full text articles were selected and 10 were further retrieved through a manual search. All 15 studies included in the systematic review were in vitro studies. Mechanical, precision and optical properties (marginal and internal fit, fracture strength and modulus, wear, translucency and opalescence, aging resistance/hydrothermal aging) were evaluated regarding 3-, 4- and 5-YTZP zirconia material and conventional, high- and high-speed sintering protocols. Mechanical and precision results were similar or better when speed or high-speed sintering methods were used for 3-, 4- and 5-YTZP zirconia. Translucency is usually reduced when 3 Y-TZP is used with speed sintering methods. All types of zirconia using the sintering procedures performed mechanically better compared to lithium disilicate glass ceramics but glass ceramics showed better results regarding translucency.

Production of GMP-Compliant Clinical Amounts of Copper-61 Radiopharmaceuticals from Liquid Targets

PET imaging has gained significant momentum in the last few years, especially in the area of oncology, with an increasing focus on metal radioisotopes owing to their versatile chemistry and favourable physical properties. Copper-61 (t_1/2 = 3.33 h, 61% β⁺, E_max = 1.216 MeV) provides unique advantages versus the current clinical standard (i.e., gallium-68) even though, until now, no clinical amounts of ⁶¹Cu-based radiopharmaceuticals, other than thiosemicarbazone-based molecules, have been produced. This study aimed to establish a routine production, using a standard medical cyclotron, for a series of widely used somatostatin analogues, currently labelled with gallium-68, that could benefit from the improved characteristics of copper-61. We describe two possible routes to produce the radiopharmaceutical precursor, either from natural zinc or enriched zinc-64 liquid targets and further synthesis of [⁶¹Cu]Cu-DOTA-NOC, [⁶¹Cu]Cu-DOTA-TOC and [⁶¹Cu]Cu-DOTA-TATE with a fully automated GMP-compliant process. The production from enriched targets leads to twice the amount of activity (3.28 ± 0.41 GBq vs. 1.84 ± 0.24 GBq at EOB) and higher radionuclidic purity (99.97% vs. 98.49% at EOB). Our results demonstrate, for the first time, that clinical doses of ⁶¹Cu-based radiopharmaceuticals can easily be obtained in centres with a typical biomedical cyclotron optimised to produce ¹⁸F-based radiopharmaceuticals.

Improvement in Mechanical Properties of 3D-Printed PEEK Structure by Nonsolvent Vapor Annealing

The broad applications of 3D-printed poly-ether-ether-ketone (3D-PEEK) structures are largely hampered by their inadequate mechanical properties which can be improved by post treatments. At present, thermal annealing is generally used to improve the mechanical properties of 3D-PEEK. However, it cannot simultaneously improve the strength and ductility. Here, a cost-effective post-processing method is developed to improve the mechanical properties of 3D-PEEK, based on annealing in nonsolvent vapor at room temperature. The annealing in nonsolvent vapor at room temperature simultaneously improves the strength, ductility, and fracture energy of as-printed 3D-PEEK by 22.6%, 151.3% and 109.1%, respectively. The improved mechanical properties are attributed to enhanced interfacial bonding, increased crystallinity, decreased pinhole defects, and stress relaxation in the 3D-PEEK. Moreover, the annealing in both polar solvents (such as acetone and chloroform) and nonpolar solvents (such as n-hexane) are demonstrated to be effective for improving the mechanical properties of 3D-PEEK. The nonsolvent vapor-annealed 3D-PEEK can thus have potential applications in the fields of medical implants, automotive, aerospace, and more. This article is protected by copyright. All rights reserved.

Optimization of dual energy computed tomography post-processing to reduce lower limb artifacts in gout

BACKGROUND

In gout, several types of dual-energy computed tomography (DECT) artifacts have been described (nail bed, skin, beam hardening, submillimeter and vascular artifacts), which can lead to overdiagnosis. The objective of this study was to determine the optimal DECT settings for post processing in order to reduce the frequency of some common artifacts in patients with suspected gout.

METHODS

Seventy-seven patients hospitalized for suspected gout (feet/ankles and/or knees) who received a DECT imaging were included (final diagnosis of 43 gout and 34 other rheumatic disorders). Different post-processing settings were evaluated using Syngovia software: nine settings (R1 to R9) were evaluated with a combination of different ratio (1.28, 1.36 and 1.55) and attenuation coefficient (120, 150, 170 HU).

