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The purpose of this study is to develop a magnetic resonance imaging (MRI)-safe iron-free electrical actuator for MR-guided surgical interventions.

The paper deals with the design of an MRI compatible electrical actuator. Three-dimensional electromagnetic and thermal analytical models have been developed to design the actuator. These models have been validated through 3D finite element (FE) computations. The analytical models have been inserted in an optimization procedure that uses genetic algorithms to find the optimal parameters of the actuator.

The analytical models are very fast and precise compared to the FE models. The computation time is 0.1 s for the electromagnetic analytical model and 3 min for the FE one. The optimized actuator does not perturb imaging sequence even if supplied with a current 10 times higher than its rated one. Indeed, the actuator’s magnetic field generated in the imaging area does not exceed 1 ppm of the B₀ field generated by the MRI scanner. The actuator can perform up to 25 biopsy cycles without any risk to the actuator or the patient since he maximum temperature rise of the actuator is about 20°C. The actuator is compact and lightweight compared to its pneumatic counterpart.

The MRI compatible actuator uses the B₀ field generated by scanner as inductor. The design procedure uses magneto-thermal coupled models that can be adapted to the design of a variety actuation systems working in MRI environment.

This paper aims to investigate the influence of post-curing temperature, post-curing time and gamma ray irradiation dose upon the tensile and compressive mechanical properties of the medical graded vat photopolymerization parts.

Medical graded vat photopolymerization specimens, made from photopolymer resin, were fabricated using bottom-up vat photopolymerization machine. Tensile and compressive tests were conducted to assess the mechanical properties. The specimens were categorized into uncured and post-curing groups. Temperature post-processing and/or gamma irradiation exposure were for post-curing specimens. The post-curing parameters considered included temperature levels of 50°C, 60°C and 70°C, with 1, 2, 3 and 4 h periods. For the gamma irradiation, the exposure doses were 25, 50, 75 and 100 kGy.

Post-curing improved the mechanical properties of medical graded vat photopolymerization parts for both tensile and compressive specimens. Post-curing temperature greater than 50°C or a prolonged post-curing period of more than 1 h made insignificant changes or deterioration in mechanical properties. The optimal post-curing condition was therefore a 50°C post-curing temperature with 1 h post-curing time. Exposure to gamma ray improved the compressive mechanical properties, but deteriorated tensile mechanical properties. Higher gamma irradiation doses could decrease the mechanical properties and also make the part more brittle, especially for doses more than 25 kGy.

The obtained results would be beneficial to the medical device manufacturer who fabricated the invasive temporary contact personalized surgical instruments by vat photopolymerization technique. In addition, it also raised awareness in excessive gamma sterilization in the medical graded vat photopolymerization parts.

The purpose of this paper is to illuminate the ethical concerns associated with the use of artificial intelligence (AI) in the medical sector and to provide solutions that allow deriving maximum benefits from this technology without compromising ethical principles.

This paper provides a comprehensive overview of AI in medicine, exploring its technical capabilities, practical applications, and ethical implications. Based on our expertise, we offer insights from both technical and practical perspectives.

The study identifies several advantages of AI in medicine, including its ability to improve diagnostic accuracy, enhance surgical outcomes, and optimize healthcare delivery. However, there are pending ethical issues such as algorithmic bias, lack of transparency, data privacy issues, and the potential for AI to deskill healthcare professionals and erode humanistic values in patient care. Therefore, it is important to address these issues as promptly as possible to make sure that we benefit from the AI’s implementation without causing any serious drawbacks.

This paper gains its value from the combined practical experience of Professor Elhassan gained through his practice at top hospitals worldwide, and the theoretical expertise of Dr. Arabi acquired from international institutes. The shared experiences of the authors provide valuable insights that are beneficial for raising awareness and guiding action in addressing the ethical concerns associated with the integration of artificial intelligence in medicine.

This paper aims to automatically obtain the implant parameter from the CBCT images to improve the outcome of implant planning.

This paper proposes automatic simulated dental implant positioning on CBCT images, which can significantly improve the efficiency of implant planning. The authors introduce the fusion point calculation method for the missing tooth's long axis and root axis based on the dental arch line used to obtain the optimal fusion position. In addition, the authors proposed a semi-interactive visualization method of implant parameters that be automatically simulated by the authors' method. If the plan does not meet the doctor's requirements, the final implant plan can be fine-tuned to achieve the optimal effect.

