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.

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.

Desktop fused filament fabrication (FFF) 3D printers have been growing in popularity among hobbyist and professional users as a prototyping and low-volume manufacturing tool. One issue these printers face is the inability to determine when a defect has occurred rendering the print unusable. Several techniques have been proposed to detect such defects but many of these approaches are tailored to one specific fault (e.g., filament runout/jam), use expensive hardware such as laser distance sensors, and/or use machine vision algorithms which are sensitive to ambient conditions, and hence can be unreliable. This paper proposes a versatile, reliable, and low-cost system, named MTouch, to detect millimeter-scale defects that tend to make prints unusable. At the core of MTouch is an actuated contact probe designed using a low-power solenoid, magnet, and hall effect sensor. This sensor is used to check for the presence, or absence, of the printed object at specific locations. The MTouch probe demonstrated 100% reliability, which was significantly higher than the 74% reliability achieved using a commercially available contact probe (the BLTouch). Additionally, an algorithm was developed to automatically detect common print failures such as layer shifting, bed separation, and filament runout using the MTouch probe. The algorithm was implemented on a Raspberry Pi mini-computer via an Octoprint plug-in. In head-to-head testing against a commercially available print defect detection system (The Spaghetti Detective), the MTouch was able to detect faults 44% faster on average while only increasing the print time by 8.49%. In addition, MTouch was able to detect faults The Spaghetti Detective was unable to identify such as layer shifting and filament runout/jam.

In this paper we describe the potentialities of a tool for the visualization of experimental results directly on a three-dimensional model. The case study concerns the visualization of the results of a dynamic finite element analysis (FEA/FEM) applied to the calculation of seismic risk on works belonging to the Italian infrastructural heritage, specifically bridges, viaducts and overpasses. The project is based on finite element analysis performed on an exemplary set of 8 structures located on the Italian territory, performed by means of the open-source software framework OpenSees, according to the guidelines indicated in the Technical Standards for Construction NTC08. The application created for this project is classifiable as a webGIS, since all data are georeferenced and visualized on a map through an application executed through a browser. The graphical interface displays the interested works on the map of the Italian territory and allows to select them by mouse click. Following the selection, a 3D rendering of the model of the work and the surrounding terrain is shown, in which the results of the analysis are represented using color gradients directly on the three-dimensional model. The necessary tools are present for the selection of the type of result and for the animation in real time of the response of the work to the seismic action. The 3D representation is freely navigable by the user thanks to intuitive tools of panning, rotation and zoom through mouse and keyboard. The application takes advantage of HTML5, CSS and Javascript to show graphical features such as Cartesian diagrams of accelerograms used in modal analysis.

Orofacial injuries are common occurrences during contact sports activities; however, there is an absence of data regarding the performance of hybrid occlusal splint mouthguards, especially during compressive loading. To evaluate the total deformation and stress concentration, a skull model was selected and duplicated to receive two different designs of mouthguard devices: one model received a conventional custom-made mouthguard (MG) with 4-mm thickness and the other received a novel hybrid occlusal splint-mouthguard (HMG) with the same thickness. Both models were subdivided into finite elements. The frictionless contacts were used, and a nonlinear analysis was performed simulating the compressive loading in occlusion. The results were presented in von-Mises stress maps (MPa) and Total Deformation (mm). A higher stress concentration in teeth was observed for the model with the conventional MG, while the HMG design displayed a promising mechanical response with lower stress magnitude. The HMG de-sign displayed a higher magnitude of stress on its occlusal portion than the MG design. The hybrid mouthguard (HMG) reduced (1) jaw displacement during chewing and (2) the generated stresses in maxil-lary and mandibular teeth.

Micro-blade design is an important factor in the cutting of single cells and other biological structures. This paper describes the fabrication process of three dimensional (3D) micro-blades for the cutting of single cells in a microfluidic “guillotine” intended for fundamental wound repair and regeneration studies. Our microfluidic guillotine consists of a fixed 3D micro-blade centered in a microchannel to bisect cells flowing through. We show that the Nanoscribe two-photon polymerization direct laser writing system is capable of fabricating complex 3D micro-blade geometries. However, structures made of the Nanoscribe IP-S resin have low adhesion to silicon, and they tend to peel off from the substrate after at most two times of replica molding in poly(dimethylsiloxane) (PDMS). Our work demonstrates that the use of a secondary mold replicates Nanoscribe printed features faithfully for at least 10 iterations. Finally, we show that complex micro-blade features can generate different degrees of cell wounding and cell survival rates compared with simple blades possessing a vertical cutting edge fabricated with conventional 2.5D photolithography. Our work lays the foundation for future applications in single cell analyses, wound repair and regeneration studies, as well as investigations of the physics of cutting and the interaction between the micro-blade and biological structures.

Recent years witnessed progressive broadening of the practical use of 3D-printed aluminium alloy parts, in particular for specific aerospace applications where weight saving is of great importance. Selective laser melting (SLM) is an intrinsically multi-parametric fabrication technology that offers multiple means of controlling mechanical properties (elastic moduli, yield strength, ductility) through the control over grains size, shape, and orientation. Ultimately, this approach implies that structural elements can be purposefully fabricated to reinforce specific zones and directions where higher mechanical loads are anticipated by design. Targeted control over mechanical properties is achieved through the tuning of 3D-printing parameters and may even obviate the need of heat treatment or mechanical post-processing. Systematic studies of grain structure for different printing orientation with the help of EBSD techniques in combination with mechanical testing at different dimensional levels are the necessary first steps to implement this agenda. Samples of 3D-printable Al-Mg-Si RS-333 alloy were fabricated in 3 orientations with respect to the principal build direction and the fast laser beam scanning direction. Sample structure and proper-ties were investigated using a number of techniques, including EBSD, in situ SEM tensile testing, roughness measurements and nanoindentation. The as-printed samples we found to display strong variation in Young’s modulus values from nanoindentation (from 43 to 66 GPa) and tensile tests (from 54 to 75 GPa), yield stress and ultimate tensile strength (100…195 and 130…220 MPa) in different printing orientations, and almost constant hardness of about 0.8 GPa. A further preliminary study was conducted of the effect of surface finishing on the mechanical performance. Surface polishing appears to reduce Young’s modulus and yield strength, but improves ductility, whereas the influence of sand blasting is more controversial. The experimental results are dis-cussed in connection with the grain morphology and orientation.

The 3D reconstruction method using RGB-D camera has a good balance in hardware cost, point cloud quality and automation. However, due to the limitation of inherent structure and imaging principle, the acquired point cloud has problems such as a lot of noise and difficult registration. This paper proposes a three-dimensional reconstruction method using Azure Kinect to solve these inherent problems. Shoot color map, depth map and near-infrared image of the target from six perspectives by Azure Kinect sensor. Multiply the 8-bit infrared image binarization with the general RGB-D image alignment result provided by Microsoft to remove ghost images and most of the background noise. In order to filter the floating point and outlier noise of the point cloud, a neighborhood maximum filtering method is proposed to filter out the abrupt points in the depth map. The floating points in the point cloud are removed before generating the point cloud, and then using the through filter filters out outlier noise. Aiming at the shortcomings of the classic ICP algorithm, an improved method is proposed. By continuously reducing the size of the down-sampling grid and the distance threshold between the corresponding points, the point clouds of each view are continuously registered three times, until get the complete color point cloud. A large number of experimental results on rape plants show that the point cloud accuracy obtained by this method is 0.739mm, a complete scan time is 338.4 seconds, and the color reduction is high. Compared with a laser scanner, the proposed method has considerable reconstruction accuracy and a significantly ahead of the reconstruction speed, but the hardware cost is much lower and it is easy to automate the scanning system. This research shows a low-cost, high-precision 3D reconstruction technology, which has the potential to be widely used for non-destructive measurement of crop phenotype.

Solar3D is an open-source software application designed to interactively calculate solar irradiation at three-dimensional (3D) surfaces in a virtual environment constructed with combinations of 3D city models, digital elevation models (DEMs), digital surface models (DSMs) and feature layers. The GRASS GIS r.sun solar radiation model computes solar irradiation based on two-dimensional (2D) raster maps for given day, latitude, surface and atmospheric conditions. With the increasing availability of 3D city models and demand for solar energy, there is an urgent need for better tools to computes solar radiation directly with 3D city models. Solar3D extends GRASS GIS r.sun from 2D to 3D by feeding the model with input, including surface slope, aspect and time-resolved shading, that is derived directly from the 3D scene using computer graphics techniques. To summarize, Solar3D offers several new features which, as a whole, distinguish itself from existing 3D solar irradiation tools: (1) the ability to consume massive heterogeneous 3D city models, including massive 3D city models such as oblique airborne photogrammetry-based 3D city models (OAP3Ds or integrated meshes); (2) the ability to perform near real-time pointwise calculation for duration from daily to annual; (3) the ability to integrate and interactively explore large-scale heterogeneous geospatial data. (4) the ability to calculate solar irradiation at arbitrary surface positions including at rooftops, facades and the ground. Solar3D is publicly available at https://github.com/jian9695/Solar3D.

The aim of this study is to provide a detailed strategy for Safe-by-Design (SbD) 3D printed lab-on-a-chip (LOC) device manufacturing, using Fused Filament Fabrication (FFF) technology. At first, the applicability of FFF in lab-on-a-chip device development is briefly discussed. Subsequently, a methodology to categorize, identify and implement SbD measures for FFF is suggested. Furthermore, the most crucial health risks involved in FFF processes are examined, placing the focus on the examination of ultrafine particle (UFP) and Volatile Organic Compound (VOC) emission hazards. Thus, a SbD scheme for lab-on-a-chip manufacturing is provided, while also taking into account process optimization for obtaining satisfactory printed LOC quality. This work can serve as a guideline for the effective application of FFF technology for lab-on-a-chip manufacturing through the safest applicable way, towards a continuous effort to support sustainable development of lab-on-a-chip devices through cost-effective means.

The liquid-vapor phase change lattice Boltzmann method is used to investigate the pinning-depinning mechanism of the contact line during droplet evaporation on the stripe-patterned surfaces in 3D space. Considering the curvature of the contact line and the direction of the unbalanced Young’s force, the local force balance theory near the stripe boundary is proposed to explain the steady state of the droplets on the stripe-patterned surfaces. An equation is proposed to evaluate the characteristic contact angle of the stabilized droplets. During the evaporation of the droplet, the stick-slip-jump behavior and the CCR-Mixed-CCA mode can be well captured by the lattice Boltzmann simulation. When the contact line is pinned to the stripe boundary, the contact line in the direction perpendicular to the stripes is slowly moving while the curvature of the contact line is gradually increasing. The gradually increasing curvature of the contact line accelerates the movement of the contact line, and the final contact line is detached from the stripe boundary. The research results provide theoretical support and guidance for the design, improvement and application of patterned surfaces in the field of micro-fluidic and evaporation heat transfer.

Non-destructive testing of metallic objects that may contain embedded defects of different sizes is an important application in many industrial branches for quality control. Most of these techniques allow defect detection and its approximate localization, but very few give enough information for its 3D reconstruction. Here we present a hybrid laser – transducer system that combines remote laser-generated ultrasound excitation and non-contact ultrasonic transducer detection. This fully non-contact method gives access to separating scan areas on different object’s faces and defect details from different angles/perspectives can be analysed. This hybrid system can analyse the whole object’s volume data and allow a 3D reconstruction image of the embedded defects. As a novelty for the signal processing improvement, we use a 2D apodization window filtering technique, applied along with the synthetic aperture focusing algorithm in order to remove the undesired effects of side lobes and wide-angle reflections of propagating ultrasound waves, thus, enhancing the resulting 3D image of the defect. We provide both qualitative and quantitative volumetric results with high accuracy and resolution compared with conventional techniques.

Public participation is significant for the success of any urban planning project. However, most members of the general public are not planning professionals and may not understand the technical details of a 2D paper-based plan, which might hamper their participation. One way to expand the participation of citizens is to present plans in well-designed, user-friendly and interactive platforms that allow participation regardless of the technical skills of the participants. This paper investigates the impacts of the combined use of 3D visualization and E-participation on public participation in Kisumu, Kenya. A 3D City model, created with CityEngine2016, was exported into a web-based geo-portal and used as a Planning Support System in two stakeholder workshops in order to evaluate its usability. For e-participation, 300 questionnaires given out to planning practitioners. Five indicators were developed for evaluating the usability of the 3D model while the usability of e-participation was evaluated using communication, collaboration and learning as indicators. Results showed that effectiveness and efficiency varies within different professional groups while the questionnaires showed strong preference for e-participation methods, especially SMSs/USSDs and emails. The study concludes that the use of 3D visualization and E-participation has the potential for improving the quality and quantity of public participation and recommends further research on the subject.