RESULTS

Among the nine settings tested, the R2 setting (170 HU, ratio =1.28) significantly reduced the presence of knee and foot/ankle artifacts compared to the standard R1 setting (85% and 94% decrease in beam hardening and clumpy artifacts in the ankle and foot, respectively (P<0.001); a decrease of 71%, 60% and 88% respectively of meniscal beam hardening, beam hardening and submillimeter artifacts in the knee (P<0.001). Compared to standard settings, the use of R2 settings decreased sensitivity [0.79 (95% CI: 0.65, 0.88) versus 0.90 (95% CI: 0.78, 0.96)] and increased specificity [0.86 (95% CI: 0.71, 0.93) versus 0.63 (95% CI: 0.47, 0.77)] (P<0.001). Settings using an attenuation coefficient to 120 HU and/or a ratio to 1.55 were all associated with a significant increasing of artifacts, especially clumpy and beam hardening artifacts.

CONCLUSIONS

Applying a ratio of 1.28 and a minimum attenuation of 170 HU in DECT post-processing eliminates the majority of artifacts located in the lower limbs, particularly clumpy artifacts and beam hardening.

A Bidirectional Interpolation Method for Post-Processing in Sampling-Based Robot Path Planning

This paper proposes a post-processing method called bidirectional interpolation method for sampling-based path planning algorithms, such as rapidly-exploring random tree (RRT). The proposed algorithm applies interpolation to the path generated by the sampling-based path planning algorithm. In this study, the proposed algorithm is applied to the path created by RRT-connect and six environmental maps were used for the verification. It was visually and quantitatively confirmed that, in all maps, not only path lengths but also the piecewise linear shape were decreased compared to the path generated by RRT-connect. To check the proposed algorithm's performance, visibility graph, RRT-connect algorithm, Triangular-RRT-connect algorithm and post triangular processing of midpoint interpolation (PTPMI) were compared in various environmental maps through simulation. Based on these experimental results, the proposed algorithm shows similar planning time but shorter path length than previous RRT-like algorithms as well as RRT-like algorithms with PTPMI having a similar number of samples.

Graph-Theoretic Post-Processing of Segmentation With Application to Dense Biofilms

Recent deep learning methods have provided successful initial segmentation results for generalized cell segmentation in microscopy. However, for dense arrangements of small cells with limited ground truth for training, the deep learning methods produce both over-segmentation and under-segmentation errors. Post-processing attempts to balance the trade-off between the global goal of cell counting for instance segmentation, and local fidelity to the morphology of identified cells. The need for post-processing is especially evident for segmenting 3D bacterial cells in densely-packed communities called biofilms. A graph-based recursive clustering approach, m-LCuts, is proposed to automatically detect collinearly structured clusters and applied to post-process unsolved cells in 3D bacterial biofilm segmentation. Construction of outlier-removed graphs to extract the collinearity feature in the data adds additional novelty to m-LCuts. The superiority of m-LCuts is observed by the evaluation in cell counting with over 90% of cells correctly identified, while a lower bound of 0.8 in terms of average single-cell segmentation accuracy is maintained. This proposed method does not need manual specification of the number of cells to be segmented. Furthermore, the broad adaptation for working on various applications, with the presence of data collinearity, also makes m-LCuts stand out from the other approaches.

Effects of Post-processing on the Surface Finish, Porosity, Residual Stresses, and Fatigue Performance of Additive Manufactured Metals: A Review

Additive manufacturing (AM) has attracted much attention due to its capability in building parts with complex geometries. Unfortunately, AM metals suffer from three major drawbacks, including high porosity, poor surface finish, and tensile residual stresses, all of which will significantly compromise the fatigue performance. These drawbacks present a major obstacle to the application of AM metals in industries that produce fatigue-sensitive components. Many post-processing methods, including heat treatment, hot isotropic pressing, laser shock peening, ultrasonic nanocrystal surface modification, advanced finishing and machining, and laser polishing, have been used to treat AM metals to decrease their porosity, improve the surface finish, and eliminate tensile residual stresses. As a result, significant improvement in fatigue performance has been observed. In this paper, the state of the art in utilizing post-processing techniques to treat AM metals and the effects of these treatments on the porosity, surface finish, and residual stresses of metal components and their resultant fatigue performance are reviewed.

