articles+ search results

штучний інтелект, fpga, ші як сервіс, гетерогенні проєкти ші систем, апаратні прискорювачі ші, dpu, інструментальні засоби розробки ші, xrt, Motor vehicles. Aeronautics. Astronautics, and TL1-4050

The subject of study in this article is modern technologies, tools and methods of building AI systems as a service using FPGA as a platform. The goal is to analyze modern technologies and tools used to develop FPGA-based projects for systems that implement artificial intelligence as a service and to prepare a practical AI service prototype. Task: to analyze the evolution of changes in the products of leading manufacturers of programmable logic devices and experimental and practical examples of the implementation of the paradigm of continuous reprogramming of programmable logic; analyze the dynamics of changes in the development environment of programmable logic systems for AI; analyze the essential elements of building projects for AI systems using programmable logic. According to the tasks, the following results were obtained. The area of application of hardware implementation of artificial intelligence for on-board and embedded systems including airspace industry, smart cars and medical systems is analyzed. The process of programming FPGA accelerators for AI projects is analyzed. The analysis of the capabilities of FPGA with HBM for building projects that require enough of high speed memory is performed. Description languages, frameworks, the hierarchy of tools for building of hardware accelerators for AI projects are analyzed in detail. The stages of prototyping of AI projects using new FPGA development tools and basic DPU blocks are analyzed. The parameters of the DPU blocks were analyzed. Practical steps for building such systems are offered. The practical recommendations for optimizing the neural network for FPGA implementation are given. The stages of neural network optimization are provided. The proposed steps include pruning of branches with low priority and the use of fixed point computations with custom range based on the requirements of an exact neural network. Based on these solutions, a practical case of AI service was prepared, trained and tested. Conclusions. The main contribution of this study is that, based on the proposed ideas and solutions, the next steps to create heterogeneous systems based on the combination of three elements are clear: AI as a service, FPGA accelerators as a technology for improving performance, reliability and security, and cloud or Edge resources to create FPGA infrastructure and AI as service. The development of this methodological and technological basis is the direction of further R&D.

Directed energy deposition, entropy, grain refinement, alloy design, Industrial engineering. Management engineering, and T55.4-60.8

Additive manufacturing (AM) is a tool for rapid prototyping with complex geometry. However, the cyclic heating and cooling in laser melting processes often cause large columnar grains that dominate the as-printed microstructure, resulting in a strong texture and anisotropic properties that limit the application of AM. In this work, we apply powder-based directed energy deposition to discover new alloys using mixtures of Inconel 718 (IN718) and Stainless Steel 316L (SS316L). We discovered that the 77 wt.% IN718 alloy mixture, with the highest configurational entropy, demonstrated an intriguingly fine grain structure in the as-built condition and after homogenization at 1180°C. Residual stress from the laser melting process was identified as the primary cause of the observed grain refinement phenomenon. Although, a quantitative analysis of the changes in grain size after homogenization in the alloy mixtures of IN718 and SS316L requires further research. The discovery of this unique microstructural behavior shows how in-situ mixing of commercially available powders can be used to develop next-generation feedstock materials for AM and improve the understanding of fundamental process-microstructure-property relationships.

3D printing, Zinc submicron particles, Osteoinductivity, Anti-inflammatory, Bone defect repair, Materials of engineering and construction. Mechanics of materials, TA401-492, Biology (General), and QH301-705.5

Long-term nonunion of bone defects has always been a major problem in orthopedic treatment. Artificial bone graft materials such as Poly (lactic-co-glycolic acid)/β-tricalcium phosphate (PLGA/β-TCP) scaffolds are expected to solve this problem due to their suitable degradation rate and good osteoconductivity. However, insufficient mechanical properties, lack of osteoinductivity and infections after implanted limit its large-scale clinical application. Hence, we proposed a novel bone repair bioscaffold by adding zinc submicron particles to PLGA/β-TCP using low temperature rapid prototyping 3D printing technology. We first screened the scaffolds with 1 wt% Zn that had good biocompatibility and could stably release a safe dose of zinc ions within 16 weeks to ensure long-term non-toxicity. As designed, the scaffold had a multi-level porous structure of biomimetic cancellous bone, and the Young's modulus (63.41 ± 1.89 MPa) and compressive strength (2.887 ± 0.025 MPa) of the scaffold were close to those of cancellous bone. In addition, after a series of in vitro and in vivo experiments, the scaffolds proved to have no adverse effects on the viability of BMSCs and promoted their adhesion and osteogenic differentiation, as well as exhibiting higher osteogenic and anti-inflammatory properties than PLGA/β-TCP scaffold without zinc particles. We also found that this osteogenic and anti-inflammatory effect might be related to Wnt/β-catenin, P38 MAPK and NFkB pathways. This study lay a foundation for the follow-up study of bone regeneration mechanism of Zn-containing biomaterials. We envision that this scaffold may become a new strategy for clinical treatment of bone defects.

Power electronics, Inverters, Rapid control prototyping, Experimental setups, Science (General), and Q1-390

A flexible power electronic converter embedding a rapid control prototyping platform suitable to be applied in research test setups and teaching laboratories is proposed and described in this paper. The electronic system is composed of three subsystems, namely, i) three half-bridge power boards, ii) a dc-link capacitor bank with a half-bridge power module for active dc-link control, iii) an interfacing board, called motherboard, to couple the power modules with a control unit, iv) a digital control unit with rapid control prototyping functionalities for controlling power electronic circuits. Power modules integrate sensors with related conditioning circuits, driving circuits for power switches, and protection circuits. Conversion circuits exploit GaN electronic switches for optimal performance. The architecture and implementation of the system are described in detail in this manuscript. Main applications are in the implementation of conversion circuits for supplying arbitrary ac or dc voltages or currents, testing of new control algorithms for power electronic converters, testing of systems of electronic converters in, for example, smart nanogrids or renewable energy applications, training of undergraduate and graduate students.

jaw defect, functional reconstruction, digital technology, computer-aided design, 3d printing, personalized surgical instruments, preoperative virtual surgery, immediate implantation, and Medicine

With the development of computer-aided surgery and rapid prototyping via 3D printing technology, digital surgery has rapidly advanced in clinical practice, especially in the field of oral and maxillofacial surgery. 3D printing technology has been applied to the functional restoration and reconstruction of the jawbone. Before surgery, a 3D digital model is constructed through software to plan the scope of the osteotomy, shape the bone graft and plan the placement of the implant. Additionally, 3D models of personalized surgical instrument guides are printed prior to surgery. With these 3D-printed models and guides, accurate excision of the jaw tumor, accurate placement of the grafted bone and precise placement of implants can be achieved during surgery. Postoperative evaluation of accuracy and function shows that 3D printing technology can aid in achieving the biomechanical goals of simultaneous implant placement in jaw reconstruction, and in combination with dental implant restoration, the technology can improve patients' postoperative occlusal and masticatory functions. Nevertheless, 3D printing technology still has limitations, such as time-consuming preparation before surgery. In the future, further development of 3D printing technology, optimization of surgical plans, and alternative biological materials are needed. Based on domestic and foreign literature and our research results, we have reviewed the process and clinical application prospects of jaw reconstruction via 3D printing technology to provide a reference for oral and maxillofacial surgeons.

Artificial intelligence, Machine learning, AutoML, Business analytics, Data-driven decision making, Digital transformation, Cybernetics, Q300-390, Electronic computers. Computer science, and QA75.5-76.95

The realization that AI-driven decision-making is indispensable in today's fast-paced and ultra-competitive marketplace has raised interest in industrial machine learning (ML) applications significantly. The current demand for analytics experts vastly exceeds the supply. One solution to this problem is to increase the user-friendliness of ML frameworks to make them more accessible for the non-expert. Automated machine learning (AutoML) is an attempt to solve the problem of expertise by providing fully automated off-the-shelf solutions for model choice and hyperparameter tuning. This paper analyzed the potential of AutoML for applications within business analytics, which could help to increase the adoption rate of ML across all industries. The H2O AutoML framework was benchmarked against a manually tuned stacked ML model on three real-world datasets. The manually tuned ML model could reach a performance advantage in all three case studies used in the experiment. Nevertheless, the H2O AutoML package proved to be quite potent. It is fast, easy to use, and delivers reliable results, which come close to a professionally tuned ML model. The H2O AutoML framework in its current capacity is a valuable tool to support fast prototyping with the potential to shorten development and deployment cycles. It can also bridge the existing gap between supply and demand for ML experts and is a big step towards automated decisions in business analytics. Finally, AutoML has the potential to foster human empowerment in a world that is rapidly becoming more automated and digital.

