Composite Tool Research Articles

The Prevalence of Fibromyalgia in Rheumatoid Arthritis Patients Using the Fibromyalgia Assessment Screening Tool (FAST 4) Based on the Multidimensional Health Assessment Questionnaire (MDHAQ).

Introduction Fibromyalgia (FM) is characterized by widespread pain and fatigue, accompanied by symptoms such as decreased concentration, autonomic dysfunction, and abdominal pain. It can be either primary or secondary, notably to rheumatoid arthritis (RA). The Fibromyalgia Assessment Screening Tools (FAST 4), derived from the Multidimensional Health Assessment Questionnaire (MDHAQ), is a composite tool allowing for the rapid screening of FM. Our primary objective is to determine the prevalence of FM among RA patients using the FAST 4 index. Secondary objectives include comparing the FAST 4 index with the FiRST score and describing the correlation between FM and RA activity and different factors associated with FM in RA patients. Methods This was an observational cross-sectional study including patients diagnosed with RA according to the ACR/EULAR criteria. The FAST questionnaire comprises four sections assessing pain and fatigue on a visual analog scale, painful joints reported by the patient, and a list of 60 symptoms. A FAST 4 score of ≥ 3/4 indicates a positive screening for FM. Demographics and disease features were compared using descriptive statistics. Univariate and multivariate analyses using logistic regression models were performed to calculate odds ratios (ORs) with 95% CI. The sensitivity and specificity of the FAST 4 index were evaluated, and Fagan's nomograms were used to illustrate post-test probability. Statistically significant results were considered for p-values less than 0.05. Results The study enrolled 97 patients diagnosed with RA. The mean age of the patients was 56 ± 12.7 years, with a predominance of females (90.7%, N=88). The mean duration of RA was 13.5 ± 8.69 years. RA activity measured by DAS 28-ESR showed that 40.2% (N=39) had high disease activity, 38.1% (N=37) had moderate disease activity, 11.3% (N=11) had low disease activity, and 10.3% (N=10) were in remission. The prevalence of comorbid FM, according to the FAST 4 index, was 30.9% (N=30). Based on the Multidimensional Health Assessment Questionnaire (MDHAQ), depression was observed in 66.7% (N=20) patients with FM, while anxiety was reported in 60% (N=18). Moreover, 30.4% of patients screened positive for FM using the FiRST score. The FAST 4 index detected FM patients defined by FiRST with a sensitivity of 78.6% and a specificity of 87.1%. The positive predictive value (PPV) was 73.3%, and the negative predictive value (NPV) was 90%. Univariate analysis revealed that a positive FAST 4 index was associated with the number of painful and swollen joints (p<0.001 and 0.03, respectively). Additionally, patients with a positive FAST 4 index showed higher DAS 28 scores (p=0.002). No significant association was found with CRP levels (p=0.328), ESR (p=0.499), or the use of biological treatments (p=0.146) or corticosteroids (p=0.940). In multivariate analysis, only depression remained a risk factor, increasing the risk sixfold with an OR of 5.917, 95% CI (1.91-18.3), p=0.002. Conclusion Our study suggests a high prevalence of concomitant FM in our population, highlighting the importance of screening for FM, particularly using the FAST 4 index based solely on the MDHAQ questionnaire.

Study on the Influence of AI Composition Software on Students' Creative Ability in Music Education

Generative AI technology for human-assisted tools has made great strides in recent years, and studying the impact of this technology on students' compositional abilities plays an important role in promoting changes in music education. Previous studies have focused on the performance of music composition software itself in terms of composition, with less consideration given to the impact of creators' compositional ability after using assistive composition tools. Thus, this paper designs a controlled experiment to investigate the changes in students' compositional ability before and after using AI composition tools. This paper finds that students' compositional abilities in all areas of composition improved to varying degrees after using AI composition tools. This paper compares the differences in compositional abilities of students with and without the education of AI composition tools, which has practical implications for vigorously promoting the adoption of AI composition tools in university music education teaching.