An Experimental Investigation of Controlled Changes in Wettability of Laser-Treated Surfaces after Various Post Treatment Methods

In this paper, a quick nanosecond laser micro structuring process was employed to change the surface wettability of Ti6Al4V alloy. The same laser structuring method was used throughout, but with varying input fluence. The laser processing parameters resulted in high surface melting. After laser treatment, four post-processing methods were used, namely high vacuum, low temperature annealing, storage in a polyethylene bag, and storage in ambient air. Subsequently, the water droplet contact angle was measured over a long time period of 55 days. The results show that the sample stored in ambient air remained hydrophilic. On the other hand, the sample post-processed in a vacuum chamber behaved hydrophobically with a contact angle of approximately 150°. Other post-processing did not lead to specific wettability behavior. After wettability testing, all samples were cleaned ultrasonically in distilled water. This cleaning process led to annulation of all obtained properties through post-processing. In summary, this paper shows that it is more important to study surface chemistry than topography in terms of effects on wettability. Moreover, surface wettability can be controlled by laser structuring, post-processing, and surface cleaning.

Towards implementing artificial intelligence post-processing in weather and climate: proposed actions from the Oxford 2019 workshop

The most mature aspect of applying artificial intelligence (AI)/machine learning (ML) to problems in the atmospheric sciences is likely post-processing of model output. This article provides some history and current state of the science of post-processing with AI for weather and climate models. Deriving from the discussion at the 2019 Oxford workshop on Machine Learning for Weather and Climate, this paper also presents thoughts on medium-term goals to advance such use of AI, which include assuring that algorithms are trustworthy and interpretable, adherence to FAIR data practices to promote usability, and development of techniques that leverage our physical knowledge of the atmosphere. The coauthors propose several actionable items and have initiated one of those: a repository for datasets from various real weather and climate problems that can be addressed using AI. Five such datasets are presented and permanently archived, together with Jupyter notebooks to process them and assess the results in comparison with a baseline technique. The coauthors invite the readers to test their own algorithms in comparison with the baseline and to archive their results. This article is part of the theme issue 'Machine learning for weather and climate modelling'.

Reconstruction of Relative Phase of Self-Transmitting Devices by Using Multiprobe Solutions and Non-Convex Optimization

Phase reconstruction is in general a non-trivial problem when it comes to devices where the reference is not accessible. A non-convex iterative optimization algorithm is proposed in this paper in order to reconstruct the phase in reference-less spherical multiprobe measurement systems based on a rotating arch of probes. The algorithm is based on the reconstruction of the phases of self-transmitting devices in multiprobe systems by taking advantage of the on-axis top probe of the arch. One of the limitations of the top probe solution is that when rotating the measurement system arch, the relative phase between probes is lost. This paper proposes a solution to this problem by developing an optimization iterative algorithm that uses partial knowledge of relative phase between probes. The iterative algorithm is based on linear combinations of signals when the relative phase is known. Phase substitution and modal filtering are implemented in order to avoid local minima and make the algorithm converge. Several noise-free examples are presented and the results of the iterative algorithm analyzed. The number of linear combinations used is far below the square of the degrees of freedom of the non-linear problem, which is compensated by a proper initial guess. With respect to noisy measurements, the top probe method will introduce uncertainties for different azimuth and elevation positions of the arch. This is modelled by considering the real noise model of a low-cost receiver and the results demonstrate the good accuracy of the method. Numerical results on antenna measurements are also presented. Due to the numerical complexity of the algorithm, it is limited to electrically small- or medium-size problems.

