In the present work, a comparative evaluation of an MBBR unit performance was carried out for the following cases: when adding 3D-printed biocarriers fabricated with 13X and bentonite, when using K1 commercial biocarriers and when not adding biocarriers at all. For the evaluation of the MBBR efficiency, various physicochemical parameters were measured, while static light scattering and optical microscopy observations were additionally used. Finally, biofilm extracted from the biocarriers was evaluated. The findings suggest that there is an optimal biodegradation of the organic load in all MBBR units. The nitrification and denitrification process were improved at the 3D MBBR as compared to the control MBBR and MBBR K1. The dry mass of the biofilm in the 3D-printed biocarriers was two orders of magnitude larger than the one in the K1 biocarriers. What is more, in the K1 biocarriers the mass of the biofilm varied in relation to time, due to the fact that it could not be kept inside the holes, something that was not observed to happen with the 3D-printed biocarriers. Finally, it was observed, mostly in the 3D MBBR and less in the K1 MBBR, that the growth of nitrifying bacteria and heterotrophs inside the units increased the biomass production in the form of SMP, which in turn favored the adhesion of biomass on the surface of biocarriers.

Recently, 3D printing techniques gained much attention in solid dosage form production. Even though the methods are increasingly studied, there are still many challenges in establishing an accurate content of active ingredients in the final products. In the present study, new experimental design techniques and statistical software were developed to identify and optimize a formula to predict the mass of the tablet to be 3D printed before it actually is. The first step was to develop a virtual 3D object in the FreeCad Software, then, using a CURA slicer software, the G-code Format was obtained. The tablets were printed using a Cartesian 3D printer based on the generated data. Finally, adapting the object sequencing mode, a predicted drug mass value was obtained. As expected, the oblong tablet's scaling directly influences its mass. The software generates a correlation coefficient (r) of 0.84, confirming the directly proportional relationship between scaling and tablet weight. However, the r values progressively decreased, indicating a poor correlation between tablet weight and other factors: infill density percent (r = 0.403) and wall thickness (r = 0.185). After repeating the 3D printing with the values ​​suggested by the software, tablets with a practical value of 1066 mg were obtained. Considering that the confidence interval calculated is [834.95—1165.05] and the experimental value is 1066 mg, it can be certified that the proposed model is valid.

This paper proposes an algorithm for transmitting and reconstructing the estimated point cloud using temporally estimating a dynamic point cloud sequence. When a non-rigid 3D point cloud sequence (PCS) is input, the sequence is divided into groups of point cloud frames (PCF), and a key PCF is selected. After the 3D skeleton is predicted through 3D pose estimation, the motion of the skeleton is estimated by analyzing the joints and bones of the 3D skeleton. For the deformation of the non-rigid human PC, the 3D PC model is transformed into a mesh model, and the key PCF is rigged using the 3D skeleton. After deforming the key PCF into the target PCF utilizing the motion vector of the estimated skeleton, the residual PC between the motion compensation PCF and the target PCF is generated. If there is a key PCF, the motion vector of the target PCF, and a residual PC, the target PCF can be reconstructed. Just as compression is performed using pixel correlation between frames in a 2D video, this paper compresses 3D PCF by estimating the non-rigid 3D motion of a 3D object in a 3D PC. The proposed algorithm can be regarded as an extension of the 2D motion estimation of a rigid local region in a 2D plane to the 3D motion estimation of a non-rigid object (human) in 3D space. Experimental results show that the proposed method can successfully compress 3D PC sequences. If it is used together with a PC compression technique such as MPEG PCC (point cloud compression) in the future, a system with high compression efficiency may be configured.

Existing methods for 3D human pose estimation mainly divide the task into two stages. The first stage identifies the 2D coordinates of the human joints in the input image, namely the 2D human joint coordinates. The second stage uses the results from the first stage as input to recover the depth information of human joints from the 2D human joint coordinates to achieve 3D human pose estimation. However, the recognition accuracy of the two-stage method relies heavily on the results of the first stage and includes too many redundant processing steps, which reduces the inference efficiency of the network. To address these issues, we propose the EDD, a fully End-to-end 3D human pose estimation method based on transformer architecture with Dual Decoders. By learning multiple human poses, the model can directly infer all 3D human poses in the image using a pose decoder, and then further optimize the recognition result using a joint decoder based on the kinematic relations between joints. With the attention mechanism, this method can adaptively focus on the most relevant features to the target joint, effectively overcoming the feature misalignment problem in the human pose estimation task and greatly improving the model performance. Any complex post-processing step, such as non-maximum suppression, is eliminated, further improving the efficiency of the model. The results show that the method achieves an accuracy of 87.4% on the MuPoTS-3D dataset, significantly improving the accuracy of end-to-end 3D human pose estimation methods.

This study demonstrates the successful synthesis of Ni/Y2O3 nanocomposite particles through the application of ultrasound-assisted precipitation using the Ultrasonic Spray Pyrolysis technique. The particle size was predicted accurately using a modified equation, and they were collected in a water suspension with Polyvinylpyrrolidone (PVP) as the stabiliser. The presence of the Y2O3 core and Ni shell was confirmed with Transmission Electron Microscopy (TEM) and with electron diffraction. The TEM observations revealed the formation of round particles with an average diameter of 466 nm, while the lattice parameter on the Ni particle’s surface was measured to be 0.343 nm. The Ni/Y2O3 nanocomposite particle suspensions were lyophilized, to obtain a dried material that was suitable for embedding into a Polylactic acid (PLA) matrix. The resulting PLA/Ni/Y2O3 composite material was successfully extruded successfully, so that a 3D printed technology Fused Filament Fabrication could be used further for the production of tensile test tubes. The tensile tests showed that the addition of lyophilised Ni/Y2O3 into the PLA matrix decreased the tensile strength by 21.8 %, while the tensile modulus was not influenced. Dynamic Mechanical Analysis (DMA) showed that the addition of the Ni/Y2O3 particles increased the glass transition temperature by 5 °C, and increased the storage modulus in the glass transition range significantly. These findings demonstrate the potential for utilising Ni/Y2O3 nanocomposite particles in 3D printing applications, and warrant further exploration of their mechanical properties and potential applications in various fields.

Small molecules that can modulate or stabilize cell-cell interactions are valuable tools for investigating the impact of collective cell behavior on various biological processes such as development/morphogenesis, tissue regeneration and cancer progression. Recently, we showed that budesonide, a glucocorticoid widely used as anti-asthmatic drug, is a potent regulator of stem cell pluripotency. Here we tested the effect of different budesonide derivatives and identified CHD-030498 as a more effective analogue of budesonide. CHD-030498 was able to prevent stem cell pluripotency exit in different cell-based models, including embryonic stem-to-mesenchymal transition, spontaneous differentiation and 3D gastruloid development, and at lower doses compared to budesonide.

Two antimicrobial agents such as silver nanoparticles (AgNPs) and titanium dioxide (TiO2) have been formulated with natural polysaccharides (chitosan or alginate) to develop innovative inks for the rapid, customizable, and extremely accurate manufacturing of 3D printed scaffolds useful as dressings in the treatment of infected skin wounds. Suitable chemical-physical properties for the applicability of these innovative devices were demonstrated through the evaluation of water content (88-93%), mechanical strength (Young’s modulus 0.23-0.6 MPa), elasticity, and morphology. The antimicrobial tests performed against Staphylococcus Aureus and Pseudomonas Aeruginosa demonstrated the antimicrobial activities against Gram+ and Gram– bacteria of AgNPs and TiO2 agents embedded in the CH or ALG macroporous 3D hydrogels (AgNPs MIC starting from 5 µg/ml). The biocompatibility of chitosan was widely demonstrated by cell viability tests and was higher than that observed for alginate. Constructs containing AgNPs at 10 µg/ml concentration level did not significantly alter cell viability as well as the presence of titanium dioxide; cytotoxicity towards human fibroblasts was observed starting with AgNPs concentration of 100 µg/ml. In conclusions, the 3D printed dressings here developed own the features to be cheap, highly defined, easy to be manufactured and further applied in personalized antimicrobial medicine applications.

Magnesium ions play an important immune-regulatory role during bone repair. For this study, we prepared micro-nano bioactive glass containing magnesium, which can release magnesium, silicon, and calcium ions and has a positive impact on osteogenic differentiation and vascular regeneration. In this study, MgMNBG was compounded and combined with PLGA and PCL for 3D printing. Afterwards, the physicochemical properties and bone repair performance of the scaffolds were evaluated through in vitro and in vivo experiments. We also investigated the effects of MgMNBG on osteogenic differentiation, immune regulation, and vascular regeneration. The results showed that MgMNBG can inhibit inflammation and promote osteogenesis and angiogenesis by regulating macrophages. PLGA/PCL/MgMNBG scaffolds have good osteogenic and angiogenic effects, and the composite scaffolds have excellent bone repair performance and potential application value.

The addition of biocarriers can improve the biological processes appearing in a bioreactor since their surface allows the immobilization, attachment, protection, and growth of microorganisms. In addition, the development of a biofilm layer allows the colonization of microorganisms in the biocarriers. The structure, composition, and roughness of the biocarriers' surface are crucial factors that affect the development of the biofilm. In the current work, the aluminosilicate zeolites 13X and ZSM-5 were examined as the main building components of the biocarrier scaffolds, using bentonite, montmorillonite, and halloysite nanotubes as inorganic binders in various combinations. 3D printing was utilized to form pastes into monoliths that underwent heat treatment. The 3d-printed biocarriers were subjected to a mechanical analysis, including density, compression, and nanoindentation tests. Furthermore, the 3d-printed biocarriers were morphologically and structurally characterized using nitrogen adsorption at 77 K (LN2), scanning electron microscopy (SEM), and X-ray diffraction (XRD). The stress-strain response of the materials being studied was obtained through nanoindentation tests combined with finite element analysis (FEA). These tests were also utilized to simulate the lattice geometries under compression loading conditions to investigate their deformation and stress distribution in relation to experimental compression testing. The results indicated that the 3d-printed biocarrier 13X/halloysite nanotubes was endowed with high specific surface area and extended mesoporous structure. Due to these assets, its bulk density was one of the lowest observed amongst the biocarriers derived from the various combinations of materials. The biocarriers based on the 13X zeolite exhibited the highest mechanical stability and appropriate morphological features. The 13X/halloysite nanotubes scaffold exhibits a moderate hardness value compared to the rest, while it presents the highest value of modulus of elasticity. In conclusion, Aluminosilicate zeolites and their combination with clays and inorganic nanotubes afford 3d-printed biocarriers of various textural and structural properties, which can be utilized to improve biological processes.

In order to study the effect of TiB2 particles on the mechanical properties of TiB2/6061Al composites, a series of TiB2/6061Al 3D representative volume element (RVE) were established based on SEM photos. This model took into account the ductile damage of the matrix and the traction separation behavior of the interface, and the linear damage evolution law was introduced to characterize the stiffness degradation behavior of the matrix elements. The mixed boundary conditions were used for RVE tensile experiments, and the accuracy of the predicted result was verified by the agreement of the experimental stress-strain curve. Results show that the addition of TiB2 particles can effectively promote the load-bearing capacity of the composite, but elongation is reduced. With the weight fraction of TiB2 increasing from 2.5% to 12.5%, the elastic modulus, yield strength, and tensile strength are increased by 8%, 10.37%, and 11.55% respectively, while the elongation decreased by 10%. The clustering rate of the TiB2 particles is also an important factor affecting the toughness of the composites. With the increase in the clustering rate of TiB2 particles from 20% to 80%, the load-bearing capacity of the composites is not improved, and the elongation of the composites is reduced by 8%. Moreover, the high strain region provides a fast expansion path for crack propagation and the particle spacing is a crucial factor that affects the stress field.

The unsolved problem in three-dimensional surgical planning for patients with facial deformity, dysgnathia, or asymmetry is the lack of a normative database of “norm skulls” that can be used as treatment objectives. A study was conducted on 90 Eurasian persons (46 male and 44 female adults) with normal and balanced facial appearance, skeletal Class I pattern, and proper interincisal relationship with normal occlusion. Cone-beam computed tomography was performed. 18 landmarks were digitized and 3D cephalometric measurements of overall facial features, skull, midface and mandible were performed and analyzed by means of proportions calculated from the landmarks. Male and female skulls were analyzed as well as subdivisions revealed by cluster analysis. The data showed that four subtypes of skulls were distinguishable with statistical significance (p< 0,05). A male and a female type subdivided in a brachiocephalic and dolichocephalic phenotype could be identified. For each type then a mean shape was calculated by a Procrustes transformation, which in turn was used to create four template skulls from a male and a female skull by means of a thin plate spline transformation. The normative data of the subtypes can individually serve as a guide for orthodontic surgery, especially helpful in 3D plan-ning and execution of craniofacial operations.