Buildability, i.e. the ability of a deposited material bulk to retain its dimmensions under increasing load, is an inherent prerequisite for formwork-free digital construction (DC). Since DC processes are relatively new, no standard methods of characterization are available yet. The paper at hand presents practice-oriented buildabilty criteria by taking various process parameters and construction costs into consideration. In doing so, direct links between laboratory buildability tests and target applications are established. A systematic basis for calculating the time interval (TI) to be followed during laboratory testing is proposed for the full-width printing (FWP) and filament printing (FP) processes. The proposed approach is validated by applying it to a high-strength, printable, fine-grained concrete. Comparative analyses of FWP and FP revealed that to test the buildability of a material for FP processes, higher velocities of the printhead should be established for laboratory tests in comparison to those needed for FWP process, providing for equal construction rates.

Introduction: Due to the great development of digital technology, through CAD (Computer - Aided Design) and CAM (Computer - Aided Manufacturing) systems, digital models could be used in orthodontic treatment planning decision-making, as there are numerous studies in the literature that support the validity of measurements of digital models of anterior teeth and the total coefficient of Bolton analysis. The aim of the study was to compare the average length value of the current upper and lower arches with that of a hypothetical nickel-titanium wire and the accuracy of the Bolton index measurement. In the present study, 138 dental casts were analyzed using Ortho3Shape software. Using the Ortho3Shape software, it was possible to measure the real and ideal lower arch lengths and, with regard to Bolton analysis, the values of the anterior and total Bolton coefficients. By comparing the values obtained with those of the study by A. Anand Kumar et al. using CBCT and plaster casts, the reliability of the measurements obtained with such CAD/CAM orthodontic software was evaluated. Considering the validity of digital measurements demonstrated by the studies and systematic reviews in the literature, it can be stated that CAD/CAM digital models can be a viable alternative to plaster models in the coming years, as they can facilitate model preservation and retrieval. For future studies and research, it would be preferable to use intra-oral scanners (IOS) in order to ensure greater accuracy, requiring only one step and ensuring a better outcome for the patient.

Aqueous Zinc ion batteries (ZIBs) possess significant potential in large energy storage systems due to their cost-effectiveness and environmental protection. However, the limited voltage window and poor reaction kinetics of the cathode material are still bottlenecks, restricting the further development of ZIBs. In this work, we rationally design Ni-doped V2O5@3D Ni core/shell composite on carbon cloth electrode (Ni-V2O5@3D Ni@CC) by growing Ni-V2O5 on the free-standing 3D Ni metal nanonets for high-voltage and high-capacity ZIBs. Impressively, the embedded Ni doping increases the interlayer spacing of V2O5, extending the working voltage and improving the Zn2+ kinetics reaction of the cathode materials, at the same time the 3D structure with high specific surface area and superior electronic conductivity benefits to fast Zn2+ transport. Consequently, the as-designed Ni-V2O5@3D Ni@CC cathodes can operate within a wide voltage window from 0.3 to 1.8 V vs. Zn/Zn2+ and deliver a high capacity of 270 mAh g-1 at a high current density of 0.8 A g-1. In addition, the reversible Zn2+ (de)-incorporation reaction mechanisms in the Ni-V2O5@3D Ni@CC cathodes are investigated by multiple characterization methods. As a result, we achieve a big step toward the practical applications of commercial ZIBs.

The decreasing width, increasing aspect ratio RDL presents significant challenges to design for reliability (DFR) of advanced package. Therefore, this paper proposes a ML based RDL modeling and simulation method. In the method, RDL is divided into blocks and subdivided into pixels of metal percentage, and the RDL is digitalized as tensors. Then, an ANN-based surrogate model is built and trained by a subset of tensors to predict the equivalent material properties of each block. Lastly, all blocks are transformed into elements for simulations. For validation, line bending simulations were conducted on an RDL, with the reaction force as accuracy indicator. The results show that neglecting layout impact causes critical errors as substrate thins. By the method, the reaction force error is 2.81% and the layout impact can accurately be considered with 200×200 elements. For application, the TCT maximum temperature state simulation was conducted on a CPU chip. The simulation indicates that for advanced package the maximum stress more likely occurs in RDL rather than bumps, both RDL and bumps are critical impacted by layouts, and RDL stress is also impacted by vias/bumps. The proposed method precisely concerns layout impacts with little resources, presents an opportunity of efficiency improvement.

The initial stability after implantology is paramount to the survival of the dental implant and the surface roughness of the implant plays a vital role in this regard. The characterisation of surface topography is a complicated branch of metrology, with a huge range of parameters available. Each parameter contributes significantly towards the survival and mechanical properties of 3D-printed specimens. The purpose of this paper is to experimentally investigate the effect of surface roughness of 3D-printed dental implants and 3D-printed dogbone tensile samples under areal height (Ra) parameters, amplitude parameters (average of ordinates), skewness (Rsk) parameters and mechanical properties. During the experiment, roughness values were analysed and the results showed that the skewness parameter demonstrated a minimum value of 0.596%. The 3D-printed dental implant recorded Ra with a 3.4 mm diameter at 43.23% and the 3D-printed dental implant with a 4.3 mm diameter at 26.18%. Samples with a complex geometry exhibited a higher roughness surface, which was the greatest difficulty of additive manufacturing when evaluating surface finish. The results show that when the ultimate tensile stress (UTS) decreases from 968.35 MPa to 955.25 MPa, Ra increases by 1.4% and when UTS increases to 961.18 MPa, Ra increases by 0.6%. When the cycle decreases from 262142 to 137433, Ra shows that less than a 90.74% increase in cycle is obtained. For 3D-printed dental implants, the higher the surface roughness, the lower the mechanical properties, ultimately leading to decreased implant life and poor performance.

Paclitaxel is a natural, highly lipophilic anti proliferative drug widely used in medicine. We have studied the release of tritium-labeled paclitaxel (³H-PTX) from matrices destined for the coating of vascular stents and produced by the electrospinning method from the solutions of polycaprolactone (PCL) with paclitaxel (PTX) in hexafluoisoropropanol (HFIP) and/or solutions of PCL with PTX and human serum albumin (HSA) in HFIP or HIFP-dimethyl sulphoxide (DMSO) blend. The release of PTX has been shown to depend on the solvent and the composition of electrospinning solution, as well as the composition of the surrounding medium, particularly the concentration of free PTX and PTX-binding biomolecules present in human serum. It was shown that 3D matrices can completely release PTX without weight loss. Two-phase PTX release from optimized 3D matrices was obtained: ~27% of PTX was released in the first day, another 8% were released over the next 26 days. Wherein ~2.8%, ~2.3%, and ~0.25% of PTX was released on day 3, 9, and 27, respectively. Considering PTX toxicity, the rate of its diffusion through the arterial wall, and the data obtained the minimum cytostatic dose of the drug in the arterial wall will be maintained for at least three months.

Mycotoxins are secondary metabolites produced by filamentous fungi associated to a variety of acute and chronic foodborne diseases. Current toxicology studies mainly rely on monolayer cell cultures and animal models, which are undeniably affected by several limitations. To bridge the gap between the current in vitro toxicology approach and the in vivo predictivity of the data, we here investigated the cytotoxic effects induced by the mycotoxins sterigmatocystin (STE), ochratoxin A (OTA) and patulin (PAT) on different 2D and 3D cell cultures. We focused on human tumours (neuroblastoma SH-SY5Y cells, and epithelial breast cancer MDA-MB-213 cells) and healthy cells (bone marrow derived mesenchymal stem cells, BM-MSC, and umbilical vein endothelial cells, HUVECs). Cytotoxicity of STE, OTA, and PAT was determined after 24, 48 and 72 h of exposure by ATP assay in both culture models. 3D spheroids morphology was also analysed using the MATLAB-based open-source software AnaSP. Our results highlighted how each cell line and different culture models showed specific sensitivities, reinforcing the importance of using more complex models for toxicology studies and a multiple cell line approach for an improved and more comprehensive risk assessment.

The article reports on a patient who required a cranial protection system.Using additive manufacturing techniques and surgical planning with the help of bio-models, a patient-specific bone implant solution was proposed that allows aesthetic restoration of the affected area and provides an adequate level of protection. In addition, through a comparative analysis with finite elements, the mechanical response to external actions of the medical device, printed with two materials: polymethylmethacrylate (PMMA) and polyether-ether-ketone (PEEK), is simulated. The tested materials have recognized biocompatibility properties, but their costs on the market differ significantly. The results obtained demonstrate the similarities in the responses of both materials. It offers the possibility that low-income people can access these devices, guaranteeing adequate biomechanical safety, considering that PMMA is a much cheaper material than PEEK.

The shaft hydropower plant (SHPP) is a novel hydraulic concept for low-head hydropower sites with several environmental and operational advantages over conventional layouts. However, the first two projects implementing this concept have shown comparatively high construction costs and project risks. Therefore, further optimization is required to the economic attractiveness and enabling broader market adoption. Initial model tests recommend a square-shaped shaft inlet with a three-sided approach flow for low-loss and fish-friendly inflow conditions. Yet, this design requires significant space for structural implementation and may be unsuitable for use with multiple shafts or as an extension of non-powered dams and weirs. This research paper presents the application of a computational fluid dynamics simulation setup to evaluate the hydraulic per-formance of various design configurations, especially, alternative design layouts with one-sided approach flow without further physical model tests,. The simulation setup is calibrated against observations including head loss and velocity measurements from the physical model tests, and its satisfactory performance enables the analysis of alternative design layouts. This aims to derive the most significant design parameters for achieving the desired hydraulic conditions at the intake. Increasing the flow depth before the intake and enlarging the inlet area have the most significant impact, while increasing the overflow of the front gate has the least significant effect.. The chosen CFD application is deemed suitable for hydraulic design optimization and provides guidance on the key parameters to focus on for tailored site-specific design development.

This study presents a novel semi-supervised deep learning method utilizing 3D TOF-MRA images for the detection of brain aneurysms, employing landmark-based techniques that mimic radiologist practices to enhance detection accuracy and efficiency.

Mapping building roof plane structures is an active research direction in urban-related studies, as understanding roof structure provides essential information for generating highly detailed 3D building models. Traditional deep learning models have been the main focus of most recent research endeavours aiming to extract pixel-based building roof plane areas from remote sensing imagery. However, significant challenges arise, such as delineating complex roof boundaries and invisible boundaries. Additionally, challenges during the post-processing phase, where pix-el-based building roof plane maps are vectorized, often result in polygons with irregular shapes. In order to address this issue, this study explores a state-of-the-art method for planar graph reconstruction applied to building roof plane extraction. We propose a framework for reconstructing regularized building roof plane structures using aerial imagery and cadastral information. Our framework employs a holistic edge classification architecture based on an attention-based neural network to detect corners and edges between them from aerial imagery. Our experiments focused on three distinct study areas characterized by different roof structure topologies: Stadsveld – 't Zwering neighbourhood and Oude Markt area, located in Enschede, The Netherlands, and the Lozenets district in Sofia, Bulgaria. The outcomes of our experiments revealed that a model trained with a combined dataset of two different study areas demonstrated superior performance, capable of delineating edges obscured by shadows or canopy. Our experiment in the Oude Markt area resulted in building roof plane delineation with an F-score value of 0.43 when the model trained on the combined dataset was used. In comparison, the model trained only on the Stadsveld – 't Zwering dataset achieved an F-score value of 0.37, and the model trained only on the Lozenets dataset achieved an F-score value of 0.32. The results from the developed approach are promising and can be used for 3D city modelling in different urban settings.

This paper presents a numerical study on the laser shock wave propagation in a 3D woven CFRP material by means of detailed and homogenized FE models. The aim of the study is to numerically characterize the shock wave response of the 3D woven CFRP in terms of back face velocity profiles and the induced damage and to investigate whether the detailed FE models could be replaced by homogenized FE models. The 3D woven geometry was designed using the TexGen software, while the numerical analyses were executed using the LS-Dyna explicit FE software. A high-strain rate behavior was considered for the matrix. The fiber bundles in the detailed models were modeled as a high fiber content unidirectional composite laminate, with its mechanical properties calculated by micromechanical equations. Both for the fiber bundles of the detailed model and the homogenized models a progressive damage material model was applied. The results of the detailed model reveal a considerable effect of material’s architecture on the shock wave propagation and the sensitivity of the back face velocity profile to the spot location. Consequently, the homogenized model is not capable of accurately simulating the shock wave response of the 3D woven composite. Moreover, the detailed predicts with high accuracy matrix cracking in the resin-rich areas and in the bundles as well as fiber failure. On the contrary, the homogenized model predicts matrix cracking at the same areas and no fiber failure.

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.

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 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.

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.

