Are we training our novices towards quality 2D profiles for 3D models?

In the history-based, feature-based, parametric CAD approach, 2D profile sketches are the basis for 3D models. Fully-constraining profiles is mandatory to create robust profiles. At present, neither CAD applications nor Model Quality Testing Tools usually check whether 2D profiles contain redundant constraints. Besides, our experience shows that novices tend to introduce redundant constraints. We hypothesize that 2D profiles over-constrained with redundant relations are more difficult to edit than those that avoid redundancies. In the present work―and as a first step to demonstrate this hypothesis―an experiment was conducted. Students of the subject “Graphics engineering” were taught on the creation of constrained 2D profiles. Then, they were asked two questions. On the one hand, novices had to identify and reason whether a simple given profile was fully-constrained, over-constrained or under-constrained. On the other hand, they had to identify and point out the types of the constraints. The results showed that in spite that novices received a specific training, roughly half of them failed to say if the 2D profile sketch was fully-constrained and which type of constraints it contained. Furthermore, the results of the second question revealed that more than the half of students did not recognize perpendicularity as a geometric constraint. As future work, we will try to demonstrate whether a reinforced training through simple exercises and a quick and effective feedback, will allow novices to improve the identification and removal of redundant 2D constraints when drawing 2D profile sketches (thus helping to produce robust profiles)

On the effects of the fix geometric constraint in 2D profiles on the reusability of parametric 3D CAD models

