Human robot collaboration in the MTA SZTAKI learning factory facility at Gyor

In recent years, interest has grown in environments where humans and robots collaborate, complementing the strengths and advantages of humans and machines. Design, construction and adjustment of such environments, as well as the training of operating personnel, requires thorough understanding of the nature of human robot collaboration which previous automation expertise does not necessarily provide. The learning factory currently being constructed by MTA SZTAKI in Gyor aims to provide hands-on experience in the design and operation of facilities supporting human robot collaboration, mainly in assembly tasks. The work-in progress paper presents design principles, functionalities and structure of the facility, and outlines deployment plans in education, training, research and development in the academic and industrial sectors. (C) 2018 The Authors. Published by Elsevier B.V

Modeling The Microrelief Structure of Ti6Al4V Titanium Alloy Surface After Exposure to Femtosecond Laser Pulses

A method of mathematical modeling of the ordered surface relief of titanium alloy Ti6Al4V after femtosecond laser treatment is proposed, which allowed obtaining the informative signs of the self-organized surface irregularities, taking into account the stochastic and cyclic nature of this process. An algorithm has been developed, and a package of computer programs has been created based on the proposed mathematical model. These methods make it possible to analyze the zone-spatial two-dimensional structure of the cyclic relief of the modified surface. They are also the basis for creating the specialized software for the automated profilometric diagnostic systems

A novel approach to fabricate load-bearing Ti6Al4V-Barium titanate piezoelectric bone scaffolds by coupling electron beam melting and field-assisted sintering

A critical-size bone defect in load-bearing areas is a challenging clinical problem in orthopaedic surgery. Titanium alloy (Ti6Al4V) scaffolds have advantages because of their biomechanical stability but lack electrical activity, which hinders their further use. This work is focused on the fabrication of Ti6Al4V-Barium Titanate (BaTiO3) bulk composite scaffolds to combine the biomechanical stability of Ti6Al4V with electrical activity through BaTiO3. For the first time, a hollow cylindrical Ti6Al4V is additively manufactured by electron beam melting and combined with piezoelectric BaTiO3 powder for joint processing in field-assisted sintering. Scanning electron microscope images on the interface of the Ti6Al4V-BaTiO3 composite scaffold showed that after sintering, the Ti6Al4V lattice structure bounded with BaTiO3 matrix without its major deformation. The Ti6Al4V-BaTiO3 scaffold had average piezoelectric constants of (0.63 ± 0.12) pC/N directly after sintering due to partial dipole alignment of the BaTiO3 tetragonal phase, which increased to (4.92 ± 0.75) pC/N after a successful corona poling. Moreover, the nanoindentation values of Ti6Al4V exhibited an average hardness and Young's modulus of (5.9 ± 0.9) GPa and (130 ± 14) GPa, and BaTiO3 showed (4.0 ± 0.6) GPa and (106 ± 10) GPa, respectively. It reveals that the Ti6Al4V is the harder and stiffer part in the Ti6Al4V-BaTiO3 composite scaffold. Such a scaffold has the potential to treat critical-size bone defects in load-bearing areas and guide tissue regeneration by physical stimulation

Efficient bridge steel bearing health monitoring using laser displacement sensors and wireless accelerometers

Steel bearings have been commonly used to counteract induced loading from thermal and traffic conditions in numerous bridges. However, their effectiveness has been compromised due to aging and maintenance limitations, potentially impacting the overall bridge system performance. Existing monitoring techniques for detecting malfunctioning steel bearings lack automation and precision, making them inadequate for long-term and real-time bridge dynamics assessment. This study proposes a response-based approach to identify bearing malfunction by analyzing the traffic-induced response in the bearing vicinity. To implement this approach, laser displacement sensors and wireless acceleration sensors were employed to monitor both malfunctioning and well-functioning steel bridge bearings. Significant differences in bearing performance were observed through response analysis and comparison. Laser sensor measurements revealed larger vertical deflections in the girder at malfunctioned bearing under traffic loading. Moreover, the investigation of the acceleration response in the bearing locality indicated that bearing malfunction could alter the vibrational characteristics of the vicinity, significantly affecting Cross Power Spectral Density (CPSD) and cross-correlation. To quantitatively evaluate the performance of steel bearings, a Condition Score (CS) was introduced. The CS exhibited a strong correlation with bearing damage, providing valuable insights for maintenance and decision-making processes in bridge asset management. This study offers a comprehensive and automated method for identifying steel bridge bearing malfunction by utilizing advanced monitoring techniques and introducing the CS for assessment. The results obtained from this approach can enhance bridge maintenance strategies and contribute to effective bridge asset management