Seismic travel time tomography using surface waves is an effective tool for three-dimensional crustal imaging. Historically, these surface waves are the result of active seismic sources or earthquakes. More recently, however, also surface waves retrieved through the application of seismic interferometry are exploited. Conventionally, two-step inversion algorithms are employed to solve the tomographic inverse problem. That is, a first inversion results in frequency-dependent, two-dimensional maps of phase velocity, which then serve as input for a series of independent, one-dimensional frequency-to-depth inversions. As such, a two-dimensional grid of localized depth-dependent velocity profiles are obtained. Stitching these separate profiles together subsequently yields a three-dimensional velocity model. Relatively recently, a one-step three-dimensional non-linear tomographic algorithm has been proposed. The algorithm is rooted in a Bayesian framework using Markov chains with reversible jumps, and is referred to as transdimensional tomography. Specifically, the three-dimensional velocity field is parameterized by means of a polyhedral Voronoi tessellation. In this study, we investigate the potential of this algorithm for the purpose of recovering the three-dimensional surface-wave-velocity structure from ambient noise recorded on and around the Reykjanes Peninsula, southwest Iceland. To that end, we design a number of synthetic tests that take into account the station configuration of the Reykjanes seismic network. We find that the algorithm is able to recover the 3D velocity structure at various scales in areas where station density is high. In addition, we find that the standard deviation on the recovered velocities is low in those regions. At the same time, the velocity structure is less well recovered in parts of the peninsula sampled by fewer stations. This implies that the algorithm successfully adapts model resolution to the density of rays. Also, it adapts model resolution to the amount of noise on the travel times. Because the algorithm is computationally demanding, we modify the algorithm such that computational costs are reduced while sufficiently preserving non-linearity. We conclude that the algorithm can now be applied adequately to travel times extracted from (time-averaged) station-station cross correlations by the Reykjanes seismic network.

As the first time, 0D-1D-3D and fully 3D steady-state aero-thermo-fluid simulations of a structural oil-to-air Fan Outlet Guide Vane Cooler (FOGVC) in a jet engine are presented. Using the commercial softwares Ansys Fluent, the thermo-mechanical module of Ansys and the 1D fluid solver Flownex, 5 simulation types (3D fully conjugate heat transfer with and without a thin wall model, 3D with a thin wall model, 1D-3D coupled, 1D and 0D) corresponding to 4 levels of simplification in 3 possible domains (oil, oil-metal and oil-metal-air) have been compared to provide selection criteria when a determined level of accuracy in the simulations without prohibited computational times is desired. The methodologies are applied to two different oil internal cavities: an inverted U with rectangular cross section and a coil internal cavity with a circular cross section. The obtained results show that depending on the scope of the research (outlet oil temperature, dissipated heat rate or oil pressure drop) and the accuracy of the results, one method or the other may be used. Experimental data would be needed to validate the numerical results by all employed methodologies and geometries.

Tuning fork gyroscopes (TFGs) are promising for potential high-precision applications. This work proposes and experimentally demonstrates a novel high-Q dual mass tuning fork microelectro-mechanical system (MEMS) gyroscope utilizing three-dimensional (3D) packaging techniques. Except for two symmetrically-decoupled proof masses (PM) with synchronization structures, a symmetrically-decoupled lever structure is designed to force the antiparallel, antiphase drive-mode motion and basically eliminate the low-frequency spurious modes. The thermoelastic damping (TED) and anchor loss are greatly reduced by the linearly-coupled, momentum- and torque-balanced antiphase sense mode. Besides, a novel 3D packaging technique is used to realize high Q-factors. A composite substrate encapsulation cap, fabricated by through-silicon-via (TSV) and glass-in-silicon (GIS) reflow processes, is anodically bonded to the sensing structures at wafer scales. A self-developed control circuit is adopted to realize loop control and characterize gyro-scope performances. It is shown that a high-reliability electrical connection together with a high-air-impermeability package can be fulfilled with this 3D packaging technique. Furthermore, the Q-factors of the drive and sense modes reach up to 51947 and 49249, respectively. This TFG realizes a wide measurement range of ±1800° /s and a high resolution of 0.1° /s with a scale-factor nonlinearity 720 ppm after automatic mode-matching. Besides, the long-term zero-rate output (ZRO) drift can be effectively suppressed by temperature compensation, inducing a small angle random walk (ARW) of 0.923°/√h and a low bias instability (BI) of 9.270°/h.

Cardiovascular-related diseases are one of the leading causes of death worldwide. An understanding of heart movement based on images plays a vital role in assisting the procedure in the postoperative and postoperative processes. In particular, if the shape information can be provided in real-time using the electrocardiogram(ECG) signal using this information, the heart’s movement information can be used for cardiovascular analysis and imaging guides during surgery. In this paper, we propose creating a 3D+t cardiac coronary artery model that is rendered in real-time according to the ECG signal. Hierarchical cage-based deformation modeling is used to generate mesh deformation used during the procedure according to the ECG signal. We match the blood vessel’s lumen obtained from the ECG-gated 3D+t CT angiography taken at the multiple cardiac phases to derive the optimal deformation. Splines for 3D deformation control points were used to continuously represent the obtained deformation at the multi-view according to the ECG signal. To verify the proposed method, we compared the manually segmented lumen and results of the proposed method for eight patients. The average distance and dice coefficient between the two models was 0.543mm and 0.735, respectively. The required time for registration of the 3D coronary artery model is 23.53 seconds/model. rendering speed to derive the model according to the ECG signal after generating the 3D+t model is faster than 120 FPS.

Computation of Common Middle Point seismic sections and their subsequent time migration and diffraction imaging provides very important knowledge about the internal structure of 3D heterogeneous geological media and are key elements for successive geological interpretation. Full-scale numerical simulation, that computes all single shot seismograms, provides a full understanding of how the features of the image reflect the properties of the subsurface prototype. Unfortunately, this kind of simulations of 3D seismic surveys for realistic geological media needs huge computer resources, especially for simulation of seismic waves’ propagation through multiscale media like cavernous fractured reservoirs. In order to significantly reduce the query of computer resources we propose to model these 3D seismic cubes directly rather than the shot-by-shot simulation with subsequent CMP stacking. To do that we modify the well known "exploding reflectors principle" for 3D heterogeneous multiscale media by use of the finite-difference technique on the base of grids locally refined in time and space. To be able to simulate realistic models and acquisition we develop scalable parallel software, which needs reasonable computational costs. Numerical results for simulation of Common Middle Points sections and their time migration are presented and discussed.

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.

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.

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.

Emerging pollutants as pharmaceuticals have been focusing international attention for few decades. Ciprofloxacin (CIP) is a common drug widely found in effluents from hospitals, industrial and different wastewater treatment plants, as well as rivers. In this work, the lab-scale 3D-BER system was established, and more than 90% of the antibiotic CIP removal from the Low C/N wastewater. Best results were obtained with current intensity, and different C/N ratio significantly improve the removal of CIP and nitrates, when the ideal conditions were; C/N = 1.5-3.5, pH =7.0-7.5, and I = 60 mA. The highest removal efficiency of CIP = 94.20 %, NO3--N= 95.53 % and total nitrogen (TN) = 84.27 %, respectively. In this novel system, the autotrophic-heterotrophic denitrifying bacteria played vital role for the removal of CIP and enhanced denitrification process. Thus, autotrophic denitrifying bacteria uses CO2 and H2 as carbon sources to reduce nitrates to N2. This system has the assortment and prosperous community revealed at the current intensity of 60 mA, and the analysis of bacterial community structure in effluent samples fluctuates under different condition of C/N ratios. According to the results of LC-MS/MS analysis, the intermediate products were proposed after efficient biodegradation of CIP. Microbial community on biodegrading was mostly found at phylum, and class level was dominantly responsible for the NO3--N and biodegradation of CIP. This work can provide some new insights towards the biodegradation of CIP and the efficient removal of nitrates from low C/N wastewater treatment by the novel 3D-BER system.

The active debate about the processes governing the organic-rich sediment deposition generally involves the relative roles of elevated primary productivity and enhanced preservation related to anoxia. However, other less spotlighted factors could have a strong impact on such deposits: e.g. residence time into the water column (bathymetry), sedimentation rate, transport behavior of organo-mineral floccules on the sea floor. They are all strongly interrelated and may be obscured in the current conceptual models inspired from most representative modern analogues (i.e. upwelling zones and stratified basins). To improve our comprehension of organic matter distribution and heterogeneities, we conducted a sensitivity analysis on the processes involved in organic matter production and preservation which have been simulated within a 3D stratigraphic forward model. The Lower-Middle Toarcian of the Paris Basin was chosen as a case study as it represents one of the best documented example of marine organic matter accumulation. The relative influence of the critical parameters (bathymetry, diffusive transport, oxygen mixing rate and primary production) on the output parameters (Total Organic Carbon, and oxygen level), determined performing a Global Sensitivity Analysis, shows that, in the context of a shallow epicontinental basin, a moderate primary productivity (> 175 gC.m^-².yr^-1) can led to local anoxia and organic matter accumulation. We argue that, regarding all the processes involved, the presence and distribution of organic-rich intervals is linked as a first-order parameter to the morphology of the basin (e.g. ramp slope, bottom topography). These interpretations are supported by very specific ranges of critical parameters which allowed to obtain output parameter values in accordance with the data. This quantitative approach and its conclusions open new perspectives about the understanding of global distribution and preservation of organic-rich sediments.

Psoriasis is a chronic immune-mediated skin disease that involves interaction of both immune and skin cells, and is characterized by cytokine-driven epidermal hyperplasia, deviant differentiation, inflammation and angiogenesis. Because available treatments for psoriasis have significant limitations, dietary products are potential natural sources of therapeutic molecules, which can rescind molecular defects associated with psoriasis and could be developed for its management. Fisetin (3,7,3′,4′- tetrahydroxyflavone), a phytochemical naturally found in pigmented fruits and vegetables has demonstrated pro-apoptotic and antioxidant effects in several malignancies. This study utilized biochemical, cellular, pharmacological and tissue-engineering tools to characterize the effects of fisetin on normal human epidermal keratinocytes (NHEKs), peripheral blood mononuclear cells (PBMC) and CD4+ T lymphocytes in 2D and 3D psoriasis-like disease models. Fisetin treatment of NHEKs dose and time-dependently induced differentiation and inhibited interleukin-22-induced proliferation, as well as activation of the PI3K/Akt/mTOR pathway. Fisetin treatment of TNF-α-stimulated NHEKs significantly inhibited the activation of p38 and JNK, but had no effect on ERK1/2. In addition, fisetin treatment significantly decreased the secretion of Th1/Th-17 pro-inflammatory cytokines, particularly IFNγ and IL-17A by 12-O- tetradecanolylphorbol 13-acetate (TPA)-stimulated NHEKs and anti-CD3/CD28-activated human PBMCs. Furthermore, we established the in-vivo relevance of fisetin functions, using a 3D full-thickness human skin model of psoriasis (FTRHSP) that closely mimics in-vivo human psoriatic skin-lesions. Herein, fisetin significantly ameliorated psoriasis-like disease features, and decreased the production of IL-17 by CD4+ T lymphocytes co-cultured with FTRHSP. Collectively, our data identify pro-differentiative, anti-proliferative and anti-inflammatory effects of fisetin, via modulation of PI3K-Akt-mTOR and p38/JNK pathways and the production of cytokines in 2D and 3D human skin model of psoriasis. These results suggest that fisetin has a great potential to be developed as an effective and inexpensive agent for the treatment of psoriasis and other related inflammatory skin disorders.

Ewing sarcoma (ES) is an aggressive bone and soft-tissue pediatric cancer. High vitronectin (VN) expression has been associated with poor prognosis in other cancers, and we aimed to determine the utility of this extracellular matrix glycoprotein as a biomarker of aggressiveness in ES. Silk-fibroin plus gelatin-tyramine hydrogels (HGs) were fabricated with and without cross-linked VN and cultivated with A673 and PDX73 ES cell lines for two and three weeks. VN secretion to culture media was assessed using ELISA. Morphometric analysis was applied for phenotypic characterization. VN release to culture media was higher in 3D-models than in monolayer cultures, and intracellular, intercellular and pericluster presence was also observed. A673-HGs showed lower density of clusters but a proportion of larger clusters than PDX73-HGs, which presented low cluster circularity. The cluster density of A673-HGs without added VN was higher than with added VN, and slightly lower in the case of PDX73-HGs. Furthermore, a culture time of three weeks provided no benefits in cluster growth compared to two weeks, especially in A673 -HGs. These advances in 3D modeling and digital quantification pave the way for future studies in ES and other cancers to deepen understanding about intra- and intercellular heterogeneity and anti-adhesion VN therapies.