[EN] In order to be reusable, history-based feature-based parametric CAD models must reliably allow for modifications while maintaining their original design intent. In this paper, we demonstrate that relations that fix the location of geometric entities relative to the reference system produce inflexible profiles that reduce model reusability. We present the results of an experiment where novice students and expert CAD users performed a series of modifications in different versions of the same 2D profile, each defined with an increasingly higher number of fix geometric constraints. Results show that the amount of fix constraints in a 2D profile correlates with the time required to complete reusability tasks, i.e., the higher the number of fix constraints in a 2D profile, the less flexible and adaptable the profile becomes to changes. In addition, a pilot software tool to automatically track this type of constraints was developed and tested. Results suggest that the detection of fix constraint overuse may result in a new metric to assess poor quality models with low reusability. The tool provides immediate feedback for preventing high semantic level quality errors, and assistance to CAD users. Finally, suggestions are introduced on how to convert fix constraints in 2D profiles into a negative metric of 3D model quality.The authors would like to thank Raquel Plumed for her support in the statistical analysis. This work has been partially funded by Grant UJI-A02017-15 (Universitat Jaume I) and DPI201784526-R (MINECO/AEI/FEDER, UE), project CAL-MBE. The authors also wish to thank the editor and reviewers for their valuable comments and suggestions that helped us improve the quality of the paper.González-Lluch, C.; Company, P.; Contero, M.; Pérez Lopez, DC.; Camba, JD. (2019). On the effects of the fix geometric constraint in 2D profiles on the reusability of parametric 3D CAD models. International Journal of Technology and Design Education. 29(4):821-841. https://doi.org/10.1007/s10798-018-9458-zS821841294Ait-Aoudia, S., & Foufou, S. (2010). A 2D geometric constraint solver using a graph reduction method. Advances in Engineering Software, 41(10), 1187–1194. https://doi.org/10.1016/j.advengsoft.2010.07.008 .Ault, H. K. (1999). Using geometric constraints to capture design intent. Journal for Geometry and Graphics, 3(1), 39–45.Ault, H. K. (2004). Over-constrained, under-constrained or just right? Goldilocks evaluates DOF of sketched profiles. Paper presented at American Society for Engineering Education, 59th annual midyear meeting past, present and future? Williamsburg, November 21–23.Ault, H. K., Bu, L., & Liu, K. (2014). Solid modeling strategies-analyzing student choices. Paper presented at proceedings of the 121st ASEE annual conference and exposition, Indianapolis, June 15–18.Ault, H. K., & Fraser, A. (2013). A comparison of manual vs. online grading for solid models. Paper presented at 120th ASEE annual conference and exposition, Atlanta, GA, June 23–26, 2013, Paper ID #7233.Barbero, B. R., Pedrosa, C. M., & Samperio, R. Z. (2016). Learning CAD at university through summaries of the rules of design intent. International Journal of Technology and Design Education. https://doi.org/10.1007/s10798-016-9358-z .Bodein, Y., Bertrand, R., & Caillaud, E. (2014). Explicit reference modeling methodology in parametric CAD system. Computers in Industry, 65(1), 136–147. https://doi.org/10.1016/j.compind.2013.08.004 .Bouma, W., Fudos, I., Hoffmann, C., Cai, J., & Paige, R. (1995). Geometric constraint solver. Computer-Aided Design, 27(6), 487–501. https://doi.org/10.1016/0010-4485(94)00013-4 .Briggs, J. C., Hepworth, A. I., Stone, B. R., Cobum, J. Q., Jensen, C. G., & Red, E. (2015). Integrated, synchronous multi-user design and analysis. Journal of Computing and Information Science in Engineering, 15(3), 031002. https://doi.org/10.1115/1.4029801 .Buckley, J., Seery, N., & Canty, D. (2017). Heuristics and CAD modelling: An examination of student behaviour during problem solving episodes within CAD modelling activities. International Journal of Technology and Design Education. https://doi.org/10.1007/s10798-017-9423-2 .Camba, J. D., & Contero, M. (2015). Assessing the impact of geometric design intent annotations on parametric model alteration activities. Computers in Industry, 71, 35–45. https://doi.org/10.1016/j.compind.2015.03.006 .Camba, J. D., Contero, M., & Company, P. (2016). Parametric CAD modeling: An analysis of strategies for design reusability. Computer-Aided Design, 74, 18–31. https://doi.org/10.1016/j.cad.2016.01.003 .Camba, J. D., Contero, M., & Company, P. (2017). CAD reusability and the role of modeling information in the MBE context. Model-based enterprise summit 2017. National Institute of Standards and Technology (NIST), Gaithersburg, MD, April 3–7. MBE17-020. https://www.nist.gov/file/361581 .Cheng, Z., & Ma, Y. (2017). A functional feature modeling method. Advanced Engineering Informatics, 33, 1–15. https://doi.org/10.1016/j.aei.2017.04.003 .Cheng, Z., Xie, Y., & Ma, Y. (2018). Graph centrality analysis of feature dependencies to unveil modeling intents. Computer-Aided Design and Applications. https://doi.org/10.1080/16864360.2018.1441236 .Chester, I. (2007). Teaching for CAD expertise. International Journal of Technology and Design Education, 17, 23–35. https://doi.org/10.1007/s10798-006-9015-z .Company, P., Contero, M., Otey, J., & Plumed, R. (2015). Approach for developing coordinated rubrics to convey quality criteria in CAD training. Computer-Aided Design, 63, 101–117. https://doi.org/10.1016/j.cad.2014.10.00 .Company, P., & González-Lluch, C. (2013). CAD 3D con SolidWorks ® Tomo I: Diseño básico. Publicacions de la Universitat Jaume I. (Colección Sapientia, Núm. 86). http://cad3dconsolidworks.uji.es .Contero, M., Company, P., Vila, C., & Aleixos, N. (2002). Product data quality and collaborative engineering. IEEE Computer Graphics Applications, 22(3), 32–42. https://doi.org/10.1109/MCG.2002.999786 .Dixon, B. M., & Dannenhoffer, J. F., III. (2014). Geometric sketch constraint solving with user feedback. Journal of Aerospace Information Systems, 11(5), 316–325. https://doi.org/10.2514/1.I010110 .Fudos, I., & Hoffmann, C. M. (1997). A graph-constructive approach to solving systems of geometric constraints. ACM Transactions on Graphics, 16(2), 179–216. https://doi.org/10.1145/248210.248223 .Ge, J. X., Chou, S. C., & Gao, X. S. (1999). Geometric constraint satisfaction using optimization methods. Computer-Aided Design, 31(14), 867–879. https://doi.org/10.1016/S0010-4485(99)00074-3 .González-Lluch, C., Company, P., Contero, M., Camba, J. D., & Colom, J. (2017a). A case study on the use of model quality testing tools for the assessment of MCAD models and drawings. International Journal of Engineering Education, 33(5), 1643–1653.González-Lluch, C., Company, P., Contero, M., Camba, J. D., & Plumed, R. (2017b). A survey on 3D CAD model quality assurance and testing tools. Computer-Aided Design, 83, 64–79. https://doi.org/10.1016/j.cad.2016.10.003 .Hamade, R. F. (2009). Profiling the desirable CAD trainee: Technical background, personality attributes, and learning preferences. Journal of Mechanical Design, 131(12), 121009–121019. https://doi.org/10.1115/1.4000455 .Hekman, K. A., & Gordon, M. T. (2013). Automated grading of first year student CAD work. Paper presented at the 120th ASEE annual conference and exposition 2013, Atlanta, GA, June 23–26. Paper ID #6379.Hepworth, A., Tew, K., Trent, M., Ricks, R., Jensen, C. G., & Red, E. R. (2014). Model consistency and conflict resolution with data preservation in multi-user computer aided design. Journal of Computing and Information Science in Engineering, 14(2), 021008. https://doi.org/10.1115/1.4026553 .Jackson, C., & Buxton, M. (2007). The design reuse benchmark report: Seizing the opportunity to shorten product development. Boston: Aberdeen Group.Joan-Arinyo, R., Soto-Riera, A., Vila-Marta, S., & Vilaplana-Pastó, J. (2003). Transforming an under-constrained geometric constraint problem into a well-constrained one. Paper presented at proceedings of ACM SM03, Seatle, June 16–20.Kirstukas, S. J. (2016). Development and evaluation of a computer program to assess student CAD models. Paper presented at ASEE annual conference and exposition, New Orleans, June 26.Kramer, G. (1991). Using degrees of freedom analysis to solve geometric constraint systems. Paper presented at proceedings of the first ACM symposium on solid modeling foundations and CAD/CAM applications 1991, Austin, June 05–07.Kwon, S., Kim, B. C., Mun, D., & Han, S. (2015). Graph-based simplification of feature-based three-dimensional computer-aided design models for preserving connectivity. Journal of Computing and Information Science in Engineering, 15(3), 031010. https://doi.org/10.1115/1.4030748 .Leea, J. Y., & Kimb, K. (1998). A 2-D geometric constraint solver using DOF-based graph reduction. Computer-Aided Design, 30(11), 883–896. https://doi.org/10.1016/S0010-4485(98)00045-1 .Mata Burgarolas, N. (1997). Solving incidence and tangency constraints in 2D. Technical report LSI-97-3R, Departament LiSI, Universitat Politècnica de Catalunya.Petrina, S. (2003). Two cultures of technical courses and discourses: The case of computer aided design. International Journal of Technology and Design Education, 13, 47–73.Race, P. (2001). The lecturers toolkit—A practical guide to learning, teaching and assessment. Great Britain: Glasgow.Red, E., French, D., Jensen, G., Walker, S. S., & Madsen, P. (2013). Emerging design methods and tools in collaborative product development. Journal of Computing and Information Science in Engineering, 13(3), 031001. https://doi.org/10.1115/1.4023917 .Robertson, B. F., Walther, J., & Radcliffe, D. (2007). Creativity and the use of CAD tools: Lessons for engineering design education from industry. Journal of Mechanical Design, 129(7), 753–760. https://doi.org/10.1115/1.2722329 .Stone, B., Salmon, J., Eves, K., Killian, M., Wright, L., Oldroyd, J., et al. (2017). A multi-user computer-aided design competition: Experimental findings and analysis of team-member dynamics. Journal of Computing and Information Science in Engineering, 17(3), 031003. https://doi.org/10.1115/1.4035674 .Summers, J. D., & Shah, J. J. (2010). Mechanical engineering design complexity metrics: Size, coupling, and solvability. Journal of Mechanical Design, 132(2), 21004–21015. https://doi.org/10.1115/1.4000759 .Szewczyk, J. (2003). Difficulties with the novices’ comprehension of the computer-aided design (CAD) interface: Understanding visual representations of CAD tools. Journal of Engineering Design, 14(2), 169–185. https://doi.org/10.1080/0954482031000091491

