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

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

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

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

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

Radar observation data with high temporal and spatial resolution are used in the data assimilation experiment to improve precipitation forecast of a numerical model. The numerical model considered in this study is Weather Research and Forecasting (WRF) model with double-moment 6-class microphysics scheme (WDM6). We calculated radar equivalent reflectivity factor using higher resolution WRF and compared with radar observations in South Korea. To compare the precipitation forecast characteristics of three-dimensional variational (3D-Var) assimilation of radar data, four experiments are performed based on different precipitation types. Comparisons of the 24-h accumulated rainfall with Automatic Weather Station (AWS) data, Contoured Frequency by Altitude Diagram (CFAD), Time Height Cross Sections (THCS), and vertical hydrometeor profiles are used to evaluate and compare the accuracy. The model simulations are performed with and with-out 3D-VAR radar reflectivity, radial velocity and AWS assimilation for two mesoscale convective cases and two synoptic scale cases. The radar data assimilation experiment improved the location of precipitation area and rainfall intensity compared to the control run. Especially, for the two convective cases, simulating mesoscale convective system was greatly improved.

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

Three-dimensional (3D) printing techniques have received considerable focus in the area of bone engineering due to its precise control in the fabrication of complex structures with customizable shapes, internal and external architectures, mechanical strength, and bioactivity. In this study, we design a new composition biomaterial consisting of polylactic acid (PLA), and halloysite nanotubes (HNTs) loaded with zinc nanoparticles (PLA+H+Zn). The hydrophobic surface of the 3D printed scaffold was coated with two layers of fetal bovine serum (FBS) on the sides and one layer of NaOH in the middle. Additionally, a layer of gentamicin was coated on the outermost layer against bacterial infection. Scaffolds were cultured in standard cell culture medium without the addition of osteogenic medium. This surface modification strategy improved material hydrophilicity and enhanced cell adhesion. Pre-osteoblasts cultured on these scaffolds differentiated into osteoblasts and proceeded to produce a type I collagen matrix and subsequent calcium deposition. 3D printed scaffolds formed from this composition possessed high mechanical strength and showed an osteoinductive potential. Furthermore, the external coating of antibiotics not only preserved the previous osteogenic properties of the 3D scaffold but also significantly reduced bacterial growth. Our surface modification model enabled the fabrication of a material surface that was hydrophilic and antibacterial, simultaneously, with an osteogenic property. The designed PLA+H+Zn may be a viable candidate for the fabrication of customized bone implants.

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

AbstractWhile the technology is relatively new, low cost 3D printing has impacted many aspects of human life. 3D printers are being used as manufacturing tools for a wide variety of devices in a spectrum of applications ranging from diagnosis to implants to external prostheses. The ease of use and availability of 3D design software and low cost has made 3D printing an accessible manufacturing and fabrication tool in many research laboratories. 3D printers can print materials with varying density, optical character, strength and chemical properties providing platforms for a huge number of strategies that can be chosen for user’s needs. In this review, we focus on applications in biomedical diagnostics and how this revolutionary technique is facilitating development of low cost, sensitive and often geometrically complex tools. 3D printing in fabrication of microfluidics, supporting equipment, optical and electronic components of diagnostic devices is presented. Emerging diagnostic 3D bioprinting as a tool to incorporate living cells or biomaterials into 3D printing is also discussed.

This study aimed to assess the response of 3D printed PLA scaffolds biomimetically coated with apatite on human primary osteoblast spheroids and evaluate the biological response to its association with Bone Morphogenetic Protein 2 (rhBMP-2) in rat calvaria. PLA scaffolds were produced via 3D printing, soaked in simulated body fluid (SBF) solution, and characterized by physical-chemical, morphological, and mechanical properties. The in vitro biological response was assessed with human primary osteoblast (HOb) spheroids. The in vivo analysis was conducted through the implantation of 3D printed PLA scaffolds either alone, covered by apatite (PLA-CaP) or PLA-CaP loaded with rhBMP-2 (PLA-CaP+rhBMP-2) on critical-sized defects (8 mm) of rat calvaria. Increased cell adhesion and in vitro release of growth factors (PDGF, bFGF, VEGF) was observed for PLA-CaP scaffolds when pre-treated with FBS. PLA-CaP+BMP2 presented higher values of newly formed bone (NFB) than other groups at all experimental periods (p<0.05), attaining 44.85% of NFB after 6 months. These findings indicate that functionalization of PLA scaffolds with biomimetic apatite can improve its biological properties in the presence of complex biological media. Its association with BMP2 may enhance bone repair, suggesting this strategy as a promising candidate for bone tissue engineering.

In recent decades, perovskite-type compounds (ABB′O3) have been exhaustively studied due to their unique ferroelectric properties. In this work, a systematic study aiming to prepare fine particles in the binary system SrZrO₃–SrTiO₃ was conducted under hydrothermal conditions in a KOH (5 M) solution at 200 °C for 4 h under a constant stirring speed of 130 rpm. The precursors employed were SrSO₄ powder (< 38 μm size) and coprecipitated hydrous gels of Zr(OH)₄•9.64 H₂O (Zr-gel) and Ti(OH)₄•4.5H₂O (Ti-gel), which were mixed according to the stoichiometry of the SrZr_1-xTixO₃ in the compositional range of 0.0>x>100.0 mol% Ti⁴⁺. The XRD results revealed the formation of two crystalline phases rich in Zr⁴⁺, an orthorhombic structured SrZr0.93Ti0.07O3 and a cubic structured SrZr0.75Ti0.25O3 within the compositional range of 0.1–0.5 mol of Ti4+. A cubic perovskite-structured solid solution, SrTi1-xZrxO3, was preferentially formed within the compositional range of 0.5>x>0.1 mol% Ti⁴⁺. The SrZrO₃ and SrZr_0.93Ti_0.07O₃-rich phases had particle sizes averaging 3 m with a cubic morphology. However, a remarkable reduction in the particle size occurred on solid solutions prepared with hydrous Ti-gel over contents of 15 mol% Ti⁴⁺ in the reaction media, resulting in the formation of nanosized particles agglomerates with cuboidal shape self-assembled via a 3D hierarchical architecture, the sizes of these particles varied in the range between 141.0–175.5 nm. The limited coarsening of the particles is discussed based on the Zr-gel and Ti-gel dehydration capability differences that occurred under hydrothermal processing.

Alunogen, Al2(SO4)3·17H2O, occurs as an efflorescent in acid mine drainage, low-temperature fumarolic or pseudofumarolic (at coal fires) terrestrial environments. It is considered as one of the main Al-sulfates of Martian soils demanding comprehensive crystal chemical data of natural terrestrial samples. However, structural studies of natural alunogen were carried out in 1970s without localization of H atoms and have not previously been performed for samples from geothermal fields, despite the fact that these environments are considered as proxies of the Martian conditions. The studied alunogen sample comes from Verkhne-Koshelevsky geothermal field (Koshelev volcano, Kamchatka, Russia). Its chemical formula is somewhat dehydrated, Al2(SO4)3×15.8 H2O. The crystal structure was solved and refined to R1 = 0.068 based on 5112 unique observed reflections with I > 2σ(I). Alunogen crystalizes in P-1 space group, a = 7.4194(3), b = 26.9763(9), c = 6.0549(2) Å, α = 90.043(3), β = 97.703(3), γ = 91.673(3) °, V = 1200.41(7) Å3, Z = 2. The crystal structure consists of isolated SO4 tetrahedra, Al(H2O)6 octahedra and H2O molecules connected by hydrogen bonds. The structure refinement includes Al, S and O positions that are similar to previous structure determinations and thirty-four H positions localized for the natural sample first. The study also shows the absence of isomorphic substitutions in the composition of alunogen despite the iron-enriched environment of mineral crystallization. The variability of the alunogen crystal structure is reflected in the number of “zeolite” H2O molecules and their splitting. The structure complexity of alunogen and its modifications ranges from 333-346 bits/cell for models with non-localized H atoms to 783-828 bits/cell for models with localized H atoms. The higher values correspond to higher hydration state of alunogen.

Utilization of Bidirectional Reflectance Distribution Function (BRDF) model parameters obtained from the multi-angular remote sensing is one of the approaches for the retrieval of vegetation structural information. In this research, the potential of multi-angular vegetation indices, formulated by the combination of multi-spectral reflectance from different view angles, for the retrieval of forest above ground biomass was assessed. This research was implemented in the New England region with the availability of a high quality forest inventory database. The multi-angular vegetation indices were generated by the simulation of the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF/Albedo Model Parameters Product (MCD43A1 Version 6) based BRDF parameters. The effects of seasonal (spring, summer, autumn, and winter) composites of the multi-angular vegetation indices on above ground biomass, angular relationship of the spectral reflectance with above ground biomass, and the interrelationships between the multi-angular vegetation indices were analyzed. Among the existing multi-angular vegetation indices, only the Nadir BRDF-adjusted NDVI ( and Hot-spot incorporated NDVI ( showed significant relationship (more than 50%) with the above ground biomass. This research proposed two more sensitive vegetation structural indices, Fore-scattering Back-scattering NDVI and Vegetation Structure Index (VSI). The Fore-scattering Back-scattering NDVI showed higher sensitivity (R² = 0.62, RMSE = 52.46) towards the above ground biomass than existing multi-angular vegetation indices. Furthermore, the VSI performed in the most efficient way explaining 64% variation of the above ground biomass, suggesting that the right choice of the spectral channel and observation geometry should be considered for improving the estimates of the above ground biomass. In addition, the right choice of seasonal data (summer) was found to be important for estimating the forest biomass while other seasonal data were either insensitive or pointless. The promising results shown by the VSI suggest that it could be an appropriate candidate for monitoring vegetation structure from the multi-angular satellite remote sensing.

Currently, the number of approved veterinary medicines are limited, and human medications are used off-label. These approved human medications are of too high potencies for a cat or a small dog breed. Therefore, there is a dire demand for smaller doses of veterinary medicines. This study aims to investigate the use of three semi-solid extrusion 3D printers in a pharmacy or animal clinic setting for extemporaneous manufacturing of prednisolone containing orodispersible films for veterinary use. Orodispersible films with adequate content uniformity and acceptance values defined by the European Pharmacopoeia was produced with one of the studied printers, namely, the Allevi 2 bioprinter. Smooth and flexible films, with high mechanical strength, neutral pH, and low moisture content were produced with high correlation between prepared design and obtained drug amount, indicating that the Allevi 2 printer could successfully be used to extemporaneously manufacture personalized doses for animals at the point-of-care.

