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

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

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

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

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

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

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

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

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

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

The effects of residual stress in a tungsten gate on a polysilicon channel in scaled 3D NAND flash memories were investigated using a technology computer-aided design simulation. The NAND strings with respect to the distance from the tungsten slit were also analyzed. The scaling of the spacer thickness and hole diameter induced compressive stress on the polysilicon channel. Moreover, the residual stress of polysilicon in the string near the tungsten slit had greater compressive stress than the string farther away. The increase in compressive stress in the polysilicon channel degraded the Bit-Line current (Ion) because of stress-induced electron mobility deterioration. Moreover, a threshold voltage shift (△Vth) occurred in the negative direction because of conduction band lowering.

This article presents, for the first time, the kinetics and the general conversion features of free radical polymerization (FRP) in a 3-component system (A/B/N), with [A] being the initiator, and [B] and [N] are additives, based on the proposed mechanism of Rahal et al. Higher FRP can be achieved by additives [B] and [N], via the dual function of (i) regeneration [A], and (ii) generation of extra radicals (R) via the radicals (S' and S) produced by N.The initiator (coumarin) shows a dual photo-oxidation and photo-reduction character for high efficacy. The FRP conversion efficacy (CE) depends not only on the property of the initiator [A], the additives [B] and [N}, but also the types of monomers. For example, when [A]=CoumC, [A]/NPG is more efficient than [A]/Iod, but revserse trend occurs in some monomers. However, 2-component systems (with CE=0% to 80%) are always less efficient than that of 3-component systems (with CE=70% to 86%, in TMPTA). Specific systems with [A]=coumarins, [B]=Iodonium salt, and N=NPG are analyzed. Analytical formulas for the role of each component concentration, light intensity and coupling rates on the conversion efficacy are derived.

Introduction: The current generation of 3D printers are lighter, cheaper, and smaller, making them more accessible to the chairside digital dentist than ever before. 3D printers in general in the industrial and chairside setting can work with various types of materials including, metals, ceramics, and polymers. Evidence presented in many studies show that an ideal material used for dental restorations is characterised by several properties related to durability, cost-effectiveness, and high performance. This review is the second part in a 3D Printing series that looks at the literature on material science and applications for these materials in 3D printing as well as a discussion on the potential further development and future evolution in 3D printing materials. Conclusions: Current materials in 3D printing provide a wide range of possibilities for providing more predictable workflows as well as improving efficiency through less wasteful additive manufacturing in CAD/CAM procedures. Incorporating a 3D printer and a digital workflow into a dental practice is challenging but the wide range of manufacturing options and materials available mean that the dentist should be well prepared to treat patients with a more predictable and cost effective treatment pathway. As 3D printing continues to become a commonplace addition to chair side dental clinics, the evolution of these materials, in particular reinforced PMMA, resin incorporating zirconia and glass reinforced polymers offer increased speed and improved aesthetics that will likely replace subtractive manufacturing milling machines for most procedures.

Introduction: The term 3D printing is commonly used to depict an assembling method whereby the final form of an object is the result of the addition of different layers to build the frame of an object. This procedure is more accurately portrayed as additive manufacturing and is likewise alluded to as fast prototyping. The term 3D printing, in any case, is generally new and has been an active part of current developments in Dentistry. Much publicity encompasses the evolution of 3D printing, which is hailed as an innovation that will perpetually change CAM manufacturing, including in the dental sector. This review is the first part in a 3D Printing series that looks at the history of 3D Printing, the technologies available and reviews the literature relating to the accuracy of these technologies. Conclusions: The recent advancement in digital dentistry to incorporate these tools has modernised dental practices by paving the way for computer-aided design (CAD) technology and rapid prototyping. The use of 3D printing has led to 3D digital models produced with intraoral scanners (IOS), which can be manipulated easily for diagnosis, treatment planning, mockups, and a multitude of other uses. Combining 3D Printing with a 3D intraoral scan eliminates the need for physical storage but makes it to retrieve a 3D models for use within all dental modalities.

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.

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.

The aim of this study was to clarify degradation characteristics in each tissue of the knee complex of a medial meniscectomy (MMx)-induced knee osteoarthritis (KOA) animal model using classical methods and a new comprehensive evaluation method called contrast-enhanced X-ray micro-computed tomography (CEX-μCT), which was developed in the study. Surgical MMx was performed in the right knee joints of five male Wistar rats to induce KOA. At 4 wk post-surgery, the synovitis was evaluated using qPCR. Degradations of the articular cartilage of the tibial plateau were evaluated using classical methods and CEX-μCT. Evaluation of the synovitis demonstrated significantly increased expression levels of inflammation-associated marker genes in MMx-treated knees compared to that in sham-treated knees. Evaluation of the articular cartilage using classical methods showed that MMx fully induced degradation of the cartilage. Evaluation using CEX-μCT showed that local areas of the medial cartilage of the tibial plateau were significantly reduced in MMx-treated knees compared to that in sham-treated knees. On the other hand, total cartilage volumes were significantly increased in MMx-treated knees. Based on the findings of this study, the researchers in KOA research could be helped to select an optimal KOA model to discover new drugs.

Despite the long and extensive history of 3D technology, it has recently attracted the attention of researchers. This technology has become the center of interest of young people because of the real feelings and sensations it creates. People see their environment as 3D because of their eye structure. In this study, it is hypothesized that people lose their perception of depth during sleepy moments and that there is a sudden transition from 3D vision to 2D vision. Regarding these transitions, the EEG signal analysis method was used for deep and comprehensive analysis of 2D and 3D brain signals. In this study, a single-stream anaglyph video of random 2D and 3D segments was prepared. After watching this single video, the obtained EEG recordings were considered for two different analyses: the part involving the critical transition (transition-state) and the state analysis of only the 2D versus 3D or 3D versus 2D parts (steady-state). The main objective of this study is to see the behavioral changes of brain signals in 2D and 3D transitions. To clarify the impacts of the human brain’s power spectral density (PSD) in 2D-to-3D (2D_3D) and 3D-to-2D (3D_2D) transitions of anaglyph video, 9 visual healthy individuals were prepared for testing in this pioneering study. Spectrogram graphs based on Short Time Fourier transform (STFT) were considered to evaluate the power spectrum analysis in each EEG channel of transition or steady-state. Thus, in 2D and 3D transition scenarios, important channels representing EEG frequency bands and brain lobes will be identified. To classify the 2D and 3D transitions, the dominant bands and time intervals representing the maximum difference of PSD were selected. Afterward, effective features were selected by applying statistical methods such as standard deviation (SD), maximum (max), and Hjorth parameters to epochs indicating transition intervals. Ultimately, k-Nearest Neighbors (k-NN), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) algorithms were applied to classify 2D_3D and 3D_2D transitions. The frontal, temporal, and partially parietal lobes show 2D_3D and 3D_2D transitions with a good classification success rate. Overall, it was found that Hjorth parameters and LDA algorithms have 71.11% and 77.78% classification success rates for transition and steady-state, respectively.

Electrospinning is known to be an effective and straightforward technique to fabricate polymer non woven matrices made of nano and microfibers. Micro patterned morphology of electrospun matrices results to be outmost advantageous in the biomedical field, since it is able to mimic extracellular matrix (ECM), and favors cell adhesion and proliferation. Controlling electrospun fibers alignment is crucial for the regenerative purposes of certain tissues, such as neuronal and vascular. In this study we investigated the impact of electrospinning process parameters on fiber alignment in tubular nanofibrous matrices made of Poly (L-lactide-co-ε-caprolactone) (PLA-PCL); a Design of Experiments (DoE) approach is here proposed in order to statistically set up the process parameters. The DoE was studied keeping constants the previously set material and environmental parameters; voltage, flow rate and mandrel rotating speed were the process parameters here investigated as variables. Orientation analysis was based on ImageJ and plugin Orientation J analysis of SEM images. The results show that voltage combined with flow rate has significant impact on electrospun fiber orientation, and the greatest orientation is achieved when all the three input parameters (voltage, flow rate and mandrel rotation speed) are at their maximum value.

Direct laser writing based on non-linear 3D nanolithography (also known as 3D laser lithography, 3DLL) is a powerful technology to manufacture polymeric micro-optical components. However, practical applications of these elements are limited due to the lack of knowledge of their optical resilience and durability. In this work, we employ 3DLL for the fabrication of bulk (i.e. fully filled) and woodpile structures out of different photopolymers. We then characterize them using S-on-1 laser induced damage threshold (LIDT) measurements. In this way, quantitative data of LIDT values can be collected. Furthermore, this method permits to gather damage morphologies. The results presented in this work demonstrate that LIDT values depend on the material and the geometry of the structure. Bulk non-photosensitized hybrid organic-inorganic photopolymer SZ2080 structures are found to be the most resilient with a damage threshold being of 169±15 mJ/cm².