Consensus document on allergic conjunctivitis (DECA)

Allergic conjunctivitis (AC) is an inflammatory disease of the conjunctiva caused mainly by an IgE-mediated mechanism. It is the most common type of ocular allergy. Despite being the most benign form of conjunctivitis, AC has a considerable effect on patient quality of life, reduces work productivity, and increases health care costs. No consensus has been reached on its classification, diagnosis, or treatment. Consequently, the literature provides little information on its natural history, epidemiological data are scarce, and it is often difficult to ascertain its true morbidity. The main objective of the Consensus Document on Allergic Conjunctivitis (Documento dE Consenso sobre Conjuntivitis Alérgica [DECA]), which was drafted by an expert panel from the Spanish Society of Allergology and Spanish Society of Ophthalmology, was to reach agreement on basic criteria that could prove useful for both specialists and primary care physicians and facilitate the diagnosis, classification, and treatment of AC. This document is the first of its kind to describe and analyze aspects of AC that could make it possible to control symptoms

Preventive treatments for breast cancer: recent developments

Breast cancer is a burden for western societies, and an increasing one in emerging economies, because of its high incidence and enormous psychological, social, sanitary and economic costs. However, breast cancer is a preventable disease in a significant proportion. Recent developments in the armamentarium of effective drugs for breast cancer prevention (namely exemestane and anastrozole), the new recommendation from the National Institute for Health and Care Excellence to use preventative drugs in women at high risk as well as updated Guidelines from the US Preventive Services Task Force and the American Society of Clinical Oncology should give renewed momentum to the pharmacological prevention of breast cancer. In this article we review recent major developments in the field and examine their ongoing repercussion for breast cancer prevention. As a practical example, the potential impact of preventive measures in Spain is evaluated and a course of practical actions is delineated

Proteomic and transcriptomic profiling reveals a link between the PI3K pathway and lower estrogen-receptor (ER) levels and activity in ER+ breast cancer

IntroductionAccumulating evidence suggests that both levels and activity of the estrogen receptor (ER) and the progesterone receptor (PR) are dramatically influenced by growth-factor receptor (GFR) signaling pathways, and that this crosstalk is a major determinant of both breast cancer progression and response to therapy. The phosphatidylinositol 3-kinase (PI3K) pathway, a key mediator of GFR signaling, is one of the most altered pathways in breast cancer. We thus examined whether deregulated PI3K signaling in luminal ER+ breast tumors is associated with ER level and activity and intrinsic molecular subtype.MethodsWe defined two independent molecular signatures of the PI3K pathway: a proteomic (reverse-phase proteomic array) PI3K signature, based on protein measurement for PI3K signaling intermediates, and a PI3K transcriptional (mRNA) signature based on the set of genes either induced or repressed by PI3K inhibitors. By using these signatures, we scored each ER+ breast tumor represented in multiple independent expression-profiling datasets (four mRNA, n = 915; one protein, n = 429) for activation of the PI3K pathway. Effects of PI3K inhibitor BEZ-235 on ER expression and activity levels and cell growth were tested by quantitative real-time PCR and cell proliferation assays.ResultsWithin ER+ tumors, ER levels were negatively correlated with the PI3K activation scores, both at the proteomic and transcriptional levels, in all datasets examined. PI3K signature scores were also higher in ER+ tumors and cell lines of the more aggressive luminal B molecular subtype versus those of the less aggressive luminal A subtype. Notably, BEZ-235 treatment in four different ER+ cell lines increased expression of ER and ER target genes including PR, and treatment with IGF-I (which signals via PI3K) decreased expression of ER and target genes, thus further establishing an inverse functional relation between ER and PI3K. BEZ-235 had an additional effect on tamoxifen in inhibiting the growth of a number of ER+ cell lines.ConclusionsOur data suggest that luminal B tumors have hyperactive GFR/PI3K signaling associated with lower ER levels, which has been correlated with resistance to endocrine therapy. Targeting PI3K in these tumors might reverse loss of ER expression and signaling and restore hormonal sensitivity

Interaction between acrylic substrates and RAD16-I peptide in its self-assembling