Post-Processing and Surface Characterization of Additively Manufactured Stainless Steel 316L Lattice: Implications for BioMedical Use

Additive manufacturing of stainless steel is becoming increasingly accessible, allowing for the customisation of structure and surface characteristics; there is little guidance for the post-processing of these metals. We carried out this study to ascertain the effects of various combinations of post-processing methods on the surface of an additively manufactured stainless steel 316L lattice. We also characterized the nature of residual surface particles found after these processes via energy-dispersive X-ray spectroscopy. Finally, we measured the surface roughness of the post-processing lattices via digital microscopy. The native lattices had a predictably high surface roughness from partially molten particles. Sandblasting effectively removed this but damaged the surface, introducing a peel-off layer, as well as leaving surface residue from the glass beads used. The addition of either abrasive polishing or electropolishing removed the peel-off layer but introduced other surface deficiencies making it more susceptible to corrosion. Finally, when electropolishing was performed after the above processes, there was a significant reduction in residual surface particles. The constitution of the particulate debris as well as the lattice surface roughness following each post-processing method varied, with potential implications for clinical use. The work provides a good base for future development of post-processing methods for additively manufactured stainless steel.

A bidirectional scanning method for scanning transmission X-ray microscopy

Scanning mode is a key factor for the comprehensive performance, including imaging efficiency, of scanning transmission X-ray microscopy (STXM). Herein is presented a bidirectional scanning method designed for STXM with an S-shaped moving track. In this method, artificially designed ramp waves are generated by a piezo-stage controller to control the two-dimensional scanning of the sample. The sample position information is measured using laser interferometric sensors and sent to a field-programmable gate array (FPGA) board which also acquires the X-ray signals simultaneously from the detector. Since the data recorded by the FPGA contain the real position of each scanned point, the influence of the backlash caused by the back-turning movement on the STXM image can be eliminated. By employing an adapted post-processing program, a re-meshed high-resolution STXM image can be obtained. This S-track bidirectional scanning method in fly-scan mode has been implemented on the STXM endstation at the Shanghai Synchrotron Radiation Facility (SSRF), and successfully resolved the ∼30 nm interval between the innermost strips of a Siemens star. This work removes the limitation on bidirectional scanning caused by motor backlash and vibration, and significantly improves the efficiency of STXM experiments.

A Non-Geodesic Trajectory Design Method and Its Post-Processing for Robotic Filament Winding of Composite Tee Pipes

With the advantages of high specific strength and well corrosion resistance, polymer-matrix composite tee pipes are widely used in aerospace and civilian fields. The robotic filament winding technology is suitable for forming complex shape parts. This paper aims to provide a novel non-geodesic trajectory design method to get a continuous trajectory for tee pipe winding. Furthermore, post-processing methods are proposed for realizing the full coverage of tee pipes by robotic filament winding. The CAD/CAM software is then designed to simulate the winding process and realize the cover of the whole tee pipe. Finally, experiments of winding a tee pipe with a desktop winding machine and a six-axis winding robot are carried out. The results show that the tee pipe is fully covered, verifying the accuracy of the design method and post-processing methods.

Magnetic Microwires with Unique Combination of Magnetic Properties Suitable for Various Magnetic Sensor Applications

There is a pressing demand to improve the performance of cost-effective soft magnetic materials for use in high performance sensors and devices. Giant Magneto-impedance effect (GMI), or fast single domain wall (DW) propagation can be observed in properly processed magnetic microwires. In this paper we have identified the routes to obtain microwires with unique combination of magnetic properties allowing observation of fast and single DW propagation and GMI effect in the same microwire. By modifying the annealing conditions, we have found the appropriate regimes allowing achievement of the highest GMI ratio and the fastest DW dynamics. The observed experimental results are discussed considering the radial distribution of magnetic anisotropy and the correlation of GMI effect, and DW dynamics with bulk and surface magnetization processes. Studies of both Fe- and Co-rich microwires, using the magneto-optical Kerr effect, MOKE, provide information on the magnetic structure in the outer shell of microwires. We have demonstrated the existence of the spiral helical structure in both studied microwires. At the same time, torsion mechanical stresses induce helical bistability in the same microwires, which allow us to consider these microwires as materials suitable for sensors based on the large Barkhausen jump.