Direct laser writing three-dimensional nano-lithography is an established technique for manufacturing functional 3D micro- and nano-objects via non-linear absorption induced polymerization process. In this Chapter an underlying physical mechanisms taking place during nano-confined polymerization reaction, induced by tightly focused ultra-short laser pulses, are reviewed and discussed. The special attention is paid on the effects that directly impact structuring resolution and minimum achievable feature size. Analysis of possible photo-initiation mechanisms as contributing multi-photon absorption and avalanche ionization in pre-polymers under diverse exposure conditions (wavelength, pulse duration) is presented. Feasible structuring of pure (non-photosensitized) and functional nanoparticles doped polymer precursors is justified and benefits of such materials/structures for microoptics, photonics and cell scaffolds are highlighted. The influence of temperature effects (induced by writing process itself or determined by ambient conditions) on polymerization process, observed in different pre-polymers under diverse exposure regimes is outlined. The further adjustment of the structuring resolution is possible via precise control of light polarization and diffusion assisted radical quenching. The work is concluded with a brief outlook on future challenges and perspectives related to refinement of 3D ultra-fast laser lithography fabrication process in the means of application of diverse post-processing methods and research into novel photo-curable materials including inorganic ones.

3D meso-scale structures that can reach up to centimeters in overall size but retain micro- or nano-features, proved to be promising in various science fields ranging from micro-mechanical metamaterials to photonics and bio-medical scaffolds. In this work we present synchronization of the linear and galvano scanners for efficient femtosecond 3D optical printing of objects at the meso-scale (from sub-μm to sub-cm spanning five orders of magnitude). In such configuration the linear stages provide stitch-free structuring at nearly limitless (up to tens-of-cm) working area, while galvo-scanners allow to achieve translation velocities in the range of mm/s-cm/s without sacrificing nano-scale positioning accuracy and preserving undistorted shape of the final print. The principle behind this approach is demonstrated, proving its inherent advantages in comparison to separate use of only linear stages or scanners. The printing rate is calculated in terms voxels/s, showcasing the capability to maintain an optimal feature size while increasing throughput. Full capabilities of this approach are demonstrated by fabricating structures that reach millimeters in size but still retain μm-scale features: scaffolds for cell growth, microlenses and photonic crystals. All this is combined into a benchmark structure: a meso-butterfly. Provided results show that synchronization of two scan modes is crucial for the end goal of industrial-scale implementation of this technology and makes the laser printing well aligned with similar approaches in nanofabrication by electron and ion beams.

Hepatitis C virus (HCV) is a major medical health burden and leading cause of chronic liver disease and cancer worldwide. More than 58 million people are chronically infected with HCV, with 1.5 million new infections occurring each year. An effective HCV vaccine is a major public health and medical need as recognized by the World Health Organization. However, due to the high variability of the virus and its ability to escape the immune response, HCV rapidly accumulates mutations making a vaccine a formidable challenge. An effective vaccine must elicit broadly neutralizing antibodies (bnAbs) in a consistent fashion. After decades of studies from basic research through clinical development, the antigen of choice is considered to be the E1E2 envelope glycoprotein due to conserved, broadly neutralizing antigenic domains located in the constituent subunits of E1, E2, and the E1E2 heterodimeric complex itself. The challenge has been elicitation of robust humoral and cellular responses leading to broad virus neutralization due to the relatively low immunogenicity of this antigen. In view of this challenge, structure-based vaccine design approaches to stabilize key antigenic domains have been hampered due to the lack of E1E2 atomic-level resolution structures to guide them. Another challenge has been development of a delivery platform in which a multivalent form of the antigen can be presented in order to elicit a more robust anti-HCV immune response. Recent nanoparticle vaccines are gaining prominence in the field due to their ability to facilitate a controlled multivalent presentation and trafficking to lymph nodes, where they can interact with both the cellular and humoral components of the immune system. This review focuses on recent advances in understanding the E1E2 heterodimeric structure to facilitate a rational design approach and the potential for development of a multivalent nanoparticle-based HCV E1E2 vaccine. Both aspects are considered important in the development of an effective HCV vaccine that can effectively address viral diversity and escape.

Soil structure is a sensitive and dynamic soil physical property which responds rapidly to different tillage systems, and thus it requires constant monitoring and evaluation. The visual evaluation of soil structure (VESS) and subsoil visual evaluation of soil structure (SubVESS) methods were used to assess the soil structure quality of clayey soils subjected to different tillage systems. The tillage systems were no-tillage (NT), conventional tillage (CT) and virgin land (VG). The study was conducted at Tshivhilwi and Dzingane in Thohoyandou, Vhembe District, Limpopo Province, South Africa. The NT system was practised for 8 and 40+ years at Tshivhilwi and Dzingahe, respectively. The results showed no impact of tillage system on both VESS and SubVESS at Tshivhilwi. The soil structure quality at Tshivhilwi as determined by VESS and SubVESS were found to be poor. However, at Dzingahe, both the VESS and SubVESS responded to the impact of tillage. At Dzingahe VESS showed a fair (Sq = 2.25) soil structural quality in the NT system, poor (Sq = 3.57) in the CT system and moderately poor (Sq = 3.05) in the VG. Similarly, at the same location the SubVESS scores were moderately good in the NT system, moderately poor for CT system and fair in the VG. The differences in the response of the VESS and SubVESS at the two locations were attributed to the differences in the duration at which the NT systems were practised. The VESS and SubVESS results were supported by selected measured soil physicochemical properties such as bulk density and porosity. In conclusion, the findings of this study showed that the VESS and SubVESS were able to effectively differentiate the impact of tillage systems on soil structural quality in clayey soils where NT was practised for a long period (40+ years) while it could not where NT was practised for a few years (8 years).

Multipactor is a common discharge phenomenon occurred in space microwave systems. The surface microstructure has been verified to be effective to mitigate multipactor. In this work, we design a square coaxial low-pass filter (SCLPF) with dielectric sheets loaded to check the multipactor dependence on the structure parameters of the loaded dielectric sheets, and further model groove structures on the sensitive area surface to lower the risk of multipactor. Simulation results indicate that the SCLPF loaded with alumina and PTFE exhibits good operational characteristics, and the multipactor threshold is significantly improved after introducing the surface grooves. Then we investigate the effects of three typical groove parameters, groove depth, groove number, and aspect ratio, on the multipactor threshold of the SCLPF device. The results show that the multipactor threshold raise at first as the groove number and groove depth increase, and then the threshold reaches a saturation status. For a deeper analysis of multipactor, we discuss how the grooves shelter the secondary electrons, and further mitigate the electron avalanche. Furthermore, the mechanisms of threshold saturation under the effect of groove parameters are analyzed in detail, and a contour map for the multipactor threshold of PTFE-loaded SCLPFs is given, which makes significant sense for predicting the multipactor threshold of the devices with its sensitive surface being grooved. The regularity of modulating the multipactor threshold by the groove structures obtained in this study is of engineering significance for suppressing multipactor in microwave devices in practical applications.

With the rapid development of the Internet industry, the problem of information overload has arisen due to the abundance of information available online. Recommendation algorithms, as the core of recommendation systems, have been attracting much attention and are a hot topic of research for many experts and scholars. The classical recommendation algorithms are mainly divided into three major categories: collaborative filtering recommendation algorithms, content-based recommendation algorithms, and hybrid-based recommendation algorithms. Although these algorithms are widely used in various fields, with the proliferation of information, these traditional recommendation algorithms are no longer able to meet the needs of the times. To address this issue, recommendation systems have been developed to provide users with personalized and relevant information or products. Despite the wide use of recommendation algorithms, such as collaborative filtering, content-based filtering, and hybrid approaches, traditional recommendation algorithms have limitations and are no longer suitable for meeting the demands of the times. This paper proposes a new recommendation algorithm, SFRRG, that fuses structure and feature information in graph neural networks to improve the performance of the recommendation system in rating prediction. The effectiveness of the proposed algorithm is demonstrated through experiments on various data sets and compared with existing recommendation algorithms.

The determination of the three-dimensional structure is a key step for the identification of new targets as well as the rational design of bioactive compounds. Herein, we report the synthesis and the structural elucidation of novel tetrameric macrocycles. Measurements were taken in solid and solution states with the help of X-ray scattering and NMR spectroscopy. The investigations made will help to find diverse applications for this new, promising compound class.

Due to the vast conformational space proteins can adopt, accurate and efficient prediction of protein structure remains still a challenging task, coupled with the intricacies of interatomic interactions and the limitations of current computational models in effectively navigating this complex molecular landscape. Additionally, the lack of comprehensive experimental data for all protein structures further exacerbates the difficulty in reliable machine learning-based prediction of the three-dimensional conformations of the proteios building block of life. Geometrically, Cartesian coordinate system (CCS, X, Y and Z) and spherical coordinate system (SCS, ρ, θ and φ) are two interconvertible coordinate systems, and are like two sides of one coin. Since the beginning of Protein Data Bank (PDB) in 1971, CCS has been the default approach to specify atomic positions with X, Y and Z in PDB. In this manuscript, therefore, I present a novel method for the reversible spherical geometric conversion of protein backbone structure coordinate matrices to three independent vectors: ρ, θ and φ. This reversible conversion facilitates lossless extraction of essential structural features from protein backbone structural data, enabling the development of advanced novel algorithms for protein structure prediction in future. In short, this inter-atomic SCS approach offers a comprehensive yet efficient means of representing protein backbone geometry, leveraging spherical coordinates to capture spatial relationships in a compact and intuitive inter-atomic manner, and to provide a robust framework for reversible feature extraction for the ongoing efforts in advancing the field of protein structure prediction, the holy grail of computational structural biology.

This paper introduces an innovative approach to numerically model Structure-Soil-Structure Interaction (SSSI) by integrating the Boundary Element Method (BEM) and the Finite Element Method (FEM) in a coupled manner. To assess the accuracy of the proposed method, a comparative study is undertaken, comparing its outcomes with those generated by the conventional FEM technique. Alongside accuracy, the computational efficiency aspect is crucial for the analysis of large-scale SSSI problems. Hence, the computational performance of the coupled BEM-FEM method undergoes a thorough examination and is compared with that of the standalone FEM method. The results from these comparisons illustrate the superior capabilities of the proposed method in comparison to the FEM method. The novel approach provides more reliable results compared to traditional FEM methods, serving as a valuable tool for engineers and researchers involved in structural analysis and design.