[EN] Self-assembling peptides (SAP) are widely used as scaffolds themselves, and recently as fillers of microporous scaffolds, where the former provides a cell-friendly nanoenvironment and the latter improves its mechanical properties. The characterization of the interaction between these short peptides and the scaffold material is crucial to assess the potential of such a combined system. In this work, the interaction between poly(ethyl acrylate) (PEA) and 90/10 ethyl acrylate-acrylic acid copolymer P(EAcoAAc) with the SAP RAD16-I has been followed using a bidimensional simplified model. By means of the techniques of choice (congo red staining, atomic force microscopy (AFM), and contact angle measurements) the interaction and self-assembly of the peptide has proven to be very sensitive to the wettability and electro-negativity of the polymeric substrate.The authors acknowledge funding through the European Commission FP7 project RECATABI (NMP3-SL-2009-229239), and from the Spanish Ministerio de Ciencia e Innovacion through projects MAT2011-28791-C03-02 and -03. This work was also supported by the Spanish Ministerio de Educacion through M. Arnal-Pastor FPU 2009-1870 grant. The authors acknowledge the assistance and advice of Electron Microscopy Service of the UPV.Arnal Pastor, MP.; González-Mora, D.; García-Torres, F.; Monleón Pradas, M.; Vallés Lluch, A. (2016). Interaction between acrylic substrates and RAD16-I peptide in its self-assembling. 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Conf Proc IEEE Eng Med Biol Soc 2013:6961–6964Soler-Botija C, Bagó JR, Llucià-Valldeperas A, Vallés-Lluch A, Castells-Sala C, Martínez-Ramos C, Fernández-Muiños T, Chachques JC, Monleón Pradas M, Semino CE, Bayes-Genis A (2014) Engineered 3D bioimplants using elastomeric scaffold, self-assembling peptide hydrogel, and adipose tissue-derived progenitor cells for cardiac regeneration. Am J Transl Res 6(3):291–301Martínez-Ramos M, Arnal-Pastor M, Vallés-Lluch A, Monleón Pradas M (2015) Peptide gel in a scaffold as a composite matrix for endothelial cells. J Biomed Mater Res Part A 103 A:3293–3302Rico P, Rodríguez Hernández JC, Moratal D, Altankov G, Monleón Pradas M, Salmerón-Sánchez M (2009) Substrate-induced assembly of fibronectin into networks: influence of surface chemistry and effect on osteoblast adhesion. 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Proc Inst Mech Eng H J Eng Med 224:1487–1507Hartgerink JD, Beniash E, Stupp SI (2002) Peptide-amphiphile nanofibers: a versatile scaffold for the preparation of self-assembling materials. Proc Natl Acad Sci U S A 99(8):5133–5138Busscher HJ, Vanpelt AWJ, Deboer P, Dejong HP, Arends J (1984) The effect of surface roughening of polymers on measured contact angles of liquids. Colloids Surf 9:319–331Birdi, KS. (1997) Surface tension of polymers. In: Yildrim Erbil H, ed. Handbook of surface and colloid chemistry CRC Press, Boca Raton, p. 292.Collier JH (2003) MessersmithPB.Enzymatic modification of self-assembled peptide structures with tissue transglutaminase. Bioconjug Chem 14(4):748–755Kakiuchi Y, Hirohashi N, Murakami-Murofushi K (2013) The macroscopic structure of RADA16 peptide hydrogel stimulates monocyte/macrophage differentiation in HL60 cells via cholesterol synthesis. 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Elsevier, pp. 367–43

Revisiting the design intent concept in the context of mechanical CAD education

[EN] Design intent is generally understood simply as a CAD model¿s anticipated behavior when altered. However, this representation provides a simplified view of the model¿s construction and purpose, which may hinder its general understanding and future reusability. Our vision is that design intent communication may be improved by recognizing the multifaceted nature of design intent, and by instructing users to convey each facet of design intent through the better-fitted CAD resource. This paper reviews the current understanding of design intent and its relationship to design rationale and builds on the idea that communication of design intent conveyed via CAD models can be satisfied at three levels provided that specialized instruction is used to instruct users in selection of the most suitable level for each intent.Otey, J.; Company, P.; Contero, M.; Camba, J. (2018). Revisiting the design intent concept in the context of mechanical CAD education. Computer-Aided Design and Applications. 15(1):47-60. https://doi.org/10.1080/16864360.2017.1353733S476015