Immediate load of full-arch rehabilitations over implants, specially over 4 implants are very well documented in the literature. More recently, the use of computed surgical guides to help the planning and the execution of these treatments, in many situations without the need of raising a flap, and diminishing the appearance of hematomas, bleeding and with less trauma to the patient has gained preference among implantologists. The objective of this case report is to show a clinical case of an immediate load full-arch fixed rehabilitation over 4 implants produced by 3D printing manufacturing technology, and placed with a computed surgical guide, in the same appointment, and the 24 months follow-up. The patient returned after 3 months to replace the immediate temporary fixed prosthesis for a new one, with metallic bar, better teeth and more delicate. Soft and hard tissue around the implants seemed to be stable, without signs of inflammation, either on the 3 or the 24 months follow-up. 3D printing of implants by direct metal laser sintering is a technology that seems to be promising for oral implantology, with solid studies showing reliable results, as seen in this single case. More clinical studies are necessary to testify its efficacy.

We are currently investigating the ultrasound imaging of a sensor consisting of a randomized encoding mask attached to a single lead zirconate titanate (PZT) oscillator for use in a puncture microscope. The proposed model was performed using a finite element method (FEM) simulator. To increase the number of measurements required by a single element system, the transducer was rotated at different angles. The image was constructed by solving a linear equation of the image model. In a previous study, the image resolution was improved by extracting phase information. In this study, we propose a strategy by integrating the weighted frequency subbands compound and a super resolution method (SCM) to improve the resolution in range and lateral resolution. We also evaluated the image performance by applying different methods to improve the image quality. The results show that better image resolution and speckle suppression were obtained by applying the proposed method.

Compound-specific isotope analysis (CSIA) can provide unique insights into the cycling of elements including carbon and nitrogen. One approach for CSIA is the use of high-performance liquid chromatography (HPLC) to separate compounds of interest, followed by analysis of these compounds using an elemental analyzer coupled to an isotope ratio mass spectrometer. A key component of this technique is the fraction collector, which automatically collects compounds as they are separated by HPLC. Here we present a fraction collector which is a simple adaptation of a 3D printer, and thus can be easily adopted by any laboratory already equipped for HPLC. In addition to the much lower cost compared to commercial alternatives, this adaptation has the advantage for CSIA that the 3D-printer is able to heat the collected fractions, which is not true for many commercial fraction collectors. Heating allows faster evaporation of the solvent, so that the dried compounds can be measured by EA-IRMS immediately. The procedure can be repeated consecutively so that dilute solutions can have the compounds concentrated for analysis. Any computer-controlled HPLC can be integrated to the fraction collector used here by means of AutoIt.

Recanalization poses challenge in coil embolization for cerebral aneurysms. Establishing predictive models for post-embolization recanalization is important for clinical decision-making. However, conventional statistical and machine learning (ML) models may overlook critical parameters during the initial selection process. In this study, we automated the identification of significant hemodynamic parameters using a PointNet-based deep neural network (DNN), leveraging their inherent 3D features. Further feature analysis was conducted utilizing saliency mapping, an explainable artificial intelligence (XAI) technique. The study encompassed the analysis of velocity, pressure, and wall shear stress (WSS) in both pre- and post-coiling models derived from computational fluid dynamic (CFD) simulations for 59 aneurysms. Velocity was identified as the most pivotal parameter, supported by the lowest P-value from statistical analysis and the highest area under the curves (AUROC)/precision-recall curves (AUPRC) values from DNN model. Moreover, visual XAI analysis revealed robust injection flow zones with notable impingement points in pre-coiling models, as well as pronounced interplay between flow dynamics and the coiling plane were important 3D features in identifying the recanalized aneurysms. The combination of DNN and XAI was found to be an accurate and explainable approach not only at predicting post-embolization recanalization but also at discovering unknown features in the future.

Background. Currently, most of the research in breast cancer has been carried out in conventional two-dimensional (2D) cell culture due to its practical benefits, however, the three-dimensional (3D) cell culture is becoming the model of choice in cancer research because it allows cell-cell and cell-extracellular matrix (ECM) interactions, mimicking the native microenvironment of tumors in vivo. Methods. in this work, we evaluated the effect of 3D cell organization on the expression pattern of miRNAs (by Small-RNAseq) and mRNAs (by microarrays) in the breast cancer SKBR3 cell line and analyzed the biological processes and signaling pathways regulated by the differ-entially expressed protein-coding genes (DE-mRNAs) and miRNAs (DE-microRNAs) found in the organoids. Results. We obtained well-defined cell-aggregated organoids with a grape cluster-like morphology with a size up to 9.2×105 μm3. The transcriptomic assays showed that cell growth in organoids significantly affected (all p < 0.01) the gene expression patterns of both, miRNAs and mRNAs, finding 20 upregulated and 19 downregulated DE-microRNAs, as well as 49 upregulated and 123 downregulated DE-mRNAs. In silico analysis showed that a subset of 11 upregulated DE-microRNAs target 70 downregulated DE-mRNAs. These genes are involved in 150 gene on-tology (GO) biological processes such as regulation of cell morphogenesis, regulation of cell shape, regulation of canonical Wnt signaling pathway, morphogenesis of epithelium, regulation of cy-toskeleton organization, as well as in the MAPK and AGE-RAGE signaling KEGG-pathways. In-terestingly, hsa-mir-122-5p (Fold Change (FC)=15.4), hsa-mir-369-3p (FC=11.4), and hsa-mir-10b-5p (FC=20.1) regulated up to the 81 % of the 70 downregulated DE-mRNAs. Conclu-sion, the organotypic 3D cell-organization architecture of breast cancer SKBR3 cells impacts the expression pattern of miRNAs-mRNAs network mainly through overexpression of hsa-mir-122-5p, hsa-mir-369-3p, and hsa-mir-10b-5p. All these findings suggest that the interaction between cell-cell and cell-ECM as well as the change in the culture architecture impacts gene ex-pression, and therefore, support the pertinence of migrating breast cancer research from conven-tional cultures to 3D models.

Microwave absorbers with lightweight, good stability and high efficiency have attracted much attention for their applications in many contemporary fields. In this work, the 3D porous (Ni@NO-C)n/NO-C composite absorber was prepared by a wet chemistry method with Ni chains and melamine as precursors, in which NO-C (N,O-doped carbon) encapsulated Ni particles are homogenously dispersed in the 3D porous networks of NO-C in the form of (Ni@NO-C)n chains. The special microstructure of the as-prepared material is proved to be benefit for the improvement of its microwave adsorption performance. The as-synthesized (Ni@NO-C)n/NO-C composite ab-sorber exhibited an effective absorption bandwidth of 4.1 GHz and an extremely large reflection loss of -72.3 dB. The excellent microwave absorbing performances can be ascribed to the coopera-tive consequence of dielectric loss and magnetic loss along with the balance between attenuation capability and impedance match.

This research focused on the perception of visually impaired individuals regarding tactile image creation using 3D printing. We developed and applied an experiment with 28 participants with visual impairments. They performed tasks based on skills whose foundations are needed and used in their daily lives, such as scanning, tactile discrimination, picture and spatial comprehension. The tactile images used in this study were developed by additive manufacturing and printed over 180 g/m² sulphite paper. The best performances were obtained when (1) the tactile image contour line heights were between 0.2 mm and 0.4 mm; and (2) the texture presented densities between 10% and 50%, when alone, or between 10% and 90%, when combined with another texture. The tested line widths (0.8 mm and 1.2 mm) did not present statistically significant differences in the results. Vision status (low vision or blindness) and moment of vision loss (congenital or late blind) did not influence the results. Schooling affected the activities of identifying objects and locating their copies. In the Conclusion section, there is a detailed recommendation list for the production and application of tactile materials, which range from simplifying forms to encouraging the use of both hands during content assimilation.

In this work, we introduce a scalable and efficient GPU-accelerated methodology for volumetric particle advection and finite-time Lyapunov exponent (FTLE) calculation, focusing on the analysis of Lagrangian Coherent Structures (LCS) in large-scale Direct Numerical Simulation (DNS) datasets across incompressible, supersonic, and hypersonic flow regimes. LCS play a significant role in turbulent boundary layer analysis, and our proposed methodology offers valuable insights into their behavior in various flow conditions. Our novel owning-cell locator method enables efficient, constant-time cell search, and the algorithm draws inspiration from classical search algorithms and modern multi-level approaches in numerical linear algebra. The proposed method is implemented for both multi-core CPUs and Nvidia GPUs, demonstrating strong scaling up to 32,768 CPU cores and up to 62 Nvidia V100 GPUs. By decoupling particle advection from other problems, we achieve modularity and extensibility, resulting in consistent parallel efficiency across different architectures. Our methodology was applied to calculate and visualize the FTLE on four turbulent boundary layers at different Reynolds and Mach numbers, revealing that coherent structures grow more isotropic proportional to the Mach number, and their inclination angle varies along the streamwise direction. We also observed increased anisotropy and FTLE organization at lower Reynolds numbers, with structures retaining coherency along both spanwise and streamwise directions. Additionally, we demonstrated the impact of lower temporal frequency sampling by upscaling with an efficient linear upsampler, preserving general trends with only 10% of the required storage. In summary, we present a particle search scheme for particle advection workloads in the context of visualizing LCS via FTLE that exhibits strong scaling performance and efficiency at scale. Our proposed algorithm is applicable across various domains requiring efficient search algorithms in large structured domains. While this manuscript focuses on the methodology and its application to LCS, an in-depth study of the physics and compressibility effects in LCS candidates will be explored in a future publication.

Auto-labeling is one of the main challenges in 3D vehicle detection. Auto-labeled datasets can be used to identify objects in LiDAR data, which is a challenging task due to the large size of the dataset. In this work, we propose a novel methodology to generate new 3D based auto-labeling datasets with a different point of view setup than the one used in the most recognized datasets (KITTI, WAYMO, etc.). The performance of the methodology has been further demonstrated with the development of our own dataset with the auto-generated labels and tested under boundary conditions on a bridge in a fixed position. The proposed methodology is based on the YOLO model trained with the KITTI dataset. From a camera-LiDAR sensory fusion, it is intended to auto-label new datasets while maintaining the consistency of the Ground Truth. The main contribution of this work is a novel methodology to auto-label autonomous driving datasets using YOLO as the main labelling system. The performance of this approach is measured retraining the contrast models of the KITTI benchmark.

Evidence regarding the effect of the onlay preparation design for different CAD/CAM restorative materials considering the preservation of cusps is lacking. Molars were 3D modeled in four preparation designs for onlay restoration: traditional design with functional cusp coverage (TFC), non-retentive design with functional cusp coverage (NFC), traditional design with non-functional cusp coverage (TNFC), non-retentive design with non-functional cusp coverage (NNFC). Restorations were simulated with two CAD/CAM restorative materials: LD – lithium disilicate (IPS e.max CAD) and RC - resin composite (GrandioBloc). A 100 N axial load was applied to the occlusal surface simulating the centric contact point. Von Mises (VM) and maximum principal (Pmax) stresses were evaluated for restorations, cement layer and dental substrate. The non-retentive preparation design reduced the stress concentration in the tooth structure in comparison to the conventional retentive design. For LD onlays, the stress distribution on the restoration intaglio surface showed that the preparation design as well as the prepared cusp, influenced the stress magnitude. The non-retentive preparation design provided better load distribution in both restorative materials and more advantageous for tooth structure. The resin composite restoration on non-functional cusp is recommended when functional cusp is preserved, in order to associate conservative dentistry and low stress magnitude.

Shales are well known for their strong anisotrophic properties. The classical Athy’s model on the exponential porosity reduction with the depth commonly uses based on localities only. Shale compaction curve affects the results of the basin modeling as it is important input data, thus the standard compaction curve of shales needs to be established. This study provided a new data and complies available data of Thailand shales to propose the new empirical relationship among porosity, burial depth, and geological age. The numerical data of the geological time were estimated by the application from the relationship of velocity and depth in each geological ages. The variation of the Thailand shale data due to the different geological ages was found in this study. Finally, the standard curve of shale compaction proposed by Puttiwongrak et al. [9] was examined and confirmed by this research findings.

Ti64 alloy plays a significant role in the biomedical applications such as bioimplants for its excellent biocompatibility. Its usage can be further extended by improving the surface hardness and wear resistance. In this respect, laser surface glazing (LSG), an advanced surface modification technique, is very useful which can produce thin hardened surface layer and strong metallurgical bonding. Investigation of temporal and spatial temperature distributions of laser glazed surface of materials are essential because temperature plays significant role in achieving required surface properties. Therefore, in this study, a 3D Finite element analysis has been developed to perform transient thermal analysis of LSG for Ti64 alloy. The model investigated temperature distribution, depth of modified zone and heating and cooling. The results show that the peak temperature is attained 2095 K for 300 W laser power, 0.2 mm beam width and 0.15 ms residence time. Since this temperature is above the melting point (1933 K) of Ti64 alloy, the melt depth is calculated 22.5 μm. Furthermore, from the simulation results, the average heating and cooling rates are estimated 1.19×10⁷ Ks^-1 and 2.71×10⁶ Ks^-1 respectively which indicate the presence of hard phases in the modified zone.