We propose a computer-generated hologram method for near-eye virtual reality and augmented reality 3D display. A 3D object located near the holographic plane is projected onto a projection plane to obtain a plurality of projected images with different angles. The hologram is calculated by superposition of projected image convolution with a specific PSF through the interference of reference wave with object wave. Holographic 3D display systems with LED as illumination, 4f optical filtering system and lens as eyepiece for near-eye VR display and HOE as combiner for near-eye AR display are designed. The results show that the proposed method is about 38 times faster than the conventional point cloud method. The proposed method is flexible to produce speckle noise free high-quality VR and AR images with efficient focus and defocus capabilities.

3D-printing with foam concrete, which is known for its distinct physical and mechanical properties, has not yet been purposefully investigated. The article at hand presents a methodological approach for the mixture design of 3D-printable foam concretes and a systematic investigation of the potential application of this type of material in digital construction. Three different foam concrete compositions with water-to-binder ratios between 0.33 and 0.36 and having densities of 1100 to 1580 kg/m³ in the fresh state were produced with a pre-foaming technique using a protein-based foaming agent. Based on the fresh-state tests, including 3D-printing as such, an optimum composition was identified and its compressive and flexural strengths were characterised. The printable foam concrete showed compressive strength above 10 MPa and low thermal conductivity, which make it suitable for 3D-printing applications, while fulfilling both load-carrying and insulating functions.

Culture systems for 3-dimensional tissues, such as multicellular spheroids, are indispensable for high-throughput screening of primary or patient-derived xenograft (PDX)-expanded cancer tissues. Oxygen supply to the center of such spheroids is particularly critical for maintaining cellular functions as well as avoiding the development of a necrotic core. In this study, we evaluated 2 methods to enhance oxygen supply: (1) using culture plate with gas-permeable polydimethylsiloxane (PDMS) membrane at its bottom and (2) embedding hydrogel beads in the spheroids. Culturing spheroids on PDMS increased cell growth and affected glucose/lactate metabolism and CYP3A4 mRNA expression and subsequent enzyme activity. The spheroids comprised 5000 Hep G2 cells and 5000 20 µm-diameter hydrogel beads did not develop a necrotic core for 9 days when cultured on a gas-permeable sheet. In contrast, central necrosis in spheroids lacking hydrogel beads was observed after day 3 of culture, even when using PDMS. These results indicate that the combination of gas-permeable culture equipment and embedded hydrogel beads improves culture 3D spheroids produced from primary or PDX-expanded tumor cells.

Poliovirus 2A protease (PV2Apro) plays a vital role in viral replication and down-regulation of host cell protein synthesis. In order to understand more concerning PV2Apro, the protein was over-expressed in bacteria following amplification using sense and antisense primers and cloning in pET15b. Several expression hosts were tested and BL21 (DE3) pLysS cells gave the best expression of PV2Apro with minimal unwanted protein expression following IPTG induction. The 2Apro protein was purified to homogeneity using column chromatography, its solubility determined and its molecular weight and composition determined by MALDI-TOF mass spectrometry. The protease was found in the insoluble fraction and the purified protein had a slightly lower molecular weight than predicted. Moreover, three dimensional structure was modelled using template 1z8r with 58% identity and validated using ramachandran plot. Results revealed that most of the residues lie in favoured and allowed regions. These findings could help in a better understanding of PV2Apro structure and inhibition thus, highlighting potential targets for antiviral drug development.

The development and generalization of Digital Volume Correlation (DVC) on X-ray computed tomography data highlight the issue of long term storage. The present paper proposes a new model-free method for pruning the DVC data. The size of the remaining sampled data can be user-defined, depending on the needs concerning storage space. The data pruning procedure is deeply linked to hyper-reduction techniques. The DVC data of a resin-bonded sand tested in uniaxial compression is used as an illustrating example. The relevance of the pruned data is tested afterwards for model calibration. A new Finite Element Model Updating (FEMU) technique coupled with an hybrid hyper-reduction method is used to successfully calibrate a constitutive model of the resin bonded sand with the pruned data only.

Fatty Acid Amide Hydrolase (FAAH) is one of the enzymes responsible of endocannabinoids metabolism. The inhibition of FAAH is a useful and indirect strategy to raise endogenous cannabinoid concentrations, which would be useful for the treatment of various pathological processes in which cannabinoid concentrations are lowered. In the present work, we present an extensive 3D-QSAR/CoMSIA study on a series of 90 irreversible inhibitors of FAAH of pyrimidinyl-piperazine-carboxamide structure. The final model obtained was extensively validated (q2 = 0.734; r2test = 0.966; r2m = 0.723), and based on the information derived from the contour maps we reported a series of 10 new compounds designed as powerful FAAH inhibitors (pIC50 of the best-proposed compounds = 12.196; 12.416).

Glioblastoma (GBM), the most common and aggressive primary brain tumor in adults, remains one of the least treatable cancers. Current standard of care—combining surgical resection, radiation, and alkylating chemotherapy—results in a median survival of only 15 months. Despite decades of investment and research into the development of new therapies, most candidate anti-glioma compounds fail to translate into effective treatments in clinical trials. One key issue underlying this failure of therapies that work in pre-clinical models to generate meaningful improvement in human patients is the profound mismatch between drug discovery systems—cell cultures and mouse models—and the actual tumors they are supposed to imitate. Indeed, current strategies that evaluate the effects of novel treatments on GBM cells in vitro fail to account for a wide range of factors known to influence tumor growth. These include secreted factors, the brain’s unique extracellular matrix, circulatory structures, the presence of non-tumor brain cells, and nutrient sources available for tumor metabolism. While mouse models provide a more realistic testing ground for potential therapies, they still fail to account for the full complexity of tumor-microenvironment interactions, as well as the role of the immune system. Based on the limitations of current models, researchers have begun to develop and implement novel culture systems that better recapitulate the complex reality of brain tumors growing in situ. A rise in the use of patient derived cells, creative combinations of added growth factors and supplements, may provide a more effective proving ground for the development of novel therapies. This review will summarize and analyze these exciting developments in 3D culturing systems. Special attention will be paid to how they enhance the design and identification of compounds that increase the efficacy of radiotherapy, a bedrock of GBM treatment.

This work presents datasets that can be used for getting a good understanding of an essential geoscience content knowledge that describe earth’s coordinate systems. This include coordinate system used for spherical/spheroidal earth with latitudes and longitudes and their subsequent transformations to 2d maps on a variety of media (paper as well as digital) using the process of map projections. The datasets include PDF documents that are embedded with 3d models, animations and mathematical equations. The dataset has separate PDF documents for geographic (for spherical earth) and projected (2d) coordinate systems. Additionally, the data set include individual 3d models that can be used in various digital systems (including apps) and the animations in mp4 format that can be watched on most of the modern digital devices.

We propose an approach for estimating the error in depth data provided by generic 3D sensors, which are modern devices capable of generating an image (RGB data) and a depth map (distance) or other similar 2.5D structure (e.g. stereo disparity) of the scene. Our approach starts capturing images of a checkerboard pattern devised for the method. Then proceed with the construction of a dense depth map using functions that generally comes with the device SDK (based on disparity or depth). The 2D processing of RGB data is performed next to find the checkerboard corners. Clouds of corner points are finally created (in 3D), over which an RMS error estimation is computed. We come up with a multi-platform system and its verification and evaluation has been done, using the development kit of the board nVIDIA Jetson TK1 with the MS Kinects v1/v2 and the Stereolabs ZED camera. So the main contribution is the error determination procedure that does not need any data set or benchmark, thus relying only on data acquired on-the-fly. With a simple checkerboard, our approach is able to determine the error for any device. Envisioned application is on 3D reconstruction for robotic vision, with a series of 3D vision sensors embarked in robots (UAV of type quadcopter and terrestrial robots) for high-precision map construction, which can be used for sensing and monitoring.

Ultrafast laser 3D lithography based on non-linear light-matter interactions, widely known as multi-photon lithography (MPL), offers unrivaled precision rapid prototyping and flexible additive manufacturing options. 3D printing equipment based on MPL are already commercially available, yet there is still no comprehensive understanding of factors determining spatial resolution, accuracy, fabrication throughput, repeatability, and standardized metrology methods for the accurate characterization of the produced 3D objects and their functionalities. The photoexcitation mechanisms, spatial-control or photo-modified volumes, and the variety of processable materials are topics actively investigated. The complexity of the research field is underlined by limited understanding and fragmented knowledge of light-excitation and material response. Research to date has only provided case-specific findings on photoexcitation, chemical modification, and material characterization of the experimental data. In this review, we aim to provide a consistent and comprehensive summary of the existing literature on photopolymerization mechanisms under highly confined spatial and temporal conditions, where, besides the excitation and cross-linking, parameters such as diffusion, temperature accumulation, and the finite amount of monomer molecules start to become of critical importance. Key parameters such as, photoexcitation, polymerization kinetics, and the properties of the additively manufactured materials at the nanoscale in 3D are examined, whereas, the perspectives for future research and as well as emerging applications are outlined.

Graph visualization has evolved significantly over time, offering various methods to effectively represent complex data structures. This study introduces a novel force-directed algorithm for 3D data visualization, specifically tailored for commonly used datasets in linked data visualization. Leveraging the power of graph theory and methods, the algorithm aims to address the challenge of creating visually appealing and easily interpretable visualizations, which often necessitate advanced user interaction. By utilizing 3D space and the Unity Engine, the research successfully visualizes data and develops interactive visualizations, overcoming limitations of basic force-directed implementations. The main contribution of presented research is in the force-directed algorithm with springs and controlled placement as a visualization technique that combines the use of springs and attractive forces to stabilize a graph in a 3D environment. The combination of these two techniques also helps prevent the formation of a single large cluster within the graph, enhancing the overall visualization quality.