Multiple health behaviour change primary care intervention for smoking cessation, physical activity and healthy diet in adults 45 to 75 years old (EIRA study): a hybrid effectiveness-implementation cluster randomised trial

Background: This study aimed to evaluate the effectiveness of a) a Multiple Health Behaviour Change (MHBC) intervention on reducing smoking, increasing physical activity and adherence to a Mediterranean dietary pattern in people aged 45–75 years compared to usual care; and b) an implementation strategy. Methods: A cluster randomised effectiveness-implementation hybrid trial-type 2 with two parallel groups was conducted in 25 Spanish Primary Health Care (PHC) centres (3062 participants): 12 centres (1481 participants) were randomised to the intervention and 13 (1581 participants) to the control group (usual care). The intervention was based on the Transtheoretical Model and focused on all target behaviours using individual, group and community approaches. PHC professionals made it during routine care. The implementation strategy was based on the Consolidated Framework for Implementation Research (CFIR). Data were analysed using generalised linear mixed models, accounting for clustering. A mixed-methods data analysis was used to evaluate implementation outcomes (adoption, acceptability, appropriateness, feasibility and fidelity) and determinants of implementation success. Results: 14.5% of participants in the intervention group and 8.9% in the usual care group showed a positive change in two or all the target behaviours. Intervention was more effective in promoting dietary behaviour change (31.9% vs 21.4%). The overall adoption rate by professionals was 48.7%. Early and final appropriateness were perceived by professionals as moderate. Early acceptability was high, whereas final acceptability was only moderate. Initial and final acceptability as perceived by the participants was high, and appropriateness moderate. Consent and recruitment rates were 82.0% and 65.5%, respectively, intervention uptake was 89.5% and completion rate 74.7%. The global value of the percentage of approaches with fidelity =50% was 16.7%. Eight CFIR constructs distinguished between high and low implementation, five corresponding to the Inner Setting domain. Conclusions: Compared to usual care, the EIRA intervention was more effective in promoting MHBC and dietary behaviour change. Implementation outcomes were satisfactory except for the fidelity to the planned intervention, which was low. The organisational and structural contexts of the centres proved to be significant determinants of implementation effectiveness. Trial registration: ClinicalTrials.gov, NCT03136211. Registered 2 May 2017, “retrospectively registered”. © 2021, The Author(s)

Alterations in PGC1[alfa] expression levels are involved in colorectal cancer risk: a qualitative systematic review

Background: Colorectal cancer (CRC) is a major global public health problem and the second leading cause of cancer-related death. Mitochondrial dysfunction has long been suspected to be involved in this type of tumorigenesis, as supported by an accumulating body of research evidence. However, little is known about how mitochondrial alterations contribute to tumorigenesis. Mitochondrial biogenesis is a fundamental cellular process required to maintain functional mitochondria and as an adaptive mechanism in response to changing energy requirements. Mitochondrial biogenesis is regulated by peroxisome proliferator-activated receptor gamma coactivator 1-? (PPARGC1A or PGC1?). In this paper, we report a systematic review to summarize current evidence on the role of PGC1? in the initiation and progression of CRC. The aim is to provide a basis for more comprehensive research. Methods: The literature search, data extraction and quality assessment were performed according to the document Guidance on the Conduct of Narrative Synthesis in Systematic Reviews and the PRISMA declaration. Results: The studies included in this review aimed to evaluate whether increased or decreased PGC1? expression affects the development of CRC. Each article proposes a possible molecular mechanism of action and we create two concept maps. Conclusion: Our systematic review indicates that altered expression of PGC1? modifies CRC risk. Most studies showed that overexpression of this gene increases CRC risk, while some studies indicated that lower than normal expression levels could increase CRC risk. Thus, various authors propose PGC1? as a good candidate molecular target for cancer therapy. Reducing expression of this gene could help to reduce risk or progression of CRC