Upscaling, Scaling up, Climate services, Prototyping, Pilot projects, Meteorology. Climatology, QC851-999, Social sciences (General), and H1-99

Translating climate data and information for use in real-world applications often involves the development of climate service prototypes within the constraints of pilot or demonstration projects. However, these services rarely make the transition from prototype to fully-fledged, transferrable and/or repeatable climate services – that is, there are problems with upscaling them beyond the pilot/demonstrator phase.In this paper we are using the mainstream understanding of the three main types of upscaling: reaching many (horizontal), enhancing the enabling environment (vertical), and expanding the product or service’s features (functional). Through a review of the general upscaling literature, coupled with focused interviews with weather/climate services experts, we found that there are common barriers to, and enablers for, successful upscaling – many of which apply to the specific case of upscaling climate services. Barriers include problems with leadership (e.g. the absence of a long-term vision and/or strategy for upscaling); limited funding or lack of a business model for the service at scale; issues with the enabling environment for upscaling (e.g. poor policy context, inadequate governance systems); and poor user engagement.Lessons learned from the literature in the context of upscaling climate services include planning for it as early as possible in the prototyping process; including a monitoring, evaluation and learning approach to inform upscaling progress; taking actions to foster and enhance the enabling environment; and searching for a balance between generic solutions and fit-for-purpose products.

additive manufacturing, 3d printing, materials mechanics, manufacturing engineering, industrial engineering, Science, Manufactures, and TS1-2301

Mechanical engineering and machinery and TJ1-1570

To overcome the inefficiency of slicing process of rapid prototyping based on STL models, an improved slicing algorithm is proposed. The method builds integral topology of STL models in advance using a Hash table, which enables to get contours directly, and then reduces the search range in slicing by establishing the slicing relation matrix, which can effectively reduce the time cost of slicing. It has been demonstrated that the algorithm has nearly linear time complexity. The method is proved to be effective and efficient through application cases, and the results show better performance than other existing algorithms, especially when the STL model is complex or large.

Shoulder reduction, Simulation device, Traction-countertraction, External rotation maneuver, Computer applications to medicine. Medical informatics, and R858-859.7

Abstract Background Shoulder dislocations are common occurrences, yet there are few simulation devices to train medical personnel on how to reduce these dislocations. Reductions require a familiarity with the shoulder and a nuanced motion against strong muscle tension. The goal of this work is to describe the design of an easily replicated, low-cost simulator for training shoulder reductions. Materials and methods An iterative, stepwise engineering design process was used to design and implement ReducTrain. A needs analysis with clinical experts led to the selection of the traction-countertraction and external rotation methods as educationally relevant techniques to include. A set of design requirements and acceptance criteria was established that considered durability, assembly time, and cost. An iterative prototyping development process was used to meet the acceptance criteria. Testing protocols for each design requirement are also presented. Step-by-step instructions are provided to allow the replication of ReducTrain from easily sourced materials, including plywood, resistance bands, dowels, and various fasteners, as well as a 3D-printed shoulder model, whose printable file is included at a link in the Additional file 1: Appendix. Results A description of the final model is given. The total cost for all materials for one ReducTrain model is under US $200, and it takes about 3 h and 20 min to assemble. Based on repetitive testing, the device should not see any noticeable changes in durability after 1000 uses but may exhibit some changes in resistance band strength after 2000 uses. Discussion The ReducTrain device fills a gap in emergency medicine and orthopedic simulation. Its wide variety of uses points to its utility in several instructional formats. With the rise of makerspaces and public workshops, the construction of the device can be easily completed. While the device has some limitations, its robust design allows for simple upkeep and a customizable training experience. Conclusion A simplified anatomical design allows for the ReducTrain model to serve as a viable training device for shoulder reductions.

3D printing, Direct ink writing, Ceramic slurry, Kaolin, Adsorption, Chemical engineering, TP155-156, Biochemistry, and QD415-436

The construction of rapid prototyping for structured ceramics has a promoting effect on potential applications. In this work, engineering slurry with different formulations were used to develop aqueous colloidal ceramic slurry for direct ink writing (DIW). Optimized slurry of Formulation 5 possessed good printing effect for DIW with stable mechanical properties. Related characteristics, including shrinkage, compressive strength, rheological behavior, and chemical property, were also examined. DIW ceramics prepared from optimized slurry can be preliminarily applied to adsorption of Rhodamine B and chlortetracycline, and possessed the advantages of easy separation and operation compared with powder adsorbents. This work provides a strategy for the design of 3D-printed kaolin ceramic slurry, and also extends to potential application in adsorption.

Prototype intervention, Usability testing, sEMG, Supine sitting posture, Comfort perception, Science (General), Q1-390, Social sciences (General), and H1-99

Employees who work long hours frequently complain of muscle fatigue caused by prolonged sitting. As a result, products that assist them when resting in a chair in a reclining position, in order to relieve fatigue and improve comfort are required. To ensure that the new product works as intended, a usability test based on prototyping must be developed. The research process was divided into three stages: firstly, the development of the perception assessment questionnaire; secondly, a validated factor analysis (CFA) was conducted on the perception assessment data of 26 subjects and the measurement model was fitted to verify the reliability and validity of the questionnaire; finally, the sEMG technique was used to verify the comfort level of 21 subjects. Based on usability experiments and an exploration of human factor relationships, this study develops a prototype testing model, which focuses on the comfort perception of body parts, as a means of promoting innovation in the design and manufacturing industry.

Usability testing, Elementary school students, and Children -- Health aspects

Keywords Cerebral visual impairment; Individualized visuoperceptual profile; Adaptive serious game-based therapy; Usability; User experience; Gameplay log-data Abstract Developing a novel game-based therapy requires expert feedback as well as full participation by the eventual end-users of the therapy. In this pilot study, we aimed to investigate (1) usability, (2) user experience, and (3) gameplay log-data of newly developed visuoperceptual games in children with cerebral visual impairment (CVI) (developmental age between 3-12 years) during three short sessions. The mini-games integrate three key features: (1) entry-level individualization defined by the child's visuoperceptual profile, (2) in-game adaptivity, and (3) gameplay log-data. We observed children's interaction with the mini-games and measured their user experience using the This-or-That method, the laddering technique, and the Relative Enjoyment Scale for Primary School Children adapted for children with CVI. Finally, we evaluated children's gameplay using their log-data. While children appreciated the games highly, several usability issues occurred regarding effectiveness, understandability, and game development. Importantly, integrating gameplay log-data optimized usability testing by providing fine-grained information on gameplay performance. By synthesizing information gained, we derive design implications for the further development, prototyping, and more thorough testing of similar games. Based on usability observations, we report nine design implications including tailored interactions/gestures/instructions, language, providing player control, time to familiarize, balancing help and challenge, autonomy, avoiding fine motor skills and multiple action sequences, and integrating visual consistency. Moreover, five design implications based on user experience and enjoyment highlight the importance of reward, challenge, immersive realistic experiences, immediate feedback, and a rich media experience, supporting 'flow' theory. Author Affiliation: (a) Department of Development and Regeneration, University of Leuven (KU Leuven), Leuven, Belgium (b) Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Brussels, Belgium (c) imec, Leuven, Belgium (d) Department of Brain & Cognition, University of Leuven (KU Leuven), Leuven, Belgium (e) Leuven Brain Institute (LBI), Leuven, Belgium (f) Child Youth, Institute (L-C&Y), Leuven, Belgium * Corresponding author. Article History: Received 7 September 2021; Revised 22 October 2022; Accepted 21 November 2022 (footnote)[white star] The views expressed in the submitted article are our own and not an official position of the institution or funder. This work is part of the iVision project which was supported by the Fund Scientific Research Flanders (FWO-project) (grant number T003817N). Author JW was supported by the Flemish Government (grant number METH/14/02). Byline: N. Ben Itzhak [nofar.benitzhak@kuleuven.be] (a,f,*), I. Franki (a), B. Jansen (b,c), K. Kostkova (b,c), J. Wagemans (d,e), E. Ortibus (a,f)

digital orthodontics, stereolithography, three-dimensional printing, and Medicine