UAV has become powerful devices for both practitioners and researchers. In recent years, there has been a substantial growth in the usage of UAV for a wide range of applications in research and engineering. UAV are mostly utilized for image capturing techniques due to their time savings, low cost, minimum field work, and high precision. The purpose of this study is to generate an accurate and reliable 3D modelling process using UAVs photogrammetric technology; hence this study allows the techniques to evaluate the practicability of modelling and mapping inaccessible tunnels using images recorded by UAVs and photogrammetry. As a result, the approach was always employed to depict the true state of the place. This research incorporates three experiments. The first experiment is to build a 3D model using only one-directional light source and evaluate the accuracy of 3D photogrammetric model and conducted at the concrete tunnel. The second one is to build a 3D model of underground sewer tunnel using different light sources one-directional and omni-directional. The last experiment was to build 3D model using an UAV system which is developed based on first and second experiment’s result, evaluate an accuracy of 3D photogrammetric model and conducted at the tunnel named in the research as a “pedestrian tunnel. There is certain limitation in this study such as Adding a payload to a drone changed its weight distribution, which affected its stability. If the payload was not properly balanced, it caused the drone to fly unevenly, making it more difficult to control.

3D bioprinting is the process of manipulating cell-laden bioinks to fabricate living structures. 3D bioprinting techniques have brought considerable innovation in biomedicine, especially in the field of tissue engineering, allowing the production of 3D organ and tissue models for in vivo transplantation purposes or for in-depth and precise in vitro analyses. Natural-derived hydrogels, especially those obtained from the decellularization of biological tissues, are promising bioinks for 3D printing purposes, as they present the best biocompatibility characteristics. Despite this, many natural hydrogels do not possess the necessary mechanical properties to allow a simple and immediate application in the 3D printing process. In this review, we focus on the bioactive and mechanical characteristics that natural hydrogels may possess to allow efficient production of organs and tissues for biomedical applications, emphasizing the reinforcement techniques to improve their biomechanical properties.

The rapid development of electrochemical CO2 reduction offers a promising route to convert in-termittent renewable energy into products of high value-added fuels or chemical feedstocks. However, low faradaic efficiency, low current density, and a narrow potential range still limited the large-scale application of CO2RR electrocatalyst. Herein, monolith 3D bi-continuous nano-porous Bismuth (np-Bi) electrodes are fabricated via a simple one-step electrochemical dealloying strategy from Pb-Bi binary alloy. The unique bi-continuous porous structure ensures highly effective charge transfer, meanwhile the controllable millimeter-size geometric porous structure enables easy catalyst adjustment to expose highly suitable surface curvatures with abundant reactive sites. This results in a high selectivity of 92.6% and superior potential window (400 mV, selectivity >88%) for electrochemical reduction of carbon dioxide to formate. Our scalable strategy provides a feasible pathway for mass-producing high-performance and versatile CO2 electrocatalysts.

Plant breeding aims to develop elite crop varieties appropriate for various environments with higher quality and quantity of production. Researchers use quantitative trait loci (QTL) mapping and association studies to identify regions in the genome responsible for the variation of the quantitative traits of interest. However, mapped regions do not always translate to functional proteins, which makes it challenging to identify genes associated with traits of interest. The biological functions of proteins are strongly dependent on their 3D structure. Alternatively, if proteins can be directly linked with the phenotypes, the effect of mutations on phenotypic changes can be assessed. Innovation of deep learning models in biology opens new avenues of exploration. AlphaFold is an AI system that predicts the 3D structure of a protein from its amino acid sequence with near experimental accuracy and was used in this study. Point mutations with a significant influence on the 3D structure of a protein can capture the effect on phenotypes through association study, and this provides insights into the regions that are of functional importance. In the current study, 534 plants were selected based on plant vigor, and 154 missense variants that change amino acid sequences, including 5 significant hits from previous study, were included. The changes in protein 3D structure were assessed by association with the phenotype. The analysis identified five significant associations, four of which were also identified in previous study of SNPs GWAS, however, a new fifth association was also identified which was annotated as disease resistance gene in Medicago truncatula. This study helps to associate SNPs that could be missed by GWAS due to stringent Bonferroni corrected p-values by providing a more robust filter for SNPs using features from predicted protein 3D structures.

Recently, new semantic segmentation and object detection methods have been proposed for direct processing of three-dimensional (3D) LiDAR sensor point clouds. LiDAR can produce highly accurate and detailed 3D maps of natural and man-made environments and is used for sensing in many contexts due to its ability to capture more information and its robustness to dynamic changes in the environment. In addition, the cost of LiDAR sensors has decreased in recent years, which is an important factor for many application scenarios. The challenge with 3D LiDAR sensors like the Velodyne HDL-64E S2 is that they can output large 3D data at up to 1,300,000 points per second, which is difficult to process in real time when applying complex algorithms and models for efficient semantic segmentation. Most existing approaches are either only suitable for relatively small point clouds or rely on computationally intensive sampling techniques to reduce their size. As a result, most of these methods do not work in real-time in realistic field robotics application scenarios, making them unsuitable for practical applications. Systematic point selection is a possible solution to reduce the amount of data to be processed, but although it is memory and computationally efficient, it selects only a small subset of points, which may result in important features being missed. To address this problem, we propose a new approach to semantic segmentation in forestry that uses a systematic sampling method in which the local neighbors of each point are retained to preserve geometric details. Our approach has been shown to process up to 1 million points in a single pass. It outperforms the state of the art in efficient semantic segmentation in large datasets such as Semantic3D. We also present a preliminary study on the performance of LiDAR-only data, i.e., intensity values from LiDAR sensors without RGB values for semi-autonomous robot perception.

The purpose of this in vitro study is to evaluate the effectiveness of incorporating a new irrigation system into a surgical guide and monitor its effect on heat generation during implant bed preparation. A total of 48 surgically guided osteotomies were performed on 12 bovine ribs divided into 4 groups, using different irrigation techniques: Group A (test) had entry and exit channels incorporated into the guide; Group B had a similar design with an entry channel only; Group C had conventional external irrigation; Group D (control) had no irrigation. Heat generation during the osteotomies was measured using thermocouples placed at a depth of 2 mm and 6 mm. The lowest mean temperature was observed in Group A (22.1°C at 2mm and 21.4°C at 6mm), this was statistically significant when compared with Groups C and D (p&lt;0.001). Group A showed a lower mean temperature compared with Group B as well, however statistically significant only at 6mm depth (p&lt;0.05). In conclusion, the proposed guide has significantly reduced heat generation during implant osteotomy. The integration of an exit cooling channel can resolve limitations found in previously designed surgical guides and can be easily incorporated into computer designing and 3D printing software.

The rapid development of Deep Learning brought novel methodologies for 3D Object Detection using LiDAR sensing technology. These improvements in precision and inference speed performances lead to notable high performance and real-time inference, which is especially important for self-driving purposes. However, the developments carried by these approaches overwhelm the research process in this area since new methods, new technologies, and software versions lead to different project necessities, specifications and requirements. Moreover, the improvements brought by the new methods may be due to improvements in newer versions of deep learning frameworks and not just the novelty and innovation of the model architecture. Thus, it became crucial to create a framework with the same software versions, specifications and requirements that accommodate all these methodologies and allow the easy introduction of new methods and models. A framework is proposed that abstracts the implementation, reusing and building of novel methods and models. The main idea is to facilitate the representation of state-of-the-art (SoA) approaches and simultaneously encourage the implementation of new approaches by reusing, improving and innovating modules in the proposed framework, which has the same software specifications to allow a fair comparison. This makes it possible to determine if the key innovation approach outperforms the current SoA by comparing models in a framework with the same software specifications and requirements.

Acute and chronic bone infections, especially those caused by methicillin-resistant Staphylococcus aureus (MRSA), remains a major complication and therapeutic challenge. It is documented that local administration of vancomycin offers better results than the usual routes of administration (e.g. intravenous) when ischemic areas are present. In this work, we evaluate the antimicrobial efficacy against S. aureus and S. epidermidis and analyzed the potential cytotoxic effect of a novel hybrid 3D-printed scaffold based on poly(caprolactone) and chitosan loaded with different vancomycin concentrations (1, 5, 10 and 20%). For this purpose, vancomycin release was measured by means of HPLC, and the biological response of ah-BM-MSCs in the presence of the scaffolds was evaluated in terms of cytotoxicity (LDH activity), proliferation (AlamarBlueⓇ) and osteogenic differentiation (ALP activity, Alizarin Red staining). In addition, two cold plasma treatments were evaluated to improve the adhesion of hydrophobic polymers to hydrogels. The hybrid PCL/CS/Van scaffolds tested were found to be biocompatible, bioactive, and bactericide, as demonstrated by no cytotoxicity or functional alteration and by bacterial inhibition. Our results suggest that the scaffolds developed would be excellent candidates to be used in a wide range of biomedical fields such as drug delivery systems or tissue engineering applications.

Background: For the treatment of bone defects, biodegradable compressive biomaterials are needed as a substitute, which degrade at the same rate as the bone regenerates. In this study, the compressive strength of CPC ceramics (with a layer thickness of more than 12 layers) should be compared with sintered ceramics. Methods: Round scaffolds with 20, 25, 30 and 45 layers were 3D printed the 3D Bioplotter, solidified in a water-saturated atmosphere for 3 days and then tested for compressive strength together with a sintered ceramic using a Zwick universal testing machine. Results: The 3D printed scaffolds are more compressive at 41.56 ± 7.12 MPa than the sintered ceramic at 24.16 ± 4.44. Conclusions: The round geometry sintered ceramics approach or exceed the upper limit of the compressive strength of cancellous bone in the direction of compacta (depending on the author).

There is a fast-growing interest in the use of selective laser melting (SLM) for metal/alloy additive manufacturing. Our current knowledge of SLM printed 316 stainless steel (SS316) is limited and sometimes appears sporadic, presumably due to the complex interdependent effects of a large number of process variables of the SLM processing. This is reflected from the discrepant findings in the crystallographic textures and microstructures in this investigation with those reported in the literatures, which also vary itself. The as-printed material is macroscopically asymmetric in both the structures and crystallographic textures. The <101> and <111> crystallographic directions align parallel with the SLM scanning direction (SD) and build direction (BD), respectively. Like-wise, some characteristic low angle boundary features are reported crystallographic, while this investigation unequivocally proves them non-crystallographic since they always maintain an identical alignment with the SLM laser scanning direction irrespective of the matrix material’s crystal orientation. There is also 500±200 nm columnar or cellular features, depending on the cross-section, generally found all over the sample. These columnar or cellular features are formed with walls made of dense packing of dislocations entangled with Mn, Si and O enriched amorphous inclusions. They remain stable after the ASM solution treatments at 1050 °C temperatures, and therefore, are capable of hindering boundary migration events of recrystallization and grain growth. Thus, the nanoscale structures can be retained at high temperatures. Large 2-4 µm inclusions form during the solution treatment, within which the chemical and phase distribution are heterogeneous.

Free-edge effect is one of the factors affecting the mechanical properties of three-dimensional woven composites under tensile load. However, current research is relatively poorly understood regarding the effect of free-edge on the stiffness and strength of the material. This paper aims at examining the influence of free-edge effect on the mechanical properties of 3D woven composites under tension through experimental and simulation mathods. The three-dimensional DIC technique is used to collect the full-field strains on the specimen surface during the test, and the stress-strain differences in different regions in the width direction are analyzed, and the overlap of the curves in each region is found to be high. Experimental studies are conducted on specimens of different widths (within the range of 15-20 mm), and the results indicate that the differences in mechanical properties of 3D woven composites under tension loading in this width range are not significant. A progressive damage finite element model is developed for calculation and compared with experimental results.

3D printing with cement-based materials is a promising manufacturing technique for civil engineering applications that already allows for the design and the construction of complex and highly customized structures using a layer-by-layer deposition approach. Usually, in this type of additive manufacturing, a mixture of cement, water, aggregate and additives is extruded through a specific print head and deposited in successive layers to form the desired shape. The extrusion mechanism is one of the most expensive parts of the 3D printer. Also, for low scale 3D printers, based on the shape of the extruder and the geometry limitation of the mixing blade, the 3D mixture is often limited to a narrow range of materials due to the risk of layer splitting or blockage. Therefore, there is a need to develop affordable and feasible alternatives to the current design-fabrication-application approach of 3D printers. In this paper, various new designed mixtures of fiber reinforced mortars that can be 3D printed using only a commercially available screw pump are analyzed based on their fresh properties and mechanical characteristics. The reduced facility requirements in this approach allow 3D-printing to be more available for civil engineering applications. With further innovation in the future, this method and mixtures can be extended for sustainable and economically feasible printing of single-family housing units.

The safe and reliable operation of autonomous vehicles in complex and dynamic environments is heavily dependent upon exteroceptive and proprioceptive sensors. A LiDAR system generates accurate 3D point clouds, which are crucial for the detection, classification, and tracking of multiple targets. LiDAR data, however, presents significant challenges due to its density, noise, and varying sampling rates. In this study, various clustering and MTT techniques for LiDAR point clouds will be identified and classified within the context of autonomous driving to assess the state-of-the-art methods’ key challenges and their performances. We have categorized clustering and MTT methods used in AV applications, identified research gaps and challenges and analyzed existing algorithms and their challenges in detail. Researchers and practitioners in the field of autonomous driving will find this review to be a valuable resource.