Treatment of Reactive Orange 16 Dye-Bearing Wastewater by Electro-Fenton Process with Stainless-Steel Electrodes: Statistical Optimization and Operational Analysis

Abstract: In the current work, the Electro-Fenton (EF) based Reactive Orange 16 (RO16) dye treatment was studied and compared with central composite (CC) and Taguchi design (TD) statistical optimization tools. Color removal (RC) and COD decay (RCOD) were chosen responses for the effect of pH (A), electrolysis time (B), initial dye concentration (C), and current density (D). The facecentred CC design and L16 orthogonal array were used in the experimental procedures. At optimal conditions, the coefficient of determination (R2) values of 0.99 for CC and 0.97 for TD suggest statistical significance and good model agreement. The results of the ANOVA and Prob. &gt; F values supported the model’s successful experimental data fitting. Taguchi method was found as an appropriate methodology for parameter percentage contributions with fewer experimental runs. Moreover, the S/N ratio charts proved to be a successful CC design replacement. The current density and pH were found to be the most important factors for the EF process. A higher biodegradability (BOD5/COD) and minimum iron concentration (0.45 mg/L) in the effluent sludge demonstrated good environmental disposal suitability. In the last, the effect of various inhibitors/scavengers (SO4 −2, PO4 −3, EDTA, etc.) on the EF process performance was also carried out.

Microstructural evolution and corrosion responses of friction stir welded SUS301L stainless steel

As a typical manifestation of elemental segregation of stainless steel, chromium depletion was often brought about by welding, leading to undesirable corrosion resistance. In light of this, we employed friction stir welding through WC-W composite welding tools to achieve sound joints of SUS301L stainless steel, with corrosion resistance exceeding that of the base material (BM). A higher austenite fraction of 20.8% enhanced corrosion resistance since the corrosion potential of austenite is nobler than that of martensite. Austenite was not decomposed into harmful σ-phases due to the shorter holding time at the elevated temperature, thus enhancing the homogeneity of the microstructure. The ultimate tensile strength of the welded joints reached 820 MPa, which was equal to 98.9% of BM. The pitting potential of the joint was increased by 0.078 V, indicating that the stability of the passive films was improved, and the ability to resist the corrosive medium was strengthened. Chromium depletion was eliminated, resulting in no sensitivity to intergranular corrosion.

Urban sustainability assessment: An analysis of how weighting and aggregating coefficient system was used in the development of SUCCEED assessment tool for developing countries

The development of a weighting and aggregating coefficient system used in urban sustainability assessment tools is a process that needs well-defined procedures using a series of steps, methodology, and a systematic approach in its development. The development of assessment tools has been successful in developed countries but developing countries would need to have a structured process that will assist in the development of an assessment tool that is tailored to its environs. This paper aims to understand the various weighting and aggregating coefficient systems employed in the development of sustainability assessment tools. Alongside using these findings to understand how these weighting and aggregating coefficients can be adopted in the development of sustainability assessment tools for developing countries based on their differences, advantages, and disadvantages. Qualitative Content Analysis based on a systematic review of existing literature was used in this study to understand various weighting and aggregating coefficients. It is imperative to note that this research will focus on how assessment tools are developed with a clear focus on sustainability assessment weighting and aggregating. The study also further analyses how a case study SUCCEED (Sustainable Composite Cities Environmental Evaluation and Design Tool) has benefited from the adoption of equal weighting and additive aggregation methods based on validation carried out. The findings of this research show that the selection of weighting and aggregating systems is defined by the relevance, importance, and purpose of the assessment tool. It also develops a guide/recommendations on the process utilised in the development of assessment tools for developing countries.