Linear polyamides, known as nylons, are a class of synthetic polymers with a wide range of applications due to their outstanding properties, such as chemical and thermal resistance or mechanical strength. These polymers have been used in various fields: from common and domestic applications, such as socks and fishing nets, to industrial gears or water purification membranes. By their durability, flexibility and wear resistance nylons have been started to be used in addictive manufacturing technology as a good material choice to get sophisticated devices with precise and complex geometric shapes. Furthermore, the emergence of triboelectric nanogenerators and the development of biomaterials have highlighted the versatility and utility of these materials. In order to enhance the triboelectric performance and the range of applications, nylons show a potential use as tribo-positive materials. Because of the easy control of their shape they can be subsequently integrated into nanogenerators. The use of nylons has also extended into the field of biomaterials, where their biocompatibility, mechanical strength and versatility have paved the way for groundbreaking advances in medical devices as dental implants, catheters and non-absorbable surgical sutures. By means 3D bioprinting nylons have been used to develop scaffolds, joint implants and drug carriers with tailored properties for various biomedical applications. The present paper aims to collect these recently specific applications of nylons by reviewing the literature produced in the last decades, with a special focus on the newer technologies in the field of energy harvesting and biomedicine.

Atopic dermatitis (AD) is a chronic inflammatory disorder presenting a dysregulated immune response and derangement of the epidermal barrier lipids. The Th2-type cytokines interleukin IL-4 and IL-13 play a prominent role in AD by activating the Janus Kinase/Signal Transduction and Activator of Transcription (JAK/STAT) intracellular signal axis. This study aimed to investigate the role of JAK/STAT in the lipid perturbations induced by Th2 signaling in 3D-epidermal equivalents. We used tofacitinib, a low-molecular-mass JAK inhibitor, to screen for the JAK/STAT-mediated deregulation of lipid metabolism. Th2 cytokines decreased the expression of elongases 1, 3, and 4, and serine-palmitoyl-transferase and increased that of sphingolipid delta(4)-desaturase, and carbonic anhydrase 2. Th2 cytokines inhibited the synthesis of palmitate and caused a depletion of triglycerides. This depletion was associated with altered PC profiles and fatty acid (FA) metabolism. Overall, the ceramide profiles were minimally affected. Except for most sphingolipids and very long chain FAs, the effects of Th2 on lipid pathways were reversed by co-treatment with tofacitinib. An increase in the mRNA levels of CPT1A and ACAT1, reduced by tofacitinib, suggests that Th2 cytokines promote FA beta-oxidation. In conclusion, pharmacological inhibition of JAK/STAT activation prevents the lipid disruption caused by halted homeostasis of FA metabolism.

Glioblastomas (GBMs) are aggressive and invasive cancers of the brain, associated with high rates of tumor recurrence and poor patient outcomes despite initial treatment. Targeting cell migration is therefore of interest in highly invasive cancers such as GBMs, to prevent tumor dissemination and regrowth. One current aim of GBM research focusses on assessing anti-migratory properties of novel or repurposed inhibitors, including plant-based drugs which display anti-cancer properties. We investigated the potential anti-migratory activity of plant-based products with known cytotoxic effects in cancers, using a range of two-dimensional (2D) and three-dimensional (3D) migration and invasion assays as well as immunofluorescence microscopy to determine specific anti-migratory and phenotypic effects of three plant-derived compounds, Turmeric, Indigo and Magnolia bark, on established glioma cell lines. Migrastatic activity was observed in all three drugs, with Turmeric exerting the most inhibitory effect on GBM cell migration into scratches and from the spheroid edge at all timepoints investigated (p < 0.001). We also observed novel cytoskeletal phenotypes affecting actin and focal adhesion dynamics. By determining the migrastatic activity of Turmeric, Indigo and Magnolia on GBM cell migration, we demonstrate a potential role for Turmeric as a novel GBM anti-migratory therapeutic, in combination with the current standard of care, to prevent tumor recurrence and promote patient survival.

Objective: The aim of this in vitro study was to evaluate the accuracy of resin-based fixed dental restorations, namely veneers, single crowns, and four-unit fixed partial dental prosthesis (FPDs) using two different 3D printers and polymer-based materials. Materials and Methods: A standard maxillary polyurethane jaw model containing prepared teeth was scanned using an intraoral scanner. The generated STL data were used to design the restorations virtually using CAD software. Two 3D printers were utilized for the provisional digital light processing and stereolithography for the castable resin patterns. Each printer produced 10 specimens of each type of restoration, for a total of 80 restorations. The 3d-printed restorations were then 3D scanned using the same intraoral scanner and evaluated for external and internal dimensional accuracy in terms of trueness and precision. A one-way ANOVA and Two-sample T-Test were implemented to compute the precision (variability between groups) and trueness (with the designed CAD model). A level of statistical significance of p-Value

In the conservation of monumental heritage, the collection and utilization of information are of primary importance. The Heritage Building Information Modeling (HBIM) procedure harnesses the potential of three-dimensional models, offering significant advantages in accessing documentation, interoperability, multidimensionality of intervention design, cost evaluation and maintenance management. Attention here is focused on the Certosa di Pisa, a large historical complex built in the 14th century as a monastery of the Carthusian order, currently in a state of deterioration and in need of restoration and re-functionalization. The multifaceted nature of this monumental complex, with its intricate interplay of architectural elements spanning different historical periods and featuring diverse techniques, poses a significant challenge for structural safety assessment. This case study presents an opportunity to explore an HBIM approach to streamline the diagnostic process and facilitate the intervention design phase. The goal is achieved by utilizing an accurate 3D model enriched with data from multiple sources and automating certain operations for structural assessment. The usefulness of the HBIM methodology is highlighted as a valuable tool in the realm of Cultural Heritage structures for both technicians and scholars alike.

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.

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.

Reconstructing a 3D model of a scene from a set of multiple views poses a significant challenge in the field of computer vision. The advent of NeRF has marked a major breakthrough in this domain. However, there is a need to extend the capabilities of the NeRF model to enable editing tasks such as relighting and deformation, as well as to enhance its training efficiency. Neural reflectance fields introduce the concept of the reflectance equation into the NeRF framework to achieve relighting of the NeRF model. We leverage the TensoRF approach, which incorporates tensor decomposition and employs multiple tensors to store features, to expedite the training process of the NeRF model. Our novel method, called StensorR, combines the reflectance equation and tensor decomposition within the radiation field model framework. Differing from previous approaches, we employ a single tensor to store scene features and render the surface color of our scene using a simplified reflectance equation. This approach accelerates model convergence and enables relighting of the NeRF model. Experimental results demonstrate that our method achieves a 50% faster convergence rate compared to existing relighting radiation field models, while successfully enabling relighting and improving the quality of synthesized images from new viewpoints.

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.

Background: Complex bone defects are challenging to treat. Autografting is the gold standard for regenerating bone defects, however limitations include donor site morbidity and increased surgical complexity. Advancements in 3D bioprinting (3DBP) offer a promising alternative for viable bone grafts. Methods: Design of Experiments (DoE) was used to design 12 hydrogel bioinks of various Gelatin meth-acrylate/hydroxyapatite (GelMA/HA) concentrations. These bioinks were assessed for pipettability and equilibrium modulus. An optimal bioink was designed using the DoE data to produce the greatest stiffness while still being pipettable. Two bioinks, the DoE designed maximal stiff-ness and the experimentally defined maximal stiffness vs. a literature based control were then printed using a 3D bioprinter and assessed for print fidelity. The resulting hydrogels were combined with human bone-marrow-derived mesenchymal stromal cells (hMSCs) and evaluated for cell viability. Results: DoE ANOVA analysis indicated that the augmented 3 level factorial design model used was a good fit (p < 0.0001). Using the model, DoE correctly predicted that a composite hydrogel consisting of 12.3% GelMA, 15.7% HA, and 2% Gelatin would produce the maximum equilibrium modulus while still being pipettable. The hydrogel with the most optimal print fidelity was 10% GelMA, 2% HA, and 5% Gelatin. There were no significant differences in cell viability within hydrogels from day 2 to day 7 (p > 0.05). There was however a significantly lower cell viability in the gel composed of 12.3% GelMA, 15.7% HA, and 2% gelatin compared to the other gels with lower HA concentration (p < 0.05), showing that higher HA or print pressure may be cytotoxic within hydrogels. Conclusions: Extrusion-based 3DBP offers significant advantages for bone-tissue implants due to its high customizability. This study demonstrates it is possible to create printable bone-like grafts from GelMA and HA with increased HA levels, favorable mechanical properties (145kPa) and >80% cell viability.