In tissue engineering scaffolds take the place of the natural extra cellular matrix (ECM). The natural ECM is the extracellular part of animal tissue that usually provides structural support to the animal cells in addition to performing various other important functions. The design aspect along with the choice of the material for the artificial scaffold is very crucial to cell differentiation, adhesion, proliferation, and the transport of the growth factors or other bio molecular signals. In addition to the material and design of the scaffolds, it is necessary to replicate the normal physiological situation if the scaffold has to function as an implant. The cells have to be located in the porous scaffold to form a three dimensional assembly. The article discusses the important factors to be considered while designing a scaffold for tissue engineering and regenerative medicine.

Although conventional immunohistochemistry for neurotropic Rabies virus (RABV) usually shows a high preference for neurons, non-neuronal cells are also potential target cells and abortive infection of astrocytes is considered a main trigger of innate immunity in the CNS. While in vitro studies indicated differences between field and less virulent lab-adapted RABVs, a systematic and quantitative comparison of astrocyte tropism in vivo is lacking. Here, a recently developed solvent-based tissue clearing technique was used to measure the RABV cell tropism in infected brains. Immunofluorescence analysis of 1 mm-thick tissue slices enabled 3D segmentation and quantification of infection frequencies of astrocytes and neurons. Comparison of highly virulent street virus clones from fox, dog, and raccoon with three lab strains of intermediate and low virulence revealed remarkable differences in the ability to infect astrocytes in vivo. While all viruses and infection routes led to comparable neuron infection frequencies, striking differences were detected for the infection of astrocytes. Consistent and inoculation route-independent astrocyte infection by field viruses, together with route-dependent or undetectable astrocyte infection by lab-adapted or vaccine viruses strongly suggests a model in which the ability to establish productive astrocyte infection in vivo functionally distinguishes field and attenuated lab RABV strains.

Osteoarthritis (OA) is a joint disease involving cartilage degeneration. This study aimed to compare properties of chondrocytes from less-affected (LA-Cartilage) and severely-affected (SA-Cartilage) of human OA articular cartilage. Based on Dougados classification, OA cartilage was classified into two groups; less-affected (Grade 0–1) and severely-affected (Grade 2–3). Chondrocytes from each group were cultured until passage (P) 4. Growth, migration, stem cell properties and chondrogenic properties under normal and inflammatory conditions, and the formation of in vitro 3D cartilage tissues were compared between groups. The growth and migratory properties of LA-chondrocytes and SA-chondrocytes were similar, except that the migration rate of SA-chondrocytes was significantly higher at P0 compared to LA-chondrocytes. Both LA-chondrocytes and SA-chondrocytes expressed mesenchymal stem cell markers and tri-lineage differentiation, but the expression of stem cell markers decreased significantly with increasing passage number. Exposure to inflammatory conditions induced distinct morphological changes and significant increases in expression of SOX9 at P4 and MMP3 at P1 for LA-chondrocytes. LA-chondrocytes and SA-chondrocytes able to develop into in vitro 3D constructs, but SA-chondrocytes exhibited superior cartilage-like properties. Chondrocytes from both less- and severely-affected regions are suitable to be used in clinical applications, however, chondrocytes from severely-affected regions could be a more favorable cell source.

A comprehensive 3D Multiphysics model was developed to simulate a plate fin heat exchanger designed for hydrogen liquefaction, incorporating ortho-para- hydrogen conversion catalyst in the hot fin channel. The model encompassed the 3D serrate fin structure, turbulent flow within the cold fin channel, and porous flow through the catalytic hot fin channel. Species transportation within the hot fin channel is coupled with ortho-para hydrogen conversion kinetics, while heat transfer mechanisms between the hot and cold fin channels are rigorously accounted for. Addi-tionally, the state- of- art equation of state is employed to accurately describe the thermodynamic properties of ortho- and para- hydrogen within the model. Numerous operational parameters, including the gas hourly space velocity, cold gas velocity, ortho-para- hydrogen conversion ki-netics, and operating pressure, were systematically varied to identify the kinetic and heat transfer constraints during the heat exchanger operation. The findings revealed that the ortho-para- hy-drogen conversion kinetic parameter predominantly governs operations requiring high gas hourly space velocity, particularly in large- scale hydrogen liquefaction processes. Furthermore, significant pressure drop within the catalytic filled channel was observed, however, operating at higher pressure mitigates this issue while mildly enhancing ortho-para-hydrogen conversion kinetics.

Most common classifications for acetabular bone defects are based on radiographic two-dimension imaging, with low reliability and reproducibility. With the rise of modern processing techniques based on 3D modelling, methodologies for volumetric quantification of acetabular bone loss are available. Our study aims to describe a new methodology for quantitative assess-ment of acetabular defects, based on 3D modelling, focused on the surface analysis of the integrity of the main anatomical structures of the acetabulum represented by four corresponding sectors (posterior, superior, anterior, and medial). The defect entity is measured as the Area Increase Ra-tio (AIR) detected in all the sectors analyzed on three planes of view (frontal, sagittal and axial) compared to healthy hemipelvises. The analysis was performed on 3D-models from the CT-scan of six exemplary specimens with a unilateral pathological hemipelvis. AIR between the native and the pathological hemipelvis was calculated for each sector, for a total of 48 analysis (range, +0.93% - +171.35%). AIR of >50% were found in 22/48(45.8%) sectors and affected mostly the posterior, medial and superior sectors (20/22, 90.9%). Qualitative analysis showed consistency of the data with the morphological features of the defects. Further studies with larger samples are needed to validate the methodology and potentially develop a new classification scheme.

Two pre-pulses focused at different positions and at different time moments were used to enhance THz emission generated by the main pulse. The emission of THz radiation from air breakdown regions of focused ultrashort fs-laser pulses (800 nm/35 fs) at shockwave front prepared by pre-pulses was investigated, and a 3D spatio-temporal control was established for the most intense emission. The laser pulse-induced air breakdown forms a ~120 micrometers-long focal volume and generates a shockwave that delivers denser air into the focal region of the main pulse for enhanced generation of THz radiation at 0.1-2.5 THz spectral window. The intensity of pre- and main-pulses was at the tunneling ionisation intensities (1-3)x10¹⁶ W/cm² and corresponded to sub-critical (transparent) plasma in air. Polarisation analysis revealed that the orientation of the air density gradients generated by pre-pulses and their time-space placement defined the ellipticity of the generated THz electrical field. The rotational electric current is the origin of THz radiation. The current is created by non-parallel gradients of electron density and temperature. Scaling dependencies of THz emission control are established.

This study reports the development of a numerical method to simulate two-phase flows of Newtonian fluids that are incompressible, immiscible, and isothermal. The interface in the simulation was located and reconstructed using the geometric volume of fluid (VOF) method. The implementation of the Piecewise-Linear Interface Calculation (PLIC) scheme of the VOF method was performed to solve the three-dimensional (3D) interface transport during the dynamics of two-phase flows. In this method, the interface is approximated by a line segment in each interfacial cell. The balance of forces at the interface was accounted for using the continuum interfacial force (CSF) model. To solve the Navier-Stokes equations, meshless finite difference schemes from the HiG-Flow computational fluid dynamics software were employed. The 3D PLIC-VOF HiG-Flow algorithm was used to simulate several benchmark two-phase flows for the purpose of validating the numerical implementation. First, the performance of the PLIC implementation was evaluated by conducting two standard advection numerical tests: the 3D shearing flow test and the 3D deforming field test. Good agreement is obtained for the 3D interface shape using both the 3D PLIC-VOF HiG-Flow algorithm and those found on the scientific literature. In addition, the absolute error of the volume tracking advection calculation obtained by our 3D PLIC-VOF HiG-Flow algorithm was found to be smaller than the one found in the scientific literature for both the 3D shearing and 3D deforming flow tests. Lastly, the 3D bubble rising problem was simulated for different fluid densities and viscosity’s ratios. Again, good agreement is obtained for the 3D interface shape using both the newly implemented algorithm and the OpenFOAM, DROPS and NaSt3D software. The bubble’s rise velocity and evolution of the bubble’s center of mass is also computed with the 3D PLIC-VOF HiG-Flow algorithm and found to be in agreement with these software.

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.

Aim of this research paper is to introduce a novel method of hybrid orthodontic tooth-borne distalizer treatment of class II malocclusion by using 3D printed biocompatible personalized distalizer. Explains 3D designing, printing and clinical application of individualized biocompatible medical device dedicated for orthodontic teeth distalization. Compares such distalizer manufactured from two different biocompatible photopolymers (white and transparent). Evaluates their clinical performance and also patients’ aesthetical perception. Clinical part includes comparison of treatment debonding on the set of 12 complete orthodontic treatments with uni-lateral class II malocclusion managed with hybrid approach (CAT-Invisalign with 3D printed distalizer). Paper offers an evaluation of the personalized distalizer functioning in regard to current publications and comparison to conventional prefabricated alternatives like Carriere® Distalizer™ appliance. Results showed no significance of material differences on clinical performance of such individualized distalizers. Research showed preference of patients towards transparent biocompatible photopolymer instead of white A2 shade.

Pure orbital blowout fractures occur within the confines of the internal orbital wall. Restoration of orbital form and volume is paramount to prevent functional and esthetic impairment. The anatomical peculiarity of the orbit has encouraged surgeons to develop implants with customized features to restore its architecture. This has resulted in worldwide clinical demand for patient-specific implants (PSIs) designed to fit precisely in the patient's unique anatomy. Fused filament fabrication (FFF) three-dimensional (3D) printing technology has enabled the fabrication of implant-grade polymers such as Polyetheretherketone (PEEK), paving the way for a more sophisticated generation of biomaterials. This study evaluates the FFF 3D printed PEEK orbital mesh customized implants with a metric considering the relevant design, biomechanical, and morphological parameters. The performance of the implants is studied as a function of varying thicknesses and porous design constructs through a finite element (FE) based computational model and a decision matrix based statistical approach. The maximum stress values achieved in our results predict the high durability of the implants, and the maximum deformation values were under one-tenth of a millimeter (mm) domain in all the implant profile configurations. The circular patterned implant (0.9 mm) had the best performance score. The study demonstrates that compounding multi-design computational analysis with 3D printing can be beneficial for the optimal restoration of the orbital floor.

Marketing is one of the important stages, the decisive factor affecting the success of production and business activities of every business. Therefore, marketing is considered to be the first and most important stage in the process of introducing, bringing products to market and branding of businesses, especially in the period when the disease situation is taking place very complicated worldwide. This study provides both qualitative and quantitative results for the following research objectives. Firstly, the study will assess the situation and analyze the appropriateness of marketing models in the current market situation trend. Secondly, the study proposes an approach in building a new type of marketing model, which is 3D web-based marketing applied in e-commerce to support the modeling of enterprise products in the form of Interactive 3D products are similar to real products. Thirdly, testing and evaluating 3D e-commerce web marketing model at Truong Hai Auto Showroom, Thai Nguyen City branch. This study also proposes a number of solutions for the research and deployment of 3D web marketing model application for businesses in the current market situation.

Microfluidics is facing critical challenges in the quest of miniaturizing, integrating, and automating in vitro diagnostics, including the increasing complexity of assays, the gap between the macroscale world and the microscale devices, and the diverse throughput demands in various clinical settings. Here a “3D extensible” microfluidic design paradigm that consists of a set of basic structures and unit operations was developed for constructing any application-specific assay. Four basic structures- check valve (in), check valve (out), double-check valve (in and out), and on-off valve, were designed to mimic basic acts in biochemical assays. By combining these structures linearly, a series of unit operations can be readily formed. We then proposed a “3D extensible” architecture to fulfill the needs of the function integration, the adaptive “world-to-chip” interface, and the adjustable throughput in the X, Y, and Z directions, respectively. To verify this design paradigm, we developed a fully integrated loop-mediated isothermal amplification microsystem that can directly accept swab samples and detect Chlamydia trachomatis automatically with a sensitivity one order higher than that of the conventional kit. This demonstration validated the feasibility of using this paradigm to develop integrated and automated microsystems in a less risky and more consistent manner.