3D printed and stimulus responsive drug delivery systems based on synthetic polyelectrolyte hydrogels manufactured via digital light processing

Hydrogels are three-dimensional hydrophilic polymeric networks absorbing up to and even more than 90 wt% of water. These superabsorbent polymers retain their shape during the swelling process while enlarging their volume and mass. In addition to their swelling behavior, hydrogels can possess other interesting properties, such as biocompatibility, good rheological behavior, or even antimicrobial activity. This versatility qualifies hydrogels for many medical applications, especially drug delivery systems. As recently shown, polyelectrolyte-based hydrogels offer beneficial properties for long-term and stimulus-responsive applications. However, the fabrication of complex structures and shapes can be difficult to achieve with common polymerization methods. This obstacle can be overcome by the use of additive manufacturing. 3D printing technology is gaining more and more attention as a method of producing materials for biomedical applications and medical devices. Photopolymerizing 3D printing methods offer superior resolution and high control of the photopolymerization process, allowing the fabrication of complex and customizable designs while being less wasteful. In this work, novel synthetic hydrogels, consisting of [2-(acryloyloxy) ethyl]trimethylammonium chloride (AETMA) as an electrolyte monomer and poly(ethylene glycol)-diacrylate (PEGDA) as a crosslinker, 3D printed via Digital Light Processing (DLP) using a layer height of 100 μm, are reported. The hydrogels obtained showed a high swelling degree q∞m,t ∼ 12 (24 h in PBS; pH 7; 37 °C) and adjustable mechanical properties with high stretchability (ϵmax ∼ 300%). Additionally, we embedded the model drug acetylsalicylic acid (ASA) and investigated its stimulus-responsive drug release behaviour in different release media. The stimulus responsiveness of the hydrogels is mirrored in their release behavior and could be exploited in triggered as well as sequential release studies, demonstrating a clear ion exchange behavior. The received 3D-printed drug depots could also be printed in complex hollow geometry, exemplarily demonstrated via an individualized frontal neo-ostium implant prototype. Consequently, a drug-releasing, flexible, and swellable material was obtained, combining the best of both worlds: the properties of hydrogels and the ability to print complex shapes

Spin Structure of the Proton from Polarized Inclusive Deep-Inelastic Muon-Proton Scattering

We have measured the spin-dependent structure function $g_1^p$ in inclusive deep-inelastic scattering of polarized muons off polarized protons, in the kinematic range $0.003 < x < 0.7$ and $1 GeV^2 < Q^2 < 60 GeV^2$. A next-to-leading order QCD analysis is used to evolve the measured $g_1^p(x,Q^2)$ to a fixed $Q^2_0$. The first moment of $g_1^p$ at $Q^2_0 = 10 GeV^2$ is $\Gamma^p = 0.136\pm 0.013(stat.) \pm 0.009(syst.)\pm 0.005(evol.)$. This result is below the prediction of the Ellis-Jaffe sum rule by more than two standard deviations. The singlet axial charge $a_0$ is found to be $0.28 \pm 0.16$. In the Adler-Bardeen factorization scheme, $\Delta g \simeq 2$ is required to bring $\Delta \Sigma$ in agreement with the Quark-Parton Model. A combined analysis of all available proton and deuteron data confirms the Bjorken sum rule.Comment: 33 pages, 22 figures, uses ReVTex and smc.sty. submitted to Physical Review

3D Printing of Piezoelectric Barium Titanate-Hydroxyapatite Scaffolds with Interconnected Porosity for Bone Tissue Engineering

The prevalence of large bone defects is still a major problem in surgical clinics. It is, thus, not a surprise that bone-related research, especially in the field of bone tissue engineering, is a major issue in medical research. Researchers worldwide are searching for the missing link in engineering bone graft materials that mimic bones, and foster osteogenesis and bone remodeling. One approach is the combination of additive manufacturing technology with smart and additionally electrically active biomaterials. In this study, we performed a three-dimensional (3D) printing process to fabricate piezoelectric, porous barium titanate (BaTiO3) and hydroxyapatite (HA) composite scaffolds. The printed scaffolds indicate good cytocompatibility and cell attachment as well as bone mimicking piezoelectric properties with a piezoelectric constant of 3 pC/N. This work represents a promising first approach to creating an implant material with improved bone regenerating potential, in combination with an interconnected porous network and a microporosity, known to enhance bone growth and vascularization