3D printing with earth-based mortar is still under development and faces challenges. Optimizing the mortar mixture, improving structural strength, determining the relationship between printing speed and the amount of extruded material, and ensuring long-term durability are areas that are still being refined. Additionally, regulatory and certification issues must also be considered to ensure the safety and compliance of 3D printed structures. This paper presents for discussion the records, analyses, studies, and considerations regarding the initial initiatives involving 3D printing with the extrusion of earth-based mortar developed at the Faculty of Engineering of the University of Porto - FEUP. Through this work, it is possible to strengthen and reaffirm that 3D printing with earth-based mortar has significant potential in the construction industry and that the incorporation of dispersed kraft paper fibres from the recycling of cement bags is an excellent resource to achieve good constructability in 3D printing with earth-based mortar.

3D human pose estimation has made significant advancements through the integration of deep learning techniques. This survey provides a comprehensive review of recent 3D human pose estimation methods, with a focus on monocular images, videos, and multi-view cameras. Our approach stands out through a systematic literature review methodology, ensuring an up-to-date and meticulous overview. Unlike many existing surveys that categorize approaches based on learning paradigms, our survey offers a fresh perspective, delving deeper into the subject. For image-based approaches, we not only follow existing categorizations but also introduce and compare significant 2D models. Additionally, we provide a comparative analysis of these methods, enhancing the understanding of image-based pose estimation techniques. In the realm of video-based approaches, we categorize them based on the types of models used to capture inter-frame information. Furthermore, in the context of multi-person pose estimation, our survey uniquely differentiates between approaches focusing on relative poses and those addressing absolute poses. Our survey aims to serve as a pivotal resource for researchers, highlighting state-of-the-art deep learning strategies and identifying promising directions for future exploration in 3D human pose estimation.

Three-dimensional (3D) and four-dimensional (4D) printing emerged as the next generation of manufacturing techniques, spanning several research areas such as engineering, chemistry, biology, computing, and materials science. Three-dimensional printing allows the manufacture of complex shapes with high precision, by adding layer by layer of different materials. The use of smart materials that change shape or color, produce an electrical current, become bioactive, or perform an intended function in response to an external stimulus. Shape memory materials (SMMs) in 3D printing technology have attracted a lot of attention due to their ability to respond to external stimuli, leading this technology towards an emerging area of research, "4D printing technology." The core part of this review summarizes the effect of the main external stimuli on 4D textile materials followed by the main applications 4D printed textiles can change their shape over time due to external stimuli such as temperature.

Copper(I) sulfide (Cu2S) is a low-cost, earth-abundant, and non-toxic thermoelectric material for applications in the middle-high temperature range (&gt;650 K). Although 3D printing these materials can simplify their manufacturing, elevated temperatures observed during sintering impair their crystal structure and energy conversion efficiency. In this study, we demonstrated a novel post-processing methodology to revert the thermoelectric properties of the 3D printed Cu2-xS materials back to the unimpaired state via sulfur infusion. After printing and sintering, sulfur was infused into the specimens under vacuum to optimize their crystal structure and achieve high thermoelectric efficiency. Chemical analysis and X-ray Diffraction (XRD) tests showed that after the sulfur infusion process, the Cu/S ratio was reverted close to the stoichiometric level. 3D printed Cu2-xS showed p-type thermoelectric behavior with electrical conductivity peaking at 143 S-cm-1 at 750 K and Seebeck coefficient of 175 µV-K-1 at 627 K. Figure of merit (ZT) value of 1.0 at 780 K was achieved which is the highest value ever reported for a 3D printed Cu2-xS thermoelectrics at this temperature. Fabrication of environmentally friendly thermoelectric materials with extended dimensional freedom and conversion efficiency has the potential to impact the thermoelectric industry with new energy conversion applications and lowered manufacturing costs.

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

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

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

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

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

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

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

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

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

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

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.

This document presents the design and manufacture of a reflectarray (RA) antenna for the Ku-band, based on a fully-metallic 3D architecture. The reflectarray unit cell is formed by a square-shaped waveguide section ended in a short circuit, that is the reflectarray back ground plane. Each cell has the ability of configuring the phase of its own reflected field by means of resonators perforated on the walls of the cell waveguide section. The resonator-based waveguide cell introduces the 3D character to the design. The geometry of the resonators and its size variation introduces the phase behaviour of each cell, conforming the radiation pattern of the reflectarray. This design explores the potential of phase value truncation (6 states and 2 states), and demonstrates that proper pattern results can be obtained with this phase truncation.

Heat shock transcription factors (HSFs) participate in regulating many environmental stress responses and biological processes in plants. Maize (Zea mays L.) is a major cash crop that is grown worldwide. However, the growth and yield of maize are affected by several adverse environmental inputs. Therefore, investigating the factors that regulate maize growth and development and resistance to abiotic stress is an essential task for developing stress-resilient maize varieties. Thus, a comprehensive genome-wide identification analysis was performed to identify HSFs in the maize genome. The current study identified 25 ZmHSFs, randomly distributed throughout the maize genome. Phylogenetic analysis revealed that ZmHSFs are divided into three classes and 13 sub-classes. Gene structure and protein motif analysis supported the results obtained through the phylogenetic analysis. Domain analysis showed the DNA-binding domain to be the most conserved region of ZmHSFs. Segmental duplication is shown to be responsible for the expansion of ZmHSFs. Most of the ZmHSFs are localized inside the nucleus, and the ZmHSFs which belong to the same group show similar physio-chemical properties. The 3D structures revealed comparable conserved ZmHSFs protein structures. RNA-seq analysis revealed a major role of class A HSFs including, ZmHSFA-1a and ZmHSFA-2a in all the maize growth stages, i.e., seed, vegetative, and reproductive development. Furthermore, ZmHSFs displayed an obvious spatiotemporal expression. Under abiotic stress conditions (heat, drought, cold, UV, and salinity), members of class A and B ZmHSFs are induced. Gene ontology (GO) annotation analysis indicated a major role of ZmHSFs in resistance to environmental stress and regulation of primary metabolism. Further, the protein-protein interaction analysis showed that ZmHSFs interact with several molecular chaperons and major stress-responsive proteins. To summarize, this study provides novel insights for functional studies on the ZmHSFs in maize breeding programs.

Alzheimer’s disease (AD) is a significant health concern worldwide with enormous social and economic impact globally. The gradual deterioration of cognitive functions and irreversible neuronal losses are primary features of the disease. Even after decades of research, most therapeutic options are merely symptomatic, and drugs in clinical practice present numerous side effects. Lack of effective diagnostic techniques prevents the early prognosis of disease, resulting in a gradual deterioration in the quality of life. Furthermore, the mechanism of cognitive impairment and AD pathophysiology is poorly understood. Microfluidics exploits different microscale properties of fluids to mimic environments on microfluidic chip-like devices. These miniature multichambered devices can be used to grow cells and 3D tissues in vitro, analyze cell-to-cell communication, decipher the roles of neural cells like microglia, and gain insights into AD pathophysiology. This review focuses on the applications and impact of microfluidics on AD research. We discuss the technical challenges and possible solutions provided by this new cutting-edge technique to understand disease-associated pathways and mechanisms.

The use of flexible sensors has tripled over the last decade due to the increased demand in various fields including health monitoring, food packaging, electronic skins and soft robotics. Flexible sensors have the ability to be bent and stretched during use and can still maintain their electrical and mechanical properties. This gives them an advantage over rigid sensors that lose their sensitivity when subject to bending. Advancements in 3D printing have enabled the development of tailored flexible sensors. Various additive manufacturing methods are being used to develop these sensors including inkjet printing, aerosol jet printing, fused deposition modelling, direct ink writing, selective laser melting and others. Hydrogels have gained much attention in the literature due to their self-healing and shape transforming. Self-healing enables the sensor to recover from damages such as cracks and cuts incurred during use and this enables the sensor to have a longer operating life and stability. Various polymers are used as substrates on which the sensing conductive material is placed. Polymers including polydimethylsiloxane (PDMS), polyvinyl acetate (PVA), and Kapton are extensively used in flexible sensors. The most widely used nanomaterials in flexible sensors are carbon and silver, however, other nanomaterials such as iron, copper, manganese dioxide and gold are also used to provide controlled levels of conductivity or other functional properties.

: Dacarbazine, DAC, 5-(3,3-dimethyltriazeno)imidazol-4-carboxamideis is an imidazole-carboxamide derivative, that is structurally related to purines. DAC belongs to the triazene compounds, which are a group of alkylating agents with antitumour and mutagenic properties. DAC is a non-cell cycle specific drug, active on all phases of cellular cycle. In the frame of this work the 3d-metal complexes (cobalt and copper) with dacarbazine were synthesized. Their spectroscopic properties by the use of FT-IR, FT-Raman and 1HNMR were studied. The structures of dacarbazine and its complexes with copper(II) and cobalt(II) were calculated using DFT methods. The effect of metals on the electronic charge distribution of dacarbazine was discussed on the basis of calculated NBO atomic charges. The reactivity of metal complexes in relation to ligand alone was estimated on the basis of calculated energy of HOMO and LUMO orbitals. The aromaticity of imidazole ring in dacarbazine and the complexes was compared (on the basis of calculated geometric indices of aromaticity). Thermal stability of the investigated 3d-metal complexes with dacarbazine and the products of their thermal decomposition were analyzed.