This paper investigates the hydroelastic responses of offshore floating solar photovoltaic farms (OFPVs) to minimize structural motion. The OFPV usually occupies a large sea space in the order of hectares and due to its huge structural length-to-thickness ratio, the structural deformation under wave action has to be taken into consideration. The flexible deformation of the structure under hydrodynamic loading is termed the hydroelastic response. Due to the relatively long structural length with respect to the encountering wavelength, the diffraction and radiation of waves have to be taken into account to accurately represent the hydrodynamic loadings on the floating platform. The numerical model is first validated by comparing the eigenvalues and eigenvectors of the OFPV obtained from the proposed numerical scheme with their counterparts obtained from an established finite element software. This is followed by the investigation of the hydroelastic response of various OFPVs designed in varying layout configurations. The various layout configurations are obtained by altering the floating modular units’ dimensions as well as the spacing of the OFPVs when deployed adjacent to each other. The optimal configuration that gives the best performance in terms of the overall smallest response, known as compliance, is then suggested. The results suggest that a longish OFPV layout has a lower hydroelastic response and the motion could be further reduced by increasing the global flexural stiffness via layout arrangement.

In this research, a design method for the graded triply periodic minimal surface (TPMS) structures with lightweight, high-strength, and high sound absorption properties is proposed. The graded TPMS structures are controlled by linear, quadratic, and sine functions. Uniform TPMS and graded TPMS were manufactured by laser powder bed fusion (LPBF) with AlSi7Mg powder, and an acoustic impedance tube test, compression test, and digital image correlation (DIC) test were ap-plied to obtain the sound absorption and compression properties. The sound absorption coefficient of a uniform Gyroid increases as the number of layers and surface thickness increase, and it in-creases as element size decreases. The sound absorption peak shifts to low frequencies as the number of layers increases. The sound absorption property of Type-Ⅰ graded TPMS is superior to the Type-Ⅱ, and the G-LinearⅠ has the highest sound absorption properties among the three functions. It reveals that the graded TPMS has superior sound absorption performance at low and medium frequencies. The compression and DIC results of graded TPMS also show excellent mechanical properties and energy absorption characteristics.

By taking advantage of a stability criterion established recently, the critical temperature T_c is reckoned with help of the microscopic parameters, characterising the normal and superconducting electrons, namely the independent-electron band structure and a repulsive two-electron force. The emphasis is laid on the sharp T_c dependence upon electron concentration and inter-electron coupling, which might offer a practical route toward higher T_c values and help to understand why high-T_c compounds exhibit such remarkable properties.

In the Standard Model of elementary particles, the rest mass, magnetic moment and electric charge of the electron are considered to be natural constants. In this article it is proposed that these properties can be calculated in a simple way from the corresponding Planck units using the well-known period doubling phenomenon in nonlinear dynamical systems. Periods corresponding to the values of the electron and positron properties belong to a subset of stable periods. The periodic structures of the rest energy and magnetic moment consist of three internal degrees of freedom, whereas the Coulomb energy of the electric charge consists of four. The number of period doublings for the elementary charge determines the value of the fine structure constant alpha.

Transient flows result in unbalanced forces and high pressure in pipelines. Under these conditions, the combined effects of flow-induced forces along with sudden pipe displacements can create cracks in the pipeline, especially at the junctions. This situation consequently results in water leakage and reduced operational efficiency of the pipeline. In this study, displacements and stresses in a buried pressurized water transmission pipe installed by pipe jacking method are investigated using numerical modeling and considering interactions between fluid, pipe, and soil. The analyses were performed consecutively under no-flow, steady flow, and transient flow conditions, in order to investigate the effects of flow conditions on displacements and stresses in the system. Analyses of the results show that displacements and stresses in the jointed concrete pipes are significant under transient flow conditions. Moreover, because of pressure transient effects, maximum tensile stresses exceed the tensile strength of concrete at the junctions, leading to cracks and consequent water leakage.

In the last decade, three-dimensional (3D) printing has allowed the field of complex microfluidic channels to expand rapidly towards channels with variable cross-sections (i.e., beyond simple rounded media with a constant diameter) and channels. Whose trajectory can be outside a single plane and has gained numerous macro- and nanoscale manufacturing advances. Three-dimensional printing is being explored for various biomedical applications and the fabrication of nanomedicines using additive manufacturing techniques. Employing 3D-printed templates for macro-to-micro interfacing, a passively operated microfluidic device was designed. The research seeks to fabricate a biodevice that enables insulin microdosing, creating a subsystem like a microvalve and a microchannel matrix using additive manufacturing techniques. Our systems feature designs that enhance fluid dynamics without affecting the stability of the insulin. We propose using Humalog insulin in tropical climates (up to 30°C) without refrigeration for 28 days. The microvalve has a spiral trajectory with four outlet channels distributed along it. These channels align with the microchannels organized in a 10 mm x 15 mm matrix with 25 microchannels, each with a 770 µm internal diameter. The system delivers a dose of 2,3 mL in 6 minutes. We designed these systems for insulin micro-dosing, but they can also serve similar devices for other drugs.

Three-dimensional flexible piezoresistive porous sensors have been used in health diagnosis and wearable devices. By utilizing 3D printed sacrificial mold casting with highly conductive polymer composites, porous sensors with high conductivity and complex structures were achieved. Traditional conductive polymer composites are usually heated using external heat sources, which are time and energy consuming. However, in this study, conductive porous sensors with triply periodic minimal surface (TPMS) structures were manufactured using self-resistance electric heating by utilizing the conductive nature of the polymers. The porous structures were designed based on Diamond (D), Gyroid (G), and I-WP (I) unit cells of the TPMS. The use of self-resistance electric heating has improved the compression performance and piezoresistive response of the structures. Among these structures, the D-based structure exhibited the maximum response strain (61 %), with a corresponding resistance response value of 0.97, which increased by 10.26 % compared to that of the structures heated by using the external heat sources. This study offers a new perspective on designing and optimizing porous materials with specific functionalities, particularly in the realm of flexible and portable piezoresistive sensors.

Microspheres, synthesized from diverse natural or synthetic polymers, are readily utilized in biomedical tissue engineering to improve the healing of various tissues. Their ability to encapsulate growth factors, therapeutics, and natural biomolecules, which can aid tissue regeneration, makes microspheres invaluable for future clinical therapies. While microsphere-supplemented scaffolds have been investigated, a pure microsphere-based scaffold with an optimized architecture has been challenging to create via 3D printing methods due to issues that prevent consistent deposition of microsphere-based materials and their ability to maintain the shape of the 3D-printed structure. Utilizing the extrusion printing process, we established a methodology which not only allows to create large microsphere-based scaffolds but also multicomposite matrices into which cells, growth factors, and therapeutics encapsulated in microspheres can be directly deposited during the printing process. Our 3D-McMap method addresses issues with scaffold shape fidelity during and after printing. Carefully timed breaks, minuscule drying steps, and adjustments to extrusion parameters, generated an evenly layered large microsphere-based scaffold that retains its internal architecture. Such scaffolds are superior to other microsphere-containing scaffolds, as they can release biomolecules in a highly controlled spatiotemporal manner. This capability permits to study cell responses to the delivered signals, to develop scaffolds that precisely modulate new tissue formation.

Bismaleimide (BMI) is a high-performance thermosetting resin widely used in the aerospace, automotive, and mechanical and electronics industries due to its chemical and mechanical stability. It also has the capability of being used as an ink in polyjets used for 3D printing evident from thinner mellamide FTIR bands and faster curing rates as observed from TGA-DSC studies.

To improve the measurement accuracy of three-dimensional rotation angle of the spherical joint, a novel approach is proposed in this study, which combines the magnetic detection by Hall sensor and surface feature identification by eddy current sensor. Firstly, a permanent magnet is embedded in the ball head of spherical joint, and Hall sensors are set and distributed in the ball socket to measure the variation of magnetic flux density when spherical joint rotating, which are related to 3D rotation angle. In order to further improve measurement accuracy and robustness, we also set grooves on the ball head and use eddy current sensors to synchronously identify the rotation angle of the ball head. After the combination of two signals is adopted, a measurement model is established using the RBF neural network by training, and realized real-time measurement of the 3D rotation angle of spherical joint. The feasibility and superiority of this method are validated through experiments. The experimental results indicated that the measurement accuracy is promoted substantially compared to the preliminary measurement scheme based on spherical coding, the average measurement error of single axis is reduced by 9'9". The root mean square errors for the measurement of 3D rotation angles in this proposed method are as follows: the pitch angle α has an error of 1'8", the yaw angle β has an error of 2'15", and the roll angle γ has an error of 29'6".

With increasing demand from unmanned driving and robotics, more attention has been paid to point cloud-based 3D object accurate detection technology. However, due to the sparseness and irregularity of the point cloud, the most critical problem is how to utilize the relevant features more efficiently. In this paper, we proposed a point-based object detection enhancement network to improve the detection accuracy in the 3D scenes understanding based on the distance features. Firstly, the distance features are extracted from the raw point sets and fused with the raw features about reflectivity of the point cloud to maximizing the use of information in point cloud. Secondly, we enhanced the distance features and raw features that we collectively refer to them as self-features of the key points in Set Abstraction (SA) layers with the self-attention mechanism, so that the foreground points can be better distinguished from the background points. Finally, we revised the group aggregation module in SA layers to enhance the feature aggregation effect of key points. We conducted experiments on the KITTI dataset and nuScenes dataset and the results show the enhancement method proposed in this paper has excellent performance.

In the realm of autonomous vehicle environment perception, the primary objective of point cloud target detection is to swiftly and accurately identify three-dimensional objects from point cloud data. To meet this requirement, the prevalent network architecture employed in the industry is the voxel-based PointPillars model. Nonetheless, this model faces challenges in maintaining detection accuracy when objects are obscured or diminutive in size. In response to this issue, we introduce AGPNet, a novel model that seamlessly integrates four key modules: Data Augmentation, Dynamic Graph CNN, Pillar Feature Net, and Detection Head (SSD). The Data Augmentation module enhances the adaptability of point cloud data to complex and ever-changing real-world environments. The Dynamic Graph CNN module endows the network structure with geometric features, which encapsulate not only the point itself but also its adjacent points. The Pillar Feature Net module translates three-dimensional point cloud data into pseudo-image data through the utilization of voxels. Subsequently, the Detection Head (SSD) module leverages this pseudo-image data to conduct target detection of three-dimensional objects. Our experiments, conducted on the KITTI dataset, demonstrate that our proposed method boosts object detection accuracy by 6-7 percentage points compared to the PointPillars model, while maintaining similar detection times.