Designing motion representations for the problem of 3D human action recognition from skeleton sequences is an important yet challenging task. An effective representation should be robust to noise, invariant to viewpoint changes and result in a good performance with low-computational demand. Two main challenges in this task include how to efficiently represent spatio-temporal patterns of skeletal movements and how to learn their discriminative features for classification task. This paper presents a novel skeleton-based representation and a deep learning framework for 3D action recognition using RGB-D sensors. We propose to build an action map called SPMF (Skeleton Posture-Motion Feature), which is a compact image representation built from skeleton poses and their motions. An Adaptive Histogram Equalization (AHE) algorithm is then applied on the SPMF to enhance their local patterns and form an enhanced action map, namely Enhanced-SPMF. For learning and classification tasks, we exploit Deep Convolutional Neural Networks based on the DenseNet architecture to learn directly an end-to-end mapping between input skeleton sequences and their action labels via the Enhanced-SPMFs. The proposed method is evaluated on four challenging benchmark datasets, including both individual actions, interactions, multiview and large-scale datasets. The experimental results demonstrate that the proposed method outperforms previous state-of-the-art approaches on all benchmark tasks, whilst requiring low computational time for training and inference.

This work investigates how the user-controlled parameters of the 3D printing process define temperature conditions on the boundary between layers of the part being fabricated and how these conditions influence the structure and strength of the part. The process studied is fused filament fabrication with a desktop 3D printer and the material utilized is PLA (polylactic acid). As a characteristic of the part strength the fracture load in the case of a three-point bend and calculated related stress were used. During the printing process parts were oriented with the long side along the Z axis, thus, in the bend tests, the maximum stress occurred orthogonally to the layers. During the fabrication process, temperature distribution on the sample surface was monitored with thermal imager. Sample mesostructure was analyzed using SEM. The influence of the extrusion temperature, the intensity of part cooling, the printing speed and the time between printing individual layers were considered. The influence of all the parameters can be expressed through two generalizing factors: the temperature of the previous layer and the flow efficiency, determining the ratio of the amount of extruded plastic to the calculated. A regression model was proposed that describes the effect of the two factors on the printed part strength. Along with interlayer bonding strength, these two factors determine the formation of the part mesostructure (the geometry of the boundaries between individual threads). It is shown that the optimization of the process parameters responsible for temperature conditions makes it possible to approximate the strength of the interlayer cohesion to the bulk material strength.

This article explores the potential of the Unreal Engine game engine as a tool for creating highly realistic 3D visualizations of GIS data, specifically in the context of significant historical areas. The research will focus on the computational techniques used in the 3D visualization of GIS data and the Unreal Engine software and its potential applications in geomatics. The article also presents several relevant scientific studies and projects that have successfully used game engines for similar purposes, explores the potential for using GIS data within a game engine, including plug-ins that provide additional functionality to GIS software, and the use of procedural modeling to create 3D objects through the CityEngine software plug-in. Finally, the research is applied to a dataset of the historical Vltava Valley covering an area of 1670 km2 to demonstrate the capabilities of Unreal Engine in creating realistic visualizations of large historical landscapes, and the resulting visualizations are presented. This practical application of the research provides valuable insights into the potential of the Unreal Engine as a powerful tool for creating highly realistic 3D visualizations of large historical areas with potential applications in the field of geomatics.

This research discusses the development of a software-centered EdTech (Education Technology) class model through the implementation of a course titled "3D Time Machine" at a 4-year university in Republic of Korea over two semesters. The course focused on teaching 3D modeling software, Blender, within the history department. The primary objective of offering this course was to equip students from the digital generation with the capability to manipulate digital technology effectively. Through studying historical materials and accumulating domain knowledge, students could construct their narratives from their unique perspectives. This aimed to foster their proficiency in digital technology operation, preparing them for an education environment increasingly centered around virtual worlds. As the use of virtual worlds gains prominence in educational settings, there is a growing need to incorporate curricula that prepare students to thrive as well-prepared citizens in future societies. Assessing the digital competencies of contemporary university students and designing instructional models with particular attention to their needs is becoming increasingly important. This research draws insights from interviews, conducted in both face-to-face and written formats, with students who participated in the "3D Time Machine" course. The interviews revealed valuable insights that can be actively incorporated into the development of software-centered EdTech instructional models. They reported that they expanded their perceptions as they learned how to make their ideas tangible. The course helped students overcome their fear of digital technology. In conclusion, the course effectively employs 3D modeling technology, a software-centered EdTech, as a core element in helping students develop their narratives rapidly and diversely, thereby playing a crucial role in their ability to articulate their unique perspectives.

In this study, we designed a functional neuro-cardiac model to help us examine the role of neuronal regulation and confirm the importance of neural innervation techniques for cardiac tissue regeneration. A three-dimensional (3D) bioprinted neuro-cardiac scaffold composed of a mixture of gelatin-alginate and alginate-genipin-fibrin hydrogels was developed with a 2:1 ratio of AC16 cardiomyocytes (CMs) and retinoic acid differentiated SH-SY5Y neuronal cells (NCs) respectively. A unique semi-3D bioprinting approach was adopted where the CMs were mixed in the cardiac bioink and printed using an anisotropic accordion design to mimic the physiological tissue architecture in vivo. The voids in this 3D structure were methodically filled in using a NCs-gel mixture and cross-linked. Confocal fluorescent imaging using Microtubule-associated protein 2 (MAP-2) antibodies for labeling NCs, and the MyoD1 antibody for CMs revealed functional coupling between the two cell types in the final cross-linked structure. This data confirmed the development of a physiologically functional neuro-cardiac model that can be used to study neuro-cardiac modulation under physiological and pathological conditions.

A chairside polishing kit is an alternative to a laboratory polishing technique. This study aimed to evaluate the effects of different polishing techniques on the surface roughness of three-dimensional (3D)-printed acrylic denture bases (ADB). One hundred twenty disc-shaped specimens were fabricated from one conventional heat-polymerized (HP) ADB resin and two 3D-printed (Asiga (AS) and NextDent (ND)) ADB resins (n=40 per ADB resin). Each group was furtherly divided based on the polishing protocol (n=10) as follows: convectional polishing protocol (C), Microdont chairside polishing kit (M), Shofu chairside polishing kit (S), and unpolished group (U). The surface roughness (surface roughness average (Ra) and average maximum profile height (Rz)) of the printed specimens were measured using an optical profilometer, and the scanning electron microscope (SEM) was used to capture the surface at ×1000. Two-way ANOVA and post hoc tests were used for data analysis (α = 0.05) at significant levels. In unpolished groups, there was a statically significant difference between HP vs 3D-printed ADBs (p &lt; 0.0001). For Ra values, the lowest values were presented in HP-C, AS-S, and ND-C. While the highest values were shown in all unpolished groups. Within the material, there were statistically significant differences between the three polishing protocols (C, M, and S) vs unpolished (p &lt; 0.0001), while there was no significant between C, M, and S groups (p = 0.05). The Rz values had the same pattern as the Ra values. The two chairside polishing kits were comparable to conventional polishing technique, and it could be recommended for the clinical application.

We calculate the parameters of the Ginzburg–Landau (GL) equation of a three-dimensional attractive Fermi gas around the superfluid critical temperature. We compare different levels of approximation throughout the Bardeen–Cooper–Schrieffer (BCS) to the Bose–Einstein Condensate (BEC) regime. We show that the inclusion of Gaussian fluctuations strongly modifies the values of the Ginzburg–Landau parameters approaching the BEC regime of the crossover. We investigate the reliability of the Ginzburg–Landau theory, with fluctuations, studying the behavior of the coherence length and of the critical rotational frequencies throughout the BCS-BEC crossover. The effect of the Gaussian fluctuations gives qualitative correct trends of the considered physical quantities from the BCS regime up to the unitary limit of the BCS-BEC crossover. Approaching the BEC regime, the Ginzburg–Landau equation with the inclusion of Gaussian fluctuations turns out to be unreliable.

A method for generating fluoroscopic (time-varying) volumetric images using patient-specific motion models derived from 4-dimensional cone-beam CT (4D-CBCT) images is developed. 4D-CBCT images acquired immediately prior to treatment have the potential to accurately represent patient anatomy and respiration during treatment. Fluoroscopic 3D image estimation is done in two steps: 1) deriving motion models and 2) optimization. To derive motion models, every phase in a 4D-CBCT set is registered to a reference phase chosen from the same set using deformable image registration (DIR). Principal components analysis (PCA) is used to reduce the dimensionality of the displacement vector fields (DVFs) resulting from DIR into a few vectors representing organ motion found in the DVFs. The PCA motion models are optimized iteratively by comparing a cone-beam CT (CBCT) projection to a simulated projection computed from both the motion model and a reference 4D-CBCT phase, resulting in a sequence of fluoroscopic 3D images. Patient datasets were used to evaluate the method by estimating the tumor location in the generated images compared to manually defined ground truth positions. Experimental results showed that the average tumor mean absolute error (MAE) along the superior-inferior (SI) direction and the 95th percentile in two patient datasets were (2.29 mm and 5.79 mm) for patient 1 and (1.89 mm and 4.82 mm) for patient 2. This study has demonstrated the feasibility of deriving 4D-CBCT-based PCA motion models that have the potential to account for the 3D non-rigid patient motion and localize tumors and other patient anatomical structures on the day of treatment.

A novel physiologically based algorithm (PBA) for the computation of fractional flow reserve (FFR) in coronary artery trees (CATs) using computational fluid dynamics (CFD) is proposed and developed. The PBA is based on the extension of Murray's law and additional inlet conditions prescribed iteratively, and is implemented in OpenFOAM for testing and validation. 3D models of CATs are created using CT scans and computational meshes, and the results are compared to in-vasive coronary angiographic (ICA) data to validate the accuracy and effectiveness of the PBA. The discrepancy between calculated and experimental FFR is within 2.33-5.26% in steady-state and transient simulations, respectively, when convergence is reached. The PBA is a reliable and physiologically sound technique compared to the current lumped parameter model (LPM), which is based on empirical scaling correlations and requires nonlinear iterative computing for conver-gence. The accuracy of the PBA method is further confirmed using the FDA nozzle, which demonstrates good alignment with CFD-validated values.

In this study, a three-dimensional bioelectrochemical reactor system (3D-BERs) with granular activated carbon (GAC) epitomizes a novel treatment technology for treating nitrate-polluted water. The conventional denitrification process faces many challenges, including the huge demand for organic carbon, long-term accumulation of intermediate products, and the adaptation period. Results shown that under the optimal conditions of the COD/NO3--N ratio was 1.5, the denitrification efficiency reached 98.62%, when compared to 81.12% at COD/ NO3--N ratio of 3.5, and the initial pH of 7.5 ± 0.5, NO3--N was entirely removed at 2.2 h without accumulation of nitrite. The high initial ratio of NO2--N/NO3--N is mainly to accelerate the denitrification rate by accelerating the reduction of nitrite. Denitrification process followed by zero-order kinetics linear model for at different concentrations of inlet NO3--N, and achieved higher denitrification rate at greater inlet NO3--N concentration. High-throughput sequencing shows that the community structure and relative abundance of bacteria changed significantly, especially at the genes and the phyla level in immobilized GAC particles. Microbial composition enhanced the removal of nitrogen at the inner surface (IS) and bottom surface (BS) of immobilized GAC carriers. Therefore, this system is expected to be a more efficient and useful supplement or a cost-effective alternative compared to the traditional low carbon to nitrogen wastewater treatment system.

The aim of this research is to investigate and use a variety of immersive multisensory media techniques in order to create convincing digital models of fossilised tree trunks for use in XR. This is made possible via the use of geospatial data derived from sources such as aerial imaging using UAS, terrestrial material using cameras and also include both the visual and audio element for better immersion, accessible and explorable in 6 Degrees of Freedom (6DoF). Immersiveness is a key factor in order to result in output that is especially engaging to the user. Both conventional and alternative methods are explored and compared, emphasising in the advantages made possible via the help of Machine Learning Computational Photography. Material is collected using both UAS and terrestrial camera devices, including a 3D-360º camera with 6 sensors, using stitched panoramas as sources for photogrammetry processing. Difficulties such as capturing large free standing objects using terrestrial means were overcome using practical solutions involving mounts and remote streaming solutions. Conclusions indicated that superior fidelity can be achieved by the help of Machine Learning Computational Photography processes and higher resolutions and technical specs of equipment not necessarily translating to superior outputs.