This paper presents a requirements specification analysis for driving the design of new systems that will allow 3D media creators to further promote and monetize from their work. The provided requirements analysis is based on the IEEE 830 standard for requirements specification. It allows us to elucidate system requirements through existing (AS-IS) and envisioned (TO-BE) scenarios affected by the latest trends on design methodologies and content promotion in social media. A total of 30 tools for content creation, promotion and monetization are reviewed. The target groups, i.e. creator groups, are divided in 10 types according to their role in 3D media production. Based on this division 10 candidate TO-BE scenarios have been identified and out of these 10 scenarios, we have selected 6 scenarios for validation by media creators. The validation was performed through a survey of 24 statements on a 5 Likert scale by 47 individuals from the domains of Media, Fine arts, Architecture, and Informatics. Useful evaluation results and comments have been collected that can be useful for future systems design.

In the past decades, regenerative medicine applied on skin lesions has been a field of constant improvement for both human and veterinary medicine. The process of healing cutaneous wound injuries implicates a well-organized cascade of molecular and biological processes. However, sometimes the normal process fails and can result in a chronic lesion. In addition, wounds are considered an increasing clinical impairment, due to the progressive ageing of the population, as well as the prevalence of concomitant diseases, such as diabetes and obesity, that represent risk aggravating factors for the development of chronic skin lesions. Stem cells regenerative potential has been recognized worldwide, including towards skin lesion repair, Tissue engineering techniques have long been successfully associated with stem cell therapies, namely the application of 3D bioprinted scaffolds. With this review we intend to explore several stem cell sources with promising aptitude towards skin regeneration, as well as different techniques used to deliver those cells and provide a supporting extracellular matrix environment, with effective outcomes. Furthermore, different studies are discussed, both in vitro and in vivo, towards their relevance in the skin regeneration field.

Scientific and technological advances in telecommunications and onboard electronics, and advances in sustainability standards, dictated major changes to various industrial sectors, including the automotive industry, where hard and soft approaches to manufacturing are vying for market dominance. This work presents a prospective analysis of the autonomous vehicle (AV) market, analyzing three of the main US AV technology firms, Tesla, Waymo and Apple. Their designs and solutions are compared, and prospective scenarios were constructed based on an analysis of their strengths, weaknesses, opportunities and threats (SWOT). The results suggest that Tesla currently exhibits the greatest market leadership in the group studied. However, it was concluded that in the medium term, Waymo would surpass Tesla and assume market leadership. In the long run, it was concluded that Apple will overcome its rivals and dominate this market.

The three-dimensional printing of scaffolds is an interesting alternative to the traditional techniques of periodontal regeneration. This technique uses computer assisted design and manufacturing after CT scan. After 3D modelling, individualized scaffolds are printed by extrusion, selective laser sintering, stereolithography, or powder bed inkjet printing. These scaffolds can be made of one or several materials such as natural polymers, synthetic polymers, or bioceramics. They can be monophasic or multiphasic and tend to recreate the architectural structure of the periodontal tissue. In order to enhance the bioactivity and have a higher regeneration, the scaffolds can be embedded with stem cells and/or growth factors. This new technique could enhance a complete periodontal regeneration. This review summarizes the application of 3D printed scaffolds in periodontal regeneration. The process, the materials and designs, the key advantages and prospects of 3D bioprinting are highlighted, providing new ideas for tissue regeneration.

Human eye is a specialized organ with complex anatomy and physiology, because it is characterized by different cell types with specific physiological functions. Given the complexity of the eye, ocular tissues are finely organized and orchestrated. In the last few years many in vitro models have been developed, in order to meet the 3Rs principle (Replacement, Reduction and Refinement) for eye toxicity testing. This procedure is highly necessary to ensure that the risks associated with ophthalmic products meet appropriate safety criteria. In vitro preclinical testing is now a well-established practice of significant importance for evaluating the efficacy and safety of cosmetic, pharmaceutical, and nutraceutical products. Along with in vitro testing, also computational procedures, herein described, for evaluating the pharmacological profile of potential ocular drug candidates including their toxicity, are in rapid expansion. In this review the ocular cell types and functionality are described providing an overview about the scientific challenge for the development of three-dimensional in vitro models.

Among many other themes, Leonardo da Vinci’s Manuscript B contains several drawings of centrally planned churches, some of which are represented using a plan view paired with a bird’s-eye view. The use of a bird’s-eye instead of an elevation represents an innovative depiction technique, which allows to combine the immediacy of the perspective view with the measurability of the façades, and therefore to describe the three-dimensionality of the buildings. To understand the reasons behind the use of this original technique, the edifices’ shape and classify them we decided to use 3D digital reconstruction techniques, for their ability to avoid misunderstandings in the reconstruction process and in the results. This article describes the method to create the digital models of sixteen churches. A Visual programming language (VPL) script was used as 3D base for modelling the churches achieved from a classification code expressing the aggregative rules of the churches. Then, the geometric process for the construction of the plan and its relationship with the elevation measures was studied for each church. Finally, this information was used for the completion of the 3D models, distinguishing more output variants each time there was an inconsistency between plan and perspective view, a variability of one architectural element or an uncertainty.

Metal 3D printing technology is a promising manufacturing method. The quality of the printed product can pass for mechanical application, if the anisotropy of the microstructure, imperfections, deformation, and residual stress of the printed sample could be lower than the appropriate level or if they are fully illuminated. Thermal stress is one of the significant reasons for deformation in the 3D printed samples. Thermal stresses are the direct consequence of the local temperature gradient. In this research, the effect of the temperature printer’s chamber (from room temperature to 900 C) was studied on thermal stress and subsequent total deformation in the printed sample. The printed sample is a six-layers-printed walk, which could be considered as a building block of other complex shapes and give us inside about deformation. The computational results show a meaningful reduction in thermal stress and deformation at the higher temperature of the printer’s chamber. The lower final deformation of the printed sample is an important subject, especially for samples with complex shapes.

3D surface scans were carried out to determine the shapes of the upper sections of (skeletal) crania of adult Eurasian otters (Lutra lutra) from Great Britain. Landmark points were placed on these shapes by using a graphical user interface (GUI) and distance measurements (i.e., the length, height, and width of the crania) could be found by using the landmark points. These “GUI-based” distances were shown to be accurate and reliable in comparison to physical measurements taken on the crania directly by using a digital calliper. The crania of males were 6.85mm, 5.44mm, 1.66mm larger in terms of length, width and height, respectively, than females in our sample (P < 0.001), i.e., male otters had significantly larger skulls than females. Significant differences in size occurred also by geographical area in Great Britain (P < 0.05). Multilevel Principal Components Analysis (mPCA) indicated that sex and geographical area explained 31.1% and 9.6% of shape variation in “unscaled” shape data and that they explained 17.2% and 9.7% of variation in “scaled” data. The first mode of variation at level 1 (sex) correctly reflected size changes between males and females for “unscaled” shape data. Modes at level 2 (geographical area) also showed possible changes in size and shape. Clustering by sex and geographical area was observed in standardised component scores. Such clustering in cranial shape by geographical area might reflect genetic differences that are known to occur in otter populations in Great Britain, although other potentially confounding factors (e.g. population age-structure, diet, etc.) might also drive regional differences. Furthermore, sample sizes per group were small for geographical comparisons. However, this work provides a successful first test of the effectiveness of 3D surface scans and multivariate methods such as mPCA to study the cranial morphology of otters.

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.

Detailed kinetics for a 3-wavelength photopolymerization confinement (PC) system is presented for both numerical solutions and analytic formulas. The dynamic profiles are simulated for oxygen, free radical, and conversion for various situations of: blue-light only, 2-light (red and UV), and 3-light (red, blue, UV). An effective PC requires two conditions: (i) a strong N-inhibition for uncured regime with a low conversion (triggered by the UV-light); and (ii) a weak S-inhibition (oxygen-induced) for high conversion under the blue-light or blue and red-light initiation. Good PC candidates are governed by collective factors of: (i) the double ratio of light-intensity and initiator-concentration, (ii) monomers rate-constant; and (iii) effective absorption constants at specific wavelength and initiators. A new reverse feature for the role of N-inhibition on the blue-conversion is found. Higher oxygen concentration leads to a lower conversion, which could be enhanced by reducing the S-inhibition via a red or blue-light pre-irradiation, having a pre-irradiation time TP=200 s for red-light only, and reduced to 150 s, when both red and blue-light. System under UV-only leads a conversion lower than that of blue-only. However, conversion could be improved by the dual-light (blue and UV), and further enhanced by the pre-irradiation of red-light. The two competing factors, N-inhibition and S-inhibition, could be independently and selectively tailored to achieve: (a) high conversion of blue-light (without UV-light), enhanced by red-light pre-irradiation for minimal S-inhibition; and (b) efficient PC initiated by UV-light produced N-inhibition for reduced confinement thickness and for high print speed.