We present a near real-time solution for 3D reconstruction from aerial images captured by consumer UAVs. Our core idea is to simplify the multi-view stereo problem into a series of two-view stereo matching problems. Our method applies to UAVs equipped with only one camera and does not require special stereo-capturing setups. We found that the neighboring two video frames taken by UAVs flying at a mid-to-high cruising altitude can be approximated as left and right views from a virtual stereo camera. Leveraging GPU-accelerated real-time stereo estimation, efficient PnP correspondence solving algorithms and extended Kalman filter, our system simultaneously predicts scene geometry and camera position/orientation from the virtual stereo cameras. Also, this method allows user selection of varying baseline lengths, which provides more flexibility given the trade-off between camera resolution, effective measuring distance, flight altitude, and mapping accuracy. Our method outputs dense point clouds at a constant speed of 25 frames per second and is validated on a variety of real-world datasets with satisfactory results.

The process of identifying and approving a new drug is a time-consuming and expensive procedure. One of the biggest issues to overcome is the risk of hepatotoxicity, which is one of the main reasons for drug withdrawal from the market. While animal models are the gold standard in preclinical drug testing, the translation of results into therapeutic intervention is often ambiguous due to interspecies differences in hepatic metabolism. The discovery of human induced Pluripotent Stem Cells (hiPSCs) and their derivatives has opened new possibilities for drug testing. We used mesenchymal stem cells and hepatocytes both derived from hiPSC, together with endothelial cells, to miniaturize the process of generating hepatic organoids. These organoids were then cultivated in vitro using both static and dynamic cultures. Additionally, we tested spheroids composed solely by induced hepatocytes. By miniaturizing the system, we demonstrated the possibility of maintaining the organoids, but not the spheroids, in culture for up to 15 days. This timeframe may be sufficient to carry out a hypothetical pharmacological test or screening. In conclusion, we propose that the hiPSC-derived liver organoids model could complement or, in the near future, replace the pharmacological and toxicological tests conducted on animals.

High efficiency and safety are critical factors in ensuring optimal performance and reliability of systems and equipment across various industries. Fault Monitoring (FM) techniques play a pivotal role in this regard by continuously monitoring system performance and identifying the presence of faults or abnormalities. However, traditional FM methods face limitations in fully capturing the complex interactions within a system and providing real-time monitoring capabilities. To overcome these challenges, Digital Twin (DT) technology has emerged as a promising solution to enhance existing FM practices. By creating a virtual replica or digital copy of a physical equipment or system, DT offers the potential to revolutionize fault monitoring approaches. This paper aims to explore and discuss the diverse range of predictive methods utilized in DT and their implementations in FM across industries. Furthermore, it will showcase successful implementations of DT in FM across a wide array of industries, including manufacturing, energy, transportation, and healthcare The utilization of DT in FM enables a comprehensive understanding of system behavior and performance by leveraging real-time data, advanced analytics, and machine learning algorithms. By integrating physical and virtual components, DT facilitates the monitoring and prediction of faults, providing valuable insights into the system’s health and enabling proactive maintenance and decision-making.

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

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

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

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

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

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

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

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

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

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

There is need to address the challenges of organ shortage, through development of tissues and organs with alternatives to those of the allograft-kind. This illustrates the quest behind novel biofabrication strategies such as 3D bio-printing, which is necessary to create artificial multi-cellular tissues/organs. Several findings have been reported in this review. First, the role of ECM components in tissue regenerative medicine is presented. Different ECM components such as collagen, gelatin, elastin, fibronectin, laminins and glycosaminoglycans are concisely examined for their tissue regenerative medicine applications. Next, current state of research on extrusion-based 3D bio-printing techniques and their limitations are reviewed. For example, we show that cell viability is still a challenge with extrusion, while the use of natural polymers such as collagen in improving composites’ mechanical properties is limited. Lastly, we examine unresolved research questions necessary to advance the present state of research in the field.

Cancer cachexia is a multifactorial syndrome that is identified by ongoing muscle atrophy, along with functional impairment, anorexia, weakness, fatigue, anemia, reduced tolerance to antitumor treatments. Thus, reducing the patients’ quality of life. Cachexia alone causes about 22-25% of cancer deaths. This review covers the symptoms, mediators, available treatment, and prospects of 3D bioprinting for cancer cachexia. Studies about cachexia have shown several factors that drive this disease – protein breakdown, inflammatory cytokines activation, and mitochondrial alteration. Even with proper nutrition, physical exercises, anti-inflammatory agents, chemotherapy, and grafting attempts, standard treatment has been unsuccessful for cachexia. But the use of 3D bioprinting shows much promise compared to conventional methods by attempting to fabricate 3D constructs mimicking the native muscle tissues. In this review, some 3D bioprinting techniques with their advantages and drawbacks, along with their achievements and challenges in in-vivo applications have been discussed. Constructs with neural integration or muscle-tendon units aim to repair muscle atrophy. But it is still difficult to properly bio-print these complex muscles. Although progress can be made by developing new bio-inks or 3D printers to fabricate high-resolution constructs. Using secondary data, this review study shows prospects of why 3D bioprinting can be a good alternate approach to fight cachexia.

Pollen analysis as a part of palynology deals with the morphological determination of pollen and spores. Different technologies with different resolutions varying from simple light microscopy to highly elaborate electron microscopy are used for the examination, depending on the area of application (e.g. sedimentology, melissopalynology, forensic palynology, etc.). To answer the question of whether laser scanning microscopy (LSM) can replace scanning electron microscopy (SEM) for the determination of pollen species, 168 species were examined using LSM. It was concluded that LSM is both efficient and easy to handle. After preparing the fresh pollen, a 3D laser scan takes 5-10 minutes and unlike using SEM, the pollen does not have to be sputtered or processed. The 3D scans can be measured quickly and easily with the integrated software and there were no observable artifacts. At magnifications up to 8545x, the image quality is comparable to that of a sputtered SEM sample whereas at higher magnifications, the SEM method is superior. Overall, pollen display by LSM is much less time consuming and more cost effective than with the SEM method.

The control of the three-dimensional (3D) polymer network structure is important for permselective materials when specific biomolecules detection is needed. Here we investigate conditions to obtain a tailored hydrogel network that combine both molecular filtering and molecular capture capabilities for biosensing applications. Along this line short oligonucleotide detection in a displacement assay is set within PEGDA hydrogels synthetized by UV radical photopolymerization. To provide insights on the molecular filter capability, diffusion studies of several probes (sulforhodamine G and dextrans) with different hydrodynamic radii were carried out using NMR technique. Moreover, fluorometric analyses of hybridization of DNA oligonucleotides inside PEGDA-hydrogels shed light on the mechanisms of recognition in 3D, highlighting that mesh size and crowding effect greatly impact of hybridization mechanism onto polymer network. Finally, we found the best probe density and diffusion transport conditions to allow the specific oligonucleotide capture and detection inside PEGDA-hydrogels for oligonucleotide detection and the filtering out of higher molecular weight molecules.

The maker movement has reached the optics labs, empowering researchers to actively create and modify microscope designs and imaging accessories. 3D printing has especially had a disruptive impact on the field, as it entails an accessible new approach in fabrication technologies, namely additive manufacturing, making prototyping in the lab available at low cost. Examples of this trend are taking advantage of the easy availability of 3D printing technology. For example, inexpensive microscopes for education have been designed, such as the FlyPi. Also, the highly complex robotic microscope OpenFlexure represents a clear desire for the democratisation of this technology. 3D printing facilitates new and powerful approaches to science and promotes collaboration between researchers, as 3D designs are easily shared. This holds the unique possibility to extend the open-access concept from knowledge to technology, allowing researchers from everywhere to use and extend model structures. Here we present a review of additive manufacturing applications in microscopy, guiding the user through this new and exciting technology and providing a starting point to anyone willing to employ this versatile and powerful new tool.

Fluorescence-linked immunosorbent assay (FLISA) is a commonly used, quantitative technique for detecting biochemical based on antigen–antibody binding reactions using a well-plate platform. With the developments in the manufacturing technology of microfluidic systems, FLISA can be implemented onto microfluidic disk platforms, which allows the detection of trace biochemical with high resolutions. Apart from requiring a lower proportion of reagent (1/10), this method also reduces the time required for the entire process to less than an hour. The incubation process involves antigen–antibody binding reactions as well as the binding of fluorogenic substrates to target proteins. The protocol for FLISA on a microfluidic platform necessitates the appropriate execution of liquid reagent movements during each step in order to ensure sufficient binding reactions. Herein, we propose a novel microfluidic disk comprising a 3D incubation chamber. Vascular endothelial growth factor as concentration with ng mL-1 is detected sequentially using a benchtop process employing this 3D microfluidic disk. The 3D microfluidic disk is implemented without requiring manual intervention or additional procedures for liquid control. During the incubation process, microbead movement is controlled through centrifugal force, generated due to disk rotation, and gravitational force via bead sedimentation on the sloped floor of the chamber.

Metal 3D printing technology is a promising manufacturing method, especially in the case of complex shapes. The quality of the printed product is still a challenging issue for mechanical applications. The anisotropy of the microstructure, imperfections, and residual stress are some of the issues that diminish the mechanical properties of the printed sample. The simulation could be used to investigate some technical details, and this research has tried to computationally study the metal 3D printing of austenitic stainless steel to address austenite microstructure and local yield strength. Two computational codes were developed in Visual basics 2015 to simulate the local heating/cooling curve and subsequent austenite microstructure. A stochastic computational code was developed to simulate austenite grain morphology based on calculated thermal history. Then Hall-Pitch equation was used to estimate the yield strength of the printed sample. These codes were used to simulate the effect of temperature of the printer’s chamber on microstructure and subsequent yield strength. The austenite grain topology is more columnar at a lower temperature. The percentage of the equiaxed zone will be increased at a higher chamber’s temperature. Almost a fully equiaxed austenite microstructure will be achieved at 800 C chamber’s temperature, but the last printed layer, which is columnar and can be removed by cutting then. The estimated local austenite grain size and the local yield strength in the equiaxed regions are in the range of 15 to 30 μm and 270 to 330 MPa at 800 C temperature of printer’s chamber, respectively.