Two-Step Laser Post-Processing for the Surface Functionalization of Additively Manufactured Ti-6Al-4V Parts

Laser powder bed fusion (LPBF) is one of the additive manufacturing methods used to build metallic parts. To achieve the design requirements, the LPBF process chain can become long and complex. This work aimed to use different laser techniques as alternatives to traditional post-processes, in order to add value and new perspectives on applications, while also simplifying the process chain. Laser polishing (LP) with a continuous wave laser was used for improving the surface quality of the parts, and an ultrashort pulse laser was applied to functionalize it. Each technique, individually and combined, was performed following distinct stages of the process chain. In addition to removing asperities, the samples after LP had contact angles within the hydrophilic range. In contrast, all functionalized surfaces presented hydrophobicity. Oxides were predominant on these samples, while prior to the second laser processing step, the presence of TiN and TiC was also observed. The cell growth viability study indicated that any post-process applied did not negatively affect the biocompatibility of the parts. The presented approach was considered a suitable post-process option for achieving different functionalities in localized areas of the parts, for replacing certain steps of the process chain, or a combination of both.

Biocompatibility of Blank, Post-Processed and Coated 3D Printed Resin Structures with Electrogenic Cells

The widespread adaptation of 3D printing in the microfluidic, bioelectronic, and Bio-MEMS communities has been stifled by the lack of investigation into the biocompatibility of commercially available printer resins. By introducing an in-depth post-printing treatment of these resins, their biocompatibility can be dramatically improved up to that of a standard cell culture vessel (99.99%). Additionally, encapsulating resins that are less biocompatible with materials that are common constituents in biosensors further enhances the biocompatibility of the material. This investigation provides a clear pathway toward developing fully functional and biocompatible 3D printed biosensor devices, especially for interfacing with electrogenic cells, utilizing benchtop-based microfabrication, and post-processing techniques.

Towards Functional Parts by Binder Jetting Calcium-Sulphate with Thermal Treatment Post-Processing

The objective of our research is to improve the properties of calcium-sulphate hemihydrate parts printed by binder jetting. In this paper, we show the thermal treatment results when using temperature time ramps on binder-jetted ceramic parts without infiltrating. The results show that the mechanical properties of printed parts are improved substantially. Two different thermal cycles were investigated for their effect on the dehydration process of CaSO_4·½H₂O using infrared analysis. The thermal-treated samples were compared with respect to porosity, surface roughness, compression strength and dimensional and weight variation. The proposed thermal treatment significantly improves the compression strength in a short time, guaranteeing dimensional stability while providing a good surface. This improvement in mechanical properties offers a great chance for using binder-jetted parts as functional components, for example, in the casting field or the medical sector (scaffolds).

Post-hoc physiological waveform extraction from motion estimation in simultaneous multislice (SMS) functional MRI using separate stack processing

PURPOSE

Motion estimation is an essential step in functional MRI (fMRI) preprocessing. Usually, fMRI processing software packages (eg, FSL and AFNI) automatically estimate motion parameters in order to counteract the effects of motion. However, the time courses of the motion estimation for fMRI data also contain information about physiological processes. Here, we show that respiration and cardiac signals can be extracted from motion estimation at significantly higher bandwidth than is possible with current methods.

METHOD

To detect motion at high effective temporal resolution (HighRes), the motion parameters of stacks of simultaneously acquired slices were estimated separately, then combined. This method was validated by extracting physiological motion signals from resting state fMRI (rsfMRI) data (Enhanced Nathan Kline Institute-Rockland Sample) and comparing them to respiration belt and pulse oximeter signals.

RESULTS

HighRes motion time-courses with an effective sampling rate of 15.5 and 11.4 Hz were extracted from repetition time (TR) = 0.645 and 1.4 s data, respectively. Respiration waveforms were extracted with significantly higher accuracy than the original motion parameters. Even cardiac waveforms could be extracted, despite the fact that the sampling time or TR values were too long to sample cardiac frequencies.

CONCLUSION

HighRes motion traces provide insight into the subjects' motion at higher frequencies than can be estimated using standard techniques. In its simplest form, this technique can recover accurate respiration signals and may reveal additional complexity in brain motion.