Laser Direct Writing (LDW), also known as 3D multi-photon laser lithography of resins, is a promising technique for fabricating complex free-form elements, including micro-optical functional components. Regular organic or hybrid (organic-inorganic) resins are often used, with latter exhibiting better optical characteristics, as well as having the option to be heat-treated into inorganic glass-like structures, particularly useful for resilient micro-optics. While this work is a continuation of SZ2080™ calcination development , the Laser-Induced Damage Threshold (LIDT) of such sol-gel-derived glass micro-structures, particularly those that undergo heat treatment, has not been well-characterized. In this pilot study, we investigated the LIDT using the Series-on-One (S-on-1) protocol of functional micro-lenses produced via LDW and subsequently calcinated. Our results demonstrate that the LIDT can be significantly increased, even multiple times, by this approach, thus enhancing the resilience and usefulness of these free-form micro-optics. This work represents the first investigation in terms of LIDT into the impact of calcination on LDW produced sol-gel-derived glass micro-structures, and provides important insights for the development of robust micro-optical devices.

The surface defects of shield subway tunnel can significantly affect the serviceability of the tunnel structure and may compromise the operation safety. To effectively detect the multiple surface defects, this research employs a tunnel inspection trolley (TIT) based on the mobile laser scanning technique. By conducting the inspection of the shield tunnel on a metro line section, various surface defects are identified by the TIT, including water leakage defect, dislocation, spalling, cross-section deformation, etc. To explore the root causes of the surface defects, the association rules between different defects are calculated via an improved Apriori algorithm. Results show that: i) there are significant differences in different association rules of various surface defects of the shield tunnel; ii) the average confidence of the association rule “dislocation &amp; spalling → water leakage” is as high as 57.78%, indicating that most of the water leakage defects are caused by dislocation and spalling of the shield tunnel in the sections being inspected; iii) the weakest rule appears at “water leakage → spalling”, with the average confidence of 13%. The association analysis can be used in predicting the critical defects influencing the structural reliability and operation safety, such as water leakage, and optimizing the construction and maintenance work for the shield subway tunnel.

Regeneration of biological tissues in medicine is challenging, and 3D bioprinting offers an innovative way to create functional multicellular tissues. One common way in bioprinting is bioink which is one type of the cell-loaded hydrogel. For clinical application, however, the bioprinting still suffers from satisfactory performance, e.g. in vascularization, effective antibacterial, immunomodulation and regulation of collagen deposition. Many studies have incorporated different bioactive materials into the 3D printed scaffolds to optimize the bioprinting. Here, we review a variety of additives added to the 3D bioprinting hydrogel. The underlying mechanisms and methodology for biological regeneration are important and will provide useful basis for future research.

A 3D graphene foam made of interconnected multilayer graphene flakes was produced on optical fibres (OF) by laser-induced transformation of a polyimide (PI) film coated on the OF cladding. This material, known as la-ser-induced graphene (LIG), was explored in the electrochemical detection and quantification of dopamine (DA) at physiologically relevant concentrations in the presence of the most relevant interfering molecules in biological fluids, ascorbic acid (AA) and uric acid (UA). The measured limit of detection is 100 nM, the linear range is 0.1 to 5 μM and a maximum sensitivity of 5.0 µA µM−1 cm−2 was obtained for LIG decorated with Pt nanoparticles (NPs). Moreover, immunity to AA and UA interference and to fouling was attained by decorating the LIG elec-trode with Pt NPs and coating with Nafion. These figures of merit underlines the potential of these sensors for the quantification of physiologically relevant concentrations of DA in biological fluids, paving the way for the development of hybrid electrochemical/optical sensing actuating platforms in a lab-on-fibre configuration, with relevant applications in biomedical engineering. The advantages of this hybrid arrangement include the possi-bility of in-situ counterproofing, extended measuring ranges, photoelectrochemical detection and the probing of inaccessible places. This elegant approach can also provide a simple and cost-effective way to fabricate biomed-ical devices with extended functionality, such as medical optical probes with added electrochemical capabilities, optogenetics combined with local electrochemical detection, among others.

A novel approach for the long-term medical treatment of the inner ear is the diffusion of drugs through the round window membrane from a patient-individualized, drug-eluting implant, which is inserted in the middle ear. In this study, drug-loaded (10 wt% Dexamethasone) guinea pig round window niche implants (GP-RNIs, ~1.30 mm x 0.95 mm x 0.60 mm) were manufactured with high precision via micro injection molding (µIM, Tmold = 160 °C, crosslinking time of 120 s). The medical grade silicone elastomer MED-4244 (NuSil Technology LLC, Radnor, PA, USA) was used. Molds for µIM were 3D printed from a commercially available resin PlasGRAY V2 (Asiga, Alexandria, Australia, TG = 84 °C) via a high-resolution DLP process (xy-resolution of 32 µm, z-resolution of 10 µm, 3D printing time of about 6 h). Drug release, biocompatibility, and bio-efficacy of the GP-RNIs were investigated in vitro. GP-RNIs could be successfully produced. Wear of the molds due to thermal stress was observed. However, the molds are suitable for single use in the µIM process. About 10% of the drug load (8.2 ± 0.6 µg) was released after 6 weeks (medium: isotonic saline). The implants showed high biocompatibility over a time of 28 days (lowest cell viability ~80%). Moreover, we found anti-inflammatory effects over a time of 28 days in a TNF-α-reduction test. These results are promising for the development of long-term drug-releasing implants for human inner ear therapy.

ORF7b-2 is an accessory protein of the SARS-CoV-2 virus of only 43 amino acids. It has been implicated in various functional hypotheses, some of which predict its involvement as a trans-membrane protein. In this study, ORF7b-2 has often been compared to ORF7b-1 of the SARS virus to highlight differences and similarities with a protein that should have a similar biological role. Structural analysis of ORF7b-2 and its electrostatic characteristics show a polypeptide with both ends negatively charged and a diffuse negative charge over the entire structure. Therefore, its behavior in solution is like that of a weak negative polyelectrolyte, more precisely a polyanion with a net charge of – 4 at neutral pH. Its structure was modeled with two different modeling systems, one of which was ab initio. The two best models are similar, as confirmed by the Ramachandran plot, and show a central alpha-helical structure with two disordered and mobile ends. A normal mode analysis characterized the low-frequency dynamic aspects of the protein. The analysis of the structural shows a rigid central segment with mobile and fluctuating extremities, involved in a conformational equilibrium of the helix ↔ coil type. The calculation of the dipole moment shows its vector is not aligned with the main axis of the structure with an outward tilt of 24°. Molecular dynamics simulations were also conducted and the one in water is in good agreement with the previous results. While, the simulation performed by inserting a pre-oriented dimer (OMP) into a solvated lipid showed the low tendency of the protein to solvate in the apolar environment of the membrane. ORF7b-2 also shows a widespread distribution of negative surfaces that dynamically adjust to changes in structural organization. The BioGrid platform's [Biological General Repository for Interaction Datasets] through the BioGrid COVID-19 Coronavirus Curation Project shows a very large number of experimentally proven physical interactions unique to ORF7b-2, some of them with cytoplasmic proteins. These features of ORF7b-2, evaluated together, suggest a remarkable propensity of ORF7b-2 to interact with multiple molecular partners on both an electrostatic and hydrophobic basis. All this makes it unreasonable that the only biological function of this protein should be that exerted as an intramembrane protein.

This study aimed to develop chitosan-based apigenin spray dried solid dispersion using 1:1,1:1.5,1:2 w/w ratios. The results of process yield and drug assay were found to be (87.5%, 94.2%, and 95.86%), (95.2 ±1.34%), (99.5 ±0.85%), and (97.6 ±2.42%), respectively, for AC1, AC2, and AC3. Flow properties indicate the free flow of powders. FTIR revealed compatibility among chitosan and apigenin, and DSC and XRD showed prepared solid dispersion was on a molecular level and available in amorphous. In contrast, SEM images reflect irregular block and near-spherical shape elongated particles in the selected AC2. The antimicrobial examination reflects that AC2 was more effective against Gram-positive, negative, and fungal strains. AC2 SDSDs has more anti-oxidant property compared to pure flavonoid (AGN). Anti-proliferative activity against A549 lung cancer cell lines showed better anti-cancer activity by AC2 SDSDs. The selected AC2 SDSD filled in a 3D shell pill and further characterized for 3D shell pill for dissolution profiles and stability studies. The product has sustained release and similar release profiles after three months of storage. The findings suggest that the AC2 SDSDs may be a promising candidate for further development as a 3D printed drug delivery system for treating multiple disease conditions using model flavonoid- apigenin.

One in 12 babies is born with a rare genetic disease. Sadly, most cases are undetected until later age, missing time for early treatment and opportunity to prevent complications. Humanity has entered a new era where Big Data collected by governments, including 2D and 3D facial scans, are available. Many rare genetic diseases can be identified by artificial intelligence (AI) analysis of the facial photo. Phenotyping AI utilizations facilitate comprehensive and accurate genetic evaluations. AI processing of this Big Data to identify rare genetic diseases could bring unimaginable benefits to healthcare, although this would be a questionable step in terms of citizen privacy and could lead to future "Orwellian" ramifications with government abuse. Going forward, a balance must be found between protecting the privacy of citizens and the enticing use of AI for their health risks and cost savings through prevention. The unimaginable potential of AI early diagnostics from facial photos also raises various ethical and legal concerns. This paper presents concept, protentional methods and legal and other limitations within EU legal framework in contrast with potential benefits. This paper is focused on AI utilization to early diagnostic of rare genetic diseases. Shift of paradigm in the screening for rare genetic diseases in population with AI face analysis is expected to have a significant impact. The potential of AI algorithms utilizations similar to face2gene app in general population or systematically on Big governmental datasets recording facial traits changes in time can have significant impact on public health but at the same time give raise to profound concern as violation of one’s privacy.

Background. To prospectively evaluate the reliability of a portable optical scanner compared to the water displacement technique for volumetric measurements of the foot and ankle, and to compare the acquisition time associated with these two methods. Methods. Foot volume was measured in 29 healthy volunteers (58 feet, 24 female/5 male) by a 3D scanner (UPOD-S 3D Laser Full-Foot Scanner ®) and by water-displacement volumetry. Measurements were performed on both feet, up to a height of 10 cm above the ground. The acquisition time for each method was evaluated. Kolmogorov-Smirnov test, Lin's Concordance Correlation Coefficient, and a Student’s t-test were performed. Results: Mean foot volume was 869.7+/-165.1cm3 (3D scanner) versus 867.9+/-155.4cm3 (water-displacement volumetry) (p <10-5). Concordance of measurements was 0.93, indicative of a high correlation between the two techniques. Volumes were 47.8 cm3 lower when using the 3D scanner versus water volumetry. After statistically correcting this underestimation, the concordance was improved (0.98, residual bias = -0.03 +/- 35.1 cm3). Mean examination time was 4.2 +/-1.7 min (3D optical scanner) versus 11.1 +/-2.9 min (water volumeter) (p<10-4). Conclusion: Ankle/foot volumetric measurements performed using this portable 3D scanner are reliable and fast, and can be used in clinical practice and research.

A key component of efforts to identify the biological and drug-specific aspects that contribute to therapeutic failure or unexpected exposure-associated toxicity is the study of drug-intestinal barrier interactions. While methods supporting such assessments are widely described for human therapeutics, there is relatively little information available for similar evaluation in support of veterinary pharmaceuticals. There is, therefore, a critical need to develop novel approaches for evaluating drug-gut interactions in veterinary medicine. Three-dimensional (3D) organoids can address these difficulties in a reasonably affordable system that circumvents the need for more invasive in vivo assays in live animals. However, a first step in the development of such systems is understanding organoid interactions in a 2D monolayer. Given the importance of orally administered medications for meeting the therapeutic need of companion animals, we demonstrate growth conditions under which canine colonoid-derived intestinal epithelial cells survive, mature, and differentiate into confluent cell systems with high monolayer integrity. We further examine the applicability of this canine colonoid-derived 2D model to assess the permeability of three structurally diverse, passively absorbed β-blockers (e.g., propranolol, metoprolol, and atenolol). Both absorptive and secretive apparent permeability (Papp) of these drugs at two different pH conditions were evaluated in canine colonoid-derived monolayers and were compared with that of Caco-2 cells. This proof-of-concept study provides promising preliminary results with regard to the utility of canine-derived organoid monolayers for species-specific assessments of therapeutic drug passive permeability.

Corneal opacity is a leading cause of vision impairment and suffering worldwide. Transplantation can effectively restore vision and reduce chronic discomfort. However, there is a considerable shortage of viable corneal graft tissues. Tissue engineering may address this issue by advancing xeno- keratoplasty as a viable alternative to conventional keratoplasty. In particular, livestock decellularization strategies offer the potential to generate bioartificial ocular prosthetics in sufficient supply to match existing and projected needs. To this end, we have examined the best practices and characterizations that have supported the current state-of-the-art driving preclinical and clinical applications. Identifying the challenges that delimit activities to supplement the donor corneal pool derived from acellular scaffolds allowed us to hypothesize a model for keratoprosthesis applications derived from livestock combining 3D printing and decellularization.