Demonstration of temperature monitoring of the curing process in resin transfer moulding using integrated phase-shifted Bragg grating sensors

Composite materials have increased in use across multiple industries due to their low weight, thermal stability and design flexibility. As applications grow, the importance of accurate process-monitoring techniques grows, with various research teams investigating a variety of in situ cure-monitoring sensors. Photonic integrated circuits (PICs) can be a feasible solution in tracking curing cycles due to their resistance to harsh conditions and ease of integration into the production tool. This paper demonstrates the integration and performance evaluation of an embedded phase-shifted Bragg grating solution, instead of commonly used fiber sensors, based on 220 nm height silicon-on-insulator platform for in-situ monitoring of the RTM-6 resin curing process in a composite tool. The embedded optical sensor presents high sensitivity (75 pm/°C) and linearity (R2=0.995) up to 120 °C, enabling precise temperature measurements throughout the curing cycle. The experimental results show consistency with previously reported simulations, throughout the calibration, dry run characterization and the curing process, up to 120 °C, allowing for accurate monitoring of the curing process.

A novel domain decomposition-based model for efficient dynamic predictions of large composite machine tools

A novel domain decomposition-based model for efficient dynamic predictions of large composite machine tools

Study on High-Shear and Low-Pressure Grinding Using Super-Elastic Composite Abrasive Tool (ECAT) for Curved Inconel718 Workpiece

Study on High-Shear and Low-Pressure Grinding Using Super-Elastic Composite Abrasive Tool (ECAT) for Curved Inconel718 Workpiece

Near Dry Powder Mixed Electric Discharge Machining of AA7050 Hybrid Composites Utilizing Composite Tool Materials

Electric Discharge Machining (EDM) is a prominent technique for producing components with complex geometry and intricate shapes. However, productivity depends on the selection of optimal input variables. This research investigates EDM and Near-Dry EDM (NDEDM) on AA7050 hybrid composites, exploring the impact of tool materials, Al2O3 powder concentration, and dielectric fluids on Material Removal Rate (MRR) and Surface Roughness (Ra). NDEDM offers a higher MRR due to localized heating and energy concentration, while hydrocarbon oil EDM provides lower Ra due to cooling and lubrication. Tool material properties, thermal conductivity and bonding strength, affect MRR and TWR. Aluminum composite tools via stir casting display a strong bonding interface, leading to efficient energy transfer and higher MRR, while copper composite tools via friction stir processing exhibit weaker bonding, potentially reducing MRR. Hydrocarbon oil significantly lowers TWR due to effective lubrication and cooling, while near dry EDM results in slightly higher TWR. Al2O3 powder enhances MRR, with an optimal concentration of 1 g/l, while higher concentrations hinder MRR. The presence of Al2O3 powder enhanced the surface quality by reducing the size of the recast layers and producing a smoother surface. Globules, craters, microcracks, pock marks and re-casted layers are the noticeable features spotted on the surface. The results were optimized using the TOPSIS optimization technique and process parameters 32 A current, 30 µs Ton, 3 mm gap distance machined under 3 g/l Al2O3 incorporated hydrocarbon oil dielectric medium using copper composites tool proffers optimal machining performance.

Body composition analysis using dual-energy x-ray absorptiometry in an Egyptian pediatric sickle cell disease cohort.

Growth failure is commonly encountered in sickle cell disease (SCD). Tissue compartment growth and development are subsequently likely to be altered in such patients. We aimed to analyze body composition in an Egyptian pediatric SCD cohort using dual-energy x-ray absorptiometry (DEXA), one of the most comprehensive and noninvasive assessment methods available. Forty children with SCD ≤18years and 40 healthy youngsters age- and gender-matched were enrolled. Patients' demographic, clinical, and laboratory parameters were obtained from their archived files. All patients and controls were subjected to body composition assessment using a MedixDR-Whole Body DEXA System. In SCD patients; weight and height relative to age Z scores were significantly lower (p<.001), total body lean was significantly higher (p=.006), and total body fat percentage was lower, yet the difference was not statistically significant (p=.09). There were no statistically significant variations in bone mineral density or content, basal metabolic rate, subcutaneous adipose tissue, android/gynoid fat ratio, and visceral adipose tissue. There were no significant gender disparities between SCD patients and controls. Faltering growth in children with SCD should be addressed with a multidisciplinary approach including nutritional support, correction of anemia, and proper medical care. Body composition parameters assessed using DEXA were comparable between cases and controls apart from total body lean. Further clinical studies are needed with multicenter cooperation and a larger sample size to assess the usefulness of DEXA as an assessment tool for body composition in children with SCD.