Antimicrobial application of carbon nanomaterials such as carbon nanotubes (CNTs), capped CNT, C60 fullerene, and C70 fullerene are increasing owing to their low cytotoxicity properties compared to other nanomaterials such as metallic nanoparticles. Enhanced mechanical property and antibacterial activity can be caused by incorporation of CNTs in 3-dimentional (3D) printed nanocomposites (NCs). Interruption of bacterial membrane resulting from cylindrical shape and high aspect ratio properties has been found as the prominent antibacterial mechanism of CNTs. However, unraveling interaction of CNT, capped CNT, C60 fullerene, and C70 fullerene with virulence factors of the main bacterial pathogenesis has not yet been known. Therefore, in the present study, interactions of CNT, capped CNT, C60, and C70 with the eight virulence factors including protein kinase A and ESX-secreted protein B of Mycobacterium tuberculosis, pseudomonas elastase and exotoxin A of Pseudomonas aeruginosa, alpha-hemolysin and penicillin binding protein 2a of Staphylococcus aureus and shiga toxin 2a and heat-labile enterotoxin of Escherichia coli have been evaluated by molecular docking method of AutoDock Vina. This study disclosed the binding strength followed the sequence CNT &gt; capped CNT &gt; C70 &gt; C60 towards alpha-hemolysin of S. aureus compared to other virulence factors with values of -19.6, -18.8, -13.6, and -12.8 kcal/mol, respectively. The lowest and highest binding affinity were found for CNT against 1TII and 1MWT by binding energy values of 97.4 and -20.1 kcal/mol. The stability of CNT-1MWT complex at the different times has resulted according to the normal mode analysis of elNémo and iMOD servers. Future studies should be focused on improving cellular uptake of CNTs, capped CNTs, C70, and C60 by surface functionalization for active targeting of bacteria.

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.

Rotational jumps are crucial techniques in sports competitions. Estimating ground reaction forces (GRFs), one of the components constituting jumps, through a biomechanical model-based approach enables analysis even in environments where force plates or machine learning training data cannot be utilized. In this study, rotational jump movements involving twists on land were measured using inertial measurement units (IMUs) and estimated GRFs and body loads using a 3D forward dynamics model. Our estimation method, based on forward dynamics and optimization calculations, generated and optimized body movements using cost functions defined by motion measurements and internal body loads. To reduce the influence of the dynamic acceleration in the optimization calculation, the 3D orientation using sensor fusion composed of acceleration and angular velocity data obtained from IMUs and an extended Kalman filter was estimated. As a result, by generating movements based on the cost function, it was possible to calculate biomechanically valid GRFs while following the measured movements even if not all joints are covered by IMUs. This estimation method allows for 3D motion analysis independent of measurement conditions or training data.

Type 1 diabetes is a chronic condition that results from the destruction of insulin-producing β-cells in the pancreas. Current treatments for type 1 diabetes, such as insulin therapy and pancreatic islet transplantation, have several limitations and, hence not quite effective in the long run. As current therapy methods fail to slow disease development, novel strategies such as the development of a bioartificial pancreas are being seriously considered. Over the last decade, research has focused on tissue engineering, which aids in the design of biological alternatives for the repair and replacement of non-functional or damaged organs. Three dimensional (3D) bioprinting technology which employs 3D printing technology to generate 3D tissue-like structures from biomaterials and cells, offers a promising solution for the treatment of type 1 diabetes by providing the ability to generate functional endocrine pancreatic tissue. Bioprinted structures are therefore an important aspect of tissue engineering because they have been found to replicate the native extracellular matrix, promoting cell survival and proliferation. In this review, we extensively discussed about bioprinting endocrine pancreas for the treatment of type 1 diabetes particularly focussing on the choice of cells, biomaterials, growth factors, and essential considerations. Additionally, the key challenges and perspectives towards recapitulation of the pancreatic function of the pancreatic organ engineering technologies have also been discussed.

We present a novel method for online measurement of multi-point opening distances of midpalatal suture during rapid palatal expansion (RPE) using fiber optic Fabry-Perot (F-P) sensors. The sensor consists of an optical fiber with a cut flat end face and an optical reflector, which are implanted into the palatal base structure of an expander and is capable of measuring the precise distance between two optical reflective surfaces. As a demonstration, a 3D printed skull model containing the maxilla and zygomaticomaxillary complex (ZMC) was produced and a miniscrew-assisted rapid palatal expander (MARPE) with two guide rods was used to generate the midpalatal suture expansion. The reflected spectrums of the sensors were used to dynamically extract cavity length information for full process monitoring of expansion. The dynamic opening of the midpalatal suture during the gradual activation of the expander was measured, and a displacement resolution of 2.5 μm was demonstrated. The angle of expansion was derived and the results suggested that the midpalatal suture was opened with a slightly V type expansion of 0.03 rad at the first loading and subsequently expanded in parallel. This finding might be useful for understanding the mechanical mechanisms that lead to different types of expansion. The use of a fiber-optic sensor for mounting the rapid palatal expander facilitates biomechanical studies and experimental and clinical evaluation of the effects of RPE.

In an industrial environment, the quality assurance of weld seams requires extensive efforts. The most commonly used methods for that are expensive and time-consuming destructive tests, since quality assurance procedures are difficult to integrate into production processes. Beyond that, available test methods allow only the assessment of a very limited set of characteristics. They are either suitable for determining selected geometric features or for locating and evaluating internal seam defects. The presented work describes an evaluation methodology based on microfocus X-ray computed tomography scans (µCT scans) which enable the 3D characterization of weld seams, including internal defects such as cracks and pores. A 3D representation of the weld contour, i.e., the complete geometry of the joint area in the component with all quality-relevant geometric criteria, is an unprecedented novelty. Both the dimensions of the weld seam and internal defects can be revealed, quantified with a resolution down to a few micrometers and precisely assigned to the welded component. On the basis of the methodology developed within the framework of this study, the results of the scans performed on the alloy AA 2219 can be transferred to other aluminum alloys. In this way, the data evaluation framework can be used to obtain extensive reference data for the calibration and validation of inline process monitoring systems employing Deep Learning-based data processing.

Crystallization is a significant procedure in the manufacturing of many pharmaceutical and solid food products. In-situ Electrical Resistance Tomography (ERT) is a novel Process Analytical Tool (PAT) to provide a cheap and quick way to test, visualize, and evaluate the progress of crystallization processes. In this work, the spatial accuracy of the non-conductive phantoms in low conductivity solutions was evaluated. Gauss-Newton, Linear Back Projection, and iterative Total Variation reconstruction algorithms were used to compare the phantom reconstructions for tap water, industrial-grade saturated sucrose solution, and demineralized water. Cylindrical phantom measuring 10 mm in diameter and a cross-section area of 1.5 % of the total beaker area was detected at the center of the beaker. Two phantoms with a 10 mm diameter were visualized separately in non-central locations. The quantitative evaluations were done for the phantoms with radii ranging from 10 mm to 50 mm in demineralized water. Multiple factors such as ERT device and sensor development, FEM mesh density and simulations, image reconstruction algorithms, number of iterations, segmentation methods, and morphological image processing methods were discussed and analyzed to achieve spatial accuracy. The development of ERT imaging modality for the purpose of monitoring crystallization in low conductivity solutions was performed satisfactorily.

Turbulent flows over and within forest canopies have recently been modeled with success using Large Eddy Simulations (LES). Validation exercises against experimental data suggest that models can be applied with a high degree of confidence for many applications, mechanical and physiological plant/atmosphere interaction analysis, seed or pollen dispersal, wildfire spread and firebrand transport, or investigation of causes of eddy-covariance technique bias. Long distances required for shear-induced turbulence to equilibrate, result in the widespread use of cyclic boundary conditions in LES atmospheric boundary layer studies. Vegetation drag dissipates air momentum in the atmosphere, but equilibrium is often achieved through compensatory momentum source, supplied by macro-scale pressure gradient forcing. Unfortunately, both classical Ekman balance or simple spatially-constant pressure gradient techniques for implementing this forcing have major drawbacks in the context of cyclic boundary conditions for the applications listed above. Among them, it is difficult to specify aspects of the mean velocity profile such as a specific desired wind velocity and direction at a reference height. In the present paper, we propose a new technique for capturing the effects of a large-scale pressure gradient force (LSPGF) that can be used at stand scale and enables simulation of realistic and specifiable wind fields. Several variants of this LSPGF are developed and analyzed here and validated against experimental data. Although this LSPGF technique is developed in the context of HIGRAD/FIRETEC wildfire simulations, LSPGF can be used for any LES wind modeling application aimed at generating detailed stand-scale wind fields with resolved turbulence and shear profiles consistent with vegetation structure in the boundary layer.

A novel and simple method to improve the corrosion resistance of copper by constructing a 3D 1-dodecanethiol self-assembled monolayers (SAMs) in 3.5% NaCl solution is reported in this study. Several drops of 1% H3PO4 solution are thinly and uniformly distributed on copper surface to form a 3D nanostructure constituted by Cu3(PO4)2 nanoflowers. The anticorrosion properties of 1-dodecanethiol SAMs on copper surface and on copper surface treated with H3PO4 solution were evaluated. Results demonstrated that 1-dodecanethiol SAMs on bare copper surface exhibit good protection capacity, whereas a copper surface pretreated with H3PO4 solution can substantially enhance the corrosion resistance of 1-dodecanethiol SAMs.

Skin inflammation associated with chronic diseases has the direct action of keratinocytes in its immunopathogenesis, leading to a series of immune responses. However, there are still no highly targeted treatments, and the development of more specific therapies is highly desirable. In the present work, nanocapsules containing quinizarin (QZ/NC) were developed, evaluating their act in a model of the keratinocytes inflammatory process in vitro with the action of Photodynamic Therapy, analyzing the permeation in a 3D skin model. Physicochemical, stability, cytotoxicity and permeation analyses of the nanomaterials were carried out. The nanocapsules showed desirable physicochemical characteristics and were stable during the analysis period, without spectroscopic modifications. The cell viability test carried out showed no cytotoxicity at the lowest QZ/NC concentrations. The permeation and cellular uptake studies showed the permeation of QZ/NC in 3D skin models and the intracellular incorporation and internalization of the drug, enhancing its action in the drug delivery technique. Promising results were presented using the model developed to induce the inflammatory process in vitro and applying the synthesized nanomaterial in conjunction with PDT, where a decrease in the levels of cytokines analyzed was observed, representing a possible new therapeutic approach for inflammatory skin diseases.

The article proposes an indirect measurement method based on a dimensional and shape analysis of forgings for the evaluation of the manufacture and the proper operation of the key elements of the crank press, in which after modernization, a quick tool assembly based on SMED (Single Minute Exchange of Die) was implemented. As a result of the introduced changes aiming at improving the forging aggregate and increasing the production efficiency, errors were observed on the manufactured products-forgings in the form of twists and joggles. The preliminary analysis showed that they can be clearances and dynamic deformation in the kinematic chain, the occurrence of side forces during automatic forging of the forging in a two-component system (a long, thin element), as well as the design and construction errors in the joining of the SMED instrument with the table tops of the press. In order to solve the presented problem, in the first place, a separate dimensional and shape analysis was made of selected elements of the press and the instrumentation with the use of the 3D scanning method with the purpose to analyze the construction tolerances of the key elements of the press geometry. Next, an evaluation of the effect of clearances and dynamic deformations of the press as well as the force distribution during the forging process was made through numerical modelling. Despite all of the above, such an approach did not make it possible to solve the problem. A proprietary method with the use of 3d reverse scanning was proposed, which allowed to solve the problem of forgings errors. Based on the measurement results and analyses for a few variants of production cycles the necessary changes was obtained, making it possible to minimize the errors and obtain proper products in respect of geometry and quality.

Neuroblastoma is an embryonal tumor arising from the sympathetic central nervous system. The epidermal growth factor (EGF) plays a role in neuroblastoma growth and metastatic behavior. Recently, we have demonstrated that cathepsin D (CD) contrasts EGF-induced neuroblastoma cell growth in 2D by downregulating EGFR/MAPK signaling. Aggressive NB is highly metastatic to the bone and the brain. In the metastatic process, adherent cells detach to form clusters of suspended cells that once reached the metastatic site adhere and form secondary colonies. Whether CD involves in survival of metastatic NB clones is not known. Therefore, in this study we addressed how CD differentially affects cell growth in suspension versus adherent condition. To mimic tumor heterogeneity, we co-cultured transgenic clones silenced for or overexpressing CD. We compared the growth kinetics of such mixed clones in 2D and 3D models in response to EGF, and we found that Over CD clone was advantaged for the growth in suspension, while the CD knocked-down clone was favored for the adherent growth as 2D. The fact that CD plays a dual role in cancer cell growth in 2D and 3D conditions indicates that during clonal evolution subclones expressing different level of CD may arise, which confers survival and growth advantages depending on the metastatic step. Whether CD involves in survival of metastatic NB clones is not known. We propose that epigenetic regulation of CD expression could be an additional strategy to prevent NB metastases.