Less than half of e-waste plastics is sorted worldwide and this rate is likely to decline as major processing countries have banned importation of e-waste plastics. This forces the development of decentralized processing facilities, also known as microfactories. The present work investigates the recyclability of different grades of acrylonitrile-butadiene-styrene (ABS) copolymer, polycarbonate, and polypropylene, which were found to be very abundant in a recycling site in the UK. The determination of the matrix relied on the resin identification code imprinted in the e-waste plastic and subsequent FTIR analysis. The melt-blend extrusion technology enabled the valorization of the wasted thermoplastics as 3D filament without significant degradation of the polymers. The recycled materials maintained the tensile strength around 2.5 MPa in agreement with the specifications offered by virgin polymers. Further characterization was done by means of laser microscope, thermogravimetric analysis, and XRF to determine the commercial viability of the recycled filament. A modified solvent-based method was developed with acetone to remove the brominated flame retardants: 25g/100mL, 30 minutes of contact time, and 4 extraction steps. The FTIR results show that the degradation of the rubbery dispersed phase corresponding to the butadiene can be accumulated in the less soluble fraction of the waste ABS.

Non-pneumatic tires have gained a lot of attention due to their advantages, including not having to worry about getting a flat tire. In this type of tire, metamaterial cells replace the pneumatic part of the tire. In general, metamaterials are formed by stacking cells together. These cells are obtained by various methods including topology optimization. Therefore, in this research, to achieve a metamaterial cell suitable for a non-pneumatic tire with the objective function of increasing compressive strength and bending fatigue life, optimization for three types of geometry including (1) square plane, (2) rectangular plane, and (3) entire circumference of tire and three types of material including polylactic acid (PLA), thermoplastic polyurethane (TPU) and void have been done. Optimization has been implemented by using MATLAB code in 2D mode. The cubic cell is obtained from extruding the optimized response of the square plane. From the optimized response of the rectangular plane, the cylindrical cell and from extruding the optimized response of the entire circumference of tire to the tire cross-section size, the main geometry of the tire has been calculated. Finally, to check the quality of 3D printing in producing cells and how they are connected, the optimal cell fabricated by the fused deposition modeling (FDM) method has been observed using a field-emission scanning electron microscopy (FE-SEM). The results show that in the optimization of the square plane, the sample with the minimum remaining weight constraint equal to 40% and in the optimization of the rectangular plane and the entire circumference of tire, the sample with the minimum remaining weight constraint equal to 60% was selected as the optimal sample. From checking the quality of 3D printing, it has been concluded that PLA and TPU materials are completely connected.

The Selective Paste Intrusion (SPI) method is a layer-by-layer additive manufacturing technique that allows for the production of complex geometries in concrete elements by selectively bonding aggregates with cement paste in a particle bed. To create reinforced concrete, the Wire and Arc Additive Manufacturing (WAAM) process shall be integrated into SPI. This technique allows the production of almost free-formed reinforcement and thus complements the advantage of SPI to produce free-formed structures of almost any geometry. However, integration of WAAM into SPI poses a considerable challenge, as high temperatures are generated during the welding process. These temperatures can negatively affect the rheological properties of the cement paste, in turn the penetration behavior of the paste in the particle bed and, subsequently, the mechanical properties of the hardened concrete. A possible passive cooling strategy is to increase the protruding length of the reinforcement bars out of the particle-bed. This requires that the distance of the print nozzle to the particle bed is as well increased, since it must be possible to move it across the reinforcement. The objective was thus to investigate the effect of that distance on print quality and to quantify a maximum allowable distance for an adequate print quality (for the printer setting used) in terms of shape accuracy and concrete strength. Compressive and flexural strength tests as well as geometrical measurements using a 3D scanning method were performed on specimen, printed with varying print nozzle to particle bed distances. It can be stated that for the used SPI print-heads, nozzle-types and parameter settings, the distance between the nozzle and the particle bed should not exceed 50 mm to ensure sufficient print quality in both shape accuracy and mechanical strength.

Abstract Natural disasters such as earthquakes have affected urban historical centers severely. Considering the limitations of the existing methods in conservation and preservation of these sensitive areas, and recent advances in technological devices and techniques such as GIS and 3D printers, this article aims to propose a new methodology utilizing available knowledge and resources. The authors of the present research propose an innovative, technological, and highly accurate method to assess the seismic vulnerability of historical contextures rectifying the existing obstacles and limitations. Through this methodology, the level of trial and error is substantially reduced and the output is stronger, more optimized and more conservative as compared with commonly used methods. Using high tech principles and theoretical foundations (i.e. sustainability principles) this method achieves updated analyses, practical plans, and economic optimization.

unlike the volume, the expression for the surface area of a regular conoid has not yet been obtained by means of direct integration or a differential geometry procedure. As this non-developable form is relatively used in engineering, the difficulty to determine its surface, represents a serious shortcoming for several problems which arise in radiative transfer, lighting and construction, to cite just a few. In order to solve the problem, I conceived the surface as a set of linearly dwindling ellipses which remain parallel to a circular directrix, a typical problem appears when searching the length of such ellipses. I employed a new procedure which, in principle, consists in dividing the surface into infinitesimal elliptic strips to which we have successively applied Ramanujan’s second approximation for the longitude of the ellipse. In this manner, we can obtain the perimeter of any transversal curve pertaining to the said form as a function of the radius of the directrix and the position of the ellipse’s center on the X-axis. Integrating the so-found perimeters of the differential strips for the whole span of the conoid, an unexpected solution emerges through the newly found number psi (ψ) which seems like a refined approximation to the third decimal of Pi but derived from a definite integral equation. As the strips are in truth slanted in the symmetry axis, their width is not uniform and we need to perform some adjustments in order to complete the problem with sufficient precision, but this is discussed separately in the annexes. Relevant implications for mathematical symmetry applied to multifarious architectural and engineering forms can be derived from this finding

Supramolecular structures are of great interest due to their applicability in various scientific and industrial fields. These fields of scientific action include promising applications i biomedical areas, in sensing, and in conductive and electrical phases. The sensible definition of supramolecular molecules is being set by investigators, who, because of the different sensitivities of their methods and observational timescales, may have different views as to what constitute these supramolecular structures. Besides, diverse polymers can be found to offer unique avenues for multifunctional systems with properties in medicine industrial applications. Aspects of this review provide different conceptual strategies to address molecular design, properties, and potential applications of self-assembly materials and the use of metal coordination as a feasible and useful strategy for constructing complex supramolecular structures. In this order of appreciations and ideas order, it is that this review report involves classic topics such as hydrogels that range from their relationship with drug delivery systems, to metallo-supramolecular materials, through applications in ophthalmic systems, in applications that require adhesiveness and electrically conductive hydrogels. This review also addresses systems that are largely based on hydrogel chemistry and the enormous opportunities to design very specific structures for applications that demand enormous specificity.

Alzheimer’s Disease (AD) has no cure. Earlier, we showed that partial inhibition of mitochondrial complex I (MCI) with small molecule CP2 induces adaptive stress response activating multiple neuroprotective mechanisms. Chronic treatment reduced inflammation, improved synaptic and mitochondrial functions, and blocked neurodegeneration in symptomatic APP/PS1 mice, a translational model of AD. Here, using serial block-face scanning electron microscopy (SBFSEM) and three-dimensional (3D) EM reconstructions combined with Western blot analysis and next-generation RNA sequencing, we demonstrate that CP2 treatment also restores mitochondrial morphology and mitochondria-endoplasmic reticulum (ER) communication in the APP/PS1 mouse brain. Using 3D EM volume reconstructions, we show that mitochondria in AD dendrites exist primarily as mitochondria-on-a-string (MOAS). Compared to other morphological phenotypes, MOAS are extensively enveloped in the ER membranes forming multiple mitochondria-ER contact sites (MERCS) known to contribute to abnormal lipid and calcium homeostasis. CP2 treatment specifically reduced MOAS formation, consistent with improved energy homeostasis in the brain, with concomitant reduction in MERCS, ER stress, and improved lipid homeostasis. These data provide novel information on the role MOAS play in AD and additional support for further development of partial MCI inhibitors as disease modifying strategy for AD.

This paper introduces a novel 3D NoC router that combines buffered and bufferless routing with approximate priority comparison when deflecting flits. Our proposal is a modification of an asymmetrical router that is buffered in the z dimension ports and bufferless in the x and y dimension ports. Flits that request output ports in the x and y dimensions are granted or deflected based on approximate, instead of accurate, priority comparison. Experimental results show that the proposed router, besides effectively combining the advantages of both buffered and bufferless routers, it achieves additional performance and area gains due to the reduced logic required for approximate priority comparison in flit deflections. Experimental results using synthetic and realistic traffic show that the proposed router begins to saturate at a sifnificantly higher injection rate than a bufferless router, but at a slightly lower injection rate than when using accurate priority comparison. Furthermore, the proposed router achieves higher clock frequencies and reduced area compared to the simpler permutation network.

The first years of an infant’s life represent a sensitive period for neurodevelopment and see the emergence of nascent forms of executive function (EF), which are required to support complex cognition. Few tests exist for measuring EF during infancy, and the available tests require painstaking manual coding of infant behaviour. In modern clinical and research practice, human coders collect data on EF performance by manually labelling video recordings of infant behaviour during toy or social interaction. Besides being extremely time-consuming, video annotation is known to be rater-dependent and subjective. To address these issues, starting from existing cognitive flexibility research protocols, we developed instrumented toys as a new task instrumentation and data collection tool suitable for infant use. A commercially available device comprising a Barometer and Inertial Measurement Unit (IMU) embedded in a 3D-printed lattice structure was used to detect when and how the infant interacts with the toy. The data collected using the instrumented toys provides a rich dataset describing the sequence of toy interaction and individual toy interaction patterns, from which EF-relevant aspects of infant cognition may be inferred. Such a tool potentially provides an objective, reliable, and scalable method of collecting early developmental data in socially interactive contexts.

Measuring pulmonary nodules accurately can help with early diagnosis of lung cancer, which can improve a patient’s chances of survival. Many methods for segmenting nodules have been developed, but they all rely on input from radiologists in the form of a 3D volume of interest (VOI) or use a constant region of interest (ROI) and only consider the presence of nodule within the given VOI. These approaches limit the networks’ ability to detect nodules outside the given VOI and can also include unnecessary structures in the VOI, leading to potentially inaccurate segmentation. In this work, we propose a novel approach for 3D lung nodule segmentation by using 2D region of interest (ROI) inputted from radiologist or computer-aided detection (CADe) system. Particularly, we design a dual-encoder-based hard attention network (DEHA-Net) which incorporates the full slice of thoracic computed tomography scan along with the ROI mask to produce an accurate segmentation mask of lung nodule in the given slice. The proposed architecture exploits the adaptive region of interest (A-ROI) algorithm to automatically investigates the penetration of lung nodule into surrounding slices while eliminating the need to drawing separate ROIs in each slice. Further, the framework performs the multi-view analysis, i.e., in sagittal and coronal views, to improve the segmentation performance. The proposed scheme has been rigorously evaluated on the lung image database consortium and image database resource initiative (LIDC/IDRI) dataset and an extensive analysis of results have been performed. The quantitative analysis shows that the proposed method not only improves the existing state-of-the-art in term of dice score but also, significantly robust against the different types, shape and dimensions of lung nodules.

The results of studying the effect of particles of few-layer graphene (FLG) synthesized by self-propagating high-temperature synthesis (SHS) on the complex of strength and thermo physical properties of polymer composite products obtained by DLP 3D printing are presented. It has been discovered to achieve an increase in thermo physical and strength parameters of polymers modified by FLG compared with samples made on the unmodified base resin. This result was achieved due to low defectiveness, namely the absence of Stone-Wales defects in the structure of FLG due to the homogeneous distribution of FLG over the volume of the polymer in the form of highly dispersed aggregates. It was possible to increase hardness by 120 %, bending strength by 102 %, Charpy impact strength by 205 %, and thermal conductivity at 25 °C by 572 % at concentrations of few-layer graphene of no more than 2 wt. %.

The increased accessibility of drone technology and the wide use of Structure from Motion 3D scene reconstruction have transformed the approach for mapping inaccessible slopes undergoing active rockfalls. The Poggio Baldi landslide offers the possibility for many of these techniques to be deployed and integrated with the aim of defining a suitable workflow for the analysis of hazards in mountainous regions. The generation of multitemporal digital slope twins (2016 – 2019), informed a rockfall trajectory analysis that was carried out with a physical-based GIS model. We tested the rockfall scenario reconstructed and calibrated on the analysis of the rock mass characteristics and the geometrical and physical constraints given by the multi-temporal analysis of the SfM point clouds. This time-independent rockfall hazard analysis is a critical component to any subsequent holistic risk analysis on this case study, and any potential similar mountainous setting.

In recent years, with the development of social media, people are more and more inclined to upload text, pictures and videos on the platform to express their personal emotions, thus the number of short videos is increasing and becoming the first choice for people to socialize. Unlike the traditional way, people can convey their personal emotions and opinions through media other than words, such as video images, etc. for external information. Therefore, the expression and analysis of emotions is not only through text, but also through the analysis of emotional needs in images and videos, and the research scholars have customized products for individual users. Compared with pure text content, video information can more intuitively express users' happiness, anger and sorrow, thus short video-related applications have gained more and more popularity among Internet users in recent years. However, not all short videos on social networking sites can accurately express users' emotions, and related text information can more accurately assist sentiment analysis and thus improve accuracy. However, short video sentiment analysis based on video frame images is inaccurate in some scenarios, such as when expressing tears of joy, the sentiment expressed by the user's facial expression and voice are different, which will cause errors in the analysis of sentiment. As a result, researchers began to consider multimodal sentiment analysis to reduce the impact of the above scenarios on short video sentiment analysis. This paper focuses on proposing a sentiment analysis method for short videos. We first propose a residual attention model to make full use of the information in audio to classify the emotions contained in them. Then the text information in the dataset is classified by feature extraction. The key to extract features from text information is not only to retain the semantic information of the text, but also to explore the potential emotional information in the text, so as to ensure the integrity of the text information features. The experiments show that the sentiment analysis model proposed in this paper is more superior than the baselines.