A series of experimental results show that the method proposed in this paper greatly improves the feasibility and accuracy of the implant planning scheme, and the visualization method of planting parameters improves the planning efficiency and the friendliness of system use.

The proposed method can be applied to dental implant planning software to improve the communication efficiency between doctors, patients and technicians.

This paper aims to prompt ideas amongst readers (especially librarians) about how they can become active partners in knowledge dissemination amongst concerned user groups by implementing 3D printing technology under the “Makerspace.”

The paper provides a brief account of various tools and techniques used by veterinary and animal sciences institutions for information dissemination amongst the stakeholders and associated challenges with a focus on the use of 3D printing technology to overcome the bottlenecks. An overview of the 3D printing technology has been provided following the instances of use of this novel technology in veterinary and animal sciences. An initiative of the University Library, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, to harness the potential of this technology in disseminating information amongst livestock stakeholders has been discussed.

3D printing has the potential to enhance learning in veterinary and animal sciences by providing hands-on exposure to various anatomical structures, such as bones, organs and blood vessels, without the need for a cadaver. This approach enhances students’ spatial understanding and helps them better understand anatomical concepts. Libraries can enhance their visibility and can contribute actively to knowledge dissemination beyond traditional library services.

The ideas about how to harness the potential of 3D printing in knowledge dissemination amongst livestock sector stakeholders have been elaborated. This promotes creativity amongst librarians enabling them to think how they can engage in knowledge dissemination thinking out of the box.

Three-dimensional (3D) printed parts usually have poor surface quality due to layer manufacturing’s “stair casing/stair-stepping”. So post-processing is typically needed to enhance its capabilities to be used in closed tolerance applications. This study aims to examine abrasive flow finishing for 3D printed polylactic acid (PLA) parts.

A new eco-friendly abrasive flow machining media (EFAFM) was developed, using paper pulp as a base material, waste vegetable oil as a liquid synthesizer and natural additives such as glycine to finish 3D printed parts. Characterization of the media was conducted through thermogravimetric analysis and Fourier transform infrared spectroscopy. PLA crescent prism parts were produced via fused deposition modelling (FDM) and finished using AFM, with experiments designed using central composite design (CCD). The impact of process parameters, including media viscosity, extrusion pressure, layer thickness and finishing time, on percentage improvement in surface roughness (%ΔRa) and material removal rate were analysed. Artificial neural network (ANN) and improved grey wolf optimizer (IGWO) were used for data modelling and optimization, respectively.

The abrasive media developed was effective for finishing FDM printed parts using AFM, with SEM images and 3D surface profile showing a significant improvement in surface topography. Optimal solutions were obtained using the ANN-IGWO approach. EFAFM was found to be a promising method for improving finishing quality on FDM 3D printed parts.

The present study is focused on finishing FDM printed crescent prism parts using AFM. Future research may be done on more complex shapes and could explore the impact of different materials, such as thermoplastics and composites for different applications. Also, implication of other techniques, such as chemical vapour smoothing, mechanical polishing may be explored.

In the biomedical field, the use of 3D printing has revolutionized the way in which medical devices, implants and prosthetics are designed and manufactured. The biodegradable and biocompatible properties of PLA make it an ideal material for use in biomedical applications, such as the fabrication of surgical guides, dental models and tissue engineering scaffolds. The ability to finish PLA 3D printed parts using AFM can improve their biocompatibility, making them more suitable for use in the human body. The improved surface quality of 3D printed parts can also facilitate their sterilization, which is critical in the biomedical field.

The use of eco-friendly abrasive flow finishing for 3D printed parts can have a positive impact on the environment by reducing waste and promoting sustainable manufacturing practices. Additionally, it can improve the quality and functionality of 3D printed products, leading to better performance and longer lifespans. This can have broader economic and societal benefits.

This AFM media constituents are paper pulp, waste vegetable oil, silicon carbide as abrasive and the mixture of “Aloe Barbadensis Mill” – “Cyamopsis Tetragonoloba” powder and glycine. This media was then used to finish 3D printed PLA crescent prism parts. The study also used an IGWO to optimize experimental data that had been modelled using an ANN.

The purpose of this study is to examine the state of research into adoption of machine learning systems within the health sector, to identify themes that have been studied and observe the important gaps in the literature that can inform a research agenda going forward.