Mechanical properties and thermal shock resistance of TiB2‒B4C composite ceramic tool materials at microscopic scale

AbstractA finite model incorporating microstructure was developed to investigate the thermal shock resistance of TiB2‒B4C composite ceramic cutting tool materials. Numerical simulations were conducted to analyze changes in the transient temperature field and thermal stress field during the thermal shock process. TiB2‒B4C composite ceramic tool materials were fabricated using discharge plasma sintering technology. With different B4C contents, different sintering temperatures and holding times as study variables, optimization of the sintering process parameters and ceramic material components was achieved through testing the mechanical and microscopic morphology of the ceramics. Thermal shock water quenching experiments were performed, and the strength‐decay method was employed to assess the thermal shock resistance of TiB2‒B4C ceramics. The findings indicate that the optimal sintering conditions are temperature of 1700°C and holding time of 5 min. The TiB2‒B4C ceramic material containing 20 vol% B4C exhibits superior comprehensive mechanical properties and thermal shock resistance, and its relative density, fracture toughness, hardness, and flexural strength were 99.3%, 6.8 MPa m1/2, 22.8 GPa, and 598 MPa, respectively. The critical thermal shock temperature difference falls within the range of 400°C‒500°C.

AIDCT: An AI service development and composition tool for constructing trustworthy intelligent systems

The growing prevalence of AI services on cloud platforms is driving the demand for technologies and tools which enable the integration of multiple AI services to handle intricate tasks. Traditional methods of evaluating intelligent systems focus mainly on the performance of AI components, without providing comprehensive metrics for the system as a whole. Additionally, as these AI components are often sourced from third-party providers, users may face challenges due to inconsistent quality assurance and limitations in further developing AI models, and dealing with third-party service providers’ limitations. These limitations often involve quality assurance and a lack of capability for secondary development and training of services. To address these issues, we have developed a tool based on our previous work. It can autonomously build Intelligent systems from AI services while tackling the issues mentioned above. This tool not only creates service composition solutions that align with user-defined functional requirements and performance metrics but also executes these solutions to verify if the metrics meet user requirements. We have demonstrated the effectiveness of this tool in constructing trustworthy intelligent systems through a series of case studies.

The Evolution of the Optimization of Cognitive and Social Functions in the Cerebellum and Thereby the Rise of Homo sapiens Through Cumulative Culture.

The evolution of the prominent role of the cerebellum in the development of composite tools, and cumulative culture, leading to the rise of Homo sapiens is examined. Following Stout and Hecht's (2017) detailed description of stone-tool making, eight key repetitive involvements of the cerebellum are highlighted. These key cerebellar learning involvements include the following: (1) optimization of cognitive-social control, (2) prediction (3) focus of attention, (4) automaticity of smoothness, appropriateness, and speed of movement and cognition, (5) refined movement and social cognition, (6) learns models of extended practice, (7) learns models of Theory of Mind (ToM) of teachers, (8) is predominant in acquisition of novel behavior and cognition that accrues from the blending of cerebellar models sent to conscious working memory in the cerebral cortex. Within this context, the evolution of generalization and blending of cerebellar internal models toward optimization of social-cognitive learning is described. It is concluded that (1) repetition of movement and social cognition involving the optimization of internal models in the cerebellum during stone-tool making was the key selection factor toward social-cognitive and technological advancement, (2) observational learning during stone-tool making was the basis for both technological and social-cognitive evolution and, through an optimizing positive feedback loop between the cerebellum and cerebral cortex, the development of cumulative culture occurred, and (3) the generalization and blending of cerebellar internal models related to the unconscious forward control of the optimization of imagined future states in working memory was the most important brain adaptation leading to intertwined advances in stone-tool technology, cognitive-social processes behind cumulative culture (including the emergence of language and art) and, thereby, with the rise of Homo sapiens.