Introduction: The digitalisation of dental models has made significant contribution to the current success of orthodontic practices. Rapid Prototyping (RP) is an innovative method of producing physical objects based on Computer-Aided Design (CAD) Computer-Aided Manufacturing (CAM). Aim: To compare the accuracy of the Three-Dimensional (3D) printed rapid prototyped models with orthodontic stone models across different ranges of crowding. Materials and Methods: A cross-sectional study carried out at the Bharati Vidyapeeth Deemed to be University, Dental College and Hospital, Sangli, Maharashtra, India during September 2019 to September 2020. A total of 36 rapid prototyped models were reconstructed from stone models using Light Emitting Diode (LED) scanner and Digital Light Processing (DLP) technology. Dental stone models and RP models were evaluated using digital caliper for different linear measurements and arch dimensions. The data was analysed using Statistical Package for Social Sciences (SPSS) version 26.0. To evaluate accuracy, t-test analyses and Bland-Altman plotting were performed. Results: T-test showed statistically non significant difference in all parameters of measurements of RP models when compared to stone models. According to Bland-Altman plotting. The mean difference between stone and RP models for the various degree of crowding was minimal and within ±0.07 mm in all planes. Conclusion: Discrepancy between dental plaster models and RP models were less than 0.5 mm which was considered clinically non significant. Suggesting that RP models can be effectively used as an alternative to stone models.

Theory and practice of education and LB5-3640

Digital games can be used as educational tools for tackling structural inequalities and promoting social justice. Designing games with these purposes is often a complex task that requires a myriad of combined expertise, including games’ mechanics, software development, educational game design, pedagogy, and knowledge of the educational topic (which can target very specific social issues). Democratising the design of educational games is used to increase the agency and participation of diverse and novice groups throughout design processes - and can be used to improve the efficiency of such games as it directly leads to the inclusion of broad voices, knowledge, experiences and perspectives. This research adopted a Design-Based Research methodology to create, evaluate and validate 13 design principles to democratise the design of educational games for social change. Three research phases were implemented in turn: a preliminary research, prototyping and evaluation phase. The preliminary research phase was based on creating these principles by grounding them on fundamentals of Critical Pedagogy, a theory of education which presents pedagogical techniques to accelerate learning, engagement and social change. The prototyping phase was based on conducting semi-structured interviews to assess and improve these principles with educational and game design experts. During the evaluation phase, these principles were applied and evaluated during two weekend-long game design events, which were mostly attended by diverse groups who had never designed a digital game before. This research presents theoretical and practical contributions related to how to democratise educational game design for social change. It evidenced the relevance of facilitating design principles that addresses what could be done to trigger learning in games by presenting design principles; why this learning could be facilitated, from both educational and gaming perspectives; and how to implement these principles into an educational game.

Additive Manufacuring, 3D Printing, Infill Pattern, Tensile Strength, Fused Filament Fabrication, Material Extrusion, and Technology

Additive Manufacturing (AM) applications have expanded significantly from rapid prototyping to high-end products such as complex spare parts. AM has enabled advantages of reduced material usage, geometric freedom, and production automation, shaping the future of the manufacturing industries. With the rapid expansion of AM applications, feedstock materials have developed noticeably, from polymers and ceramics to metals and composites. The progress in metal feedstock material discoveries has empowered the exploration of implementing new AM technologies. Fused Filament Fabrication (FFF) is one of the most common and cost-effective material extrusion AM technologies. This study explores the effect of the infill pattern on the tensile mechanical properties of metal parts produced via FFF, using two feedstock materials, 17-PH stainless steel and copper. Two approaches are designed to investigate the results: experimental tensile test, and Finite Element Analysis (FEA) with digital twin reconstruction method. Results show that 17-4 PH Stainless Steel samples with a triangular infill exhibited a 42% drop in ultimate tensile strength compared to solid infill. However, it also revealed a 34% reduction in mass, cost saving of 36%, and a faster fabrication with a 25% reduction in lead time. At the same time, copper samples with triangular infill exhibited a 22% drop in ultimate tensile strength and a 12% mass reduction. However, it revealed a similar lead time with only a 3% reduction. A Scanning Electron Microscope (SEM) was used to investigate the parts’ internal structure and average pore size, to understand the failure mode of the test specimens.

Metal additive manufacturing (MAM), Laser powder bed fusion (L-PBF), Machine learning (ML), Process parameter optimization, Anomaly detection, and Technology

Metal Additive Manufacturing (MAM) applications are growing rapidly in high-tech industries such as biomedical and aerospace, and in many other industries including tooling, casting, automotive, oil and gas for production and prototyping. The onset of Laser Powder Bed Fusion (L-PBF) technology proved to be an efficient technique that can convert metal additive manufacturing into a reformed process if anomalies occurred during this process are eliminated. Industrial applications demand high accuracy and risk-free products whereas prototyping using MAM demand lower process and product development time. In order to address these challenges, Machine Learning (ML) experts and researchers are trying to adopt an efficient method for anomaly detection in L-PBF so that the MAM process can be optimized and desired final part properties can be achieved. This review provides an overview of L-PBF and outlines the ML methods used for anomaly detection in L-PBF. The paper also explains how ML methods are being used as a step forward toward enabling the real-time process control of MAM and the process can be optimized for higher accuracy, lower production time, and less material waste. Authors have a strong believe that ML techniques can reform MAM process, whereas research concerned to the anomaly detection using ML techniques is limited and needs attention.This review has been done with a hope that ML experts can easily find a direction and contribute in this field.

Android, Communication, Deaf, Disability, Dumb, Hardware, and Science

People living with disability constitute a significant percentage of the world population. For many people with disabilities, assistance and support are prerequisites for participating in societal activities. This research work developed a hardware prototype of a robotic hand forfor sign language communication with persons living with hard-of-hearing disabilities (deaf and/or dumb). The prototype has three basic modules: the input unit, the control unit, and the robotic hand. The input unit is designed as an Android-based mobile application with speech recognition capabilities while the control unit is ATMEGA 2560 microcontroller board. The robotic hand is constructed using locally available materials (bathroom Slippers, expandable rubber, straw pipe, and tiny rope) together with three servo motors and is designed to look and perform movements similar to a human hand. The prototype was evaluated quantitatively in terms of empirical accuracy and response time. It was also evaluated qualitatively by thirty-five (35) users which included fifteen (15) experience ASL users, eighteen (18) non-experience ASL users, and two (2) ASL experts, who completed questionnaires to rate the prototype on a 5-point Likert scale in terms of five parameters: functionality, reliability, ease of use, efficiency, and portability. An accuracy of 78.43% with an average response time of 2 s was obtained from empirical experiments. Statistical analysis of user responses showed that 97%, 68%, 77%, 80%, and 83% of users rated the system as above average for functionality, reliability, ease of use, efficiency, and portability, respectively. The robotic hand effectively communicates American Sign Language which includes English Alphabets, numbers (1–9), and some selected common words, which can be demonstrated with a single hand for hard of hearing persons. To the best of our knowledge, this work is the first ASL robotic hand that is based on locally sourced cost-effective materials, and we build on flaws from existing literature, most of which are either template-based, not real-time, or expensive. In terms of future work, the prototype can be improved by extending the single robotic hand to a fully robotic body with two hands.

3d printing, food, additives, rheological properties, processing characteristics, Food processing and manufacture, and TP368-456

As a new technology in the field of food science, three-dimensional (3D) printing technology has tremendous development potential due to its rapid prototyping capabilities, suitability for complex structures, and customization. Proteins, lipids, and other edible substances are generally used as materials in 3D food printing, but not all ingredients can be printed or processed well. 3D food printing technology, the properties of 3D printing materials, common food additives and their effects on rheological properties, processing properties, and nutritional properties of print materials are reviewed in this paper. This study would provide a scientific basis for the application of 3D food printing technology in the food field and theoretical references.