Simulating the mechanical stimulation of cells on a porous hydrogel scaffold using an FSI model to predict cell differentiation

3D-structured hydrogel scaffolds are frequently used in tissue engineering applications as they can provide a supportive and biocompatible environment for the growth and regeneration of new tissue. Hydrogel scaffolds seeded with human mesenchymal stem cells (MSCs) can be mechanically stimulated in bioreactors to promote the formation of cartilage or bone tissue. Although in vitro and in vivo experiments are necessary to understand the biological response of cells and tissues to mechanical stimulation, in silico methods are cost-effective and powerful approaches that can support these experimental investigations. In this study, we simulated the fluid-structure interaction (FSI) to predict cell differentiation on the entire surface of a 3D-structured hydrogel scaffold seeded with cells due to dynamic compressive load stimulation. The computational FSI model made it possible to simultaneously investigate the influence of both mechanical deformation and flow of the culture medium on the cells on the scaffold surface during stimulation. The transient one-way FSI model thus opens up significantly more possibilities for predicting cell differentiation in mechanically stimulated scaffolds than previous static microscale computational approaches used in mechanobiology. In a first parameter study, the impact of the amplitude of a sinusoidal compression ranging from 1% to 10% on the phenotype of cells seeded on a porous hydrogel scaffold was analyzed. The simulation results show that the number of cells differentiating into bone tissue gradually decreases with increasing compression amplitude, while differentiation into cartilage cells initially multiplied with increasing compression amplitude in the range of 2% up to 7% and then decreased. Fibrous cell differentiation was predicted from a compression of 5% and increased moderately up to a compression of 10%. At high compression amplitudes of 9% and 10%, negligible areas on the scaffold surface experienced high stimuli where no cell differentiation could occur. In summary, this study shows that simulation of the FSI system is a versatile approach in computational mechanobiology that can be used to study the effects of, for example, different scaffold designs and stimulation parameters on cell differentiation in mechanically stimulated 3D-structured scaffolds

Simulating the mechanical stimulation of cells on a porous hydrogel scaffold using an FSI model to predict cell differentiation

3D-structured hydrogel scaffolds are frequently used in tissue engineering applications as they can provide a supportive and biocompatible environment for the growth and regeneration of new tissue. Hydrogel scaffolds seeded with human mesenchymal stem cells (MSCs) can be mechanically stimulated in bioreactors to promote the formation of cartilage or bone tissue. Although in vitro and in vivo experiments are necessary to understand the biological response of cells and tissues to mechanical stimulation, in silico methods are cost-effective and powerful approaches that can support these experimental investigations. In this study, we simulated the fluid-structure interaction (FSI) to predict cell differentiation on the entire surface of a 3D-structured hydrogel scaffold seeded with cells due to dynamic compressive load stimulation. The computational FSI model made it possible to simultaneously investigate the influence of both mechanical deformation and flow of the culture medium on the cells on the scaffold surface during stimulation. The transient one-way FSI model thus opens up significantly more possibilities for predicting cell differentiation in mechanically stimulated scaffolds than previous static microscale computational approaches used in mechanobiology. In a first parameter study, the impact of the amplitude of a sinusoidal compression ranging from 1% to 10% on the phenotype of cells seeded on a porous hydrogel scaffold was analyzed. The simulation results show that the number of cells differentiating into bone tissue gradually decreases with increasing compression amplitude, while differentiation into cartilage cells initially multiplied with increasing compression amplitude in the range of 2% up to 7% and then decreased. Fibrous cell differentiation was predicted from a compression of 5% and increased moderately up to a compression of 10%. At high compression amplitudes of 9% and 10%, negligible areas on the scaffold surface experienced high stimuli where no cell differentiation could occur. In summary, this study shows that simulation of the FSI system is a versatile approach in computational mechanobiology that can be used to study the effects of, for example, different scaffold designs and stimulation parameters on cell differentiation in mechanically stimulated 3D-structured scaffolds.</p