Solar Insolation is the major contributor of earth’s radiation and energy budget. The insolation reaching the surface is a prime input for eco-physiological processes such as evapotranspiration and photosynthesis. Therefore, it is as critical component to assess bio-energy and bio-fuel resources. It is also a crucial input to crop simulation model for yield forecasting and its further applications in solar energy solutions. Although ground observations are better for accuracy purpose, they have challenges of maintenance, regular calibration and upkeeping etc. This call for the continuous spatio-temporal satellite based observations barring the acceptable accuracy. In case of INSAT3D/3DR, Bhattacharya et al. (2015) have derived the surface insolation product which is being used widely. We propose a method of improvement in this product. It is envisaged that a correction applied with the help of ground truth estimates may enhance the utilization of insolation products derived from INSAT3D/3DR datasets. In the present study, surface insolation product derived from INSAT 3D/3DR data at an interval of 30 minutes each (collectively 15 minutes interval) with 4 km spatial resolution was used for duration from May-2017 to Apr-2019 over Nagpur. Ground truth observations for same duration were carried out with CNR4, which were used to correct the INSAT 3D/3DR surface insolation product using the statistical best-fit method. Corrected INSAT 3D/3DR products are found correlating with the ground values well with differences of approximately < 1 W/m2. Best-fit parameters evolved in the present study uses only 2 years of simultaneous ground and satellite data which can be further improved by multi-year data base. We propose better utilization of INSAT 3D/3DR based surface insolation products in the assessment of solar resource mapping over Nagpur (and possibly other regions, such as Bhandara) with the help of best-fit parameters as assessed in the present study.

Dynamic thermogravimetric (TG) analysis under nitrogen environment was used to understand the thermal decomposition process of 3D printing filaments made of wood-filled polylactic acid (PLA)/starch blend. The characteristic temperatures and apparent activation energy (AAE) of the filaments with various starch contents were calculated with well-known kinetic models by Friedman, Flynn-Wall-Ozawa, Coats-Redfern and Kissinger. With the increased starch content in the filament, the onset thermal decomposition temperatures of the filaments decreased gradually from 272.4 to 155.1°C. The thermal degradation degree became smaller, and the transitional temperature interval became larger with increased starch proportion. The AAE values of the three types of filaments with different starch ratios varied between 97 kJ/mol and 114 kJ/mol, depending on material composition and method of calculation. The improved understanding of thermal decomposition behavior of PLA-starch-wood composites can help develop more biodegradable PLA/starch-based filaments for 3D printing.

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

Duplex Stainless Steels (DSS) and Superduplex Stainless Steels (SDSS) are an important class of stainless steels because they combine the benefits of austenite and ferrite phases, resulting in steels with better mechanical properties and higher corrosion resistance. Due to these characteristics are widely employed in various industries. However, the appearance of deleterious phases in their microstructure impairs the properties of DSS and SDSS. Among the deleterious phases, the main one is the sigma phase (σ), which can be nucleated when the steel is exposed to the temperature range between 650 °C and 900 °C, reducing its toughness and resistance to corrosion. In a previous work, Fonseca and collaborators used two descriptors of the microstructural path to analyze the formation of sigma phase (σ), SV, interfacial area per unit volume between sigma phase and austenite, and <λ>, mean chord length of sigma, both in function of the VV, volume fraction of sigma, known in the literature as microstructural partial path (MP). In this work, the contiguity ratio is applied for the first time to describe the microstructural path in the study of sigma phase precipitation in SDSS. The contiguity ratio showed that the distribution of the ferrite/sigma boundaries is homogeneous. Thus, it is reasonable to infer that one has a uniform distribution of sigma phase nuclei within the ferrite. About the kinetics of sigma phase formation, the DSS can be described by the classical JMAK equation, whereas for the SDSS, the kinetics tends to follow the Cahn model for grain edge nucleation. Finally, we present the 3D reconstruction of the sigma phase in SDSS. The results demonstrate that the sigma phase nucleates at the edges of the ferrite/austenite interfaces. Moreover, the sigma phase grows consuming the ferrite, but it is not fully interconnected.

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

3D bioprinting holds great promise in the field of regenerative medicine as it can create complex structures in a layer-by-layer manner using cell-laden bioinks, making it possible to imitate native tissues. Current bioinks lack both the high printability and the biocompatibility required in this respect. Hence, the development of bioinks that are capable of both properties is needed. In our previous study, a furfuryl-gelatin based bioink, crosslinkable by visible light, was used for creating mouse mesenchymal stem cell-laden structures with high fidelity. In this study, lattice mesh geometries were printed in a comparative study to test against the properties of a traditional rectangular-sheet. After 3D printing and crosslinking, both structures were analysed for swelling and rheological properties, and their porosity estimated using scanning electron microscopy. Results showed that the lattice structure was relatively more porous but sturdy and exhibited a lower degradation rate compared to the rectangular-sheet. Further, the lattice allowed encapsulation of a greater number of cells, allowing them to proliferate to a greater extent compared to the rectangular-sheet that retained a lesser number of cells initially. All of these results collectively affirmed that the lattice poses as a superior scaffold design for tissue engineering applications.

3D plotting is an additive manufacturing technology enabling biofabrication, thus the integration of cells or biologically sensitive proteins or growth factors into the manufacturing process. However, most (bio-)inks developed for 3D plotting were not shown to be processed into clinical relevant geometries comprising critical overhangs and cavities, which would collapse without a sufficient support material. Herein, we have developed a support hydrogel ink based on methylcellulose (mc), which is able to act as support as long as the co-plotted main structure is not stable. Therefore, 6 w/v %, 8 w/v % and 10 w/v % mc were allowed to swell in water, resulting in viscous inks, which were characterized for their rheological and extrusion properties. The successful usage of 10 w/v % mc as support ink was proven by multichannel plotting of the support together with a plottable calcium phosphate cement (CPC) acting as main structure. CPC scaffolds displaying critical overhangs or a large central cavity could be plotted accurately with the newly developed mc support ink. The dissolution properties of mc allowed complete removal of the gel without residuals, once CPC setting was finished. Finally, we fabricated a scaphoid bone model by computed tomography data acquisition and co-extrusion of CPC and the mc support hydrogel.

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

Malignant cells cultured in three-dimensional (3D) models have been found to be phenotypically and biochemically different from their counterparts cultured conventionally. Since most of these studies employed solid tumor types, how 3D culture affects multiple myeloma (MM) cells is not well understood. Here, we compared MM cells (U266 and RPMI8226) in a 3D culture model with those in conventional culture. While the conventionally cultured cells were present in single cells or small clusters, MM-3D cells grew in large spheroids. We discovered that STAT3 was the pathway that was more activated in 3D in both cell lines. The active form of STAT3 (phospho-STAT3 or pSTAT3), which was absent in MM cells cultured conventionally, became detectable after 1-2 days in 3D culture. This elevated pSTAT3 level was dependent on the 3D environment, since it disappeared after transferring to conventional culture. STAT3 inhibition using a pharmacological agent, Stattic, significantly decreased the cell viability of MM cells and sensitized them to bortezomib in 3D culture. Using an oligonucleotide array, we found that 3D culture significantly increased the expression of several known STAT3 downstream genes implicated in oncogenesis. Since most primary MM tumors are naturally STAT3-active, studies of MM in 3D culture can generate results that are more representative of the disease.

We previously designed and synthesized dehydroxyepoxyquinomicin (DHMEQ) as an inhibitor of NF-κB based on the structure of microbial secondary metabolite epoxyquinomicin C. DHMEQ showed anti-inflammatory and anticancer activity in various in vivo disease models without toxicity. Cell detachment from the primary tumor and subsequent invasion are considered to be early phase of metastasis, while tumor cell attachment to the tissue and secondary tumor formation the late phase. The assay system for late phase was set up with intra-portal-vein injection of pancreatic cancer cells. Administration of DHMEQ was found to inhibit the liver metastasis possibly by decreasing the expression of MMP-9 and IL-8. Also when the pancreatic cancer cells treated with DHMEQ was inoculated into the peritoneal cavity of mice, the metastatic foci formation was inhibited. These results indicate that DHMEQ is likely to inhibit the late phase of metastasis. Meanwhile, we have recently employed three-dimensional (3D) culture of breast cancer cells for the model of early phase metastasis. DHMEQ inhibited the 3D invasion of breast cancer cells without toxicity. In this way, DHMEQ was shown to inhibit the late and early phases of metastasis. Thus, DHMEQ is likely to be useful for the suppression of cancer metastasis.

Inexpensive piezoelectric diaphragms can be used as sensors to facilitate both nozzle height setting and build platform leveling in FFF (Fused Filament Fabrication) 3D printers. Tests simulating nozzle contact are conducted to establish the available output and an output of greater than 8 Volts found at 20 ºC, a value which is readily detectable by simple electronic circuits. Tests are also conducted at a temperature of 80 ºC and, despite a reduction of greater than 80% in output voltage, this is still detectable. The reliability of piezoelectric diaphragms is investigated by mechanically stressing samples over 100,000 cycles at both 20 ºC and 80 ºC and little loss of output over the test duration is found. The development of a nozzle contact sensor using a single piezoelectric diaphragm is described.

Prolonged high-intensity grinding can modify the crystal structure of solid substances and/or induce chemical reaction, which is referred to as mechanochemical reaction. Such reactions can exert positive influences on hydrometallurgical processes, therefore, many researchers have applied mechanochemical reactions for metals dissolution from minerals. The mechanism of mechanochemical reaction has been investigated using solid analyses and simulations. Structural changes caused by mechanochemical reaction are not yet sufficiently clarified because the ground samples are amorphous. The objective of this study was to analyze structural changes of cerianite in weathered residual rare earth ore by mechanochemical reduction. Structural change was analyzed by x-ray absorption near-edge structure and extended x-ray absorption fine structure analysis at the cerium L_III- and K-edges. These analyses revealed that the structural change of cerianite in this ore induced by mechanochemical reduction involved oxygen vacancy production. The process of the oxygen vacancy formation was closely coupled with the quantum effect of localization–delocalization of the 4f electron of cerium.

We have proposed a data-driven approach for designing mesoscale porous structures of Li-ion battery electrode with three-dimensional virtual structures and machine learning techniques. Over 2,000 artificial 3D structures assuming positive electrode composed of random packed spheres as active material particles are generated, and charge/discharge resistance has been evaluated using simplified Physico-chemical model. In this model, resistance from Li diffusion in active material particles (diffusion resistance), transfer resistance of Li+ in electrolyte (electrolyte resistance) and reaction resistance on the interface between active material and electrolyte are simulated based on mass balance of Li, Ohm’s law in and linearized Butler-Volmer equation, respectively. Using these simulation results, regression models via Artificial Neural Network (ANN) have been created in order to predict charge/discharge resistance from porous structure features. In this study, porosity, active material particle size and volume fraction, pressure in the compaction process, electrolyte conductivity, and binder volume fraction are adopted as features, associated with controllable process parameters for manufacturing battery electrode. As results, the predicted electrode resistance by ANN regression model is good agreement with the simulated values. Furthermore, sensitivity analysis and optimization of the process parameters have been carried out. The proposed data-driven approach could be a solution as a guiding principle for manufacturing battery electrode.

