Liquitronics Final Project Report

This final project report details the design evaluation and tests the Liquitronics team conducted on the 96 well plate robotic liquid handler. The team was able to create a prototype that reflects the most important aspects the team set out to accomplish. The main focus of the semester was completing a functioning chassis and movement system along with the pipette mechanism. The following tests were completed: z-axis positional accuracy, x/y-axis positional accuracy, tip discard test, plunger actuator test, fluid volume test, sustained power draw test, and a size and weight test. Both positional accuracy tests passed without significant issues. The z-axis needed to be within 0.5 millimeters of the location for every trial, and the trial with the largest error had an error of 0.1 millimeters. Similarly, the x/y test needed each trial to be within 1 millimeter and the greatest error measured was only 0.6 millimeters. The tip discard test proved that the prototype could eject a pipette tip without fail. This test also gave the time a relationship between the voltage supplied to the linear actuator and the speed at which it moved. These results will aid in determining the working voltage for the prototype’s actuators and electronics. Unfortunately, there were two tests that did not meet their acceptance criteria. The final design is limited to a four foot wide and 2 foot deep space. The current prototype is currently 2.23 feet in both directions. However, after speaking with the project sponsor, it was agreed that the size limit was more flexible than originally stated and thus the current dimensions do not present any practical issues. Additionally, the prototype is well under the 500 pound weight limit measuring at 34 pounds. The second unsuccessful test was the sustained power draw test. This test is meant to prove that the circuitry of the prototype can run for extended periods of time without any components failing. Without any of the motors running, the prototype was drawing just over 300 milliamps. This was lower than what was expected. Also, the voltage regulator began to burn out, and 2 of the 9 stepper motor drivers stopped working. The reason for these failures is not yet known, but the team is currently brainstorming ideas for how to pinpoint the solution, and ensure that it will be fixed. Future improvements will be focused on getting a fully automated prototype. For this to happen, assembly of the mechanical parts must be completed, a full code must be written, and the power draw problems must be addressed

A pre-registered, multi-lab non-replication of the Action-sentence Compatibility Effect (ACE)

The Action-sentence Compatibility Effect (ACE) is a well-known demonstration of the role of motor activity in the comprehension of language. Participants are asked to make sensibility judgments on sentences by producing movements toward the body or away from the body. The ACE is the finding that movements are faster when the direction of the movement (e.g., toward) matches the direction of the action in the to-be-judged sentence (e.g., Art gave you the pen describes action toward you). We report on a pre-registered, multi-lab replication of one version of the ACE. The results show that none of the 18 labs involved in the study observed a reliable ACE, and that the meta-analytic estimate of the size of the ACE was essentially zero.Fil: Morey, Richard. Cardiff University; Reino UnidoFil: Kaschak, Michael. Florida State University; Estados UnidosFil: Díez Álamo, Antonio. Universidad de Salamanca; España. Arizona State University; Estados UnidosFil: Glenberg, Arthur. Arizona State University; Estados Unidos. Universidad de Salamanca; EspañaFil: Zwaan, Rolf A.. Erasmus University Rotterdam; Países BajosFil: Lakens, Daniël. Eindhoven University of Technology; Países BajosFil: Ibáñez, Santiago Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés; Argentina. University of San Francisco; Estados Unidos. Universidad Adolfo Ibañez; Chile. Trinity College Dublin; IrlandaFil: García, Adolfo Martín. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés; Argentina. University of San Francisco; Estados Unidos. Universidad Nacional de Cuyo. Facultad de Educación Elemental y Especial; Argentina. Universidad de Santiago de Chile; ChileFil: Gianelli, Claudia. Universitat Potsdam; Alemania. Scuola Universitaria Superiore; ItaliaFil: Jones, John L.. Florida State University; Estados UnidosFil: Madden, Julie. University of Tennessee; Estados UnidosFil: Alifano Ferrero, Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Bergen, Benjamin. University of California at San Diego; Estados UnidosFil: Bloxsom, Nicholas G.. Ashland University; Estados UnidosFil: Bub, Daniel N.. University of Victoria; CanadáFil: Cai, Zhenguang G.. The Chinese University; Hong KongFil: Chartier, Christopher R.. Ashland University; Estados UnidosFil: Chatterjee, Anjan. University of Pennsylvania; Estados UnidosFil: Conwell, Erin. North Dakota State University; Estados UnidosFil: Wagner Cook, Susan. University of Iowa; Estados UnidosFil: Davis, Joshua D.. University of California at San Diego; Estados UnidosFil: Evers, Ellen R. K.. University of California at Berkeley; Estados UnidosFil: Girard, Sandrine. University of Carnegie Mellon; Estados UnidosFil: Harter, Derek. Texas A&m University Commerce; Estados UnidosFil: Hartung, Franziska. University of Pennsylvania; Estados UnidosFil: Herrera, Eduar. Universidad ICESI; ColombiaFil: Huettig, Falk. Max Planck Institute for Psycholinguistics; Países BajosFil: Humphries, Stacey. University of Pennsylvania; Estados UnidosFil: Juanchich, Marie. University of Essex; Reino UnidoFil: Kühne, Katharina. Universitat Potsdam; AlemaniaFil: Lu, Shulan. Texas A&m University Commerce; Estados UnidosFil: Lynes, Tom. University of East Anglia; Reino UnidoFil: Masson, Michael E. J.. University of Victoria; CanadáFil: Ostarek, Markus. Max Planck Institute for Psycholinguistics; Países BajosFil: Pessers, Sebastiaan. Katholikie Universiteit Leuven; BélgicaFil: Reglin, Rebecca. Universitat Potsdam; AlemaniaFil: Steegen, Sara. Katholikie Universiteit Leuven; BélgicaFil: Thiessen, Erik D.. University of Carnegie Mellon; Estados UnidosFil: Thomas, Laura E.. North Dakota State University; Estados UnidosFil: Trott, Sean. University of California at San Diego; Estados UnidosFil: Vandekerckhove, Joachim. University of California at Irvine; Estados UnidosFil: Vanpaeme, Wolf. Katholikie Universiteit Leuven; BélgicaFil: Vlachou, Maria. Katholikie Universiteit Leuven; BélgicaFil: Williams, Kristina. Texas A&m University Commerce; Estados UnidosFil: Ziv Crispel, Noam. BehavioralSight; Estados Unido