In Vivo Biosynthesis of Inorganic Nanomaterials Using Eukaryotes-A Review

Bionanotechnology, the use of biological resources to produce novel, valuable nanomaterials, has witnessed tremendous developments over the past two decades. This eco-friendly and sustainable approach enables the synthesis of numerous, diverse types of useful nanomaterials for many medical, commercial, and scientific applications. Countless reviews describing the biosynthesis of nanomaterials have been published. However, to the best of our knowledge, no review has been exclusively focused on the in vivo biosynthesis of inorganic nanomaterials. Therefore, the present review is dedicated to filling this gap by describing the many different facets of the in vivo biosynthesis of nanoparticles (NPs) using living eukaryotic cells and organisms-more specifically, live plants and living biomass of several species of microalgae, yeast, fungus, mammalian cells, and animals. It also highlights the strengths and weaknesses of the synthesis methodologies and the NP characteristics, bio-applications, and proposed synthesis mechanisms. This comprehensive review also brings attention to enabling a better understanding between the living organisms themselves and the synthesis conditions that allow their exploitation as nanobiotechnological production platforms as these might serve as a robust resource to boost and expand the bio-production and use of desirable, functional inorganic nanomaterials.

Selective Laser Sintering (SLS) and Post-Processing of Prosopis Chilensis/Polyethersulfone Composite (PCPC)

The range of selective laser sintering (SLS) materials is currently limited, and the available materials are often of high cost. Moreover, the mechanical strength of wood–plastic SLS parts is low, which restricts the application of a SLS technology. A new composite material has been proposed to address these issues, while simultaneously valorizing agricultural and forestry waste. This composite presents several advantages, including reduced pollution associated with waste disposal and reduced CO₂ emission with the SLS process in addition to good mechanical strength. In this article, a novel and low-cost Prosopis chilensis/polyethersulfone composite (PCPC) was used as a primary material for SLS. The formability of PCPC with various raw material ratios was investigated via single-layer experiments, while the mechanical properties and dimensional accuracy of the parts produced using the various PCPC ratios were evaluated. Further, the microstructure and particle distribution in the PCPC pieces were examined using scanning electron microscopy. The result showed that the SLS part produced via 10/90 (wt/wt) PCPC exhibited the best mechanical strength and forming quality compared to other ratios and pure polyethersulfone (PES), where bending and tensile strengths of 10.78 and 4.94 MPa were measured. To improve the mechanical strength, post-processing infiltration was used and the PCPC-waxed parts were enhanced to 12.38 MPa and 5.73 MPa for bending and tensile strength.

Effect of Various Peening Methods on the Fatigue Properties of Titanium Alloy Ti6Al4V Manufactured by Direct Metal Laser Sintering and Electron Beam Melting

Titanium alloy Ti6Al4V manufactured by additive manufacturing (AM) is an attractive material, but the fatigue strength of AM Ti6Al4V is remarkably weak. Thus, post-processing is very important. Shot peening can improve the fatigue strength of metallic materials, and novel peening methods, such as cavitation peening and laser peening, have been developed. In the present paper, to demonstrate an improvement of the fatigue strength of AM Ti6Al4V, Ti6Al4V manufactured by direct metal laser sintering (DMLS) and electron beam melting (EBM) was treated by cavitation peening, laser peening, and shot peening, then tested by a plane bending fatigue test. To clarify the mechanism of the improvement of the fatigue strength of AM Ti6Al4V, the surface roughness, residual stress, and surface hardness were measured, and the surfaces with and without peening were also observed using a scanning electron microscope. It was revealed that the fatigue strength at N = 10⁷ of Ti6Al4V manufactured by DMLS was slightly better than that of Ti6Al4V manufactured by EBM, and the fatigue strength of both the DMLS and EBM specimens was improved by about two times through cavitation peening, compared with the as-built ones. An experimental formula to estimate fatigue strength from the mechanical properties of a surface was proposed.

Post-Processing of FDM 3D-Printed Polylactic Acid Parts by Laser Beam Cutting

In this paper, the post-processing of 3D-printed poly lactic acid (PLA) parts is investigated. Workpieces are manufactured by fused deposition modeling (FDM) 3D printing, while they may have defects in some areas such as edges. A post-processing is introduced here for 3D-printed samples by low power CO₂ laser. The thickness of the FDM samples are 3.2 mm and printed by optimum conditions. Effects of process parameters such as focal plane position (-3.2-3.2 mm), laser power (20-40 W), and laser cutting speed (1-13 mm/s) are examined based on the design of experiments (DOE). Geometrical features of the kerf; top and bottom kerf; taper; ratio of top to the bottom kerf are considered as output responses. An analysis of the experimental results by statistical software is conducted to survey the effects of process parameters and to obtain regression equations. By optimizing of the laser cutting process; an appropriate kerf quality is obtained and also optimum input parameters are suggested. Experimental verification tests show a good agreement between empirical results and statistical predictions. The best optimum sample with 1.19 mm/s cutting speed, 36.49 W power and 0.53 mm focal plane position shows excellent physical features after the laser cutting process when 276.9 μm top and 261.5 μm bottom kerf width is cut by laser.