Workflow software, Sustainable development -- Methods, Founding -- Methods, Sand, gravel and stone industry -- Production processes, and Manufacturing costs -- Methods

Keywords: cost modeling system; knowledge database; sand casting process; Set-based concurrent engineering; User interface Abstract In recent years, the reliable, accurate, and timely estimate of product cost at the conceptual design stage can enhance the competitiveness of a casting part. Set-based concurrent engineering has emerged as an efficient solution to overcome this limitation as it provides simultaneous design procedures to positively assist the designer in achieving the required customer values in a short time and low cost. Therefore, this study attempts to integrate the set-based concurrent engineering methodology into the development of a cost modeling system for the metal casting process. The system architecture is comprised of a user interface, knowledge database, and CAD modeling system. A detailed working flow process of the developed cost modeling system has been proposed under the guidelines of set-based concurrent engineering. Further, the proposed methodology is demonstrated and validated by employing a real-time casting part that was manufactured using the sand casting process. The implementation of the system provided many tangible benefits to the collaborative company including a decrease in cost estimation time (â¼50%) and part rejection rate (â¼32.3%). Further, the developed cost modeling approach provided a cost estimate near the actual cost of the product (â¼4% deviation). It truly proves the significance of the developed system for the practitioners who believe that accurate and timely estimates of product manufacturing cost at the design stage can enhance the competitiveness of a product. Biographical information: Muhammad Sajid was born in Layyah, Punjab, Pakistan, in 1993. He received his PhD degree in Engineering Management from UET Taxila in 2020. He is currently working as an Assistant Professor in the Industrial Engineering Department of the University of Engineering and Technology (UET), Taxila, Punjab, Pakistan, and MSc, PhD supervisor. His research interests are in the field of Cost Engineering, Lean Thinking, and Metal Casting Processes. Currently, his research projects include the development of Rapid Prototyping Tooling Technology to Assist the Development of Low Cost Dies to realize sustainable developments in the manufacturing sector of Pakistan. Wasim Ahmad is professor at Industrial Engineering Department, University of Engineering and Technology, Taxila, Pakistan. He has received his PhD degree from Canfield University, United Kingdom. His research area is product design and development, Lean Thinking, Cost Engineering, optimization and manufacturing processes. Salman Hussain is Associate Professor at Industrial Engineering Department, University of Engineering and Technology, Taxila, Pakistan. He has received his PhD degree from University, United Kingdom. His research area is Automation and Robotics, Process Planning and CAM, optimization and manufacturing processes. Muhammad Huzaifa Raza is a PhD student at Industrial and Manufacturing Systems Engineering, The University of Hong Kong. His research area mainly includes mechanical characteristics analysis, cost analysis of manufacturing components. Professor Mirza Jahanzaib is chairman at Industrial Engineering Department, University of Engineering and Technology, Taxila, Pakistan. He has received his PhD degree from University of Engineering and Technology Taxila. His research area is Sustainable Manufacturing Systems, Advanced Manufacturing Processes, Metal Forming and Cutting Analysis, and Optimization. Byline: Muhammad Sajid, Ahmad Wasim, Salman Hussain, Muhammad Huzaifa Raza, Mirza Jahanzaib

Keywords: ab initio; electronic structure; FANCI; method development; Python Abstract Fanpy is a free and open-source Python library for developing and testing multideterminant wavefunctions and related ab initio methods in electronic structure theory. The main use of Fanpy is to quickly prototype new methods by making it easier to convert the mathematical formulation of a new wavefunction ansätze to a working implementation. Fanpy is designed based on our recently introduced Flexible Ansatz for N-electron Configuration Interaction (FANCI) framework, where multideterminant wavefunctions are represented by their overlaps with Slater determinants of orthonormal spin-orbitals. In the simplest case, a new wavefunction ansatz can be implemented by simply writing a function for evaluating its overlap with an arbitrary Slater determinant. Fanpy is modular in both implementation and theory: the wavefunction model, the system's Hamiltonian, and the choice of objective function are all independent modules. This modular structure makes it easy for users to mix and match different methods and for developers to quickly explore new ideas. Fanpy is written purely in Python with standard dependencies, making it accessible for various operating systems. In addition, it adheres to principles of modern software development, including comprehensive documentation, extensive testing, quality assurance, and continuous integration and delivery protocols. This article is considered to be the official release notes for the Fanpy library. Article Note: Funding information Canada Research Chairs; Natural Sciences and Engineering Research Council of Canada; CANARIE; Compute Canada; Research Board of Ghent University; University of Florida Byline: Taewon D. Kim, M. Richer, Gabriela Sánchez-Díaz, Ramón Alain Miranda-Quintana, Toon Verstraelen, Farnaz Heidar-Zadeh, Paul W. Ayers

H∞ algorithm, rapid prototyping, displacement volume control, axial piston pump, Industrial engineering. Management engineering, T55.4-60.8, Electronic computers. Computer science, and QA75.5-76.95

A system for the rapid prototyping of real-time control algorithms for open-circuit variable displacement axial-piston pumps is presented. In order to establish real-time control, and communication and synchronization with the programmable logic controller of an axial piston pump, the custom CAN communication protocol is developed. This protocol is realized as a Simulink® S-function, which is a part of main Simulink® model. This model works in real-time and allows for the implementation of rapid prototyping of various control strategies including advanced algorithms such as H∞ control. The aim of the algorithm is to achieve control system performance in the presence of various load disturbances with an admissible control signal rate and amplitude. In contrast to conventional systems, the developed solution suggests using an embedded approach for the prototyping of various algorithms. The obtained results show the advantages of the designed H∞ controller that ensure the robustness of a closed-loop system in the presence of significant load disturbances. These type of systems with displacement volume regulation are important for industrial hydraulic drive systems with relatively high power.

tissue engineering and regenerative medicine, biopolymers, nanofabrication techniques, additive manufacturing, rapid prototyping, customized therapy 3D scaffolds, Technology, Biology (General), and QH301-705.5

Over the last few years, biopolymers have attracted great interest in tissue engineering and regenerative medicine due to the great diversity of their chemical, mechanical, and physical properties for the fabrication of 3D scaffolds. This review is devoted to recent advances in synthetic and natural polymeric 3D scaffolds for bone tissue engineering (BTE) and regenerative therapies. The review comprehensively discusses the implications of biological macromolecules, structure, and composition of polymeric scaffolds used in BTE. Various approaches to fabricating 3D BTE scaffolds are discussed, including solvent casting and particle leaching, freeze-drying, thermally induced phase separation, gas foaming, electrospinning, and sol–gel techniques. Rapid prototyping technologies such as stereolithography, fused deposition modeling, selective laser sintering, and 3D bioprinting are also covered. The immunomodulatory roles of polymeric scaffolds utilized for BTE applications are discussed. In addition, the features and challenges of 3D polymer scaffolds fabricated using advanced additive manufacturing technologies (rapid prototyping) are addressed and compared to conventional subtractive manufacturing techniques. Finally, the challenges of applying scaffold-based BTE treatments in practice are discussed in-depth.

cardiopulmonary resuscitation, Mechanical ventilation, Mechanical chest-compression, Respiratory monitoring, Thiel embalmed cadaver, Biomechanics, Computer applications to medicine. Medical informatics, R858-859.7, Science (General), and Q1-390

The data presented in this article relate to the research article, “Reliability of mechanical ventilation during continuous chest compressions: a crossover study of transport ventilators in a human cadaver model of CPR” [1].This article contains raw data of continuous recordings of airflow, airway and esophageal pressure during the whole experiment. Data of mechanical ventilation was obtained under ongoing chest compressions and from repetitive measurements of pressure-volume curves. All signals are presented as raw time series data with a sample rate of 200Hz for flow and 500 Hz for pressure. Additionally, we hereby publish extracted time series recordings of force and compression depth from the used automated chest compression device. Concomitantly, we report tables with time stamps from our laboratory book by which the data can be sequenced into different phases of the study protocol.We also present a dataset of derived volumes which was used for statistical analysis in our research article together with the used exclusion list.The reported dataset can help to understand mechanical properties of Thiel-embalmed cadavers better and compare different models of cardiopulmonary resuscitation (CPR). Future research may use this data to translate our findings from bench to bedside. Our recordings may become useful in developing respiratory monitors for CPR, especially in prototyping and testing algorithms of such devices.

inter-cell interference, sub-channel allocation, interference prediction, Electronics, and TK7800-8360

Inter-cell interference cancellation has been investigated for several decades and has become an elementary technique for modern wireless networks. However, the existing interference cancellation mechanism rarely considers the historical channel variations and interference characteristics. In this paper, we propose an interference-aware prediction-based resource-allocation strategy to deal with multi-cell interference, where the historical noisy channel state and the acknowledgment feedback are fully utilized. Together with the predicted interference patterns, our proposed joint sub-channel allocation and rate selection mechanism can achieve better average throughput performance. Through the numerical as well as the prototyping results, we show that our proposed scheme is able to provide more than 9.7% and 8% average throughput improvement compared with many existing baselines.