A systematic literature strategy was utilized to identify and analyze scientific papers between 2012 and 2022. A total of 28 articles were identified and reviewed.

The outcomes reveal that while advances in machine learning have the potential to improve service access and delivery, there have been sporadic growth of literature in this area which is perhaps surprising given the immense potential of machine learning within the health sector. The findings further reveal that themes such as recordkeeping, drugs development and streamlining of treatment have primarily been focused on by the majority of authors in this area.

The search was limited to journal articles published in English, resulting in the exclusion of studies disseminated through alternative channels, such as conferences, and those published in languages other than English. Considering that scholars in developing nations may encounter less difficulty in disseminating their work through alternative channels and that numerous emerging nations employ languages other than English, it is plausible that certain research has been overlooked in the present investigation.

This review provides insights into future research avenues for theory, content and context on adoption of machine learning within the health sector.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

This study aims to explore the potential benefits favoring the adaptation of structural optimization techniques in the additive manufacturing (AM) of medical utilities to meet the repetitive demand for functionally precise customized orthoses. Irregularities encountered during the conventional treatment of tendon injuries can be eschewed using advanced structural simulation in design and innovative splint fabrication using 3D printing.

A customized mallet finger splint designed from 3D scans was subjected to ANSYS topological simulation comprising multi-level weight reduction to retain optimal mass (100%, 90%, 80%, 70% and 60%). A batch of the four typical 3D printing materials was chosen to conduct a comparative mechanical and thermal stress analysis, facilitating the selection of the optimal one for fabricating functionally adaptive splints. Assurance of structural safety was accomplished through the experimental validation of simulation results against the testing data set of ASTM D695 and ASTM D638 Type-1 specimens over a universal testing machine (UTM). Fused deposition modeling (FDM) 3D printing processed the optimized splint fabrication to assist evaluation of weight reduction percentage, fitting aesthetics, appearance, comfort, practicality and ventilation ease at the user end.

AM efficacy can efficiently execute the design complexity involved in the topology optimization (TO) results and introduces rehabilitation practicality into the application. Topologically optimized splint provided with favorable comfort, stiffness and strengthening features, offers ventilation ease and structural stability for customized appliances, with 30.52% lighter weight and 121.37% faster heat dissipation than unoptimized one.

The state of art multidisciplinary optimization featured with structural and material optimization attributes can deliberately meet medical necessity for performance-oriented orthotic devices.

The purpose of this study is to find the best geometries among the cylindrical, enamel and honeycomb geometries based upon the mechanical properties (tensile test, compression test and shear test). Further this obtained geometry could be used to fabricate products like exoskeleton and its supporting members.

The present research focuses on the mechanical testing of cylindrical, enamel and honeycomb-shaped parts fabricated through multi-jet printing (MJP) process with a wall thickness of 0.26, 0.33, 0.4 and 0.66 mm. The polymer specimens (for tensile, compression and shear tests) were fabricated using a multi-jet fusion process. The experimental results were compared with the numerical modelling. Finally, the optimal geometry was obtained, and the influence of wall thicknesses on various mechanical properties (tensile, compression and shear) was studied.

In comparison to cylindrical, enamel structures the honeycomb structures required less time to fabricate and had lower tensile, compressive and shear strengths. The most efficient geometry for fully functional parts where tensile, compressive and shear forces are present during application – cylindrical geometry is preferred followed by enamel, and then honeycomb. It was found that as the wall thickness of various geometries was increased, their ability to withstand tensile, compressive and shear loads also enhanced. The enamel shape structure exhibits greater strain energy storage capacity than other shape structures for compressive loads, and the strength to resist the compressive load will be lower. In the case of cylindrical geometries for tensile loading, the resisting area toward the loading will be higher in comparison to honeycomb- and enamel-based structures. At the same time, the ability to store the stain energy is less. The results of the tensile, compression and shear load finite element analysis using ANSYS are in agreement with those of the experiments.

From the insight of literature review, it is found that a wide range of work is done on fused deposition modeling (FDM) process. But in comparison to FDM, the MJP provide the better dimensional accuracy and surface properties (Lee et al., 2020). Therefore, it is observed that past research works not incorporated the effect of wall thickness of the embedded geometries on mechanical properties of the part fabricated on MJP (Gibson, n.d.). Hence, in this work, effect of wall thickness on tensile, compression and shear strength is considered as the main factor for the honeycomb, enamel and cylindrical geometries.