E072 The psoriatic arthritis disease activity score demonstrates excellent test-retest reliability in early, untreated psoriatic arthritis

Abstract Background/Aims Psoriatic arthritis (PsA) is a chronic inflammatory arthritis characterised by heterogenous clinical features including peripheral arthritis, spondylitis, enthesitis, dactylitis, skin and nail disease. Historically, outcome measures in PsA trials focused on the articular manifestations of disease, with a recent emphasis in composite tools. The Psoriatic Arthritis Disease Activity Score (PASDAS) is a validated, composite measure with defined cut-off and excellent responsiveness when compared with other PsA-specific and non-specific composite measures. Although PASDAS is one of the recommended GRAPPA measures for research trials, data on its test-retest reliability are limited particularly in PsA of short disease duration. Aims and Objectives - To assess the test-retest reliability of the PASDAS composite index in a cohort of early, untreated PsA patients. Methods Data were collected from a subset of participants recruited to the GOLMePsA clinical trial (EudraCT Number: 2013-004122-28), after a minor protocol amendment enabling additional data collection at the screening visit. The test-retest reliability of PASDAS was performed by calculating the intraclass correlation coefficient (ICC) between measurements collected at screening and baseline time-points (maximum 4 weeks apart, by protocol). Table 1 details the sample size calculation. Baseline variables collected in the GOLMePsA trial were described by absolute numbers, percentages, means, medians, absolute and inter-quartile ranges (IQR). Results The PASDAS test-retest reliability was assessed in 37 consecutive participants. Average time between the two time-points was 1.9 weeks (range 0.4 to 4.0). Baseline characteristics of test-retest subset compared to all GOLMePsA participants were similar (table 1). The ICC was 0.85 (95% confidence interval 0.73-0.92). The observed ICC was identical to the value assumed in the sample size calculation for this analysis, yielding an acceptably narrow confidence interval around the estimate. There was no substantial correlation between the means of the two measurements and the differences between them (Pearson’s r=-0.26). The Bland-Altman limits of agreement were -0.11 ± 1.24 (-1.35 to 1.13). Conclusion These results confirm the excellent test-retest reliability of PASDAS in early, untreated PsA, supporting its use as an outcome measure in interventional studies in newly diagnosed disease of short-duration. Disclosure G. De Marco: Consultancies; Janssen, Novartis. E.M.A. Hensor: None. D.G. McGonagle: Consultancies; AbbVie, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, UCB. Grants/research support; AbbVie, BMS, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, UCB. A. Tan: None. L.C. Coates: Consultancies; AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly, Gilead, Galapagos, Janssen, Moonlake, Novartis, Pfizer and UCB. Honoraria; AbbVie, Amgen, Biogen, Celgene, Eli Lilly, Galapagos, Gilead, GSK, Janssen, Medac, Novartis, Pfizer and UCB. Grants/research support; AbbVie, Amgen, Celgene, Eli Lilly, Janssen, Novartis, Pfizer and UCB. P. Emery: None. P.S. Helliwell: None. H. Marzo Ortega: Consultancies; AbbVie, Celgene, Eli-Lilly, Janssen, Moonlake, Novartis, Pfizer, Takeda and UCB. Grants/research support; Janssen, Novartis and UCB.