induction heating, energy dosing, resonant power converters, analysis, design and prototyping, and Technology

This article presents an analysis and methodology for designing resonant inverters with energy dosing for induction heating applications. These power topologies are characterized by the fact that the power consumption of the DC power source does not depend on the magnitude and changes of the load but is a function of the operating frequency, the value of the resonant capacitor and the DC supply voltage. Based on a description of the electromagnetic processes in the power circuit, analytical dependencies have been determined that describe the behavior of the studied power electronic devices. The expressions for the current of the AC circuit in the various stages of the converter’s operation are obtained, and on this basis an engineering methodology for design and prototyping is presented. The proposed methodology is verified through two specific numerical examples, simulation and experimental studies. In this way, the possibilities of these power electronic devices for self-adaptation to the needs and changes of the load, which is very important in the implementation of induction technologies, are demonstrated. Furthermore, the creation and testing of engineering methodologies for the design of power electronic devices are very useful for improving power electronics education.

mathematical prototyping method, energy processes, systems identification, symbolic regression, digital twins, and Technology

The use of digital twins in smart power systems at the stages of the life cycle is promising. The dynamics of such systems (smart energy renewable sources, smart energy hydrogen systems, etc.), are determined mainly by the physical and chemical processes occurring inside the systems. The basis for developing digital twins is reliable mathematical models of the systems. In the present paper, the authors present a method of energy processes mathematical prototyping—an overall approach to modeling processes of various physical and chemical natures based on modern non-equilibrium thermodynamics, mechanics, and electrodynamics. Controlled parameters are connected with measured ones by developing a theoretically correct system of process dynamics equations with accuracy up to the experimentally studied properties of substances and processes. Subsequent transformation into particular mathematical models of a specific class of systems makes this approach widely applicable. The properties of substances and processes are given in the form of functional dependencies on the state of the system up to experimentally determined constant coefficients. The authors consider algorithms for identifying the constant coefficients of the functions of substances and processes properties, which complement the proposed unified approach of designing models of various physical and chemical nature systems.

coloured BIPV, optimization, simulation, and Technology

Coloured building integrated photovoltaics (BIPVs) may contribute to meeting the decarbonisation targets of European and other countries. Nevertheless, their market uptake has been hindered by a lack of social acceptance, technical issues, and low economic profitability. Being able to assess in advance the influence of the coloured layers on a module’s power generation may help reduce the need for prototyping, thereby allowing optimisation of the product performance by reducing the time and costs of customised manufacturing. Therefore, this review aims at investigating the available literature on models and techniques used for assessing the influence of coloured layers on power generation in customised BIPV products. Existing models in the literature use two main approaches: (i) detailed optical modelling of the layers in the module’s stack, including coloured layers, and (ii) mathematical elaboration of the final product’s measured characteristics. Combining the two approaches can provide improved future models, which can accurately assess every single layer in the module’s stack starting from measured parameters obtained with simpler equipment and procedures.

computing arrays, field programmable analog arrays, leaky integrate and fire neuron, tactile sensing system, field programmable gate arrays, Neurosciences. Biological psychiatry. Neuropsychiatry, and RC321-571

Intelligent sensor systems are essential for building modern Internet of Things applications. Embedding intelligence within or near sensors provides a strong case for analog neural computing. However, rapid prototyping of analog or mixed signal spiking neural computing is a non-trivial and time-consuming task. We introduce mixed-mode neural computing arrays for near-sensor-intelligent computing implemented with Field-Programmable Analog Arrays (FPAA) and Field-Programmable Gate Arrays (FPGA). The combinations of FPAA and FPGA pipelines ensure rapid prototyping and design optimization before finalizing the on-chip implementations. The proposed approach architecture ensures a scalable neural network testing framework along with sensor integration. The experimental set up of the proposed tactile sensing system in demonstrated. The initial simulations are carried out in SPICE, and the real-time implementation is validated on FPAA and FPGA hardware.

aged, deprescribing, frailty, polypharmacy, primary health care, referral and consultation, Medicine (General), R5-920, Public aspects of medicine, and RA1-1270

Abstract Background In older people living with frailty, polypharmacy can lead to preventable harm like adverse drug reactions and hospitalization. Deprescribing is a strategy to reduce problematic polypharmacy. All stakeholders should be actively involved in developing a person‐centred deprescribing process that involves shared decision‐making. Objective To co‐design an intervention, supported by a logic model, to increase the engagement of older people living with frailty in the process of deprescribing. Design Experience‐based co‐design is an approach to service improvement, which uses service users and providers to identify problems and design solutions. This was used to create a person‐centred intervention with the potential to improve the quality and outcomes of the deprescribing process. A ‘trigger film’ showing older people talking about their healthcare experiences was created and facilitated discussions about current problems in the deprescribing process. Problems were then prioritized and appropriate solutions were developed. The review located the solutions in the context of current processes and procedures. An ideal care pathway and a complex intervention to deliver better care were developed. Setting and Participants Older people living with frailty, their informal carers and professionals living and/or working in West Yorkshire, England, UK. Deprescribing was considered in the context of primary care. Results The current deprescribing process differed from an ideal pathway. A complex intervention containing seven elements was required to move towards the ideal pathway. Three of these elements were prototyped and four still need development. The complex intervention responded to priorities about (a) clarity for older people about what was happening at all stages in the deprescribing process and (b) the quality of one‐to‐one consultations. Conclusions Priorities for improving the current deprescribing process were successfully identified. Solutions were developed and structured as a complex intervention. Further work is underway to (a) complete the prototyping of the intervention and (b) conduct feasibility testing. Patient or Public Contribution Older people living with frailty (and their informal carers) have made a central contribution, as collaborators, to ensure that a complex intervention has the greatest possible potential to enhance the experience of deprescribing medicines.

luxury products, counterfeit, authentication, blockchain, NFT, Engineering machinery, tools, and implements, TA213-215, Technological innovations. Automation, and HD45-45.2

High-quality luxury products cater to a specific group of consumers due to their durability and the value attached to them. Counterfeiting luxury products has resulted in economic losses for both the producers and consumers. The market for counterfeit luxury products has continued to grow due to the difficulty in authenticating genuine luxury products. The traditional system of verification largely depends on the expert use of specialized equipment for visually inspecting physical luxury products and their associated certificates. This conventional process of authenticating luxury products is expensive, slow, and not easily accessible to consumers. Hence, there is a need for a digital verification approach for luxury products. Blockchain provides the potential for providing traceable and immutable information about a given luxury product. The focus of this paper is to develop a blockchain decentralized application (DApp) for authenticating luxury products in the class of luxury accessories such as jewelry across their respective lifecycles. To achieve this, qualitative analytics is applied to identify useful features for the digital authentication of luxury products. Blockchain requirement engineering modelling is then applied to explore the use of blockchain technologies to realize the features that guarantee transparency in the ownership and use of luxury products. Furthermore, this paper explores the existing blockchain technologies for realizing and implementing the developed requirements of the authentication DApp for luxury products. The selected blockchain technology stack is applied in prototyping authentication systems for luxury products. The implemented platform is simulated to demonstrate the operations carried out in authenticating luxury products.