Collagen immobilization on ultra-thin nanofiber membrane to promote in vitro endothelial monolayer formation

The endothelialization on the poly (ε-caprolactone) nanofiber has been limited due to its low hydrophilicity. The aim of this study was to immobilize collagen on an ultra-thin poly (ε-caprolactone) nanofiber membrane without altering the nanofiber structure and maintaining the endothelial cell homeostasis on it. We immobilized collagen on the poly (ε-caprolactone) nanofiber using hydrolysis by NaOH treatment and 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide/sulfo-N-hydroxysulfosuccinimide reaction as a cost-effective and stable approach. NaOH was first applied to render the poly (ε-caprolactone) nanofiber hydrophilic. Subsequently, collagen was immobilized on the surface of the poly (ε-caprolactone) nanofibers using 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide/sulfo-N-hydroxysulfosuccinimide. Scanning electron microscopy, Fourier transform infrared spectroscopy, transmission electron microscopy, and fluorescence microscopy were used to verify stable collagen immobilization on the surface of the poly (ε-caprolactone) nanofibers and the maintenance of the original structure of poly (ε-caprolactone) nanofibers. Furthermore, human endothelial cells were cultured on the collagen-immobilized poly (ε-caprolactone) nanofiber membrane and expressed tight junction proteins with the increase in transendothelial electrical resistance, which demonstrated the maintenance of the endothelial cell homeostasis on the collagen-immobilized-poly (ε-caprolactone) nanofiber membrane. Thus, we expected that this process would be promising for maintaining cell homeostasis on the ultra-thin poly (ε-caprolactone) nanofiber scaffolds.

Improvement of the Non-Destructive Testing of Heritage Mural Paintings Using Stimulated Infrared Thermography and Frequency Image Processing

Within the framework of conservation and assistance for the restoration of cultural property, a method of analysis assistance has been developed to help in the restoration of cultural heritage. Several collaborations have already demonstrated the possibility of defects detection (delamination, salts) in murals paintings using stimulated infrared thermography. One of the difficulties encountered with infrared thermography applied to the analysis of works of art is the remanence of the pictorial layer. This difficulty can sometimes induce detection artifacts and false positives. A method of thermograms post-processing called PPT (pulse phase thermography) is described. The possibilities offered by the PPT in terms of reducing the optical effects associated with the pictorial layer are highlighted first with a simulation, and then through experiments. This approach can significantly improve the study of painted works of art such as wall paintings.

Beltrami-net: domain-independent deep D-bar learning for absolute imaging with electrical impedance tomography (a-EIT)

OBJECTIVE

To develop, and demonstrate the feasibility of, a novel image reconstruction method for absolute electrical impedance tomography (a-EIT) that pairs deep learning techniques with real-time robust D-bar methods and examine the influence of prior information on the reconstruction.

APPROACH

A D-bar method is paired with a trained convolutional neural network (CNN) as a post-processing step. Training data is simulated for the network using no knowledge of the boundary shape by using an associated nonphysical Beltrami equation rather than simulating the traditional current and voltage data specific to a given domain. This allows the training data to be boundary shape independent. The method is tested on experimental data from two EIT systems (ACT4 and KIT4) with separate training sets of varying prior information.

MAIN RESULTS

Post-processing the D-bar images with a CNN produces significant improvements in image quality measured by structural SIMilarity indices (SSIMs) as well as relative [Formula: see text] and [Formula: see text] image errors.

SIGNIFICANCE

This work demonstrates that more general networks can be trained without being specific about boundary shape, a key challenge in EIT image reconstruction. The work is promising for future studies involving databases of anatomical atlases.