P153 Exploring the relationships between objective and subjective clinical measures in Sjogren's Syndrome

Abstract Background/Aims Patient Reported Outcome Measures (PROMs) are standardised, validated questionnaires designed to measure the patient’s perception of their disease. Discordance between the patient’s perspective and objective clinical measures (clinical scores, laboratory data) has led to increased interest in PROMs in Sjogren’s syndrome (SS). Initial concern about the subjectivity of PROMs has given way to methodological rigour and clear guidance for the development of PROMs. Several studies have now used PROMs for symptom-based stratification, and recently researchers have developed composite disease assessment tools incorporating PROMs and objective clinical measures to create more clinically meaningful endpoints for SS trials. With the advent of PROM-based stratification tools and composite endpoints, it is vital to better understand the relationship between clinical measures in SS. In this project we performed network analysis with data from a large cohort of well-characterised SS patient to improve our understanding of the relationship between objectively measured parameters and PROMs. Methods The UK Primary Sjogren’s Syndrome Registry (UKPSSR) is a nationwide observational cohort of primary SS patients who fulfil the 2002 American European Consensus Group classification criteria. The UKPSSR holds detailed clinical and laboratory data that is collected prospectively, including patient-reported outcomes collected using standardized questionnaires. To assess concordance between clinical measures we used the ARACNE algorithm, which calculates mutual information between the variables of a multidimensional dataset to construct a network of shared information. Statistical analysis was performed in R-v4.1.3 and JMP Pro-v15 and network visualisation in Cytoscape-v3.8.2. Results The ARACNE network highlights key areas of concordance and discordance between PROMs, clinician-based and laboratory-based measurements. Providing assurance to this approach, multi-domain PROMs and ESSDAI (EULAR Sjögren's syndrome disease activity index) subdomains are strongly associated with their component scores and different PROMs measuring the same symptoms were also correlated. In contrast, there is a clear separation between PROMs, clinician-based and laboratory-based measurements each forming their own sub-networks. Furthermore, most laboratory measurements do not have strong relationship with clinician-based disease activity score or PROMs. EQ-5D utility and HADS (Hospital Anxiety and Depression Scale) values provide the primary link between ESSPRI (EULAR Sjogren's Syndrome Patient Reported Index) and ESSDAI subdomain scores and both ESSDAI and ESSPRI are important contributors to quality-of-life. Conclusion The dissociation between PROMs and objective clinical measures is important for clinical management and trial design. Whilst it complicates clinical management of SS including any treat-to-target strategy; it highlights the importance of PROMs in supporting clinician assessment and laboratory measurements to better capture all aspects of SS and give a more individualised, meaningful assessment. Finally, it supports the dual-target strategy of systemically pursuing two targets in the design of clinical trials: one focused on the disease activity and another focused on the symptoms and impact. Disclosure J.S. Berry: None. J. Tarn: None. D. Lendrem: None. J. Casement: None. W. Ng: Consultancies; Expert advice in the area of Sjogren’s syndrome to GlaxoSmithKline, MedImmune, UCB, Abbvie, Roche, Eli Lilly, Takeda, Resolves Therapeutics, Sanofi, Novartis and BMS.

Dose-dependent effects of enteral nutrition on the faecal microbiota and short chain fatty acids

IntroductionEnteral nutrition (EN) involves replacing all or part of a person’s habitual diet with a nutritional formula. The impact of varying doses of EN on the gut microbiome remains understudied. MethodsHealthy adults replaced all (100% EN) or part (85% EN, 50% EN and 20% EN) of their energy requirements with EN for 7 days. Faecal samples were collected before and on day 7 of interventions. Faecal pH, short chain fatty acids (SCFAs), branched-chain fatty acids (BCFAs) and 16S rRNA sequencing were performed. Dietary assessment was performed with 7-day food diaries. ResultsSixty-one participants (31 females; median (IQR) age: 24.7 (23.0-27.8) years) were recruited. A dose-dependent impact of EN on faecal microbiota, SCFAs, BCFAs) and pH was observed, with changes detectable at EN intakes of at least 50% of energy requirements. 100% and 85% EN reduced the abundance of fibre-fermenting taxa such as Agathobacter, Faecalibaterium, Succinivibrio and Acidaminococcus. In parallel, potentially harmful organisms like Eubacterium, Actinomyces, and Klebsiella increased. In the 50% EN group, adherence to a diet high in fish, vegetables, potatoes, non-alcoholic beverages, and fat spreads, and low in cereal products, milk, and meat negatively correlated with changes in microbiota structure (r=-0.75, P=0.025). This signal was not observed when using compositional tools for microbiota analysis. ConclusionsEN detrimentally influences the faecal microbiota and diet-related bacterial metabolites in a dose-dependent manner, particularly at doses of at least 50%. The findings of this study have implications for the dietary management and counselling of patients receiving high volume EN.