DNA methylation-based classification of sinonasal tumors

The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent potentially previously misclassified adenoid cystic carcinomas. Our findings can aid in improving the diagnostic classification of sinonasal tumors and could help to change the current perception of SNUCs

Systematic review to identify and appraise outcome measures used to evaluate childhood obesity treatment interventions: evidence of purpose, application, validity, reliability and sensitivity

Background: Lack of uniformity in outcome measures used in evaluations of childhood obesity treatment interventions can impede the ability to assess effectiveness and limits comparisons across trials. Objective: To identify and appraise outcome measures to produce a framework of recommended measures for use in evaluations of childhood obesity treatment interventions. Data sources: Eleven electronic databases were searched between August and December 2011, including MEDLINE; MEDLINE In-Process and Other Non-Indexed Citations; EMBASE; PsycINFO; Health Management Information Consortium (HMIC); Allied and Complementary Medicine Database (AMED); Global Health, Maternity and Infant Care (all Ovid); Cumulative Index to Nursing and Allied Health Literature (CINAHL) (EBSCOhost); Science Citation Index (SCI) [Web of Science (WoS)]; and The Cochrane Library (Wiley) - from the date of inception, with no language restrictions. This was supported by review of relevant grey literature and trial databases. Review methods: Two searches were conducted to identify (1) outcome measures and corresponding citations used in published childhood obesity treatment evaluations and (2) manuscripts describing the development and/or evaluation of the outcome measures used in the childhood intervention obesity evaluations. Search 1 search strategy (review of trials) was modelled on elements of a review by Luttikhuis et al. (Oude Luttikhuis H, Baur L, Jansen H, Shrewsbury VA, O'Malley C, Stolk RP, et al. Interventions for treating obesity in children. Cochrane Database Syst Rev 2009;1:CD001872). Search 2 strategy (methodology papers) was built on Terwee et al.'s search filter (Terwee CB, Jansma EP, Riphagen II, de Vet HCW. Development of a methodological PubMed search filter for finding studies on measurement properties of measurement instruments. Qual Life Res 2009;18:1115-23). Eligible papers were appraised for quality initially by the internal project team. This was followed by an external appraisal by expert collaborators in order to agree which outcome measures should be recommended for the Childhood obesity Outcomes Review (CoOR) outcome measures framework. Results: Three hundred and seventy-nine manuscripts describing 180 outcome measures met eligibility criteria. Appraisal of these resulted in the recommendation of 36 measures for the CoOR outcome measures framework. Recommended primary outcome measures were body mass index (BMI) and dual-energy X-ray absorptiometry (DXA). Experts did not advocate any self-reported measures where objective measurement was possible (e.g. physical activity). Physiological outcomes hold potential to be primary outcomes, as they are indicators of cardiovascular health, but without evidence of what constitutes a minimally importance difference they have remained as secondary outcomes (although the corresponding lack of evidence for BMI and DXA is acknowledged). No preference-based quality-of-life measures were identified that would enable economic evaluation via calculation of quality-adjusted life-years. Few measures reported evaluating responsiveness. Limitations Proposed recommended measures are fit for use as outcome measures within studies that evaluate childhood obesity treatment evaluations specifically. These may or may not be suitable for other study designs, and some excluded measures may be more suitable in other study designs. Conclusions: The CoOR outcome measures framework provides clear guidance of recommended primary and secondary outcome measures. This will enhance comparability between treatment evaluations and ensure that appropriate measures are being used. Where possible, future work should focus on modification and evaluation of existing measures rather than development of tools de nova. In addition, it is recommended that a similar outcome measures framework is produced to support evaluation of adult obesity programmes. Funding: The National Institute for Health Research Health Technology Assessment programme