317 research outputs found

    Benchmarking analysis of digital light processing resins in terms of dimensional accuracy and geometric tolerances

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    Additive Manufacturing (AM) is a groundbreaking fabrication technology that is revolutionizing traditional manufacturing processes. Generally, following a layer-by-layer approach, in AM the final shape of the product is built through the progressive deposition of one or more materials. The most common extrusion-based AM technique for thermoplastic polymers is Fused Filament Fabrication (FFF), whilst for photopolymer resins, Digital Light Processing (DLP) and Stereolithography (SLA) are widely used. In the last years, DLP has spread rapidly, due to its low average cost and simple use. Moreover, a lower layer thickness can be used in DLP if compared to the FFF process. Therefore, hobbyists or amateur end users and many companies use DLP to achieve high dimensional accuracy and smooth surfaces for small products. This work aims to evaluate the performance of three different DLP resins in terms of dimensional and geometrical accuracy. A benchmarking activity is carried out using a Rover printer by Sharebot to produce replicas of a reference part using Sharebot resins. After production, the replicas were inspected using a Coordinate Measuring Machine (CMM) for comparing the dimensional accuracy of the geometric features according to ISO IT grades and tolerances of the GD&T system. The results of this study are also compared with previous works from the literature in the conclusions

    Development of a low-cost monitoring system for open 3d printing

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    3D printers for Rapid Prototyping and Additive Manufacturing have been widely accepted by large and small-scale industries or by many hobbyists. Due to its nature of layer by layer addition of material, identifying defects between the layers can be a crucial strategy to determine the quality of a 3D printed product by carefully monitoring the layerwise process during part building. This kind of approach gives an advantage in the applications where 3D printing of products requires high customization without compromise on part quality. In this work, a low-cost camera is installed in an open 3D printer, and computer vision algorithms are used to implement an in-situ monitoring system. The defects can be evaluated by comparing the printed layer to the deposition path of the open ISO G-code. The G-code printing file is modified to introduce the image capture step after each layer. The value of the area of missing or exceeding material is returned to the user with the corresponding images. A decision can be made to abort the job in case of important defects to avoid unnecessary waste in material, time, and costs

    Experimental testing of 3D printed polymeric heat exchangers

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    Unlike conventional manufacturing technologies, additive manufacturing and 3D printing empower engineers with much more design freedom. Heat exchangers with complex internal channels or lattice structures can be designed for layerwise manufacturing by maximizing the surface to volume ratio. Low-weight polymeric heat exchangers are employed in aviation and aerospace applications. For increasing the thermal performance of polymers, additives can be used such as graphene. In this study, a Grafylon filament is used for the production of a simple heat exchanger by 3D printing. The heat exchanger is composed of two external shells and an interior duct with a two-stage 45-degree bend. For watertight purposes, the duct is manufactured by selective laser sintering of polyamide powder. Two replicas of the shells are fabricated by 3D printing of Grafylon and acrylonitrile butadiene styrene (ABS) respectively. The thermal performance of the two materials is experimentally tested and compared also to numerical simulations. The results of the study show that the Grafylon filament provides enhanced thermal performance to 3D printed heat exchangers of polymeric material

    Experimental assessment of compensated distortion in selective laser melting of Ti6Al4V parts

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    Selective laser melting (SLM) is a well-established Additive Manufacturing technique for the fabrication of end-use metal components. Process reliability and maximum product quality are ensured by 20 years of technology development. Nevertheless, depending on the complexity of the part geometry and on the operator experience, different trials are often needed before getting a part first time right. To reduce the number of failed jobs, simulation software packages predict residual stresses and related distortions in SLM parts and propose a compensated geometry for the “right first time” production of the product. In this works, the simulation routines of Amphyon software by Additive Works are experimentally calibrated and validated for the fabrication of a reference geometry by means of an EOSINT M270 machine and Ti6Al4V powder. The calibration of Amphyon is performed using three cantilever specimens and the calibrated SLM simulation is then used to compute the compensated shape of the reference part. The validation of the compensated shape by comparison to the real part geometry shows that Amphyon routines have good prediction capability and dimensional accuracy

    An approach to evaluate the wear of customized manufacturing fixtures through the analysis of 3D scan data