This paper aims to analyse the mechanical properties response of polylactic acid (PLA) parts manufactured through fused filament fabrication. The influence of six manufacturing factors (layer height, filament width, fill density, layer orientation, printing velocity, and infill pattern) on the flexural resistance of PLA specimens is studied through an L27 Taguchi experimental array. Different geometries have been tested on a four-point bending machine and on a rotating bending machine. From the first experimental phase, an optimal set of parameters deriving in the highest flexural resistance have been determined. Results show that layer orientation is the most influential parameter, followed by layer height, filament width, and printing velocity, whereas the fill density and infill pattern show no significant influence. Finally, the fatigue fracture behaviour is evaluated and compared with previous studies results, to present a comprehensive study of the mechanical properties of the material under different kind of solicitations.

The kinetics and modeling of dual-wavelength controlled photopolymerization confinement (PC) are presented and measured data are analyzed by analytic formulas and numerical data. The UV-light initiated inhibition effect is strongly monomer-dependent and different monomers have different C=C bond rate constants and conversion efficacy. Without the UV-light, for a given blue-light intensity, higher initiator concentration (C₁₀) and rate constant (k’) lead to higher conversion, as also predicted by analytic formulas, in which the total conversion rate (R_T) is an increasing function of k’R, which is proportional to k[gB₁C₁]^0.5. However, the coupling factor b₁ plays a different role that higher b₁ leads to higher conversion only in the transient regime; whereas higher b₁ leads lower steady-state conversion. For a fixed initiator concentration C₁₀, higher inhibitor concentration (C₂₀) leads to lower conversion due to stronger inhibition effect. However, same conversion reduction was found for the same H-factor of H₀ = [b₁C₁₀ - b₂C₂₀]. Conversion of blue-only are much higher than that of UV-only and UV-blue combined, in which high C₂₀ results a strong reduction of blue-only-conversion, such that the UV-light serves as the turn-off (trigger) mechanism for the purpose of spatial confirmation within the overlap area of UV and blue light. For example, UV-light controlled methacrylate conversion of a glycidyl dimethacrylate resin formulated with a tertiary amine co-initiator, and butyl nitrite, subject to a continuous exposure of a blue light, but an on-off exposure of a UV-light. Finally, we developed a theoretical new finding for the criterion of a good material/candidate governed by a double ratio of light-intensity and concentration, [I₂₀C₂₀.]/[I₁₀C₁₀].

3D city models are being extensively used in applications such as evacuation scenarios and energy consumption estimation. The main standard for 3D city models is the CityGML data model which can be encoded through the CityJSON data format. CityGML and CityJSON use polygonal modelling in order to represent geometries. True topological data structures have proven to be more computationally efficient for geometric analysis compared to polygonal modelling. In a previous study, we have introduced a method to topologically reconstruct CityGML models while maintaining the semantic information of the dataset, based solely on the combinatorial map (C-Map) data structure. As a result of the limitations of C-Map's semantic representation mechanism, the resulting datasets could suffer either from semantic information loss or the redundant repetition of them. In this article, we propose a solution for a more efficient representation of both geometry, topology and semantics by incorporating the C-Map data structure in the CityGML data model and implementing a CityJSON extension to encode the C-Map data. In addition, we provide an algorithm for the topological reconstruction of CityJSON datasets to append them according to this extension. Finally, we apply our methodology to three open datasets in order to validate our approach when applied to real-world data. Our results show that the proposed CityJSON extension can represent all geometric information of a city model in a lossless way, providing additional topological information for the objects of the model.

Abstract: The broad clinical use of synthetic vascular grafts for vascular diseases is limited by their thrombogenicity and low patency rate, especially for vessels with a diameter inferior to 6 mm. Alternatives such as tissue-engineered blood grafts (TEBGs) have gained increasing interest. Among the different manufacturing approaches, 3D bioprinting presents numerous advantages and enables the fabrication of multi-scale, multi-material, and multicellular tissues with heterogeneous and functional intrinsic structures. Extrusion-, inkjet- and light-based 3D printing techniques have been used for the fabrication of TEBG out of hydrogels, cells, and/or solid polymers. This review discusses the state-of-the-art research on the use of 3D printing for TEBG with a focus on the biomaterials and deposition methods.

The sTetro is a stair cleaning robot which can climb the staircase with its shapeshifting capabilities. As this robot is intended to traverse multi-floor environment autonomously, hence its localization/positioning information is an essential component of the overall system. Usually, the indoor mobile robots rely on some external system for localization information, e.g., WiFi, UWB, vision, RFID signals, or indoor Global Positioning System (GPS). This requires the installation of additional hardware and/or modification of the working environment for precise positioning information of the mobile platform. As the dimensions of the staircase are known a priori, this knowledge can be used to localize the sTetro robot on the stairs. In this article, the geometry of the staircase has been exploited to localize the robot in 3D space with measurements from the onboard time-of-flight (ToF) range sensors only. The heading angle of the robot is also estimated with two ToF sensors installed in front of the sTetro robot. Results achieved by conducting experiments on real robot prove the efficacy of the proposed approach.

This paper investigates the effects of air void topology on hydraulic conductivity in asphalt mixtures with porosity in the range 14%-31%. Virtual asphalt pore networks were generated using the Intersected Stacked Air voids (ISA) method, with its parameters being automatically adjusted by the means of a differential evolution optimisation algorithm, and then 3D printed using transparent resin. Permeability tests were conducted on the resin samples to understand the effects of pore topology on hydraulic conductivity. Moreover, the pore networks generated virtually were compared to real asphalt pore networks captured via X-ray Computed Tomography (CT) scans. The optimised ISA method was able to generate realistic 3D pore networks corresponding to those seen in asphalt mixtures in term of visual, topological, statistical and air void shape properties. It was found that, in the range of porous asphalt materials investigated in this research, the high dispersion in hydraulic conductivity at constant air void content is a function of the average air void diameter. Finally, the relationship between average void diameter and the maximum aggregate size and gradation in porous asphalt materials was investigated.

Intercellular transport of auxin is driven by PIN-formed (PIN) proteins. PINs are localized at the plasma membrane (PM) and on constitutively recycling endomembrane vesicles. Therefore, PINs can mediate auxin transport either by direct translocation across the PM or by pumping it into secretory vesicles (SVs), leading to its secretory release upon fusion with the PM. Which of these two mechanisms dominates is a matter of debate. Here we addressed the issue with a mathematical modeling approach. We demonstrate that the efficiency of secretory transport depends on SV size, half-life of PINs on the PM, pH, exocytosis frequency and PIN density. 3D-SIM microscopy was used to determine PIN density on the PM. Combing this data with published values of the other parameters, we show that the transport activity of PINs in SVs would have to be at least 1000x greater than on the PM in order to produce a comparable macroscopic auxin transport. If both transport mechanisms operated simultaneously and PINs were equally active on SVs and PM, the contribution of secretion to the total auxin flux would be negligible. In conclusion, while secretory vesicle-mediated transport of auxin is intriguing and theoretically possible model, it unlikely to be a major mechanism of auxin transport in planta.

Purpose: The aim of the present experimental 3D-finite element study was to evaluate the influence of an augmented sinus lift with an additional inserted bone graft block. The bone graft block stabilizes the implant in addition to conventional augmented bone. We placed the block in three different positions. The implants were loaded with axial force and forces secondary to laterotrusion and protrusion. Material and Methods: A simplified U-shaped 3D finite element model of the upper jaw and a more complex anatomical model of the left maxilla were created. The bone graft block was placed in three positions: in the lower third in contact with the sinus floor, the middle, and the upper third of the implant. Van Mises’ stress distribution was calculated and analyzed for the different models. We also compared the complex anatomical model with the simplified one. Results: The position of the bone graft block significantly influences the magnitude of stress distribution. A bone graft block positioned in the upper third or middle of the implant reduces the quantity of stress compared to the reference model without a bone graft block. The low bone graft block position is clearly associated with lower stress distribution in compact bone. We registered no significant differences in stress in compact bone with regard to laterotrusion or protrusion. Conclusions: Maximum values of von Mises stresses in compact bone can be reduced significantly by using a bone graft block. The reduction of stress is nearly the same for positions in the upper third and the middle of the implant. It is much more pronounced when the bone graft block is in the lower third of the implant near the sinus floor, which appeared to be the best position in the present study.