Deterioration of concrete subjected to freezing and thawing climatic conditions is one of most important factors affecting the durability of concrete infrastructure in cold climates. The freeze-thaw resistance of cementitious materials like concrete and mortar can be determined by the CDF test (Capillary Suction of De-icing chemicals and Freeze-Thaw Test). Here, concrete specimens are subjected to repeated freeze-thaw cycles with simultaneous addition of de-icing salt and the amount of material weathered near the surface is determined. For concretes with adequate freeze-thaw resistance, this test method works very well. However, specimens with inadequate or unknown performance often experience increased edge weathering, which is caused by the detachment of the lateral isolation tape. The increasing edge influence thus leads to a falsification of the results and consequently to an underestimation of the actual freeze-thaw resistance of the material. In materials research in particular, however, concretes with high levels of weathering are studied in order to be able to investigate various factors of influence on the freeze-thaw resistance of concretes in a targeted manner. This paper presents a novel methodology that delivers new information regarding the weathering of CDF test samples and the associated distribution function of the height decrease using high resolution 3D scan data. The results indicate a correlation between the progression of the distribution function and the sample's maximum aggregate size. The change of the sample volume can be used to support the weathering results of the standard CDF methodology. The increase of the surface area is used to estimate the tortuosity of the sample surface. It indicates an asymptotic curve approaching a specific maximum value, which is dependent on the the weathering depth of the sample.

Methacrylated silk (Sil-MA) is a chemically modified silk fibroin specifically designed to be crosslinkable under UV light. This allows the structuring of this material throught additive manufacturing techniques and then to easily prototype patient specific construct. In this study we used Sil-MA to produce single layer crosslinked structures that can be withdrawal and ejected recovering their shape after rehydration. A complete chemical and physical characterization of the material has been conducted. Additionally, we tested the material biocompatibility according to the International Standard Organization protocols (ISO 10993) ensuring the possibility to use it in future trials. The material was also tested to verify its ability to support the osteogenesis. Two different additive manufacturing techniques have been tested (a Digital Light Processing (DLP) UV projector and a pneumatic extrusion technique) to develop Sil-MA grid. Finally, we provide a proof-of-concept that the printed Sil-MA structures are injectable.

Precise binding affinity predictions are essential for structure-based drug discovery (SBDD). Focal adhesion kinase (FAK) is a member of the tyrosine kinase protein family and is overexpressed in a variety of human malignancies. Inhibition of FAK using small molecules is a promising therapeutic option for several types of cancer. Here, we conducted computational modeling of FAK targeting inhibitors using 3-dimensional structure-activity relationship (3D-QSAR), molecular dynamics (MD), and hybrid topology-based free energy perturbation (FEP) methods. The structure-activity relationship (SAR) studies between the physicochemical descriptors and inhibitory activities of the chemical compounds were performed with reasonable statistical accuracy using CoMFA and CoMSIA. These are two well-known 3D-QSAR methods based on the principle of supervised machine learning (ML). Essential information regarding residue-specific binding interactions was determined using the MD and MM-PB/GBSA methods. Finally, physics-based relative binding free energy (〖∆∆G〗_RBFE^(A→B)) values of analogous ligands were estimated using the alchemical FEP simulation. An acceptable agreement was observed between the experimental and computed relative binding free energies. The overall results using ML and physics-based hybrid approaches could be useful for the rational optimization of accessible lead compounds with similar scaffolds targeting the FAK receptor.

This paper presents a proof-of-concept study on the biocolonization of 3D-printed hydroxyapatite scaffolds with mesenchymal stem cells (MSCs). Three-dimensional (3D) printed biomimetic bone structure made of Calcium Deficient HydroxyApatite (CDHA) intended as future bone graft was made from newly developed composite material for FDM printing. The biopolymer polyvinyl alcohol serves in this material as a thermoplastic binder for 3D molding of the printed object with a passive function and is completely removed during sintering. The study presents the material, the process of fused deposition modeling (FDM) of CDHA scaffolds and its post-processing at three temperatures (1200, 1300, 1400 °C), as well it evaluates the cytotoxicity and biocompatibility of scaffolds with MTT and LDH release assays after 14 days. The study also includes a morphological evaluation of the cellular colonization with scanning electron microscopy (SEM) in two different filament orientations (rectilinear and gyroid). The results of the MTT assay showed that the tested material was not toxic, and cells were preserved in both orientations, with most cells present on the material fired at 1300°C. Results of the LDH release assay showed a slight increase in LDH leakage from all samples. Visual evaluation of SEM confirmed the ideal post-processing temperature of the 3D-printed FDM framework for samples fired at 1300°C and 1400°C, with a porosity of 0.3 mm between filaments. In conclusion, the presented fabrication and colonization of CDHA scaffolds have great potential to be used in the tissue engineering of bones.

There has been considerable research on reconstructing 3D shapes from single-view images; however, preserving the detailed information of the input image remains difficult. In this paper, we propose the application of a gradient map to train a network, aimed at improving the visual quality of fine-grained details such as the thin and tiny components of generated shapes. Each gradient map was created from the original voxel data, and each value represented the amount of information per volume. Here, the gradient map was defined by several methods that mathematically quantify and represent the detailed structure of an object. By applying this map to the loss function in training, we could induce the network to intensively train partial details, such as thin and narrow parts. We demonstrated that the detailed information was well-recovered when a weight that is proportional to the gradient value was applied to the loss. Furthermore, it is expected that our method will contribute to the development of 3D technologies related to the construction of virtual space for simulation and new customer experience.

Fluorescence microscopy is an important tool for disease diagnosis, often requiring costly optical components, such as fluorescence filter cubes and high-power light sources. Due to its high cost, conventional fluorescence microscopy cannot be fully exploited in low-income settings. Smartphone-based fluorescence microscopy becomes an interesting low-cost alternative, but raises challenges in the optical system. We present the development of a low-cost inverted laser fluorescence microscope, that uses a smartphone to visualize the fluorescence image of biological samples. Our fluorescence microscope uses a laser-based simplified optical filter system, that provides analog optical filtering capabilities of a fluorescence filter cube. Firstly, we validated our inverted optical filtering by visualizing microbeads labeled with three different fluorescent compounds or fluorophores, commonly used for disease diagnosis. Secondly, we validated the disease diagnosis capabilities, by comparing the results of our device with those of a commercial fluorescence microscope. We successfully detected and visualized Trypanosoma cruzi parasites, responsible of the Chagas infectious disease, and the presence of Antineutrophil cytoplasmic antibodies of the ANCA non-communicable autoimmune disease. The samples were labeled with the fluorescein isothiocyanate (FITC) fluorophore, one of the most commonly used for disease diagnosis. Our device provides a 400 X magnification and is at least two orders magnitude cheaper than conventional commercial fluorescence microscopes.

Phase imaging of biochemical samples has been demonstrated for the first time at the Infrared Microspectroscopy (IRM) beamline of the Australian Synchrotron using the usually discarded Near-IR (NIR) region of the synchrotron-IR beam. The synchrotron-IR beam at the Australian Synchrotron IRM beamline has a unique fork shaped intensity distribution as a result of the gold coated extraction mirror shape, which includes a central slit for rejection of the intense X-ray beam. The resulting beam configuration makes any imaging task challenging. For intensity imaging, the fork shaped beam is usually tightly focused to a point on the sample plane followed by a pixel-by-pixel scanning approach to record the image. In this study, a pinhole was aligned with one of the lobes of the fork shaped beam and the Airy diffraction pattern was used to illuminate biochemical samples. The diffracted light from the samples was captured using a NIR sensitive lensless camera. A rapid phase-retrieval algorithm was applied to the recorded intensity distributions to reconstruct the phase information corresponding to different planes. The preliminary results are promising to develop multimodal imaging capabilities at the IRM beamline of the Australian Synchrotron.

Additive manufacturing or 3D printing applying polycaprolactone-(PCL)-based medical devices represents an important branch of tissue engineering, where the sterilization method is a key process for further safe application in vitro and in vivo. In this study, the authors intend to access the most suitable gamma radiation conditions to sterilize PCL-based scaffolds in a preliminary biocompatibility assessment, envisioning future studies for airway obstruction conditions. Three radiation levels were considered, 25 kGy, 35 kGy and 45 kGy and evaluated as to their cyto- and biocompatibility. All three groups presented biocompatible properties, indicating an adequate sterility condition. As for the cytocompatibility analysis, devices sterilized by 35 kGy and 45 kGy showed better results, with the 45 kGy showing overall improved outcomes. This study allowed to select the most suitable sterilization condition for PCL-based scaffolds, aiming at immediate future assays, by applying 3D-customized printing techniques to specific airway obstruction lesions of the trachea.

Transparent and high-hardness materials have become the object of wide interest. Most notably, it concerns technical glasses and crystals. A notable example is a sapphire – one of the most rigid materials having impressive mechanical stability and good optical properties. Nonetheless, using this material for 3D micro-fabrication is not straightforward due to its brittle nature. On the microscale, selective laser etching (SLE) technology is an appropriate approach for such media. Therefore, we present our research on c-cut crystalline sapphire microprocessing by using femtosecond radiation-induced SLE. Here we demonstrate a comparison between different wavelength radiation (1030 nm, 515 nm, 343 nm) usage for modification inscription and various etchants (Hydrofloridic acid, Sodium Hydroxide, Potassium Hydroxide and Sulphuric and Phosphoric acid mixture) comparison. We show that regular SLE etchants such as Hydrofluoric acid or Potassium Hydroxide are unsuitable materials for selective sapphire laser etching. Meanwhile, a 78% sulphuric and 22% phosphoric acid mixture at 270°C temperature is a good alternative for this process. We present the changes in the material after the separate processing steps. Finally, a protocol for advanced sapphire structure formation and a few exemplary structures are presented.

The repurposing of licenced drugs for use against COVID-19 is one of the most rapid ways to develop new and alternative therapeutic options to manage the ongoing pandemic. Given the approximately 8,000 licenced compounds available from Compounds Australia that can be screened, this paper demonstrates the utility of commercially-available ex vivo/3D airway and alveolar tissue models. These models are a closer representation of in vivo studies compared to in vitro models, but retain the benefits of rapid in vitro screening for drug efficacy. We demonstrate that several existing drugs appear to show anti-SARS-CoV-2 activity against both Delta and Omicron Variants of Concern in the airway model. In particular, fluvoxamine, as well as aprepitant, everolimus, and sirolimus have virus reduction efficacy comparable to the current standard of care (remdesivir, molnupiravir, nirmatrelvir). Whilst these results are encouraging, further testing and efficacy studies are required before clinical use can be considered.

3D object detection is crucial for autonomous driving to understand the driving environment. Since the pooling operation causes information loss in the standard CNN, we have designed a wavelet multiresolution analysis-based 3D object detection network without a pooling operation. Additionally, instead of using a single filter like the standard convolution, we use the lower-frequency and higher-frequency coefficients as a filter. These filters capture more relevant parts than a single filter, enlarging the receptive field. The model comprises a discrete wavelet transform (DWT) and an inverse wavelet transform (IWT) with skip connections to encourage feature reuse for contrasting and expanding layers. The IWT enriches the feature representation by fully recovering the lost details during the downsampling operation. Element-wise summation is used for the skip connections to decrease the computational burden. We train the model for the Haar and Daubechies (Db4) wavelets. The two-level wavelet decomposition result shows that we can build a lightweight model without losing significant performance. The experimental results on the KITTI’s BEV and 3D evaluation benchmark show our model outperforms the Pointpillars base model by up to 14 \% while reducing the number of trainable parameters. Code will be released.

The Coronavirus disease 2019 (COVID-19) rapidly spread to over 180 countries and abruptly disrupted the production rates and supply chains worldwide. Since then, 3D printing also recognized as additive manufacturing (AM) and known to be a novel technique that uses layer-by-layer deposition of material to produce the intricate 3D geometry, has been engaged in reducing the distress caused by the outbreak. During the early stages of this pandemic, shortages of Personal Protection Equipment (PPE), including facemasks, shields, respirators, and other medical gears, were significantly answered by remotely 3D printing them. Amidst the growing testing requirements, the 3D printing emerged as a potential and fast solution manufacturing process to meet the production needs due to its flexibility, reliability, and rapid response capabilities. In the recent past, some of the other medical applications that have gained prominence in the scientific community include 3D printed ventilator splitters, device components, and patient-specific products. Regarding the non-medical applications, researchers have successfully developed contact-free devices to address the sanitary crisis in public places. This work aims to systematically review the applications of 3D printing or AM techniques that have been involved in producing various critical products essential to limit this deadly pandemic's progression.