Abstract: In complex revision total hip arthroplasties, careful preoperative planning is crucial for the proper reconstruction of hip biomechanics. With conventional 2D radiographic images and computed tomography (CT) the 3D extension of the defect and the remaining bone stock may not be evaluated properly. 3D printed models can aid the surgeon in planning complex acetabular re-construction. The purpose of this study is to compare the accuracy of bony defect assessment in severe acetabular defects surgery with 3D printing planning as compared to conventional 2D ra-diographic planning and CT. Twenty-five patients with severe acetabular defects (Paprosky IIC and III) undergoing revision surgery were enrolled. Each patient had a 3D printed model of their femur and pelvis created based on CT scans. Clinical and radiographic assessments were conducted before and after surgery, with four key bone landmarks measured and compared between X-ray, CT, 3D models, and surgical reports. The findings revealed discrepancies in defect assessment between different imaging methods. X-rays and CT scans sometimes incorrectly identified affected areas, while the 3D models showed more accurate results. This study suggests that 3D printed models can significantly improve the preoperative evaluation of complex hip arthroplasty revisions, enabling surgeons to better select optimal surgical strategies.

Introduction: There is no standardised, universal method to assess physical conditions such as pressure in the pelvicalyceal system in real time during RIRS (retrograde intrarenal surgery). Therefore, the problem concerning increased pressure in the upper urinary tract during the procedure is underestimated. Moreover, it potentially may cause micro-damage and longer postoperative recovery. The aim of this study was to evaluate intrapelvic pressure (IPP) during RIRS procedures. Materials and methods: The 3D printed models of the pelvicalyceal system were printed based on CT-scan of real patient. They were used to perform 50 RIRS procedures with laser lithotripsy of artificially synthesised kidney stones with two different sizes of ureteral access sheath-UAS (10/12Fr vs. 12/14Fr) together with different energy settings generated by the holmium:YAG laser. IPP monitoring during RIRS was performed with the use of the PressureWire X Guidewire compatible with the CoroFlow system. Results and Conclusions: The results showed that high IPP of up to 400 cmH2O would be achieved using a 10/12Fr UAS, while the use of a 12/14Fr UAS would significantly reduce the peak pressure to approximately 100 cmH2O, hence the size of the UAS is a pivotal factor of the IPP generated during the procedure.

Bone tissue engineering has developed significantly in recent years as the increasing demand for bone substitutes due to trauma, cancer, arthritis, and infections. The scaffolds for bone regeneration need to be mechanically stable and have a 3D architecture with interconnected pores. With the advances in additive manufacturing technology, these requirements can be fulfilled by 3D printing scaffolds with controlled geometry and porosity using a low-cost multistep process. The scaffolds, however, must also be bioactive to promote the environment for the cells to regenerate into bone tissue. To determine if a low-cost 3D printing method for bespoke SiOC(N) porous structures can regenerate bone these structures were tested for osteointegration potential by using human mesenchymal stem cells (hMSCs). This includes checking the general biocompatibilities under the osteogenic differentiation environment (cell proliferation and metabolism). Moreover, cell morphology was observed by confocal microscopy and gene expressions on typical osteogenic markers at different stages for bone formation were determined by real-time PCR. The results of the study showed the pore size of the scaffolds had a significant impact on differentiation. A certain range of pore size could stimulate osteogenic differentiation, thus promoting bone regrowth and regeneration.

The accuracy of wind field simulation and prediction is one of the most significant parameters in the field of atmospheric science and wind energy. Limited by the observation data, there are few researches on wind energy development. A 3D Doppler wind lidar (DWL) providing the high-vertical-resolution wind data over the urban complex underlying surface in February 2018 was employed to evaluated the accuracy of vertical wind field simulation systematically for the first time. 11 PBL schemes of the Weather Research and Forecasting Model (WRF) were employed in simulation. The model results were evaluated in groups separated by weather (sunny days, haze days and windy days), observation height layers, and various observation wind speeds. The test results presented that the vertical layer altitude of the observation point position was the most important factor. The simulation is fairly well at a height of 1000-2000m, as most of the relative mean bias of wind speed and wind direction are less than 20% and 6% respectively. Below 1000 m, the wind speed and direction biases are about 30%-150% m.s-1 and 6%-30% respectively. Moreover, when the observed wind speed was lower than 5 m.s-1, the bias were usually large, and the wind speed relative mean bias is up to 50-300%. In addition, the accuracy of simulated wind profile is better in 10-15m.s-1 than other speed ranges, and is better up 1000m than below 1000m in the boundary layer. We see that the WRF boundary layer schemes have different applicability to different weather conditions. The WRF boundary layer schemes have significant differences in wind field simulation with larger error under the complex topography. A PBL scheme is not likely to maintain its advantages in the long term under different conditions including altitude and weather conditions.

Mild traumatic brain injury mTBI is a common occurrence around the world, associated with a variety of blunt force and torsion injuries affecting all age groups. Most never reach medical attention, and identification of acute injury and later clearance to return to usual activities is relegated to clinical evaluation particularly in sports injuries. Advanced structural imaging is rarely performed due to the usual absence of associated acute anatomic/hemorrhagic changes. This review targets physiologic imaging techniques available to identify subtle blood brain barrier dysfunction and white matter tract shear injury, and their association with chronic traumatic encephalopathy. These techniques provide needed objective measures to assure recovery from injury in those patients with persistent cognitive/emotional symptoms and in the face of repetitive mTBI.

In the previous work, the pure fatigue behavior of AM60 magnesium alloy (PF-AM60) was compared with the corrosion fatigue behavior of these specimens (CF-AM60). In this research, in continuation of the previous job, the pure fatigue behaviors of AM60 with polylactic acid (PLA) coating (PF-AM60-PLA) and also, corrosion fatigue behaviors of magnesium alloy with PLA coating (CF-AM60-PLA) were evaluated. Polymer coating was made by fused deposition modeling (FDM) with a 3D printer and attached to standard fatigue test specimens with a glue. Then, they were immersed in the simulated body fluid (SBF) for 27 days. In the end, a high-cycle bending fatigue test was performed on samples. The fracture surface of the samples was also observed using the field emission scanning electron microscopy (FESEM). Due to corrosion, the weight of the specimens redcued by an average of 35%. The corrosion rate decreased in the first 7 days and then increased. PF samples with coating had an average of 49% increase in fatigue lifetime. Regarding the CF samples, despite the use of a 10 times stronger solution, the fatigue lifetime of these samples decreased by only 35%. FESEM results also showed cleavage plates and striations. In addition, the separation of the glue from the coating and Mg was observed. Corrosion products including microcracks and holes were seen on the fracture surface of CF specimens, which caused stress concentration and crack growth. Holes caused by the release of gases were also observed in polymer coatings.

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.

This paper focuses on leveraging a cutting-edge 3D state-space model for a holistic eco-friendly assessment in petrochemical operations. - By applying the ecological carrying capacity theory and the three-dimensional state-space model, this research aims to unleash the next frontier of sustainability in the petrochemical industry. - The proposed methodology will enable advanced and comprehensive eco efficiency evaluation in petrochemical operations. - Through the integration of the ecological carrying capacity theory and advanced modeling techniques, this research seeks to revolutionize sustainability assessments in the petrochemical sector. - The utilization of the cutting-edge 3D state-space model will provide a more advanced and accurate understanding of eco-friendly practices in petrochemical operations. This research presents a unique approach distinct from existing literature, which primarily examines business eco efficiency from behavioral motivation and strategic perspectives. In contrast, this paper introduces a novel three-dimensional state-space model to evaluate the ecological efficiency of petrochemical operations. By combining the ecological carrying index and state space, this model represents the ecological impact of petrochemical operations in a three-dimensional geometric space. It considers petrochemical operations as a significant factor exerting pressure on natural resources and the natural environment. In this three-dimensional state-space model, the three axes represent different dimensions of petrochemical operations. The first axis represents the economic status, which quantitatively describes the financial aspects of the operation. The second axis represents the utilization of resources, capturing the extent to which resources are consumed in the operation. The third axis focuses on the impact of the operation on the environment, allowing for a quantitative assessment of its ecological footprint. By incorporating these dimensions, the model aims to provide a comprehensive and quantitative description of the economic activities of petrochemical operations and their interactions with resources and the environment.The primary focus of this research is to apply the three-dimensional state-space model to calculate the ecological carrying capacity of petrochemical operations. By doing so, it aims to verify the feasibility and applicability of the model in determining the ecological efficiency of these operations. The research also aims to provide theoretical tools that can assist operations in making more informed ecological efficiency judgments. By utilizing this model, petrochemical operations will have a quantitative framework to assess and improve their environmental impact, thus fostering more sustainable practices. The findings of this research demonstrate that the implementation of this method can effectively identify issues related to resources, economy, and environment throughout the development of petrochemical operations. By identifying these problems, it provides managers with a solid foundation for making strategic decisions that promote sustainable development. With this valuable information at their disposal, managers can proactively address challenges, optimize resource utilization, and minimize environmental impacts, thus steering the petrochemical operations towards a more sustainable and responsible path.

The complexity of urban spatial configuration, which affects human-well being and landscape functioning, needs acquisition and 3d visualisation data to inform decision-making process better. One of the main challenges in sustainability research is to conceive spatial models which are capable of adapting to changes in scale and recalibrating the related indicators depending on the degree of detail and data availability. In this perspective, the inclusion of the third dimension into Urban Ecosystem Services (UES) assessment studies highlights the details of urban structure-function relationships, improves modelling and visualisation of data and impacts, aiding decision-makers to localise, assess and manage urban development strategies. The main goal of the proposed framework concerns mapping, evaluating and planning of the UES within a 3d-virtual environment to improve the visualisation of the spatial relationships among the services allocation and the urban fabric density.

Background: Early diagnosis of postoperative complications is an urgent task, allowing timely prescribing of appropriate therapy and reducing the cost of patient treatment. Prognostic models based on various data could help in the early diagnosis of postoperative complications after cardiac surgery. Objectives: The purpose of the study was to determine whether an integrated approach based on clinical data along with metabolites and biomarkers had greater predictive value than the models built on less data. Methods: The study included patients (n=62) admitted for planned cardiac surgery (coronary artery bypass grafting with cardiopulmonary bypass), who were retrospectively divided into two groups depending on the presence (n=26) or absence (n=36) of postoperative complications of all types. Clinical and laboratory data on the first day after surgery were analyzed. Additionally, patients' blood samples were collected before and on the first day after surgery to determine biomarkers (interleukin-6, procalcitonin, NT-proBNP, high-sensitivity troponin T) and metabolites (8 aromatic and 2 dicarboxylic acids were detected using gas chromatography-mass spectrometry). Results: Patients before surgery, compared with healthy donors, differed in the concentration of metabolites (p &lt; 0.05), and had concentrations of a number of biomarkers exceeding the corresponding reference values. Multivariate PLS-DA models, predicting the presence or absence of postoperative complications, were built using clinical data (ROC-AUC=0.71), concentrations of metabolites and biomarkers (ROC-AUC=0.60), and the entire data set (ROC-AUC=0.75). For comparison we built univariate models using the EuroScore2 (ROC-AUC=0.59) and SOFA (ROC-AUC=0.76) scales; concentrations of lactate (ROC-AUC=0.71), the dynamic changes of 4-hydroxyphenyllactic acid (ROC-AUC=0.69), and the sum of three sepsis-associated metabolites (ROC-AUC=0.70). The proposed complex model using entire data set was comparable to the SOFA scale, which confirms the expediency of searching for new predictive models based on a variety of factors.

Milk serves as a crucial source of natural bioactive compounds essential for human nutrition and health. The gastrointestinal digestion of milk proteins releases various biologically active peptides that positively impact human health and enhance physiological performance. With the growing production of cheese, Greek yogurt, and other dairy products, the volume of unutilized acid whey is significantly increasing. Acid whey, containing almost all whey proteins and approximately one-quarter of casein, presents a valuable raw material for generating peptides with potential health benefits. These peptides exhibit properties such as antioxidant, antimicrobial, anti-inflammatory, anticarcinogenic, antihypertensive, antithrombotic, opioid, mineral-binding, and growth-stimulating activities, contributing to improved human immunity and the treatment of chronic diseases. Enzymatic hydrolysis of milk proteins has been developed as a method to produce these peptides, facilitating their use in food fortification. To incorporate whey into functional beverages, it undergoes fermentation by lactic acid bacteria with proteolytic activity. To specifically enrich these beverages with peptides exhibiting targeted bioactivities, it is essential to select lactic acid bacteria strains possessing the requisite protease profiles. Additionally, the sensory properties of the final product can be enhanced using starter cultures with diverse metabolic capabilities, even in the absence of added flavoring agents. Given the imperative to develop waste-free technologies and enhance the profitability of the dairy industry, there is a growing need to efficiently utilize and transform acid whey into a broad spectrum of valuable products and food additives. This approach is justified not only by the nutritional benefits of the bioactive components in whey but also by the commercial potential of safe and health-enhancing products.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.