The emergence of new methodologies and tools for digitizing objects belonging to the Cultural Heritage (CH) changed the paradigms adopted so far. Traditionally, the process to acquire artifacts required specialized and often costly equipment tailored to specific purposes. However, the development of more generalized, adaptable, and affordable tools led to novel approaches. This manuscript provides a glimpse into the evolving landscape of custom-made tools for digital documentation, both hardware and software, and their transformative impact on the digitization techniques, built to meet requirements of specific case studies, including ancient drawings, manuscripts, paintings, and museum objects. The advent of self-built instruments has revolutionized the way professionals work today, by leveraging a new generation of low-cost, adaptable gears, leading to unprecedented flexibility and efficiency, while facilitating the capture of high-quality digital representations of objects with minimal damage and preserving their integrity. The outcomes of instruments and tools specifically produced for the contexts described in this paper highlight their potential for promoting interdisciplinary collaboration, facilitating scholarly research, enhancing conservation efforts, and fostering cultural exchange. Ultimately, this research contributes to illustrate how custom software, in combination with recent devices such as smartphones and 3D printers, underscores the importance of adopting these innovative approaches to generate an ecosystem of tools and methods able to preserve, document, and promote the richness of our collective past for future generations.

Grape dehydration is practiced widely in the food industry with large yields of sultanas produced globally. This paper proposes an investigation into grape microstructure changes as it is dried by imaging specimens at intervals during dehydration at two temperatures using scanning electron microscopy. Detailed images of the microstructure were obtained, and a unique image processing algorithm was developed to quantitatively analyse the properties of this microstructure. Two main methods were developed to obtain the complex boundaries of cells present in the grape tissue in over 36 SEM images. Segmentation of the binary image using an adapted watershed function obtained the most consistent and accurate morphological shape. This was compared to a secondary method which used Canny’s edge detection function, morphological closing and skeletonizing to outlines the cellular microstructure. MATLAB was utilised to convert these boundaries into measurable areas so that quantitative data on average cell area, perimeter and cell axis lengths was acquired. It was found that over drying time cell area and perimeter reduced as expected. Some variability in the data was clear due to only single samples being analysed for each temperature and time combination. The development of automatic image processing techniques will enable quantitative data to be extracted from these images. Trends in cell perimeter, diameter and shape will be used to demonstrate relationships between morphological structure, drying temperature, and duration.

In this study we have investigated the effect of the addition of Nb2O5 (up to 5 mol%) on the structure and luminescent properties of ZnO-B2O3 glass doped with 0.5 mol % Eu2O3 by using of infrared (IR), Raman and photoluminescence (PL) spectroscopy. Physical properties as molar volume, oxygen packing density and glass transition temperature were determined using the results of differential thermal analyisis (DTA) and Archimedes principle for density. IR and Raman spectra revealed that niobium ions incorporate into the base zinc borate glass as NbO4 trtraherda and NbO6 octahedra. A strong red emission from the 5D0 level of Eu3+ ions was registered under near UV (392 nm) excitation using the sharp 7F0 - 5L6 transition of Eu3+. The integrated fluorescence intensity ratio R (5D0 → 7F2/5D0 → 7F1) was calculated to estimate the degree of asymmetry around the active ion, suggesting a location of Eu3+ in non-centrosymmetric sites. The higher Еu3+ luminescence emission observed in zinc borate glasses containing 1÷5 mol% Nb2O5 compared to the Nb2O5-free zinc borate glass evidences that Nb2O5 is suitable component for modification of host glass structure and improving the emission intensity.

In this paper, the sol−gel method was used to synthesize powders of LaMnO3 (LMO), La0.85Ca0.15MnO3 (LCM), and La0.85Sr0.15MnO3 (LSM). We investigated the impact of substituting Ca and Sr at the A−site on the perovskite crystal structure and electrochemical capabilities of LMO. LCM retained its orthogonal structure in comparison to the parent LMO components, whereas LSM transitioned to a rhombic structure. At 0.5 A/g, the specific capacitance of LCM and LSM electrodes is 185.5 F/g and 248 F/g, respectively.The specific capacitance of LCM was more three times than that of the LMO electrode. Among the three samples (LMO, 22.25 m2 g−1; LSM, 31.56 m2 g−1), the LCM sample exhibited the highest specific surface area of 38.79 m2 g−1. The charge transfer resistances of the LMO, LCM, and LSM are 0.48 Ω, 0.36 Ω, and 0.38 Ω, correspondingly. The LCM electrode exhibits the greatest capacitance performance due to its more refined morphology, increased concentration of oxygen vacancy, and more complete utilization of the perovskite bulk structure. The above results demonstrate that Ca or Sr substitution of A−site compounds has great potential for supercapacitor applications.

Herpesviridae is a family of enveloped double-stranded DNA viruses that cause a wide range of diseases in hosts. Among the various components of herpesvirus particles, tegument proteins residing between the envelop and nucleocapsid play crucial roles in viral replication, immune evasion, and modulation of host cellular pathways. Understanding the three-dimensional structure of herpesvirus tegument proteins help to reveal the molecular mechanism underlying the crosstalk with other viral and cellular components, and thus is crucial for the investigation of their biological and pathological functions. In this review, we summarize the current knowledge of the structural features of herpesvirus tegument proteins, highlighting the structure-based functional implications, including the potential as targets for antiviral drug development.

Hong Kong was under strike from Super Typhoon Saola (2309), necessitating the issuance of the highest tropical cyclone warning signal. Saola skirted past the south-southwest of Hong Kong, bringing hurricane force winds and significant storm surge. Saola had its closest approach to Hong Kong on 1 September 2023, posing a unique challenge in forecasting and early warning for the commencement date of the new school term, where higher impact to traffic and public safety was anticipated. This paper covers the challenges on the forecasting aspect of the super typhoon. The predicted tropical cyclone track, intensity and wind structure are reviewed. Experience in this case showed that while there was not a perfect numerical weather prediction model in terms of the forecast track, intensity and wind structure of Saola, multi-model approach provided very use-ful and crucial information for operational weather warning services.

: Extra- and intra-cellular activity occurs under the direction of numerous inter-molecular interactions, and in any tissue or cell, molecules are densely packed, thus promoting those molecular interactions. Galectins and chemokines, the focus of this review, are small, protein effector molecules that mediate various cellular functions, in particular cell adhesion and migration, as well as cell signaling/activation. In the past, researchers have reported that combinations of these (and other) effector molecules act separately, yet sometimes in concert, but nevertheless physically apart and via their individual cell receptors. This view that each effector molecule functions independently of the other limits our thinking about functional versatility and cooperation, and, in turn, ignores the prospect of physiologically important inter-molecular interactions, especially when both molecules are present or co-expressed in the same cellular environment. This review is focused on such protein-protein interactions with chemokines and galectins, their homo- and hetero-oligomeric structures that they can form, and the functional consequences of those paired interactions.

Ethylene is an ideal CO2 product in an electrocatalytic CO2 reduction reaction (CO2RR), which has high economic value. In this paper, Al–doped octahedral Cu2O (Al–Cu2O) catalyst was synthesized by a simple wet chemical method. The selectivity of CO2RR products was improved by doping Al onto the surface of octahedral Cu2O by regulating the Al content. The Al–Cu2O was used as an efficient electrocatalyst for CO2RR with selective ethylene production. The Al–Cu2O exhibited a high Faradic efficiency (FEC2H4) of 44.9% at -1.23 V (vs. RHE) in CO2 saturated 0.1 M KHCO3 electrolyte. Charge transferring from Al atom to Cu atom take place after Al doping in Cu2O, thereby optimizing the electronic structure, which facilitates CO2RR to ethylene production. The DFT calculation showed that the Al–Cu2O catalyst can effectively reduce the adsorption energy of the *CHCOH intermediate and promote the mass transfer of charges, thus improving the FEC2H4. After Al doping into Cu2O, the center of d orbitals shift positively, which makes the d–band closer to the Fermi level. Furthermore, the density of electronic states increases, which was conducted to the interaction between Cu atoms and intermediates, thus accelerating the electrochemical CO2 reduction process. This work proved that the metal doping strategy can effectively improve the catalytic properties of Cu2O, thus providing a useful way for CO2 cycling and green production of C2H4.

The composition, structure and functionalities of prolamins from highland barley was investigated. These parameters of was compared with the widely applied prolamins (zein). There are more charged and hydrophilic amino acids in prolamins from highland barley than zein. The molecu-lar weight of prolamins from highland barley were between 30 to 63 kDa, which was larger than zein (20 to 24 kDa). β-turn helices is the main secondary structure in prolamins from highland barley, while α-helical structure is the main secondary structure in zein. The water holding capacity, thermal stability, emulsifying capacity and stability of prolamins from highland barley is quite lager than zein, while opposite results can be observed for oil absorption capacity. The diameter of fibers prepared with prolamins from highland barley was almost 6 times that of zein, while ribbon structures rather than fibers were formed by prolamins from highland barley. The results would provide the guidance for application of prolamins from highland barley.

Montes de María is the best-preserved tropical dry forest fragment in the Colombian Caribbean, making it an ideal location for studying the impacts of human disturbance on local ecosystems. This study analyzed the ecological structure of diurnal butterflies in both forested and disturbed areas using 16 circular plots to identify relationships between alpha and beta diversity, and the geographic distance between disturbed areas and native forests, using a range of metrics, including range-abundance and rarefaction curves, nonlinear models, and the Bray–Curtis dissimilarity index. Results revealed three distinct species assemblages associated with forest, intermediate disturbed areas (IDA), and disturbed areas (DA). Nonlinear models show that IDA are more diverse than forest and DA. However, forests have more beta diversity among plots than IDA and DA. Indicator species for each butterfly assemblage were also identified. Thus, although new butterfly species assemblages emerge from a new human land-scape, it is clear that species that only occur within dry forest fragments are lost when forest fragments disappear. Overall, these findings have important implications for conservation efforts and understanding how human disturbance affects biodiversity in tropical ecosystems.