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    With the recent gain in popularity and adoption of additive manufacturing in various industrial sectors, quality assessments to determine the functionality of 3D printed parts are critical. This holds especially when the parts are subjected to wear as in the case of the production of customized fixtures. Some reinforced polymeric materials for additive manufacturing can be employed as a substitute for low-resistance metals like Aluminium. In this paper, a custom-made tribometer was used to simulate the wear of 3D printed fixtures of Alumide material for sheet metal inspection operations. Contact 3D scanning is used to monitor the condition of the fixture for increasing numbers of wear cycles. This study aims to calculate the wear volume of cylindrical pins starting from the surface points of 3D scan data. The methodology employs alpha shapes to obtain the progression of the volume and area of the worn zone. Experimental tests to evaluate the wear volume were carried out to compare the durability of Alumide to that of Aluminium, filling the gap of previous literature, which had focused exclusively on diametral wear. The findings indicate a better wear resistance for Alumide specimens and this work contributes to broadening the knowledge about the wear behaviour and the lifetime of 3D printed parts

    Association of Wilms tumor-1 protein in urinary exosomes with kidney injury: a population-based cross-sectional study

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    ObjectiveLoss of Wilms tumor-1 (WT1) protein, a podocytopathy marker, through urine exosome (uE), could be an early indication of kidney injury. We examined WT1 in uE (uE-WT1), along with other urine markers of glomerular and kidney tubule injury, in individuals without chronic kidney disease (CKD).MethodologyThe cross-sectional study included individuals who reported having no evidence of chronic kidney disease (CKD). Albumin-to-creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) were used to assess kidney function. eGFR was calculated using the 2009 CKD-EPI (CKD-Epidemiological) equation. WT1 was analyzed in uE from humans and Wistar rats (before and after the 9th week of diabetes, n = 20). uE-WT1, urinary neutrophil gelatinase-associated lipocalin (NGAL), and kidney injury molecule-1 (KIM-1) were estimated using ELISA. The Kruskal-Wallis H test, Mann-Whitney U test, and stepwise multivariable linear regression were performed.ResultsUrine NGAL and ACR increase with uE-WT1 quartiles (n = 146/quarter). Similarly, uE-WT1, KIM-1, and NGAL were positively associated with ACR. Furthermore, KIM-1, NGAL, and uE-WT1 correlated with ACR. uE-WT1 outperformed KMI-1 and NGAL to explain ACR variability (25% vs. 6% or 9%, respectively). Kidney injury in streptozotocin-induced diabetic rats was associated with a significant rise in uE-WT1. Moreover, the findings were confirmed by the histopathology of kidney tissues from rats.ConclusionuE-WT1 was strongly associated with kidney function in rats. In individuals without CKD, uE-WT1 outperformed NGAL as a determinant of differences in ACR

    Multiarticular chronic tophaceous gout with severe and multiple ulcerations: a case report

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    <p>Abstract</p> <p>Introduction</p> <p>Gout is a common inflammatory arthritis caused by articular precipitation of monosodium urate crystals. It usually affects the first metatarsophalangeal joint of the foot and less commonly other joints, such as wrists, elbows, knees and ankles.</p> <p>Case presentation</p> <p>We report the case of a 75-year-old Caucasian man with tophaceous multiarticular gout, soft-tissue involvement and ulcerated tophi on the first metatarsophalangeal joint of the left foot, on the first interphalangeal joint of the right foot and on the left thumb.</p> <p>Conclusion</p> <p>Ulcers due to tophaceous gout are currently uncommon considering the positive effect of pharmaceutical treatment in controlling hyperuricemia. Surgical treatment is seldom required for gout and is usually reserved for cases of recurrent attacks with deformities, severe pain, infection and joint destruction.</p

    Completeness of Reporting in Diet- and Nutrition-Related Randomized Controlled Trials and Systematic Reviews With Meta-Analysis:Protocol for 2 Independent Meta-Research Studies