Cancer invasion through basement membranes represents the initial step of tumor dissemination and metastasis. However, little is known about how human cancer cells breach basement membranes. Here, we used a 3-dimensional in vitro invasion model consisting of cancer spheroids encapsulated by a basement membrane and embedded in 3D collagen gels to visualize the early events of cancer invasion by confocal microscopy and live-cell imaging. Human breast cancer cells generated large numbers of basement membrane perforations, or holes, of varying sizes that expanded over time during cell invasion. We used a wide variety of small molecule inhibitors to probe the mechanisms of basement membrane perforation and hole expansion. Protease inhibitor treatment (BB94), led to a 63% decrease in perforation size. After myosin II inhibition (blebbistatin), basement membrane perforation area decreased by only 15%. These treatments produced correspondingly decreased cellular breaching events. Interestingly, inhibition of actin polymerization dramatically decreased basement membrane perforation by 80% and blocked invasion. Our findings suggest that human cancer cells can primarily use proteolysis and actin polymerization to perforate the BM and to expand perforations for basement membrane breaching, with a relatively small contribution from myosin II contractility.

Smart health applications have received significant attention in recent years. Novel applications hold significant promise to overcome many of the inconveniences faced by persons with disabilities throughout daily living. For people with blindness and low vision (BLV), environmental perception is compromised, creating myriad difficulties. Precise localization is still a gap in the field and is critical to safe navigation. Conventional GNSS positioning cannot provide satisfactory performance in urban canyons. 3D mapping-aided (3DMA) GNSS may serve as an urban GNSS solution, since the availability of 3D city models has widely increased. As a result, this study developed a real-time 3DMA GNSS-positioning system based on state-of-the-art 3DMA GNSS algorithms. Shadow matching was integrated with likelihood-based ranging 3DMA GNSS, generating positioning hypothesis candidates. To increase robustness, the 3DMA GNSS solution was then optimized with Doppler measurements using factor graph optimization (FGO) in a loosely-coupled fashion. This study also evaluated positioning performance using an advanced wearable system’s recorded data in New York City. The real-time forward processed FGO can provide a root-mean-square error (RMSE) with about 21 m. The RMSE drops to 16 m when the data is post-processed with FGO in a combined direction. Overall results show that the proposed loosely-coupled 3DMA FGO algorithm can provide a better and more robust positioning performance for the multi-sensor integration approach used by this wearable for persons with BLV.

As the additive manufacturing industry grows, it is compounding the global plastic waste problem. Distributed recycling and additive manufacturing (DRAM) offers an economic solution to this challenge, but it has been relegated to either small-volume 3D printers (limiting waste recycling throughput) or expensive industrial machines (limiting accessibility and lateral scaling). To overcome these challenges, this paper provides proof-of-concept for a novel open-source hybrid 3D printer that combines a low-cost hanging printer design with a compression screw-based end-effector that allows direct extrusion of recycled plastic waste in large expandable printing volumes. Mechanical testing of the resultant prints from 100% waste plastic, however, showed that combining challenges of non-uniform feedstocks and a heavy printhead for a hangprinter reduced the strength of the parts compared to fused filament fabrication. The preliminary results are technologically promising, however, and provide opportunities to improve on the open source design to help process the volumes of waste plastic needed for DRAM to address the negative environmental impacts of global plastic use.

3D reconstruction from a single 2D input is a classic problem in the field of computer vision. With the advancements in deep learning, the performance of 3D reconstruction has also significantly improved. The reconstruction task is more difficult for objects with no textures or complex deformations. This paper serves as a review of recent literature on 3D reconstruction from a single view, with a focus on deep learning methods from 2018 to 2021. Due to lack of standard datasets or 3D shape representation methods, it is hard make direct comparisons between all reviewed methods. However, this paper reviews different approaches for reconstructing 3d shape as depth maps, surface normals, point clouds and meshes; along with various loss functions and evaluation metrics used to train and evaluate these methods.

Single-layer core corrugated sandwich panels generally consist of a corrugated core and two layers of panels, while multi-layer core corrugated sandwich panels are formed by stacking multiple layers of panels with multiple layers of core layers. In this study, integrated multilayer core corrugated sandwich panels with different shapes of corrugated cores (triangular, trapezoidal, and rectangular) and the different number of core layers were fabricated using 3D printing technology, and the mechanical behavior of such multilayer core corrugated sandwich panels under quasi-static three-point bending was investigated using experiments and numerical simulations. The effects of core shape and number of core layers on the bending deformation process, damage mode, load carrying capacity, and bending energy dissipation capacity of multilayer core sandwich panels are discussed. Parametric design of multilayer triangular core corrugated sandwich panels was also carried out by finite element software ABAQUS. It was found that a new multilayer corrugated sandwich panel with a multi-layer core is better than the single core shape multilayer corrugated sandwich panel in terms of bending load capacity, energy dissipation capacity and deformation capacity can be obtained through the combination design of different core shapes.

A refractive lens is one of the simplest, cost-effective and easily available imaging elements. With a spatially incoherent illumination, a refractive lens can faithfully map every object point to an image point in the sensor plane, when the object and image distances satisfy the imaging conditions. However, static imaging is limited to the depth of focus, beyond which the point-to-point mapping can be only obtained by changing either the location of the lens or the imaging sensor. In this study, the depth of focus of a refractive lens in static mode has been expanded using a recently developed computational reconstruction method, Lucy-Richardson-Rosen algorithm (LRRA). The technique consists of three steps. In this first step, the point spread functions (PSFs) were recorded along different depths and stored in the computer as PSF library. In the next step, the object intensity distribution was recorded. The LRRA was then applied to deconvolve the object information from the recorded intensity distributions in the final step. The results of LRRA were compared against two well-known reconstruction methods namely Lucy-Richardson algorithm and non-linear reconstruction.

This retrospective study evaluated changes in the pharyngeal portion of the upper airway in pa-tients with constricted and normal airway treated with clear aligners (Invisalign, Align). Additionally, the paper has assessed the change of tongue position in the oral cavity from lateral view. Evaluation was performed with specialized software (Invivo 6.0, Anatomage) on pre-treatment and posttreatment pairs of cone beam computed tomography imaging (CBCT) data. The level of airway constriction, volume, cross-section minimal area, and tongue profile were evaluated. Patients with malocclusion, with pair or initial and finishing CBCT and without sig-nificant weight change between the scans, treated with Invisalign clear aligners were distributed in two groups. Group A consisted of fifty-five patients with orthodontic malocclusion and con-stricted upper airway. Control group B consisted of thirty-one patients with orthodontic malocclusions without any airway constriction. In the group with airway constriction, there was a statistically significant increase in volume during therapy (p<0.001). The surface of the most con-stricted cross-section of airway did not change significantly after treatment in any of the groups. The airway constriction was most frequently localized at the level of 2nd cervical vertebra. The final tongue position was different from initial in 62.2% of all clear aligner treatments.

Lesion studies are crucial in establishing brain-behavior relationships, and accurately segmenting the lesion represents the first step in achieving this. Manual lesion segmentation is the gold standard for chronic strokes. However, it is labor-intensive, subject to bias, and limits sample size. Therefore, our objective is to develop an automatic segmentation algorithm for chronic stroke lesions on T1-weighted MR images. Methods: To train our model, we utilized an open-source dataset: ATLAS v2.0 (Anatomical Tracings of Lesions After Stroke). We partitioned the dataset of 655 T1 images with manual segmentation labels into five subsets and performed a 5-fold cross-validation to avoid overfitting of the model. We used a deep neural network (DNN) architecture for model training. Results: To evaluate the model performance, we used three metrics that pertain to diverse aspects of volumetric segmentation including shape, location, and size. The Dice similarity coefficient (DSC) compares the spatial overlap between manual and machine segmentation. The average DSC was 0.65 (0.61- 0.67; 95% bootstrapped CI). Average symmetric surface distance (ASSD) measures contour distances between the two segmentations. ASSD between manual and automatic segmentation was 12mm. Finally, we compared the total lesion volumes and the Pearson correlation coefficient (ρ) between the manual and automatically segmented lesion volumes, which was 0.97(p-value &lt; 0.001). Conclusions: We present the first automated segmentation model trained on a large multicentric dataset. This model will enable automated on-demand processing of MRI scans and quantitative chronic stroke lesion assessment.

Along with the popularity of the Internet, people are exposed to more and more ways of micro-videos, and a huge amount of micro-video data has emerged. micro-videos have gradually become the Internet content preferred by the public, and a large number of micro-video apps have also emerged, such as Tiktok and Kwai. Intelligent classification and mining of micro-videos can greatly enhance user experience, improve business operation efficiency and enhance user experience. Through deep intelligent analysis and mining of micro-videos, important information in micro-videos can be extracted to provide an important basis for beautifying videos, content appreciation, video recommendation, content search, etc. In the past, content understanding for short videos often used human work annotation, but in recent years, with the great success of deep convolutional neural networks in image recognition, short video content understanding based on this method has gradually developed. Nowadays, most recognition algorithms extract the feature representation of each frame independently and then fuse them. However, while extracting the feature representation, some low-level semantic features are lost, which makes the algorithm unable to accurately distinguish the category of the video. At present, the algorithm of micro-video recognition based on deep learning has surpassed the iDT algorithm, making these traditional methods fade out of people’s view. In this paper according to the micro-video classification task, a new network model is proposed to concatenate features of each modality into the overall features of various modalities through the network, and then fuse the various modal features with the attention mechanism to obtain the whole micro-video features, which will be used for classification. In order to verify the effectiveness of the algorithm proposed in this paper, experiments are conducted in the public dataset, and it is shown the effectiveness of our model.

The Galleon was considered a masterpiece of shipbuilding in the sixteenth century, but from a modern point of view, the shape of her hull looks archaic and primitive. However, how accurate is this perception? Is the hull form of Galleon primitive? What were the reasons for its unique design features? This article investigates these questions by directly analysing the hull’s features from the point of view of modern ship’s theory, as well as from a historical perspective. A careful evaluation of specific design criteria of a typical Galleon, together with analysing a 3D model of its hull on modern software, with further insight for the seakeeping behaviour of Galleon with a comparison to more modern full-rigged ship (Barque of 19 CE), showed that these features were not random, but instead had a good rationale behind it, and served specific and carefully decided functions, required at the time.

The soft robot has many degrees of freedom, strong environmental adaptability and good human-computer interaction ability. As the end-effector of the soft robot, the soft gripper can grasp objects of different shapes without destructivity. Based on the theoretical analysis of the soft robot, the kinematics model of the flexible gripper and the theoretical model of the bending deformation of the air cavity were established. Accordingly, the relationship between the bending angle of the soft gripper and the air pressure was determined. Through the application of finite element software, the bending degree of pneumatic network multi-cavity soft gripper was simulated by finite element software, and the influence of structural parameters of soft actuator on bending deformation was determined. In addition, with the 3D technology conducting the printing of soft gripper fixtures and molds, the injection molding the actuator and the human-computer interaction interface controlling the movement of the gripper, the adaptability of the soft gripper in grasping object was verified. The result shows that the software gripper possesses good flexibility and can better grasp objects of different shapes.

INT-FFT algorithm presented in this work uses an interpolation methodology to densify 3D-GPR datasets to sharpen images obtained in GPR surveys obtained in an archaeological context. It allows the reconstruction of missing data from the combined use of mathematical transforms (e.g., the Fourier and Curvelet transform) and predictive filters. This technique makes it possible to calculate the missing signal simply by meeting two requirements: the data in the frequency domain must be limited in a range of values and must be able to be represented by a distribution of Fourier coefficients (verified conditions). The INT-FFT algorithm uses an open-access routine (Suinterp, Seismic Unix) to interpolate the GPR profiles based on seismic trace interpolation. This process uses automatic event identification routines by calculating spatial derivatives to identify discontinuities in space by detecting very subtle changes in the signal, thus allowing for more efficient interpolation without artifacts or signal deterioration. We successfully tested the approach using GPR datasets from the Roman Villa of Horta da Torre (Fronteira, Portugal). The results show an increase in the geometric sharpness of the GPR reflectors and have not produced any numerical artifacts. The tests performed to apply the methodology to GPR-3D data allowed for assessing the interpolation efficiency, the level of recovery of missing data, and the level of information lost when one chooses to increase the distance between profiles in the acquisition stage of the data.

Scattering has been always considered a problem in most of the imaging and holography systems. In this project, a 3D imaging system has been developed based on scattering against common beliefs. The 3D imaging system consists of only two components namely a scattering lens, fabricated by grinding the surface of a convex lens using sandpaper and a web camera. The point spread function (PSF) in the form of speckle distribution was recorded using a laser source in the first step. A synthetic object was selected which was convolved with the PSF in a computer to generate the object intensity distribution. The image of the object was reconstructed by processing the PSF and object intensity distribution using a computational reconstruction method called non-linear reconstruction. The recorded PSF was scaled and the process was repeated for a different synthetic object. The concept was extended to 3D by summing the object intensity distributions generated using PSFs with different scaling factors. The image at different planes can be reconstructed using the PSFs corresponding to that plane.