Epstein-Barr virus (EBV)-encoded RNAs (EBERs) are structurally conserved small, noncoding RNAs constitutively expressed in EBV infection. Although primarily localised in the nucleus, EBERs are found in the cytoplasm and exosomes. However, the mechanism(s) of EBERs transport is not known. This study aimed to investigate the structural impact of EBER1 on its transport. EBER1 stem-loop (SL) deletion mutants (ΔSL1, ΔSL3 and ΔSL4) were created and stably transfected into HEK293T cells. The expression of EBER1 was quantified in total cell, nuclear, cytoplasmic and exosomal fractions. The quantification was performed in the presence of physiological expression of RPL22 and La, and after silencing them. These proteins are believed to be involved in EBER1 transport and secretion. Compared to the wildtype EBER1 transfectants, the expression level of EBER1 gene in all mutants was significantly lower in the total cell, cytoplasmic and exosomal fractions. However, ΔSL3 mutant showed significant nuclear retention. Silencing RPL22 resulted in increased nuclear-cytoplasmic trafficking of EBER1. Silencing La protein did not affect EBER1 secretion. Alternatively, the store-operated intracellular Ca2+ was found to correlate with EBER1 expression in exosomes. Taken together, EBER1 structure and its interaction with RPL22 appeared to be important in the nuclear-cytoplasmic transport of the RNA.

Bunyaviruses represent the largest group of RNA viruses, and are the causative agent of a variety of febrile and hemorrhagic illnesses. Originally characterized as a single serotype in Africa, the number of described bunyaviruses now exceeds over 500, with its presence detected around the world. These predominantly tri-segmented, single-stranded RNA viruses are transmitted primarily through arthropod and rodent vectors, and can infect a wide variety of animal and plants. Although encoding for a small number of proteins, these viruses can inflict potentially fatal disease outcomes, and have even developed strategies to suppress the innate antiviral immune mechanisms of the infected host. This short review will attempt to provide an overall description of the order Bunyavirales, describing the mechanisms behind their infection, replication and their evasion of the host immune response. Furthermore, the historical context of these virus will be presented, starting from their original discovery almost 80 years ago, to the most recent research pertaining to viral replication and host immune response.

The present work reports on the calculated electronic and magnetic structure of the binary Co-Ga system at high Co content. β-CoGa adopts a simple cubic CsCl type structure. Well-ordered CoGa does not exhibit collective magnetism but is a paramagnetic, metallic compound. Neither Co nor Ga deficiency induces magnetic order, however, ferromagnetism is observed for Co-Ga anti-site disorder. The magnetic moment per cell increases up to about 1.2 μB in the completely disordered body centered cubic structure. With increasing Co content, Co1+xGa1−x maintains the CsCl type structure and becomes ferromagnetic. Most important, a discontinuity of the magnetic order with composition is observed at about 10% excess Co, where a change from a low magnetic moment state to a high moment state is observed. This is accompanied by a change in the electronic structure and transport properties. The discontinuity is forced by the increasing exchange splitting related to the localized moment of the additional Co atoms that replace Ga. Subsequently, the magnetic moment increases continuously up to 2.5 μB for x=0.6. For x≳0.6, the structure changes to face centered cubic with random site occupation and the magnetic moment further increases. Above the magnetic discontinuity, the Curie temperature increases linearly with the Co content from the onset of ferromagnetism, until it reaches its maximum in pure Co.

A model for parasitic motility has been proposed in which parasite filamentous actin (F-actin) is attached to surface adhesins by a large component of the glideosome, known as the glideosome-associated connector protein (GAC). This large 286 kDa protein interacts at the cytoplasmic face of the plasma membrane with the phosphatidic acid-enriched inner leaflet and cytosolic tails of surface adhesins to connect them to the parasite actomyosin system. GAC is observed initially to the conoid at the apical pole and re-localised with the glideosome to the basal pole in gliding parasite. GAC presumably functions in force transmission to surface adhesins in the plasma membrane and not in force generation. Proper connection between F-actin and the adhesins is as important for motility and invasion as motor operation itself. This notion highlights the need for new structural information on GAC interactions, which has eluded the field since its discovery. We have obtained crystals that diffracted to 2.6-2.9 Å for full-length GAC from Toxoplasma gondii in native and selenomethionine-labelled forms. These crystals belong to space group P212121, cell dimensions are roughly a=119 Å, b=123Å, c=221Å, α=90, β=90, γ=90 with 1 molecule per asymmetric unit, suggesting a more compact conformation than previously proposed.

Graphite nanoplatelets (GNPs) were produced from flake graphite that had been immersed in isopropyl alcohol solution (70%) and converted to powder form in an ultrasonic bath (5 h, room temperature). Scanning and transmission electron microscopy, X-ray diffractometry, and Raman spectroscopy identified 120-nm-thick GNP crystallites and 0.5–21 µm plates with different areas and shapes. Extensive exfoliation was observed by transmission electron microscopy with abundant multilayer and some monolayer GNPs. X-ray diffractometry confirmed 43 GNP layers along the c-axis. Raman spectroscopy indicated well-defined GNPs with few defects and no oxide content. Rietveld analysis indicated a GNP crystal lattice with stacks of parallel two-dimensional graphene layers and tightly bound hybridized carbon atoms stacked in a translational …ABAB… sequence in hexagonal rings.

Spike protein is the surface glycoprotein of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) necessary for the entry of the virus via the transmembrane receptors of the human endothelial cells of the respiratoty system for the virus to be engulfed causing COVID-19 disease after priming by type II transmembrane protease TMPRSS2 and then binding with the angiotensin-converting enzyme 2 (ACE2). Therefore, mutations and amino acid variants analysis are essential in understanding the mechanism of binding of spike protein with its receptor to have an insights on possibilities to design a peptide or nucleotide-based vaccine for COVID-19. Here, we employed Iterative Threading Assembly Refinement (I-TASSER) and Multiple Alignment using Fast Fourier Transform (MAFFT) to predict the three-dimensional monomer structure of spike protein of SARS-CoV-2 and to analyze the amino acid variants for protein sequences from GISAID database for samples collected from Jordan in a try to find an explanation for the low confirmed number of COVID-19 in Jordan. Our Protein Homology/analogY Recognition Engine V 2.0 (Phyre2) findings showed four single amino acid variants (SAV) found in 20 samples of SARS-CoV-2. What is equal to 5% of samples showed tyrosine deletion at Y144 located in the SARS-CoV-like_Spike_S1_NTD (N terminal domain), 62% showed aspartate substitution to glycine at D614G located in the SARS-CoV-2_Spike_S1_RBD (spike recognition binding site), 5% showed aspartate substitution to tyrosine at D1139Y and 5% showed glycine substitution to serine at G1167S both located in the Corona_S2 domain. The findings have shown lower mutational sensitivity in all variants that might not affect the function of spike glycoprotein except for D614G, which has the highest mutational sensitivity score (5 out of 9) indicating a higher likelihood to affect the function of the spike protein. This might suggest, in general, a reduced transmitability of SARS-CoV-2 in Jordan.

Through history, particular attention has been paid of the study of the relationship between the energy use and the city structure. Improving energy efficiency in modern agglomerations is the most promising means to mitigate climate change and its impacts. In this current context of globalisation, European Union proposes initiatives and policy targets to rethink the urban development strategies towards the ‘zero energy objectives’. Providing a methodological approach with a simulation district analysis, the present article summarizes how the ‘zero energy’ challenge is analyzed in an existing district (Epinlieu) to articulate the users’ requirements in energy. This study contributes to the scientific discussion of the districts’ urban structure and energy planning by establishing a linkage among the beneficial influence of the KPIs of the districts’ form to increase their energy efficiency and its application in a real case study in Belgium.

Untranslated regions (UTRs) of flaviviruses contain a large number of RNA structural elements involved in mediating the viral life cycle, including cyclisation, replication, and encapsidation. Here we report on a comparative genomics approach to characterize evolutionarily conserved RNAs in the 3'UTR of tick-borne, insect-specific and no-known-vector flaviviruses in silico. Our data support the wide distribution of previously experimentally characterized exoribonuclease resistant RNAs xrRNAs within tick-borne and no-known-vector flaviviruses and provide evidence for the existence of a cascade of duplicated RNA structures within insect-specific flaviviruses. On a broader scale, our findings indicate that viral 3'UTRs represent a flexible scaffold for evolution to come up with novel xrRNAs

The dark proteome as we define it, is the part of the proteome where 3D structure has not been observed either by homology modeling or by experimental characterization in the protein universe. From the 550.116 proteins available in Swiss-Prot (as of July 2016) 43.2% of the Eukarya universe and 49.2% of the Virus universe are part of the dark proteome. In Bacteria and Archaea, the percentage of the dark proteome presence is significantly less, with 12.6% and 13.3% respectively. In this work, we present the map of the dark proteome in Human and in other model organisms. The most significant result is that around 40%- 50% of the proteome of these organisms are still in the dark, where the higher percentages belong to higher eukaryotes (mouse and human organisms). Due to the amount of darkness present in the human organism being more than 50%, deeper studies were made, including the identification of ‘dark’ genes that are responsible for the production of the so-called dark proteins, as well as, the identification of the ‘dark’ organs where dark proteins are over represented, namely heart, cervical mucosa and natural killer cells. This is a step forward in the direction of the human dark proteome.

After brings about a brief review of the theoretical explanations and researches on the reasons for being a victim, this article is organized into two sections. The first presents a comparative analysis of the data for 1999 and 2016 in terms of perceptions, profiles and most significant sociodemographic and socioeconomic variables. The second one shows an explanatory analysis based on a multivariate logistical regression model using as an independent variable lifestyle of the population and socioeconomic variables, and as dependent variables individual’s susceptibility to becoming a victim of certain crimes. The results points towards an explanatory model of victimization in which sociodemographic variables play an increasingly less important role while variables related to lifestyle and subjective perceptions make a significant contribution to greater understanding of the nature of being the victim of a crime.

This paper studies a model of dynamic compensation and capital structure with managerial traits. We show that Optimistic manager perceives equity as more undervalued than debt, while, confident manager perceives debt as more undervalued than equity. Managerial risk aversion mitigates manager’s bias. The risk aversion of the optimistic manager has a convex effect on the optimal coupon. There exists the level of risk aversion eliminating the bias on the leverage. The managerial optimist has an ambiguous effect on the owner’s bankruptcy level. The risk aversion has a convex effect on the owner’s bankruptcy level. The optimistic/confident manager underestimates the credit spread. The risk aversion has convex effect on the credit spread. In contrast to rational manager, the optimistic/confident manger has higher level of effort. The risk aversion has a negative effect on the effort.