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    Background: Journal articles describing randomized controlled trials (RCTs) and systematic reviews with meta-analysis of RCTs are not optimally reported and often miss crucial details. This poor reporting makes assessing these studies’ risk of bias or reproducing their results difficult. However, the reporting quality of diet- and nutrition-related RCTs and meta-analyses has not been explored. Objective: We aimed to assess the reporting completeness and identify the main reporting limitations of diet- and nutrition-related RCTs and meta-analyses of RCTs, estimate the frequency of reproducible research practices among these RCTs, and estimate the frequency of distorted presentation or spin among these meta-analyses. Methods: Two independent meta-research studies will be conducted using articles published in PubMed-indexed journals. The first will include a sample of diet- and nutrition-related RCTs; the second will include a sample of systematic reviews with meta-analysis of diet- and nutrition-related RCTs. A validated search strategy will be used to identify RCTs of nutritional interventions and an adapted strategy to identify meta-analyses in PubMed. We will search for RCTs and meta-analyses indexed in 1 calendar year and randomly select 100 RCTs (June 2021 to June 2022) and 100 meta-analyses (July 2021 to July 2022). Two reviewers will independently screen the titles and abstracts of records yielded by the searches, then read the full texts to confirm their eligibility. The general features of these published RCTs and meta-analyses will be extracted into a research electronic data capture database (REDCap; Vanderbilt University). The completeness of reporting of each RCT will be assessed using the items in the CONSORT (Consolidated Standards of Reporting Trials), its extensions, and the TIDieR (Template for Intervention Description and Replication) statements. Information about practices that promote research transparency and reproducibility, such as the publication of protocols and statistical analysis plans will be collected. There will be an assessment of the completeness of reporting of each meta-analysis using the items in the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) statement and collection of information about spin in the abstracts and full-texts. The results will be presented as descriptive statistics in diagrams or tables. These 2 meta-research studies are registered in the Open Science Framework. Results: The literature search for the first meta-research retrieved 20,030 records and 2182 were potentially eligible. The literature search for the second meta-research retrieved 10,918 records and 850 were potentially eligible. Among them, random samples of 100 RCTs and 100 meta-analyses were selected for data extraction. Data extraction is currently in progress, and completion is expected by the beginning of 2023. Conclusions: Our meta-research studies will summarize the main limitation on reporting completeness of nutrition- or diet-related RCTs and meta-analyses and provide comprehensive information regarding the particularities in the reporting of intervention studies in the nutrition field

    Completeness of reporting in diet- and nutrition-related randomized controlled trials and systematic reviews with meta-analysis: protocol for 2 independent meta-research studies

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    Background: Journal articles describing randomized controlled trials (RCTs) and systematic reviews with meta-analysis of RCTs are not optimally reported and often miss crucial details. This poor reporting makes assessing these studies’ risk of bias or reproducing their results difficult. However, the reporting quality of diet- and nutrition-related RCTs and meta-analyses has not been explored. Objective: We aimed to assess the reporting completeness and identify the main reporting limitations of diet- and nutrition-related RCTs and meta-analyses of RCTs, estimate the frequency of reproducible research practices among these RCTs, and estimate the frequency of distorted presentation or spin among these meta-analyses. Methods: Two independent meta-research studies will be conducted using articles published in PubMed-indexed journals. The first will include a sample of diet- and nutrition-related RCTs; the second will include a sample of systematic reviews with meta-analysis of diet- and nutrition-related RCTs. A validated search strategy will be used to identify RCTs of nutritional interventions and an adapted strategy to identify meta-analyses in PubMed. We will search for RCTs and meta-analyses indexed in 1 calendar year and randomly select 100 RCTs (June 2021 to June 2022) and 100 meta-analyses (July 2021 to July 2022). Two reviewers will independently screen the titles and abstracts of records yielded by the searches, then read the full texts to confirm their eligibility. The general features of these published RCTs and meta-analyses will be extracted into a research electronic data capture database (REDCap; Vanderbilt University). The completeness of reporting of each RCT will be assessed using the items in the CONSORT (Consolidated Standards of Reporting Trials), its extensions, and the TIDieR (Template for Intervention Description and Replication) statements. Information about practices that promote research transparency and reproducibility, such as the publication of protocols and statistical analysis plans will be collected. There will be an assessment of the completeness of reporting of each meta-analysis using the items in the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) statement and collection of information about spin in the abstracts and full-texts. The results will be presented as descriptive statistics in diagrams or tables. These 2 meta-research studies are registered in the Open Science Framework. Results: The literature search for the first meta-research retrieved 20,030 records and 2182 were potentially eligible. The literature search for the second meta-research retrieved 10,918 records and 850 were potentially eligible. Among them, random samples of 100 RCTs and 100 meta-analyses were selected for data extraction. Data extraction is currently in progress, and completion is expected by the beginning of 2023. Conclusions: Our meta-research studies will summarize the main limitation on reporting completeness of nutrition- or diet-related RCTs and meta-analyses and provide comprehensive information regarding the particularities in the reporting of intervention studies in the nutrition field. International Registered Report Identifier (IRRID): DERR1-10.2196/4353
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