Weaving is an ancient and effective structural forming technique characterized by the ability to convert two-dimensional ribbons to three-dimensional structures. However, most 3D structures woven from straight ribbons have topological defects. Baek et al. proposed a method to weave smoother continuous 3D surface structures using naturally curved (in-plane) ribbons, obtained a new surface structure with relatively continuous variation of Gaussian curvature, and analyzed its geometric properties. We believe that this new 3D surface structure with smooth geometric properties must correspond to new mechanical properties. To this end, we investigated a 3D surface structure using naturally curved (in-plane) ribbon weaving, and the results of calculations and experiments show that such structures have better buckling stability than those woven with straight ribbons. It is observed that the number of ribbons influences the buckling behavior of different types of woven structures.

In engineering, connections between components are often weak areas. Unreasonable connection methods can easily reduce the strength of components, resulting in unpredictable failure modes. In nature, numerous connection methods for biological structures with excellent mechanical properties have evolved. Studying the connection methods of organisms in nature can inspire new ideas for bionic connection methods. When the diabolical ironclad beetle is under pressure, the elytra are not easy to separate, which ensures the stability of the beetle's external structure, thus making the beetle extremely resistant to pressure. The reason for this is the interlocking and toughening effect of the unique jigsaw connection between the elytra. Therefore, in this paper a theoretical analysis model is established and used to analyze the mechanical behavior of the diabolical ironclad beetle's jigsaw connection during the drawing process and determine the influence of factors such as quantity, angle, and geometric characteristics on the mechanical properties of the jigsaw connection. The results of the theoretical analysis are then compared with the results of experiments and ABAQUS finite element simulation.

Additive manufacturing (3D printing) and computer-aided design (CAD) still have limited up-take in biomedical and bioengineering research and education, despite the significant potential of these technologies. The utility of organ-scale 3D-printed models of living structures is widely appreciated, while the workflows for microscopy data translation into tactile-accessible replicas are not well developed yet. Here, we demonstrate an accessible and reproducible CAD-based methodology for generating 3D-printed scalable models of human cells cultured in vitro and imaged using conventional scanning confocal microscopy and fused deposition modelling (FDM) 3D printing. We termed this technology CiTo-3DP (Cells-in-Touch for 3D Printing). As a proof-of-concept, we created CiTo-3DP models of human pancreatic cancer cells and healthy dermal fibroblasts by using selectively stained nuclei and the cytoskeleton components (f-actin and α-smooth muscle actin). The production of dismountable sets of cellular components was al-so shown. The CiTo-3DP approach can be adapted to comprehensively present various cell types, subcellular structures and extracellular matrices. We envisage that the resulting CAD and 3D printed models could be used for further applications, including but not limited to in silico simulations for biology, medicine, pharmacological research, tissue engineering, morphometrical analysis, multiphysics modelling, education, rehabilitation of visually impaired people, and integration into virtual reality.

In plants, water flows are the major driving force behind the growth and play a crucial role in the life cycle. To study hydrodynamics, methods based on tracking small particles inside water flows occupy a special place. Due to these tools, it is possible to get information about the dynamics of the spatial distribution of the fluxes characteristics. In this paper, using contrast-enhanced MRI, we have shown that gadolinium chelate, used as an MRI contrast agent, marks the structural characteristics of xylem bundles of maize stem nodes and internodes. Supplementing MRI data, a high-precision visualization of xylem vessels by laser scanning microscopy was used to reveal structural and dimensional characteristics of the stem vascular system. In addition, we proposed the concept of using the prototype "Y-type xylem vascular bundles" as a model of the elementary connection of vessels within the vascular system. A Reynolds number can match the microchannel model with the real xylem vessels.

The cuttlebone-like structure is a complex porous bionic structure with asymmetric sinusoidal S-shaped wall structure connecting laminar septa, and studies have shown that the cuttlebone-like structure has light weight, high strength and excellent energy absorption capability. It has become an important research to investigate the mechanical mechanism of cuttlebone-like structure and to design a bionic structure beyond nature structure based on it. In order to investigate the mechanical properties of the static compression and shearing processes of the cuttlebone-like structure, this paper establishes theoretical formulas and analyzes the influence of dimensionless parameters such as height-to-thickness ratio $\lambda$, period-to-thickness ratio $\xi$ and amplitude to period ratio $\eta$ on the compression and shearing processes with the help of ABAQUS finite element software.The parameter sensitivity analysis method was used to compare the important influence degree of each dimensionless parameter on the mechanical properties of the structure and to determine the relative optimal parameters of the structural mechanical properties under compression and shearing. Based on the relatively optimal parameter of the cuttlebone-like structure, the cross-sectional geometry of the structure is improved to build a new cuttlebone-like structure.The experimental results showed that the new cuttlebone-like structure with revised cross-section improved the mechanical properties of the cuttlebone-like structure.The study results are of theoretical guidance to enhance the mechanical properties and geometric design of cuttlebone-like structures.

We present a novel passive satellite remote sensing approach for observing the three-dimensional distribution of aerosols emitted from wildfires. This method, called AEROS5P, retrieves vertical profiles of aerosol extinction from measurements of the TROPOMI satellite sensor onboard the Sentinel 5 Precursor mission. It uses a Tikhonov-Phillips regularization which iteratively fits cloud-free near-infrared and visible selected reflectances to simultaneously adjust the vertical distribution and abundance of aerosols. The information on the altitude of the aerosol layers is provided by TROPOMI measurements of the reflectance spectra at the oxygen A-band near 760 nm. In the present paper, we use this new approach for observing the daily evolution of the three-dimensional distribution of biomass burning aerosols emitted by Australian wildfires on 20-24 December 2019. Aerosol optical depths (AOD) derived by vertical integration of the aerosol extinction profiles retrieved by AEROS5P are compared with MODIS, VIIRS and AERONET coincident observations. They show a good agreement in the horizontal distribution of biomass burning aerosols, with a correlation coefficient of 0.86 and a mean absolute error of 0.2 with respect to VIIRS. A fair agreement is found between coincident transects of vertical profiles of biomass burning aerosols derived from AEROS5P and from the CALIOP spaceborne lidar. The mean altitude of these aerosols derived from these two measurements show a good agreement, with a small mean bias (185 m) and a correlation coefficient of 0.83. Moreover, AEROS5P observations reveal the height of injection of the biomass burning aerosols in 3D. The highest injection heights during the period of analysis are coincident with the largest fire radiative power derived from MODIS. Consistency is also found with respect to the vertical stability of the atmosphere.

The mechanical properties and stability of hydrophobic surface structures prepared by traditional methods are still the main technical bottlenecks restricting the broad application of hydrophobic systems on workpiece surfaces. In this contribution, we propose a technique called selective laser shock peening (SLSP) to enable large-scale high efficient, low-cost manufacturing of hydrophobic metal surfaces with enhanced mechanical properties for durable applications. Using the method of experimental investigation combined with numerical calculation, the hydrophobic properties, mechanical properties, and tribological properties of the samples prepared under SLSP, all-laser shock peening (ALSP), and non-laser shock peening (NLSP) are studied. The SLSP process could prepare a 3D gradient structure material with surface structures, a two-phase (strong phase, soft phase) distribution on the surface, and a multi-level gradient distribution in the thickness direction. Compared with the 2D gradient structure prepared by the traditional process, 3D gradient structures by SLSP have more significant advantages in improving the wetting behavior and the mechanical properties of the material, which proves SLSP to be a novel method to fabricate functional metal surface structures, with highly high engineering application value.

Tri-dimensional (3D) cell aggregates or spheroids are considered to be closer to physiological conditions than traditional 2D cell culture. Mesenchymal stem cells (MSCs) assembling in spheroids have increased the survival of transplanted cells. The regulation of the biological processes that maintain crucial physiological reactions of MSCs is closely related to the functioning of ion channels. The pattern of expression, role and regulatory mechanisms of ion channels could be significantly different in 3D compared to 2D culture, and, thus, needed to be properly analyzed on the level of ionic currents. We developed a specific approach that allowed us to register, for the first time, endogenous ion channels in endometrial MSCs (eMSCs) assembled in spheroids. Particularly, using the single-channel patch-clamp technique, we have recorded the activity of ion channels and observed their functional interplay in mechanosensitive clusters. Our experimental protocol could be applied for identification and studying of ion channels in 3D cell cultures.

The extrusion-based 3D concrete printing (3DCP) technology allows the fabrication of permanent formwork with intricate shapes, into which fresh concrete is cast to build structural members with complex geometry. This significantly enhances the geometric freedom of concrete structures without the use of expensive temporary formwork. In addition, with proper material choice for the permanent formwork, the load-bearing capacity and durability of the resulting structure can be improved. This paper investigates 3DCP of permanent formwork for reinforced concrete (RC) beam construction. A 3D-printable engineered geopolymer composite (3DP-EGC, or strain-hardening geopolymer composite, 3DP-SHGC) recently developed by the authors was used for fabrication of the permanent formwork. The 3DP-EGC exhibits strain-hardening behaviour under direct tension. Two different printing patterns were used for the soffit of the permanent formwork to investigate the effect of this parameter on the flexural performance of RC beams. A conventionally mould-cast RC beam was also prepared as the control beam for comparison purposes. The results showed that the RC beams constructed using the 3DP-EGC permanent formwork exhibited superior flexural performance to the control beam. Such beams yielded significantly higher cracking load (up to 43%), deflection at ultimate load (up to 60%), ductility index (50%) and absorbed energy (up to 107%) than those of the control beam. The ultimate load was comparable with or slightly higher than that of the control beam. Furthermore, the printing pattern at the soffit of the permanent formwork was found to have a significant influence on the flexural performance of the RC beams.

One of the major limitations of the current 3D-concrete-printing technology is incorporation of reinforcement. Furthermore, there is a need to decrease the ecological footprint of printable concrete. As a possible solution for these challenges, this paper presents a 3D-printable strain-hardening geopolymer composite (3DP-SHGC) that shows pseudo-ductile behaviour under direct tension. The developed 3DP-SHGC is composed of one-part (just-add-water) geopolymer binder made of slag (GGBFS), fly ash (FA) and solid activator. The one-part geopolymer binder eliminates the need for elevated temperature curing and handling of corrosive alkaline liquids. At first, an optimum matrix was identified by studying the effects of FA to GGBFS ratio on the rheological properties and compressive strength. Subsequently the optimum matrix was reinforced by PVA fibres to make the 3DP-SHGC, which printing performance and rheological properties were evaluated. In addition, the influences of curing temperature on the compressive, flexural and tensile performances of the printed specimens were also investigated. The results were compared with those obtained for the mould-cast specimens. The 3DP-SHGC exhibited superior flexural performance, higher tensile strength, and comparable tensile strain capacity to the mould-cast counterpart. Further, the curing temperature had influence on the mechanical properties of both 3D-printed and mould-cast SHGCs. The underlying reasons for the differences are discussed.

Despite all their advantages, load-bearing concrete shell structures with double curvatures are not frequently in use. The main reason is the complexity of their construction. In such a context, this article starts with a brief, critical review of existing technologies while their pros and cons are highlighted. Against that background the authors then propose a new approach for the highly automated fabrication of gridshell structures from variable modules. To demonstrate the feasibility of such a new technology, a demonstrator called ConDIT 1.0, a sphere-like shell structure composed of several frames was designed and built. The frame modules were fabricated automatically using extrusion-based 3D printing and a printable, strain-hardening cement-based composite (SHCC). This article presents the design of ConDIT 1.0, the mechanical material characterization of printed SHCC, the technology of module production, the results of geometry verification for print modules using 3D scanning, and the procedure for the demonstrator’s assembly.

Shell-like, double curved and thus above-average performance structures, are usually produced monolithically on site. For industrial advancement, however, they must be divided into transportable modules which can be assembled on the construction site (design for assembly). Models are lattice shells made of steel and glass, in which predominantly flat sub-surfaces (modules) are used. Therefore, the main question is: Which modularizations are suitable for flow production with mineral building materials? In this paper designed free-form surface is going to be discretized as PQ circular mesh system, suitable modules for 3D concrete printing. Moreover, the multi-criteria optimization is done with Response Surface Methodology (RSM) in order to get optimal final shape. The goal is to start from the arbitrary shape, that can be generated from two curves, with possible two-way division into modules and compare it with the resulted discretized PQ circular mesh system, realized with new algorithm. The comparison can be defined through two main criteria: geometrical and structural.

In surveying engineering tasks, close-range photogrammetry belongs to leading technology considering different aspects like the achievable accuracy, availability of hardware and software, accessibility to measured objects, or the economy. Hence, constant studies on photogrammetric data processing are desirable. Especially in industrial applications, the control points for close-range photogrammetry are usually measured using total stations. In the case of small objects, more precise positions of control points can be obtained by deploying and adjusting a three-dimensional linear network set up on the object. The article analyzes the accuracy of the proposed method, based on the measurement of the linear network using a tape with a precision of ±1 mm. The experiment shows that the adjusted positions of the network control points can be determined with high, one-millimeter accuracy. The photogrammetric 3D model derived referring to such control points and stereo-images captured with a non-metric camera is also characterized by the highest possible precision, which qualifies the presented method to accurate measurements used in surveying engineering. The authors prove that the distance between two randomly optional points derived from the 3D model of a dimensioned object is equal to the actual distance measured directly on it with one-millimeter accuracy.