Protein engineering, Protein–protein interactions, Nanostructures, Multimodal chromatography, Biotechnology, TP248.13-248.65, Medical technology, and R855-855.5

Abstract Background Protein nanostructures produced through the self-assembly of individual subunits are attractive scaffolds to attach and position functional molecules for applications in biomaterials, metabolic engineering, tissue engineering, and a plethora of nanomaterials. However, the assembly of multicomponent protein nanomaterials is generally a laborious process that requires each protein component to be separately expressed and purified prior to assembly. Moreover, excess components not incorporated into the final assembly must be removed from the solution and thereby necessitate additional processing steps. Results We developed an efficient approach to purify functionalized protein nanostructures directly from bacterial lysates through a type of multimodal chromatography (MMC) that combines size-exclusion, hydrophilic interaction, and ion exchange to separate recombinant protein assemblies from excess free subunits and bacterial proteins. We employed the ultrastable filamentous protein gamma-prefoldin as a material scaffold that can be functionalized with a variety of protein domains through SpyTag/SpyCatcher conjugation chemistry. The purification of recombinant gamma-prefoldin filaments from bacterial lysates using MMC was tested across a wide range of salt concentrations and pH, demonstrating that the MMC resin is robust, however the optimal choice of salt species, salt concentration, and pH is likely dependent on the protein nanostructure to be purified. In addition, we show that pre-processing of the samples with tangential flow filtration to remove nucleotides and metabolites improves resin capacity, and that post-processing with Triton X-114 phase partitioning is useful to remove lipids and any remaining lipid-associated protein. Subsequently, functionalized protein filaments were purified from bacterial lysates using MMC and shown to be free of unincorporated subunits. The assembly and purification of protein filaments with varying amounts of functionalization was confirmed using polyacrylamide gel electrophoresis, Förster resonance energy transfer, and transmission electron microscopy. Finally, we compared our MMC workflow to anion exchange chromatography with the purification of encapsulin nanocompartments containing a fluorescent protein as a cargo, demonstrating the versatility of the protocol and that the purity of the assembly is comparable to more traditional procedures. Conclusions We envision that the use of MMC will increase the throughput of protein nanostructure prototyping as well as enable the upscaling of the bioproduction of protein nanodevices. Graphic Abstract

3D printing, upper extremity, rapid prototyping, patient-specific, and Medicine

Three-dimensional printing for medical applications in surgery of the upper extremity has gained in popularity as reflected by the increasing number of publications. This systematic review aims to provide an overview of the clinical use of 3D printing in upper extremity surgery. Methods: We searched the databases PubMed and Web of Science for clinical studies that described clinical application of 3D printing for upper extremity surgery including trauma and malformations. We evaluated study characteristics, clinical entity, type of clinical application, concerned anatomical structures, reported outcomes, and evidence level. Results: We finally included 51 publications with a total of 355 patients, of which 12 were clinical studies (evidence level II/III) and 39 case series (evidence level IV/V). The types of clinical applications were for intraoperative templates (33% of a total of 51 studies), body implants (29%), preoperative planning (27%), prostheses (15%), and orthoses (1%). Over two third of studies were linked to trauma-related injuries (67%). Conclusion: The clinical application of 3D printing in upper extremity surgery offers great potential for personalized approaches to aid in individualized perioperative management, improvement of function, and ultimately help to benefit certain aspects in the quality of life.

dual-phase steel, aspect ratio, necking modes, fracture angle, rapid alloy prototyping, Technology, Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Engineering (General). Civil engineering (General), TA1-2040, Microscopy, QH201-278.5, Descriptive and experimental mechanics, and QC120-168.85

This work investigated the feasibility of using a miniaturised non-standard tensile specimen to predict the post-necking behaviour of the materials manufactured via a rapid alloy prototyping (RAP) approach. The experimental work focused on the determination of the Lankford coefficients (r-value) of dual-phase 800 (DP800) steel and the digital image correlation (DIC) for some cases, which were used to help calibrate the damage model parameters of DP800 steel. The three-dimensional numerical simulations focused on the influence of the size effect (aspect ratio, AR) on the post-necking behaviour, such as the strain/stress/triaxiality evolutions, fracture angles, and necking mode transitions. The modelling showed that although a good correlation can be found between the predicted and experimentally observed ultimate tensile strength (UTS) and total elongation. The standard tensile specimen with a gauge length of 80 mm exhibited a fracture angle of ∼55°, whereas the smaller miniaturised non-standard specimens with low ARs exhibited fractures perpendicular to the loading direction. This shows that care must be taken when comparing the post-necking behaviour of small-scale tensile tests, such as those completed as a part of a RAP approach, to the post-necking behaviours of standard full-size test specimens. However, the modelling work showed that this behaviour is well represented, demonstrating a transition between the fracture angles of the samples between 2.5 and 5. This provides more confidence in understanding the post-necking behaviour of small-scale tensile tests.

laser transfer, LIFT, graphene oxide, PEDOT:PSS, hybrids, copper ions, Technology, Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Engineering (General). Civil engineering (General), TA1-2040, Microscopy, QH201-278.5, Descriptive and experimental mechanics, and QC120-168.85

Composites based on poly(3,4-ethylenedioxythiophene): poly(styrene sulfonate) (PEDOT:PSS)—graphene oxide (GO) are increasingly considered for sensing applications. In this work we aim at patterning and prototyping microscale geometries of PEDOT:PSS: GO composites for the modification of commercially available electrochemical sensors. Here, we demonstrate the laser-induced forward transfer of PEDOT:PSS: GO composites, a remarkably simple procedure that allows for the fast and clean transfer of materials with high resolution for a wide range of laser fluences (450–750 mJ/cm2). We show that it is possible to transfer PEDOT:PSS: GO composites at different ratios (i.e., 25:75 %wt and 50:50 %wt) onto flexible screen-printed electrodes. Furthermore, when testing the functionality of the PEDOT:PSS: GO modified electrodes via LIFT, we could see that both the PEDOT:PSS: GO ratio as well as the addition of an intermediate release layer in the LIFT process plays an important role in the electrochemical response. In particular, the ratio of the oxidation peak current to the reduction peak current is almost twice as high for the sensor with a 50:50 %et PEDOT:PSS: GO pixel. This direct transfer methodology provides a path forward for the prototyping and production of polymer: graphene oxide composite based devices.

Perforations, Subtractive manufacturing, Negative Poisson’s ratio, 3D auxetic structures, Materials of engineering and construction. Mechanics of materials, and TA401-492

Prototyping of three-dimensional mechanical metamaterials that exhibit negative Poisson’s ratio is usually performed through additive manufacturing. Although this technique has a huge potential, its use to engineer mechanical metamaterials for consumer products is still challenging. In this work, a novel design method is being proposed where 3D auxetic metamaterials can be produced by introducing continuous voids of constant cross-sectional area. Such voids would be inserted at strategic positions in different perpendicular planes of a solid block to obtain a continuous three-dimensional mechanical metamaterial that can exhibit the desired mechanical characteristics. The use of continuous voids to design the 3D meatamaterial makes it possible to use additive manufacturing, subtractive manufacturing as well as casting to produce these systems. The proposed design method is explained by using continuous voids having a diamond shaped cross-sectional area. The resulting group of structures can be described as connected polygons and were found to exhibit a negative or zero Poisson’s ratio. The analysed systems were also found to have a strain independent Poisson’s ratio up to at least 7% strain. The proposed design method can thus facilitate the availability of three dimensional auxetic metamaterials in the consumer market which to date is conspicuous by their absence.

Bioprinting, Engineered living materials, Biosensors, Synthetic biology, Engineered bacteria, Medicine (General), R5-920, Biology (General), and QH301-705.5

The intertwined adoption of synthetic biology and 3D bioprinting has the potential to improve different application fields by fabricating engineered living materials (ELMs) with unnatural genetically-encoded sense & response capabilities. However, efforts are still needed to streamline the fabrication of sensing ELMs compatible with field use and improving their functional complexity. To investigate these two unmet needs, we adopted a workflow to reproducibly construct bacterial ELMs with synthetic biosensing circuits that provide red pigmentation as visible readout in response to different proof-of-concept chemical inducers. We first fabricated single-input/single-output ELMs and we demonstrated their robust performance in terms of longevity (cell viability and evolutionary stability >15 days, and long-term storage >1 month), sensing in harsh, non-sterile or nutrient-free conditions compatible with field use (soil, water, and clinical samples, including real samples from Pseudomonas aeruginosa infected patients). Then, we fabricated ELMs including multiple spatially-separated biosensor strains to engineer: level-bar materials detecting molecule concentration ranges, multi-input/multi-output devices with multiplexed sensing and information processing capabilities, and materials with cell-cell communication enabling on-demand pattern formation. Overall, we showed successful field use and multiplexed functioning of reproducibly fabricated ELMs, paving the way to a future automation of the prototyping process and boosting applications of such devices as in-situ monitoring tools or easy-to-use sensing kits.