Machining performance of micro-pit and micro-groove composite textured tools in tungsten alloy turning

Tungsten alloys are widely used in aerospace because of their high-temperature resistance, corrosion resistance, high strength, and other excellent comprehensive properties. But tungsten alloys are typical hard-to-machining materials. Surface micro-textures can improve friction properties, such as preparing micro-textures on the surface of cutting tools for tungsten alloys, which is expected to enhance the cutting performance of tungsten alloys. Still, the relevant cutting laws need to be further studied. A combination texture of micro-pit and micro-groove was designed, and the micro-textured tool surface was prepared by laser machining. Compared with non-textured tools, micro-pit and micro-groove composite textured tools can effectively improve the processing quality of tungsten alloys. It happened because textures on the tool’s surfaces enhance machining performance by reducing the actual contact area between the tool and the chip and storing lubrication medium. At the same time, comparative experiments of micro-textured tools and non-textured tools were carried out. The results showed that when cutting W93NiFe alloys with textured and non-textured tools, the maximum reduction in resultant cutting forces with textured tools was 9%. The maximum reduction in surface roughness was 39.3%, the surface burr height of the tungsten alloy workpiece was lower, the number of surface grooves was lesser, and the surface was more flat. The research results are significant in achieving the efficient processing and high-quality manufacturing of tungsten alloys.

In Development: 3D printed large Format composite tooling using a Robot-Mounted pellet extruder

Large Format Additive Manufacturing (LFAM) addresses the limitations of traditional 3D printing, including slow deposition rates, limited scalability, lengthy prints, and high tooling costs for large structures. Current LFAM relies on quasi-planar, 2.5D printing strategies. This fails to reap the advantages of multi-axis printing, such as reduced support material use and the ability to create complex curved surfaces. A pellet-fed, multi-axis, large-format 3D printer was developed, featuring a KUKA robot and linear rail to enable multi-axis capabilities. LFAM’s potential is demonstrated by designing and simulating the printing process for a mold of a composite wing with a winglet.

Monitoring Citizen Science Performance: Methodological Guidelines

This research paper aims to co-design a theoretical framework and methodological guidelines to monitor the performance, outcomes, and impact of Citizen Science projects. Hence, the proposed methodology com- bines the previous research efforts on the engagement of external stakeholders into a composite monitoring tool, which allows measuring and comparing CS project progress towards defined objectives. The develop- ment of methodology adopted a pragmatic mixed-method research design. Firstly, analysis of the theoretical sources and available monitoring tools provided the basis for a conceptual framework and identification of measurement indicators. The rationale of the conceptual framework was based on the co-creation workshop and stakeholders` interviews. In addition, the aggregation of indicators during the expert Focus group re- search resulted in a meaningful design of the composite CS Performance Index. The designed methodology is a part of the three-year Horizon 2020 “Science with and for Society” project INCENTIVE (Grant Agreement No. 101005330) that brings on board four Research Performing and Funding Organizations: the University of Twente, the Autonomous University of Barcelona, the Aristotle University of Thessaloniki and the Vilnius Gedi- minas Technical University. Methodological guidelines set the structure for applying the monitoring in four national CS Hubs and support their coordination. In particular, the values of the indicators could be compared with the targets set, with the respective values of other Citizen Science Hubs, or to worldwide trends.

Performance Test of Circular Cutting Tool for Composition of Brack Drum for Commercial Vehicles Using Angle Spindle Graphite Cast Iron 3-Axis Machining Center Pocket Processing

Performance Test of Circular Cutting Tool for Composition of Brack Drum for Commercial Vehicles Using Angle Spindle Graphite Cast Iron 3-Axis Machining Center Pocket Processing