Fingerprint recognition systems have achieved widespread integration into various technological devices, including cell phones, computers, door locks, and time attendance machines. Nevertheless, individuals with worn fingerprints encounter challenges when attempting to unlock original fingerprint systems, resulting in disruptions to their daily activities. This study explores two distinct methods for fingerprint backup: traditional fingerprint impression and 3D printing technologies. Unlocking tests were conducted on commonly available optical fingerprint lock-equipped cell phones to assess the efficacy of these methods, particularly in unlocking worn fingerprints. The research findings indicated that traditional fingerprint impression method exhibited high fidelity in reproducing fingerprint patterns, achieving an impressive unlocking success rate of 97.8% for imprinting unworn fingerprints. However, when dealing with worn fingerprints, traditional fingerprint impression technique showed a reduced unlocking success rate, progressively decreasing with increasing degrees of finger wear. In contrast, 3D printed backup fingerprints, with image processing and optimization of ridge height, mitigated the impact of fingerprint wear on unlocking capability, resulting in an unlocking success rate of 84.4% or higher. Thus, the utilization of 3D printing technology proves advantageous for individuals with severely worn or incomplete fingerprints, providing a viable solution for unforeseen circumstances.

The assortment of low-cost 3D printers for “in-practice” use, e.g., for clear aligner therapies, is ever increasing. To address concerns about the accuracy of orthodontic models produced on such printers when cost efficient modes of 3D printing are employed, this study examined the effect of print model body type and print angulation on accuracy. Six printing-configuration groups were included: 2 model types (solid or hollow shell) combined with 3 print angles (0°, 70°, or 90°) with 10 models/group; all models were printed with 100-µm layer thickness using a digital light processing-based 3-dimensional printer. Eleven selected structures and distances were measured on the printed models with a digital microscope and compared to the same measures on a digitized master model. The clinically-acceptability range was set at ±0.25 mm difference from the master model for single tooth measurements (intra-tooth) and ±0.5 mm for cross-arch measurements (inter-tooth). For individual measurements across all models, 98% fell within clinical acceptability. For mean measurements within each model group, only canine height for the shell-0° model had a mean difference (0.26 mm ± 0.03) outside the clinically acceptable range for intra-tooth measurements. Standard deviations for all intra-tooth measurements were within 0.07 mm. While none of the mean inter-tooth measurements exceeded the acceptability range, the standard deviations were larger (0.04 to 0.30 mm). Accuracy of orthodontic models for clear aligner therapies was not impacted beyond the clinically acceptable range when altering model body type and print angulation to improve efficiency of 3D printing. These findings suggest greater flexibility of the practitioner to alter print settings to address time and cost efficiency in various clinical scenarios and still maintain clinically acceptable model accuracy.

With the development of organizational biology and forced from the EU Cosmetic Regulation (EU/1223/2009) with the complete ban of animal testing for cosmetic purposes, 3D skin models have been widely developed due to their similar physiological structure and metabolic function to native human tissue. 3D skin models for in vitro cosmetic evaluation are still promising alternative methods for evaluating phototoxicity, corrosivity and irritation. These models have been used for early screening and later validation of toxicity and efficacy evaluation by many well-known cosmetic companies. 3D skin models have become an important tool in cosmetic evaluation research. This article reviews the development of 3D skin models and their application in cosmetic evaluation. An outlook on the current application and future technological development directions in the cosmetic field is also presented.

Implementing digital technologies, such augmented reality and 3D models, to various cultural sectors is an ongoing procedure, especially favorable after COVID-19 pandemic. Even though such technologies are familiar to museums, galleries and archaeological places all over the world, little research or practical cases have been developed when it comes to theaters and theatrical costumes. Proposed research article describes the methodology of both reference material collection and applications development, while an analysis of functions and aesthetic results are described, especially when it comes to 3D models. The paper’s aim to reveal that theatrical operations (as part of cultural sector) as well as structured parts (such as acts, performances and costumes) can be preserved and served to larger audiences via technological means, such as an augmented reality application.

This pioneering study presents an in-depth biomechanical examination of soccer's diving header, aiming to quantify its impact on ball speed enhancement (BSE) and effective offensive range (EOR). Despite the diving header's widespread acclaim and historical significance, there remains a dearth of scientific scrutiny into its biomechanical intricacies. Employing an innovative research design featuring a static hanging ball at varied offensive distances and heights, the study replicates diverse header scenarios. The results of 3D motion quantification have shown that a physically excellent player (identified through the maximal standing long jump test) could reach an EOR around 2.64 times his body height. Furthermore, the study unveils that proficient players could attain BSE surpassing 9 m/s, signifying the diving header's heightened efficacy compared to traditional heading techniques, which could only result in 4.5 m/s. Correlation analyses unveil noteworthy relationships, highlighting the pivotal role of head speed at impact and the influence of minimizing speed-drop and temporal disparities for amplified effectiveness. Considerations for optimizing diving header execution are introduced, emphasizing the necessity for targeted training programs. Despite acknowledged limitations inherent to its pilot nature, this exploration furnishes foundational knowledge to guide subsequent research and practical applications, providing valuable insights into soccer training and skill development through a biomechanical lens.

This paper introduces an innovative approach to lipreading, leveraging a web application designed to generate subtitles for videos where the speaker's mouth is visible and a comprehensive literature review that precedes the discussion, encompassing a thorough examination of various lipreading methods employed over the past decade. Our method employs a powerful deep learning model, featuring a 3D-convolution network and bidirectional LSTM, enabling accurate sentence-level predictions based solely on visual lip movements. With an impressive accuracy of 97%, our model is trained using pre-segmented lips regions, transformed into animated GIFs for effective pre-training. This work stands as a significant contribution to the evolving landscape of lipreading research, offering a practical and accurate solution for real-world applications.

Background: Anthropometric measurements play a crucial role in medico-legal practices. Actually, several scanning technologies are employed in post-mortem investigations for forensic anthropological measurements. This study aims to evaluate the precision, in-ter-rater reliability, and accuracy of a hand-held scanner in measuring various body parts. Methods: Three independent raters measured seven longitudinal distances using an iPad Pro equipped with a LiDAR sensor and specific software. These measurements were sta-tistically compared to manual measurements conducted by an operator using a laser level and a meterstick (considered the gold standard). Results: The Friedman’s test revealed minimal intra-rater variability in digital measurements. Inter-rater variability analysis yielded an ICC=1, signifying high agreement among the three independent raters. Addi-tionally, the accuracy of digital measurements displayed errors below 2%. Conclusions: Preliminary findings demonstrate that the pairing of LiDAR technology with the Polycam app showcases high precision, inter-rater agreement, and accuracy. Hand-held scanners show potential in forensic anthropology due to their simplicity, affordability, and porta-bility. However, further validation studies under real-world conditions are essential to es-tablish the reliability and effectiveness of handheld scanners in medico-legal settings.

Real-time multi-axis distributed tactile sensing is a critical capability if robots are to perform stable gripping and dexterous manipulation, as it provides crucial information about the sensor-object interface. In this paper, we present an optical-based 6-axis tactile sensor designed in a fingertip shape for robotic dexterous manipulation. The distributed sensor can precisely estimate local XYZ force and displacement at ten distinct locations, and provide global XYZ force and torque measurements. Its compact size, comparable to that of a human thumb, and minimal thickness allow seamless integration onto existing robotic fingers, eliminating the need for complex modifications to the gripper. The proposed sensor design uses a simple, low-cost fabrication method. Moreover, the optical transduction approach uses light angle and intensity sensing to infer force and displacement from deformations of individual sensing units that form the overall sensor, providing distributed 6-axis sensing. The local force precision at each sensing unit in the X, Y, and Z axes is 20.89 mN, 19.19 mN, and 43.22 mN, respectively, over an local force range of approximately ±1.5 N in X and Y and 0 to -2 N in Z. The local displacement precision in the X, Y and Z axes is 56.70 μm, 50.18 μm and 13.83 μm, respectively, over a local displacement range of ±2 mm in the XY directions and 0 to -1.5mm in Z (i.e., compression). Additionally, the sensor can measure global torques, Tx, Ty and Tz, with a precision of of 1.90 N-mm, 1.54 N-mm and 1.26 N-mm, respectively. The fabricated design is showcased by integrating it with an OnRobot RG2 gripper and illustrating real-time measurements during in simple demonstration task which generate changing global forces and torques.

Bacteriotherapy is emerging as a strategic and effective approach to treat infections by providing putatively harmless bacteria (i.e., probiotics) as antagonists to pathogens. A proper delivery of probiotics or their metabolites (i.e., post-biotics) can avail itself of biomaterial encapsulation by innovative manufacturing technologies. This review paper aims at providing the most recent biomaterial-assisted strategies proposed to treat infections or disbiosis using bacteriotherapy. We revised the encapsulation processes across multiscale biomaterial approaches, which could be ideal to target different tissues and suit diverse therapeutic opportunities. Hydrogels, and in particular polysaccharides, are the focus of this review, as they have been reported to better sustain vitality of the live cells incorporated. Specifically, the approaches for fabricating hydrogel-based devices with increasing dimensionality (D), namely, 0D (i.e., particles), 1D (i.e., fibers), 2D (i.e., fiber meshes), and 3D (i.e., scaffolds) endowed with probiotics, were detailed by describing their advantages and challenges, along with a future overlook in the field. Electrospinning, electrospray and 3D bioprinting were investigated as new biofabrication methods for probiotic encapsulation within multidimensional matrices. Finally, examples of biomaterial-based systems for cell and post-biotic release were reported.

Accurate weight measurement is pivotal for monitoring the growth and well-being of cattle. However, the conventional weighing process, which involves physically placing cattle on scales, is labor-intensive and distressing for the animals. Hence, the development of automated cattle weight prediction techniques assumes critical significance. This study proposes a weight prediction approach for Korean cattle using 3D segmentation-based feature extraction and regression machine learning techniques from incomplete 3D shapes acquired from real farm environments. In the initial phase, we generated mesh data of 3D Korean cattle shapes using a multiple-camera system. Subsequently, deep learning-based 3D segmentation with the PointNet network model was employed to segment two dominant parts of the cattle. From these segmented parts, three crucial dimensions of Korean cattle were extracted. Finally, we implemented five regression machine learning models (CatBoost regression, LightGBM, Polynomial regression, Random Forest regression, and XGBoost regression) for weight prediction. To validate our approach, we captured 270 Korean cattle in various poses, totaling 1190 poses of 270 cattle. The best result was achieved with mean absolute error (MAE) of 25.2 kg and mean absolute percent error (MAPE) of 5.81% using the random forest regression model.