Medicine (General) and R5-920

Background. The complexity of decision science models may prevent their use to assist in decision making. User-centered design (UCD) principles provide an opportunity to engage end users in model development and refinement, potentially reducing complexity and increasing model utilization in a practical setting. We report our experiences with UCD to develop a modeling tool for cancer control planners evaluating cancer survivorship interventions. Design. Using UCD principles (described in the article), we developed a dynamic cohort model of cancer survivorship for individuals with female breast, colorectal, lung, and prostate cancer over 10 y. Parameters were obtained from the National Program of Cancer Registries and peer-reviewed literature, with model outcomes captured in quality-adjusted life-years and net monetary benefit. Prototyping and iteration were conducted with structured focus groups involving state cancer control planners and staff from the Centers for Disease Control and Prevention and the American Public Health Association. Results. Initial feedback highlighted model complexity and unclear purpose as barriers to end user uptake. Revisions addressed complexity by simplifying model input requirements, providing clear examples of input types, and reducing complex language. Wording was added to the results page to explain the interpretation of results. After these updates, feedback demonstrated that end users more clearly understood how to use and apply the model for cancer survivorship resource allocation tasks. Conclusions. A UCD approach identified challenges faced by end users in integrating a decision aid into their workflow. This approach created collaboration between modelers and end users, tailoring revisions to meet the needs of the users. Future models developed for individuals without a decision science background could leverage UCD to ensure the model meets the needs of the intended audience. Highlights Model complexity and unclear purpose are 2 barriers that prevent lay users from integrating decision science tools into their workflow. Modelers could integrate the user-centered design framework when developing a model for lay users to reduce complexity and ensure the model meets the needs of the users.

prototyping, user evaluation, augmented reality, virtual reality, simulations, urban applications, Technology, and Science

Augmented reality (AR) has the potential to fundamentally change how people engage with increasingly interactive urban environments. However, many challenges exist in designing and evaluating these new urban AR experiences, such as technical constraints and safety concerns associated with outdoor AR. We contribute to this domain by assessing the use of virtual reality (VR) for simulating wearable urban AR experiences, allowing participants to interact with future AR interfaces in a realistic, safe and controlled setting. This paper describes two wearable urban AR applications (pedestrian navigation and autonomous mobility) simulated in VR. Based on a thematic analysis of interview data collected across the two studies, we find that the VR simulation successfully elicited feedback on the functional benefits of AR concepts and the potential impact of urban contextual factors, such as safety concerns, attentional capacity, and social considerations. At the same time, we highlight the limitations of this approach in terms of assessing the AR interface’s visual quality and providing exhaustive contextual information. The paper concludes with recommendations for simulating wearable urban AR experiences in VR.

autism spectrum disorder, neuroimaging, early diagnoses, multiscale entropy., Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Neurology. Diseases of the nervous system, and RC346-429

Louise Bogéa Ribeiro,* Manoel da Silva Filho* Federal University of Pará, Assistive Prototyping Lab, Belém-PA, Brazil*These authors contributed equally to this workCorrespondence: Louise Bogéa Ribeiro, Federal University of Pará, Assistive Prototyping Lab, Governador José Malcher Ave, 1423, Belém-PA, 66060230, Brazil, Tel +55 (91) 992341623, Email Louisebr@ufpa.brAbstract: An abnormality in neural connectivity is linked to autism spectrum disorder (ASD). There is no way to test the concept of neural connectivity empirically. According to recent network theory and time series analysis findings, electroencephalography (EEG) can assess neural network architecture, a sign of activity in the brain. This systematic review aims to evaluate functional connectivity and spectral power using EEG signals. EEG records the brain activity of an individual by displaying wavy lines that depict brain cells’ communication through electrical impulses. EEG can diagnose various brain disorders, including epilepsy and related seizure illness, brain dysfunction, tumors, and damage. We found 21 studies using two of the most common EEG analysis methods: functional connectivity and spectral power. ASD and non-ASD individuals were found to differ significantly in all selected papers. Due to high heterogeneity in the outcomes, generalizations cannot be drawn, and no single method is currently beneficial as a diagnostic tool. For ASD subtype delineation, the lack of research prevented the evaluation of these techniques as diagnostic tools. These findings confirm the presence of abnormalities in the EEG in ASD, but they are insufficient to diagnose. Our study suggests that EEG is useful in diagnosing ASD by evaluating entropy in the brain. Researchers may be able to develop new diagnostic methods for ASD which focuses on particular stimuli and brainwaves if they conduct more extensive studies with higher numbers and more rigorous study designs.Keywords: autism spectrum disorder, neuroimaging, early diagnoses, multiscale entropy

additive manufacturing, photopolymer, strain sensor, soft application, stereolithography, 3D printing, Organic chemistry, and QD241-441

As a result of the developments in additive manufacturing (AM) technology, 3D printing is transforming from a method used only in rapid prototyping to a technique used to produce large-scale equipment. This study presents the fabrication and experimental studies of a 3D-printed strain sensor that can be used directly in soft applications. Photopolymer-based conductive and flexible ultraviolet (UV) resin materials are used in the fabrication of the sensor. A Stereolithography (SLA)-based printer is preferred for 3D fabrication. The bottom base of the sensor, which consists of two parts, is produced from flexible UV resin, while the channels that should be conductive are produced from conductive UV resin. In total, a strain sensor with a thickness of 2 mm was produced. Experimental studies were carried out under loading and unloading conditions to observe the hysteresis effect of the sensor. The results showed a close linear relationship between the strain sensor and the measured resistance value. In addition, tensile test specimens were produced to observe the behavior of conductive and non-conductive materials. The tensile strength values obtained from the test results will provide information about the sensor placement. In addition, the flexible structure of the strain sensor will ensure its usability in many soft applications.

additive manufacturing, 3D printing, auxetic structures, polymers, FDM, Organic chemistry, and QD241-441

Additive Manufacturing (AM) techniques have recently attracted the attention of scientists for the development of prototypes with complex or particular geometry in a fast and cheap way. Among the different AM processes, the Fused Deposition Modelling process (FDM) offers several advantages in terms of costs, implementation features and design freedom. Recently, it has been adopted to realise auxetic structures, which are characterised by negative Poisson ratio, enhanced mechanical properties, and a higher compression resistance than conventional structures. This review outlines the use of AM processes, in particular FDM, to design and obtain auxetic structures, with the final aim to exploit their applications in different fields. The first part of this work presents a brief classification of auxetic structures and materials. Subsequently, a summary of additive manufacturing processes is presented, focusing on the use of FDM and its limitations. Finally, the studies on the use of additive manufacturing to produce auxetic structures are shown, evidencing the potential of the concurrent combination of a fast prototyping technique such as FDM and the characteristics of polymer- and/or composite-based auxetic structures. Indeed, this new technological field opens the possibility of realising novel structures with integrated smart behaviour, multifunctional properties, compression resistance, and a tailored microstructure and shape.

Medicine and Science

Abstract Patellar luxation with condylar defect is a challenging situation for reconstruction in humans. Patella reluxation, cartilage damage and pain are the most common complications. This study aims to present a new patient specific method of overformed implant design and clinical implantation that prevents luxation of patella without damaging the cartilage in a dog. Design processes are Computer Tomography, Computer Assisted Design, rapid prototyping of the bone replica, creation of the implant with surgeon’s haptic knowledge on the bone replica, 3D printing of the implant and clinical application. The implant was fully seated on the bone. Patella reluxation or implant-related bone problem was not observed 80 days after the operation. However, before the implant application, there were soft tissue problems due to previous surgeries. Three-point bending test and finite element analysis were performed to determine the biomechanical safety of the implant. The stress acting on the implant was below the biomechanical limits of the implant. More cases with long-term follow-up are needed to confirm the success of this method in patellar luxation. Compared with trochlear sulcoplasty and total knee replacement, there was no cartilage damage done by surgeons with this method, and the implant keeps the patella functionally in sulcus. This is a promising multidisciplinary method that can be applied to any part of the bone and can solve some orthopaedic problems with surgeon’s haptic knowledge.

smart governance, regulatory requirements, best practices, energy communities, citizen empowerment, Engineering (General). Civil engineering (General), and TA1-2040

