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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.
(© 2023. The Author(s).)
Hydrodynamics, Kinetics, Ultraviolet Rays, Disinfection methods, and Water Purification methods
We developed and studied one of the first high-flow UV-LED water disinfection reactors applicable to point-of-entry (POE) water disinfection. A multiphysics computational model was created to predict the performance of UV reactor design concepts by modeling the synergic effect of radiation, hydrodynamics, and the inactivation kinetics of microorganisms. The geometrical optics that describe light propagation in terms of rays were employed to model the radiation profile of multiple UV-LEDs with optical components in complex reactor geometries, the first account of such an approach. The computational solution of the mass, momentum, and species equations was applied to model the hydrodynamics and kinetics. We designed a reactor through a detailed computational study of the optical and hydrodynamic performance of various design strategies. Highly efficient UV fluence distribution in the reactor was achieved by creating nearly collimated UV radiation beams across the reactor and managing the hydrodynamics using a flow distributor. We fabricated a prototype of the optimized reactor design for experimental studies. Biodosimetry tests were conducted for various flow rates and UV transmittances (UVTs), and the experimental results were compared with the model predictions. The design, which employed 14 UV-LEDs assembled over custom-made optical modules, resulted in a reduction equivalent dose (RED) of 65 mJ/cm 2 at a flow rate of 20 liters per minute (LPM) while consuming about 50 W energy. This reactor design required only 0.05 W radiant power per LPM flow rate to achieve an NSF Class A UV dose equivalent of 40 mJ/cm 2 . The findings of this study provide insights into UV-LED reactor development strategies as well as the creation and application of reactor virtual prototyping tools for designing and optimizing highly efficient UV-LED reactors.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (Copyright © 2023. Published by Elsevier Ltd.)
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. (© 2023. The Author(s).)
Electrons, Quantum Theory, and Software
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.
(© 2022 Wiley Periodicals LLC.)
Polydimethylsiloxane (PDMS) based microfluidic devices have found increasing utility for electrophoretic and electrokinetic assays because of their ease of fabrication using replica molding. However, the fabrication of high-resolution molds for replica molding still requires the resource-intensive and time-consuming photolithography process, which precludes quick design iterations and device optimization. We here demonstrate a low-cost, rapid microfabrication process, based on electrohydrodynamic jet printing (EJP), for fabricating non-sacrificial master molds for replica molding of PDMS microfluidic devices. The method is based on the precise deposition of an electrically stretched polymeric solution of polycaprolactone in acetic acid on a silicon wafer placed on a computer-controlled motion stage. This process offers the high-resolution (order 10 μ $\umu$ m) capability of photolithography and rapid prototyping capability of inkjet printing to print high-resolution templates for elastomeric microfluidic devices within a few minutes. Through proper selection of the operating parameters such as solution flow rate, applied electric field, and stage speed, we demonstrate microfabrication of intricate master molds and corresponding PDMS microfluidic devices for electrokinetic applications. We demonstrate the utility of the fabricated PDMS microchips for nonlinear electrokinetic processes such as electrokinetic instability and controlled sample splitting in ITP. The ability to rapid prototype customized reusable master molds with order 10 μ $\umu$ m resolution within a few minutes can help in designing and optimizing microfluidic devices for various electrokinetic applications.
(© 2023 Wiley-VCH GmbH.)
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.
Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2023 Mallan, Gopi, Reghuvaran, Radhakrishnan and James.)
We demonstrate a method to emulate the optical performance of silicon photonic devices fabricated using advanced deep-ultraviolet lithography (DUV) processes on a rapid-prototyping electron-beam lithography process. The method is enabled by a computational lithography predictive model generated by processing SEM image data of the DUV lithography process. We experimentally demonstrate the emulation method's accuracy on integrated silicon Bragg grating waveguides and grating-based, add-drop filter devices, two devices that are particularly susceptible to DUV lithography effects. The emulation method allows silicon photonic device and system designers to experimentally observe the effects of DUV lithography on device performance in a low-cost, rapid-prototyping, electron-beam lithography process to enable a first-time-right design flow.
Dimethylpolysiloxanes, Microfluidics methods, and Microfluidic Analytical Techniques
Soft lithography has permitted rapid prototyping of precise microfluidic features by patterning a deformable elastomer such as polydimethylsiloxane (PDMS) with a photolithographically patterned mold. In microfluidics applications where the flexibility of PDMS is a drawback, a variety of more rigid materials have been proposed. Compared to alternatives, devices fabricated from epoxy and glass have superior mechanical performance, feature resolution, and solvent compatibility. Here we provide a detailed step-by-step method for fabricating rigid microfluidic devices from soft lithography patterned epoxy and glass. The bonding protocol was optimized yielding devices that withstand pressures exceeding 500 psi. Using this method, we demonstrate the use of rigid high aspect ratio spiral microchannels for high throughput cell focusing.
(© 2023. The Author(s).)
Humans, Pregnancy, Female, Pilot Projects, Feasibility Studies, Pregnancy Outcome, Life Change Events, and Prenatal Care
Background: A healthy lifestyle plays a key role in the prevention of lifestyle-related diseases, including subfertility and pregnancy complications. Although the benefits of a healthy lifestyle are well-known, long-term adherence is limited. Moreover, memory for lifestyle-related information as well as medical information provided by the medical professional is often poor and insufficient. In order to innovate and improve health care for both the patients and health care professionals, we developed a prototype of a digital life course care platform (Smarter Health app), providing personalized lifestyle care trajectories integrated in medical care journeys.
Objective: This pilot study aimed to evaluate the feasibility, defined as the actual app use, and the acceptability, which included patient satisfaction and appreciation, of the Smarter Health app. Methods: Between March 17, 2021, and September 30, 2021, pregnant women familiar with the Dutch language seeking tertiary preconception and pregnancy care were offered the app as part of standard medical care at the outpatient clinic Healthy Pregnancy of the Department of Obstetrics and Gynecology of the Erasmus University Medical Center. Three months after activation of the app, patients received a digital questionnaire consisting of aspects of feasibility and acceptability. Results: During this pilot study, 440 patients visited the outpatient clinic Healthy Pregnancy. Of the 440 patients, 293 (66.6%) activated the app. Of the 293 patients who activated the app, 125 (42.7%) filled out the questionnaire. Of these 125 patients, 48 (38.4%) used the app. Most app users used it occasionally and logged in 8 times during their medical care trajectory. Overall, app users were satisfied with the app (median 5-point Likert scale=2.4, IQR 2.0-3.3). Conclusions: Our findings showed that the Smarter Health app, which integrates lifestyle care in medical care, is a feasible health care innovation, and that patients were satisfied with the app. Follow-up and evaluation of pregnancy outcomes should be performed to further substantiate wider clinical implementation. (©Melissa van der Windt, Sofie Karolina Maria van Zundert, Sam Schoenmakers, Lenie van Rossem, Régine Patricia Maria Steegers-Theunissen. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 20.01.2023.)
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