Polymer adhesives have emerged as a promising dielectric passivation layer in hybrid bonding for 3D integration while they raise misalignment problems during curing. In this work, the synergistic effect of oxygen plasma surface activation and wetting is utilized to achieve bonding between completed cured polyimides. The optimized process achieves a void-less bonding with a maximum shear strength of 35.3 MPa at a low temperature of 250 °C in merely 2 min, significantly shortening the bonding period and decreasing thermal stress. It is found that the plasma activation generated hydrophilic groups on the polyimide surface, and the wetting process further introduced more -OH groups and water molecular on the activated polyimide surface. The synergistic process of plasma activation and wetting facilitate bridging polyimide interfaces to achieve bonding, providing an alternative path for adhesive bonding in 3D integration.

Tumor cells evolve in a complex and heterogeneous environment composed of different cell types and an extracellular matrix. Current 2D culture methods are very limited in their ability to mimic the cancer cell environment. In recent years, various 3D models of cancer cells have been developed, notably in the form of spheroids/organoids, using scaffold or cancer-on-chip devices. However, these models have the disadvantage of not being able to precisely control the organization of multiple cell types in complex architecture and are sometimes not very reproducible in their production, and this is especially true for spheroids. Three-dimensional bioprinting can produce complex, multi-cellular, and reproducible constructs in which the matrix composition and rigidity can be adapted locally or globally to the tumor model studied. For these reasons, 3D bioprinting seems to be the technique of choice to mimic the tumor microenvironment in vivo as closely as possible. In this review, we discuss different 3D-bioprinting technologies, including bioinks and crosslinkers that can be used for in vitro cancer models, and the techniques used to study cells grown in hydrogels; finally, we provide some applications of bioprinted cancer models.

This article describes the methodology used to identify the mathematical model that describes the correlations between the input parameters of an experiment and the parameters being followed. As a technological process, the aerodynamic separation was chosen, respectively, the behavior of a solid particle within an ascending vertical airflow. The experimental data obtained were used to identify two parameters, the average linear velocity, and the angular velocity, and through the Table Curve 3D program was developed a mathematical model which describes the dependence between the input parameters (the shape and size of the solid particle and the velocity of the airflow) and the monitored parameters. In order to determine a single mathematical equation that describes as accurately as possible the correlation between the input variables and those obtained, a pyramid-type analysis was designed. The determination of the mathematical equation started from the number of equations generated by the Table Curve 3D program, then the equations with a correlation coefficient greater than 0.85 were chosen, and finally, the common equations were identified. Respecting the working methodology was identified one equation which has for the average linear velocity a correlation coefficient r2 between 0.88-0.99 and 0.86-0.99 for the angular velocity.

Numerous cases and a shortage of resources usually limit wild animal rescue. New technology implemented might save these severely injured wild animals from the situation of euthanasia by easing the requirement of intensive medication. Three-dimensional (3D) technologies provide precise and accurate results that improve the quality of the medical application. These 3D tools have become relatively low-cost and accessible in the past years. In the medical field of exotic animal, turtle shell defect is highly challenging because of inevitable water immersion. This report is the first attempt to apply the combination of 3D scanning, computer-aid design (CAD), and 3D printing to make a protective device that frees the wound from exposure to water or infection sources. The presenting techniques successfully extricate a wild freshwater turtle from an extensive shell defect within a short period. Integration of multiple sciences to 3D technology can provide a facile model for veterinary medical applications.

This article presents, for the first time, the efficacy and curing depth analysis of photo-thermal dual polymerization in metal (Fe) polymer composites for 3D printing of a 3-component (A/B/M) system based on the proposed mechanism of our group, in which the co initiators A and B are Irgacure-369, and charge-transfer complexes (CTC), respectively; and the monomer M is filled by Fe. Our formulas show the depth of curing (Zc) is an increasing function of the light intensity, but a decreasing function of the Fe and photoinitiator concentrations. Zc is enhanced by the additive [B] which produces extra thermal radical for polymerization under high temperature. The heat (or temperature) increase in the system has two components : (i) due to the light absorption of Fe filler, and (ii) heat released from the exothermic photopolymerization of the monomer. The heat is transported to the additive (or co-initiator) [B] to produce extra radical R' and enhance the monomer conversion function (CF). The Fe filler leads to temperature increase, but also limits the light penetration leading to lower CF and Zc, which could be overcome by the additive initiator [B] in thick polymers. Optimal Fe for maximal CF and Zc are explored theoretically.

Abstract: The calibrator is one of the most important factors in the calibration of various laser 3D scanning instruments. The requirements for diffuse reflection surface are specially emphasized in many national standards. In this study, the spherical calibrator and plane calibrator compara-tive measurement experiments were carried out. The black ceramic standard sphere, white ce-ramic standard sphere, metal standard sphere, metal standard plane and white ceramic standard plane were used to test the laser 3D scanner. In the spherical calibrators comparative measure-ment experiments, the results indicated that the RMS of the white ceramic spherical calibrator with reflectance about 60% is 10 times that of the metal spherical calibrator with the reflectance of about 15%, and the RMS of the black ceramic spherical calibrator with reflectance of about 11% is of the same order as the metal spherical calibrator. In the plane calibrators comparative measurement experiments, the RMS of flatness measurement is 0.077 mm for metal plane cali-brator with reflectance of 15%, and 2.915 mm for ceramic plane calibrator with reflectance of 60%. The results show that when the optimal measurement distance and incident angle are selected, the reflectance of the calibrator has a great effect on the measurement results, regardless of the outlines or profiles. Based on the experiments, it is recommended to use the spherical calibrator or the standard plane with reflectance of around 18% as the standard, which can obtain the rea-sonable results. In addition, it is necessary to clearly provide the material category and surface reflectance information of the standard when calibrating the scanner according to the measure-ment standard.

Based on the historical research on the shape of armor in Ming Dynasty, this paper explores the shape characteristics of general armor in Ming Dynasty in China through field research on the general stone statue of Ming Xiaoling Mausoleum in Nanjing. Through Ming Xiaoling Mausoleum general stone carving 3D animation technology restoration project, virtual material heritage practice is carried out. Through the modeling of the general stone statue in Ming Xiaoling Mausoleum by MAYA and Zbrush, UE4 realizes the construction of scenes and the output of interactive effects, so as to explore a mode of application engine animation that can preserve and propagate general stone carving in Ming Xiaoling Mausoleum.

Electric energy has become essential nowadays not only for the daily life of each of us but also for the economy of different countries. The dissemination of geographic information plays an important role in national development as it facilitates communication between managers, investors, and consumers in this sector. Since the management of electricity network data was previously done in Tunisia based on paper maps and plans, the purpose of this article is to present a case of planning based on GIS, Web, and 3D Web GIS, which would have significant positive consequences on this sector from a technical and financial sides with an improvement in customer satisfaction and the creation of an intelligent electricity network which will be a real decision-making tool. This work draws up an inventory of the network MV (Medium Voltage)/LV (Low Voltage) of the region of Medjez El Bab which routes electricity to the big centers of consumption with access to MV/LV subscribers. The analysis of the network's impedance allowed carrying out different scenarios to optimize performance and obtain more realistic routes. Many thematic maps were produced as part of this project (Slope map, Land use map, map of the MV voltage domains, map of the MV/LV transformer stations power, etc.). A three-dimensional virtual city has been developed to visualize the graphical and attribute data for the study area. A Web and 3D Web GIS applications that allows the publication of the interactive maps on the Web as well as the database information have been developed to offer users the possibility of consulting the produced products by internet. Finally, a website related to the study was developed.

Additive manufacturing (AM) are used in several industries such as automotive, aerospace, and medical sciences. One of the most common devices used in additive manufacturing is fused deposition modeling (FDM) 3D printers. This fabrication method has different inputs that affect the quality of the parts. In this research, the bending fatigue properties of polylactic acid (PLA) biomaterial made with a 3D printer are investigated. To demonstrate the influence of printing parameters on fatigue lifetime, standard specimens with nozzle diameters of 0.2-0.6 mm, extruder temperature of 180-240°C, and print speed of 5-15 mm/s were printed. After performing fully-reversed bending fatigue tests, it was found that printed specimens at 180°C have the best fatigue lifetime in most cases. Accordingly, fatigue behavior improved by reducing the nozzle diameter. Printing at lower temperatures also improved fatigue lifetime. The printing speed affected the slope of the S-N diagram, known as the fatigue strength exponent.

Bone tissue engineering has been developed in the past decades, with the engineering of bone substitutes on the vanguard of this regenerative approach. PCL based scaffolds are fairly applied for bone regeneration, and several composites have been incorporated, as to improve the devices’ mechanical properties and tissue ingrowth. In this study, HA was incorporated on PCL based scaffolds with two different proportions, 80:20 and 60:40. Devices were produced with two different techniques, SC and MB, and further investigated with regards to their mechanical characteristics and in vitro cytocompatibility. Results show the MB devices to present more promising mechanical properties, along with the incorporation of HA. The latter is also related to an increase in osteogenic activity and promotion. Overall, this study suggest PCL:HA scaffolds to be promising candidates for bone tissue engineering, particularly when produced by the MB method.

3D facial surface imaging is a useful tool in dentistry and in terms of diagnostics and treatment planning. Between-groups PCA (bgPCA) is a method that has been used to analyse shapes in biological morphometrics, although various “pathologies” of bgPCA have recently been proposed. Monte Carlo (MC) simulated datasets were created here in order to explore “pathologies” of multilevel PCA (mPCA), where mPCA with two levels is equivalent to bgPCA. The first set of MC experiments involved 300 uncorrelated normally distributed variables, whereas the second set of MC experiments used correlated multivariate MC data describing 3D facial shape. We confirmed previous results of other researchers that indicated that bgPCA (and so also mPCA) can give a false impression of strong differences in component scores between groups when there is none in reality. These spurious differences in component scores via mPCA reduced strongly as the sample sizes per group were increased. Eigenvalues via mPCA were also found to be strongly effected by imbalances in sample sizes per group, although this problem was removed by using weighted forms of covariance matrices suggested by the maximum likelihood solution of the two-level model. However, this did not solve problems of spurious differences between groups in these simulations, which was driven by very small sample sizes in one group here. As a “rule of thumb” only, all of our experiments indicate that reasonable results are obtained when sample sizes per group in all groups are at least equal to the number of variables. Interestingly, the sum of all eigenvalues over both levels via mPCA scaled approximately linearly with the inverse of the sample size per group in all experiments. Finally, between-group variation was added explicitly to the MC data generation model in two experiments considered here. Results for the sum of all eigenvalues via mPCA predicted the asymptotic amount for the total amount of variance correctly in this case, whereas standard “single-level” PCA underestimated this quantity.

This paper is part of a study of earthen mixtures for 3D printing of buildings. To meet the ever-growing environmental needs, the focus of the paper is on a particular type of biocomposite for the stabilization of earthen mixtures—the rice husk-lime biocomposite—and on how to enhance its effect on the long-term mechanical properties of the hardened product. Having assumed that the shredding of the vegetable fiber is precisely one of the possible ways to improve the mechanical properties, we compared the results of uniaxial compression tests performed on cubic specimens made with both shredded and unaltered vegetable fiber, for three curing periods. The results showed that the hardened earthen mixture is not a brittle material in the strict sense, because it exhibits some peculiar behaviors, anomalous for a brittle material. However, being a “designable” material, its properties can be varied with a certain flexibility to get as close as possible to the desired ones. One of the peculiar properties of the hardened earthen mixture deserves further investigation, rather than corrections. This is the vulcanization that occurs (in a completely natural way) in the long term, thanks to the mineralization of the vegetable fiber by carbonation of the lime.

This study provides a contribution to the research field of 3D printed earthen buildings, focusing, for the first time, on the load-bearing capacity of these structures. The study involves the entire production and testing process of the earthen elements, from design, to the preparation of the mixture and the 3D printing, up to the uniaxial compression test on a wall segment. The results indicate that 3D printed earthen elements have a compressive strength of 2.32 MPa, comparable to that of rammed earth structures. The experimental data also made it possible to draw conclusions on the action of the infill, which seems to have the function of stopping the propagation of cracks. This has a positive effect on the overall behavior of 3D printed earthen elements, since it avoids the onset of dilative behavior in the final stages of the load test and maintains ultimate load values higher than 50% of the maximum load.

3D city models integrate heterogeneous urban data from multiple sources in a unified geospatial representation, combining both semantics and geometry. Although in the last decades, they are predominantly used for visualization, today they are used in a large range of tasks related to exploration, analysis, and management across multiple domains. The complexity of urban processes and the diversity of urban environment bring challenges to the implementation of 3D city models. To address such challenges, this paper presents the development process of a 3D city model of a single neighborhood in Sofia city based on CityGML 2.0 standard. The model represents the buildings in LOD1 with a focus on CityGML features of related to the buildings like building part, terrain intersection curve and address. Similar building models of 18 cities provided as open datasets are explored and compared in order to extract good modeling practices. As a result, workflows for generation of 3D building models in LOD1 are elaborated and improvements in the feature modeling are proposed. Two options of building model are examined: modeling of a building as a single solid and modeling of a building with separate building parts. Finally, the possibilities for visualization of the model in popular platforms such as ArcGIS Pro and Cesium Ion are explored.