This study explores novel techniques to improve the detection accuracy of skarn iron deposits using advanced image processing methodologies. Leveraging the capabilities of Aster image, Band Ratio (BR) images, and Principal Component Analysis (PCA), alongside the power of 3D Convolutional Neural Networks (3D-CNN), the research aims to enhance the precision and efficiency of ore detection in complex geological environments. The proposed method employs a specific 3D-CNN architecture, accepting input as a 7×7×C image patch, where C represents the combined number of selected Aster image bands, Principal Component (PC) bands, and computed BR images. To evaluate the accuracy of the proposed method, five distinct image bands combinations, including the proposed bands combination, were tested and evaluated based on the overall accuracy (OA), average accuracy (AA), and kappa coefficient. The results demonstrated that while the incorporation of BR images alongside Aster bands initially seemed promising, it introduced significant confusion in certain classifications, leading to unexpected mis-classification rates. Surprisingly, utilizing solely Aster bands as input parameters yielded higher accuracy rates (OA= 93.13%, AA = 91.96%, Kappa = 90.91%) compared to scenarios involving the integration with band ratios (OA = 87.02%, AA = 79.15, and Kappa = 82.60%) or the integration of BR images to PC bands (OA= 87.78%, AA = 82.39%, Kappa = 83.81%). However, the amalgamation of Aster bands with selected PC bands showed slight improvements in accuracy (OA= 94.65%, AA = 92.93%, Kappa = 93.45%), although challenges in accurately classifying certain features persisted. Ultimately, the proposed combination of Aster bands, PC bands, and BR images (proposed bands combination) presented the most visually appealing and statistically accurate results (OA = 96.95%, AA= 94.87%, and Kappa = 95.93%), effectively addressing misclassifications observed in the other combinations. These findings underscore the synergistic contributions of each of the Aster bands, PC bands, and BR images, with Aster bands proving pivotal for optimal skarn classification, PC bands enhancing intrusions classification accuracy, and BR images strengthening wall rock classification accuracy. In conclusion, the proposed combination of input image bands emerges as a robust and comprehensive methodology, demonstrating unparalleled accuracy in the remote sensing detection of skarn iron minerals.

The integration of three-dimensional (3D) printed resin denture teeth represents a significant ad-vancement in digital dentistry. This study aimed to assess their ability to withstand chipping and indirect tensile fractures, comparing them with conventionally manufactured resin denture teeth. Four groups, each comprising 30 specimens, were examined: Group 1 featured 3D printed denture teeth (NextDent, 3D Systems, Soesterberg, The Netherlands), while the others included commer-cially obtained Ivostar Shade, SpofaDent Plus, and Major Super Lux teeth. Stereolithography 3D printing was utilized to produce methacrylate-based photopolymerized resin teeth models for Group 1, while the remaining groups were commercially sourced. Chipping and indirect tensile fracture tests were performed at a speed of 1 mm/min until fracture occurred. Statistical analysis was conducted using one-way analysis of variance (ANOVA) with Tukey's honestly significant difference multiple comparisons test (p < 0.05). Results indicated that 3D-printed teeth exhibited higher indirect tensile fracture resistance than Major Super Lux and Ivostar Shade but lower than SpofaDent Plus. Additionally, in the chipping test, buccal chipping occurred in 3D-printed resin teeth without distortion. In the indirect tensile test, the fracture line emerged near the loading point, extending cervically from the inner incline of both cusps. Overall, denture teeth produced via 3D printing with printable resin materials demonstrated sufficient fracture resistance, making them suitable for prosthetic applications.

Verifying the accuracy of a 3D-printed object involves using an image processing system. This system compares images of the CAD model of the object to be printed with its 3D-printed counterparts to identify any discrepancies. It is important to note that the integrity of the accuracy measurement is heavily dependent on the image processing settings chosen. This study focuses on this issue by developing a customized image processing system. The system generates binary images of a given CAD model and its 3D-printed counterparts and then compares them pixel-by-pixel to determine the accuracy. Users can experiment with various image processing settings, such as grayscale to binary image conversion threshold, noise reduction parameters, masking parameters, and pixel-fineness adjustment parameters, to see how they affect accuracy. The study concludes that the grayscale to binary image conversion threshold has the most significant impact on accuracy and that the optimal threshold varies depending on the color of the 3D-printed object. The system can also effectively eliminate noise (filament marks) during image processing, ensuring accurate measurements. Additionally, the system can measure the accuracy of highly complex porous structures where the pores size, depth, and distribution are random. The insights gained from this study can be used to develop intelligent systems for the metrology of additive manufacturing.

Wavelength selective switches (WSSs) are essential elements for wavelength division multiplexing (WDM) optical networks, as they offer cost-effective, high port-count and flexible spectral channel switching. This work proposes a new hybrid WSS architecture that leverages the beam shaping and steering features of uniform silicon nitride (SiN) based end-fire optical phased arrays (OPAs). By introducing beamforming to a WSS system, the spectral channels on the liquid crystal on silicon (LCoS) panel can be tailored and arranged properly, depending on the optical configuration, using the beam control capabilities of OPAs. Combining 3D-FDTD and ray tracing simulations, the study shows that by reducing the input beam dimensions with proper sizing of the OPAs, the WSS design with the null-steering OPAs layout and 4×No switch size features increased spectral resolution. This extensive beamforming study on the steering-enabled layout reveals the acquirement of an even higher input channel number, achieving up to the 8×No WSS scheme with flexible channel routing on the LCoS panel. Such implementation of beamsteerers can unlock an extra degree of freedom for the switching capabilities of hybrid WSS devices. The results show great promise for the introduction of OPAs in WSS systems and provide valuable insight for the design of future wireless communication links and WDM systems.

This study investigates the effect of scaffold architecture on bone regeneration, focusing on 3D-printed polylactic acid-bioceramic calcium phosphate (PLA-bioCaP) composite scaffolds in rabbit femoral condyle critical defects. To assess their influence on bone healing and scaffold performance, we explored two distinct scaffold designs, alternate and helical laydown patterns. The scaffolds were meticulously characterized for pore size, strut thickness, porosity, pore accessibility, and mechanical properties. The in vivo efficacy of these scaffolds was evaluated using a rabbit femoral condyle critical defect model. Our findings indicate that both scaffold architectures are biocompatible and support bone formation. The helical scaffolds, characterized by larger pore sizes and higher porosity, demonstrated significantly greater bone regeneration than the alternate structures. However, their lower mechanical strength presented limitations for use in load-bearing sites. This study highlights the importance of scaffold architecture in bone tissue engineering and underscores the need to balance porosity and mechanical strength for optimal bone regeneration. The findings provide crucial insights for the design of 3D- printed scaffolds in clinical applications, particularly in the context of critical-sized bone defects. The study also outlines potential areas for future research, including exploring hybrid scaffold designs to achieve optimal porosity without compromising mechanical integrity.

3D printing is a non-traditional additive manufacturing process. It is different from the traditional subtractive manufacturing process. It offers exceptional rapid prototyping capabilities and results that traditional subtractive manufacturing methods cannot attain, especially in applications involving curved or intricately shaped components. Despite its advantages, metal 3D printing will face porosity, warpage, and surface roughness issues. These issues will affect the future practical application of the parts indirectly, for example, the structural strength and the parts assembly ca-pability. Therefore, this study compares the qualities of the warpage, weight, and surface rough-ness after milling and grinding processes under the same materials (316L stainless steel) between general rolled steel and 3D additive steel. Experimental results show that 3D printing parts are approximately 13% to 14% lighter than the general rolled steel. The surface roughness performance of 3D printing steel is better than general rolled steel under the same material after milling or grinding processing. The hardness of the 3D printing steel is better than that of the gen-eral rolled steel. The research verifies that 3D additive manufacturing can use surface processing to optimize surface performance and achieve the functions of lightness and hardness.

(1) Background: Pseudotumor of the hip is a sterile, non-neoplastic soft tissue mass associated with total hip arthroplasties. Pseudotumors may mimic soft tissue tumors, or infections, so the differential diagnosis is crucial and biopsy is recommended. The purpose of this study was to compare complications and functional results between one-stage and two-stage procedures. (2) Methods: We retrospectively analyzed 21 patients surgically treated at our Institution with “pseudotumor” associated with hip prosthesis (8 male,13 female; mean age 69 years). One-stage revision was performed in 10 cases, two-stage in 10, excision only in one case. Complications were classified as major and minor and functional results assessed using the Harris Hip Score (HHS). (3) Results: Five patients (24%) reported major complications. Survival rate to all com-plications was 75%. Overall survival was 95% at five years. Mean HHS went from 35 pre-operative to 75 post-operative, highlighting improved functional results in all cases. We rec-orded no differences in complications and functional outcome between one and two-stage proce-dures. (4) Conclusions: In our experience, two-stage surgical approach is preferable in cases with major bone defects and larger pseudotumor size. The use of custom-made 3D-printed prostheses is increasing and is a further reason to prefer two-stage revision.

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.

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.

Scaffolds for tissue engineering are expected to respond to a challenging combination of physical and mechanical requirements, guiding the research towards the development of novel hybrid materials. This study introduces innovative three-dimensional bioresorbable scaffolds, in which a stiff poly(lactic acid) lattice structure is meant to ensure temporary mechanical support, while a bioactive gelatin-chitosan hydrogel is incorporated to provide a better environment for cell adhesion and proliferation. The scaffolds present a core-shell structure, in which the lattice core is realized by additive manufacturing, while the shell is nested throughout the core by grafting and crosslinking a hydrogel forming solution. After subsequent freeze-drying, the hydrogel network forms a highly interconnected porous structure that completely envelops the poly(lactic acid) core. Thanks to this strategy, it is easy to tailor the scaffold properties for a specific target application, by properly designing the lattice geometry and the core/shell ratio, which are found to significantly affect the scaffold mechanical performance and its bioresorption. Compression stiffness and strength provided by poly(lactic acid) lattices are overall within the range of values displayed by human bone tissue and remain stable after prolonged immersion in water at body temperature for several weeks. On the other hand, the hydrogel undergoes gradual and homogeneous degradation over time, but the core-shell integrity and structural stability are nevertheless maintained during at least 7-week hydrolytic degradation tests. In vitro experiments with human mesenchymal stromal cells reveal that the core-shell scaffolds are biocompatible and their physical-mechanical properties and architecture are suitable to support cell growth and osteogenic differentiation, as demonstrated by hydroxyapatite formation. These results suggest that the bioresorbable core-shell scaffolds can be considered, and further studied, in view of clinically relevant endpoints in bone regenerative medicine.