Renewable energy communities, first outlined in the European Directives and recently transposed into the Italian regulatory framework, are introduced as innovative entities capable of fostering cooperation between active and passive users involved in the production, sharing, and use of locally produced energy according to innovative management schemes. Renewable energy communities empower the end-customers. Citizens and legal entities are committed to a rational and economical use of energy to achieve the community’s climate neutrality goals and pursue the ecological and energy transition objectives defined in the national recovery and resilience plan. In the future, a significant number of energy communities different actors participating from the residential, industrial, commercial, and tertiary sectors are expected to develop within city districts or in suburban settings. This paper proposes and develops a methodology capable of bridging the complexity that can characterise the prototyping, implementation, and management of an energy community within a positive energy district. The approach presented here can also be extended to other application contexts in urban or rural settings. Requirements and best practices for administrative, technical, and technological management have been identified to achieve this goal. Italy is one of the first states to embed in its regulatory framework the European Directives regarding renewable energy communities. These will have a significant impact on network management models and will provide new ways for creating social inclusion that may help achieve climate sustainability goals. A governance model has been formalised for the empowerment of energy community members, outlining a framework useful for planning the proper implementation of a renewable energy community according to current Italian regulations.

multi-layered, digital twin, framework, asset lifecycle management, sustainable mine, Internet of Things, Environmental effects of industries and plants, TD194-195, Renewable energy sources, TJ807-830, Environmental sciences, and GE1-350

In the era of digitalization, many technologies are evolving, namely, the Internet of Things (IoT), big data, cloud computing, artificial intelligence (IA), and digital twin (DT) which has gained significant traction in a variety of sectors, including the mining industry. The use of DT in the mining industry is driven by its potential to improve efficiency, productivity, and sustainability by monitoring performance, simulating results, and predicting errors and yield. Additionally, the increasing demand for individualized products highlights the need for effective management of the entire product lifecycle, from design to development, modeling, simulating, prototyping, maintenance and troubleshooting, commissioning, targeting the market, use, and end-of-life. However, the problem to be overcome is how to successfully integrate DT into the mining business. This paper intends to shed light on the state of art of DT case studies focusing on concept, design, and development. The DT reference architecture model in Industry 4.0 and value-lifecycle-management-enabled DT are also discussed, and a proposition of a DT multi-layered architecture framework for the mining industry is explained to inspire future case studies.

system innovations, sustainable smart ports, strategic foresight, intelligent ports, global value chains, digital transformation, Systems engineering, TA168, Technology (General), and T1-995

Integrated technology management in building smart ports or intelligent ports is a crucial concern for global sustainable development, especially when human societies are facing increasing risks from climate change, sea-levels rising, and supply chain disruptions. By mapping the knowledge base of 103 papers on intelligent ports, retrieved in late December 2022 from the Web of Science, this study conducted a roadmapping exercise using knowledge mapping findings, assisted by Bibliometrix, VoSviewer, and customized Python scripts. The three structural (intellectual, social, and conceptual) aspects of knowledge structure reveal the significance of the internet of things (IoT), the fourth industrial revolution (Industry 4.0), digitalization and supply chains, and the need for digital transformation alignment across various stakeholders with Industry 4.0 practices. Furthermore, an even geographical distribution and institutional representation was observed across major continents. The results of the analysis of the conceptual structure demonstrated the existence of several established and emerging clusters of research, namely (1) industry data, IoT, and ICT, (2) industry 4.0, (3) smart airports, (4) automation; and (5) protocol and security. The overall empirical findings revealed the underlying technology and innovation management issues of digital transformation alignment across stakeholders in IoT, Industry 4.0, 5G, Big Data, and AI integrated solutions. In relation to roadmapping, this study proposed a socio-technical transition framework for prototyping ecosystem innovations surrounding smart sustainable ports, focusing on contributing to valuable carbon or greenhouse gas emission data governance, management, and services in global value chains.

virtual simulation, online course platform, creative thinking, design guidelines, user interface, college students, Systems engineering, TA168, Technology (General), and T1-995

With the rapid development of science and technology, the ability to creative thinking has become an essential criterion for measuring talents. Current creative thinking courses for college students are affected by COVID-19 and are challenging to conduct. This study aimed to explore practical ways to teach creative thinking knowledge online and explored design opportunities for working on this teaching activity online. Through qualitative interviews, we found that the factors that influenced the design of the online virtual simulation course platform were focused on five dimensions: information presentation, platform characteristics, course assessment, instruction design, and presentation format. Through the analysis of user requirements, we obtained six corresponding design guidelines. Based on the knowledge system of design thinking, we set up eight modules in the course platform and developed a prototype including 100 user interfaces. We invited three experts and 30 users to conduct cognitive walk-through sessions and made design iterations based on the feedback. After user evaluation, dimensions of attractiveness, efficiency, dependability, and novelty reached excellent rating and were recognized by users.

Robustness optimization design, Rapid prototyping, Functional artifacts, Fuzzy decision-making, Infrared thermographs, Visualized computing digital twins, Drawing. Design. Illustration, NC1-1940, Computer applications to medicine. Medical informatics, R858-859.7, Computer software, and QA76.75-76.765

Abstract This study presents a robustness optimization method for rapid prototyping (RP) of functional artifacts based on visualized computing digital twins (VCDT). A generalized multiobjective robustness optimization model for RP of scheme design prototype was first built, where thermal, structural, and multidisciplinary knowledge could be integrated for visualization. To implement visualized computing, the membership function of fuzzy decision-making was optimized using a genetic algorithm. Transient thermodynamic, structural statics, and flow field analyses were conducted, especially for glass fiber composite materials, which have the characteristics of high strength, corrosion resistance, temperature resistance, dimensional stability, and electrical insulation. An electrothermal experiment was performed by measuring the temperature and changes in temperature during RP. Infrared thermographs were obtained using thermal field measurements to determine the temperature distribution. A numerical analysis of a lightweight ribbed ergonomic artifact is presented to illustrate the VCDT. Moreover, manufacturability was verified based on a thermal-solid coupled finite element analysis. The physical experiment and practice proved that the proposed VCDT provided a robust design paradigm for a layered RP between the steady balance of electrothermal regulation and manufacturing efficacy under hybrid uncertainties.

Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Computer software, and QA76.75-76.765

Establishing the indoor and outdoor humidity values in a greenhouse allows us to describe the crop yield during its entire developmental cycle. This study seeks to develop a predictive model of indoor relative humidity values in a greenhouse with high accuracy and interpretability through the use of optimized fuzzy inference systems, in order to offer greenhouse users a clear and simple description of their behaviour. The three-phase methodology applied made use of descriptive statistics techniques, correlation analysis, and prototyping paradigm for the iterative and incremental development of the predictive model, validated through error measurement. The research resulted in six models which define the behaviour of humidity as a result of temperature, CO2, and soil moisture, with percentages of effectiveness above 90%. The implementation of a Mamdani-type fuzzy inference system, optimized by a hybrid method combining genetic and interior point algorithms, allowed to predict the relative humidity in greenhouses with high interpretability and precision, with an effectiveness percentage of 90.97% and MSE (mean square error) of 8.2e − 3.

3D printing, Arduino, educational robotics, design thinking, open-source project, open-source platform, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, and QD1-999

The dynamic spread of 3D printing technologies and open-source electronics prototyping platforms has significantly enriched the diversity of instruments used within educational robotics (ER) settings. An active, low-entry-level community offering ready-to-use libraries for a broad variety of devices assists in the development of quite sophisticated projects. However, the flipside of the coin is represented by the current research findings, which reveal that students’ interest in science, technology, engineering and mathematics (STEM) subjects has declined across Europe, as manifested in difficulties when approaching scientific topics and dealing with problems and phenomena studied from a multidisciplinary perspective. Consequently, a significant percentage of youths are at risk of social exclusion due to the direct relationship between low academic achievements and school dropout. Moreover, learners lack guidance in applied and life-context skills, such as creative thinking, problem solving, and collaboration, which highlights the need to introduce innovative pedagogical approaches. In this context, the design thinking (DT) methodology was proposed to tackle the problem. Originating in the development of psychological studies on creativity in the 1950s within the educational context, DT is known to foster creative thinking, help develop empathy, promote action-oriented actions, improve meta-cognitive awareness, contribute to problem-solving skills, and enhance students’ imagination. The last point supports the students’ development of critical thinking, social inclusion, teamwork skills, and academic performance. Thus, this paper introduces a methodological framework combining DT with ER classes. First, to approach the problem, the teachers’ survey data were collected and analysed to reveal the respondents’ level of integration of the DT methodology into current school curricula. Then, the work focused on the application of this framework in a learning experience by addressing the weakest points established and their elaboration through the combined ER and DT classes in the context of secondary schools.