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.

Blood testing is a crucial application in the field of clinical studies for disease diagnosis and screening, biomarkers discovery, organ function assessment, and personalized medication. Therefore, it is of utmost importance to collect precise data in a short time. In this study, we utilized Raman spectroscopy to analyze blood samples and extracted comprehensive biological information, including the primary components and compositions present in the blood. We conducted short-wavelength (532 nm green light) Raman scattering spectroscopy on blood samples, plasma, and serum, and subsequently analyzed the biological characteristics detected in each sample type. Our results indicated that whole blood had high hemoglobin content, which suggests that hemoglobin is a major component of blood. The characteristic Raman peaks of hemoglobin were observed at 690, 989, 1015, 1182, 1233, 1315, and 1562–1649 cm−1. Analysis of plasma and serum samples indicated the presence of β-carotene, which exhibited characteristic peaks at 1013, 1172, and 1526 cm−1. Additionally, in the field of medical blood testing, the novel 3D Silicon micro-channel device technology holds immense potential. It can serve as a substrate and helps to detect various diseases and biomarkers, providing real-time data to help medical professionals and patients better understand their health conditions. Changes in biological data collected in this manner could potentially be used to diagnose clinical diseases.

This article addresses the need to know the thermal conductivity in different filaments that this FDM technology uses. Because there are multiple applications that these additive manufacturing products play in the field of thermal insulation. For the study of thermal conductivity, the DTC-25 commercial conductivity measurement bench is used, where the tests will be carried out on a set of seven different materials with 100% fabrication density. From base materials such as acrylonitrile butadiene styrene (ABS) or polylactic acid (PLA), materials of high mechanical and thermal resistance, polyether ether ketone (PEEK) and high-performance polyetherimide thermoplastic (ULTEM), to materials with metal inclusions (aluminum 6061) that would later be subjected to thermal aftertreatments. The study shows how the parts manufactured with aluminum inclusion have a higher thermal conductivity, 0.40 ±0.05 W/m·K, compared to another material, such as TPU, of high mechanical and thermal resistance, with a conductivity of 0.26 ±0.05 W/m·K.

(1) Background: Type-2 Diabetes (T2DM) is a long-term medical disorder characterized by Insulin deficiency and high blood glucose levels. Among other medication to cure T2DM, the review of the literature found that various Pyrimidine derivative act as an agonist for G-protein-coupled receptor 119 (GPR119) was proposed to control blood glucose levels by enhancing the function of pancreatic beta-cells and its mechanism of action with fewer adverse effects.; (2) Methods: In the present research work, in-silico investigations were carried out to investigate the potential of Pyrimidine analogue as an agonists to the protein target GPR119 receptor. We performed exhaustive molecular modelling and protein modelling methodologies such as homology mod-elling, molecular docking along with various drug designing tools such as 3D-QSAR and pharmacophore mapping to ascertain the design of better GPR119 agonists.; (3) Results: On the basis of in-depth computa-tional studies, we designed new pyrimidine moiety and analyzed them for GPR-119 receptor agonist and fur-ther explored the ADME properties. Designed compounds found to exhibit better predicted activities as com-pared to reference compound; (4) Conclusions: The current research on pyrimidine derivatives, using molec-ular docking, 3D-QSAR and Pharmacophore mapping demonstrated that the obtained computational model has significant properties and the designed molecules and Dataset from this model, produced antidiabetic compound against the target GPR119 i.e., compound 1S, 1Z and 1D with the docking score of −11.696, -9.314 and -8.721 respectively. The pharmacokinetics and drug-likeness studies revealed that these compounds may be the future candidate for the treatment of diabetes acting via GPR119 agonist mechanism.

Robin sequence is a congenital anomaly characterized by a triad of features that include micrognathia, glossoptosis, and airway obstruction. This comprehensive historical review maps the evolution of approaches and appliances for its treatment from the past until current modern possibilities of interdisciplinary combination of modern engineering, medicine, materials, and computer science combined approach with emphasis to design appliances inspired by nature - individual human anatomy. Current biomimetic designs are clinically applied resulting in appliances that are more efficient, comfortable, sustainable, and safer than legacy traditional designs. Review maps the treatment modalities that have been used for patients with Robin sequence over the years. Early management of Robin sequence focused primarily on airway maintenance and feeding support, while current management strategies involve both nonsurgical and surgical interventions and biomimetic biocompatible personalized appliances. The goal of this paper was to provide a review of the evolution of management strategies for patients with Robin sequence that led to the current interdisciplinary biomimetic approaches impacting the future of Robin Sequence treatment with biomimetics at the forefront.

The aim of this study is to introduce and evaluate a new approach by using 3D printed anthropomorphic breast phantoms in teaching X-ray mammography techniques Radiologic technologists. For this purpose, a physical anthropomorphic breast phantom is created, based on a computational breast version. The phantom is created by a stereolithography 3D printer. The practical exercises were conducted in three sessions with the participation of radiographers students first, second and third year of training, respectively. A survey was prepared to summarise the participants´ opinion about this new form of training in mammography technique. A total of 83 students were trained with the new approach. From these 52 responded to the survey questions. More than half of the students (71.2%) successfully handled the exercise with the physical breast phantom. The training provoked a substantial number of students to express the belief that incorporating modern methods based on digital technologies into their X-ray device training is essential. The instructor was well prepared and with the needed competence. The experience within this training convinces the future professionals to introduce the new technologies in their routine work, particularly for exercising the compression technique and breast positioning.

Unmanned aerial vehicles (UAV) have emerged as a solution to day to day survey tasks, allowing users to visualize phenomena in real-time. This paper explores the capabilities of UAV or drones in the collection of accurate, geo-tagged data quickly, including photogrammetry software processes to deliver standardized data output. In order to explore the capabilities of UAV, Gatu Township in Centenary, Muzabani District of Zimbabwe was chosen from the national mapping topographic series. This study demonstrates the efficiency of data collection using drones, generate 2D orthomosaics in real time, so that analysts can easily visualize land cover and identify any changes, map and model large areas to produce data for 2D and 3D models. The recent development of innovative optical image processing has further lowered the costs high resolution topographic surveys.

This paper presents the use of Graph Neural Networks (GNNs) to predict the tensile strength of Fused Deposition Modeling (FDM) specimens. In the present work, there are four main input parameters i.e. Infill percentage, Layer height, Print speed and Extrusion temperature while the Tensile Strength is an output parameter were considered. This study includes use of central composite design based response surface methodology to finalize the experimental layout. 3D printed specimen were manufactured as per the ASTM E8 standard on FDM printer using Polylactic Acid (PLA) as filament. Micro-tensile test were performed on the printed specimen as per ASTM E8 standard. The GNN algorithm was trained on a dataset of FDM specimens, achieving a mean squared error (MSE) of 2.47, mean absolute error (MAE) of 1.14, and R-squared value of 0.78. An adjacency matrix, which shows the connections between nodes in a graph. The obtained plot for nodes and weights in a GNN provide valuable information about the model and its performance. The results show the potential of using GNNs in predicting the mechanical properties of additively manufactured specimens and provide a promising direction for further research in this field.

The two-phase flow of water and reactive gas in the channel of proton exchange membrane fuel cell (PEMFC) plays an important role in high-quality water management. In this study, the removal effect of 3D wave channel and 2D straight channel for liquid water was studied by volume of fluid method. The dynamic behavior of droplet emerge from the gas diffusion layer (GDL) into the channel under the influence of gas flow was investigated. The effects of droplet growth, deformation, detachment, force, pore size on water critical behavior and water content in the channel are discussed. The results show that the 3D wave channel is superior to the removal of liquid water than the 2D straight channel. The increase of velocity is conducive to the discharge liquid water. While infinite increase of velocity will cause more parasitic power loss. The larger pore size of GDL is not advantageous to the performance of PEMFC, but the appropriate increase of pore size is conducive to the discharge of liquid water. The basic knowledge obtained in this study will help to deepen the understanding of droplet dynamics in PEMFC gas channels, and help to optimize the design and working conditions of these channels.

The paper presents the conceptualization and realization of a novel platform for additive manu-facturing, an industrial robot arm-based system for additive manufacturing applications. Tradi-tional 3D printers, especially those employing fused deposition modelling (FDM) processes, are restricted to depositing material in a single toolpath plane (e.g. x-y plane). The focus of this study was to explore the feasibility of integrating commercial off the shelf (COTS) additive manufac-turing technologies with a six degree of freedom industrial robot arm to yield a 3D additive manufacturing system with the capability to perform free-form six degree of freedom fused deposition modelling. The present paper presents the development of a platform from stage 0, i.e. materials to its use, and finally a printed product with the developed extruder.

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