An Investigation of Modeing Behaviors in Function Structure Modeling With Respect to Chaining Methods

The systematic engineering design process equips designers with tools and methods necessary to understand and solve a given design problem. Function decomposition is one such tool that allows designers to decompose the given problem into sub-problems which may be easier to address. Research on Function modeling, specifically Function Structure models, has focused on improving model construction techniques and using the Function Structure models to support concept generation. Additionally, Function Structure models have also been traditionally used as individual design tools; however, most other conceptual design tools are used in a collaborative setting (e.g. gallery sketching, method 3-6-5, etc.). This research investigates the use of Function Structure models as a collaborative tool by using seed models constructed using three different chaining methods (forward chaining, backward chaining, and nucleation) identified in a pilot protocol study. These seed models were intended to represent a partially completed model created by one designer, which was then delivered to the next designer for completion. A designer study and a protocol study were conducted to identify differences between the final Function Structure models generated using different seed models, based on the percent increase in the number of functions and flows, change in model complexity, and a rubric based evaluation of the model. Results show that using a nucleation seed model yield a higher increase in function and flows, as well as a larger change in model complexity. Analysis of the rubric based model evaluation shows that the presence of the seed model improves the evaluation scores, however, the type of chaining method used does not impact the final score. These results suggest that teaching of Function Structure models should include explicit identification of the different chaining methods, and recommends nucleation as the chaining method of choice. Moreover, future research areas are identified with respect to further comparison of chaining methods, as well as investigation of behavioral patterns in the modeling activity

Exploring the Role of Individual Differences in Function Structure Modeling: A Theory Building Approach

Functions are a critical concept in engineering that support problem clarification and early-stage conceptual design. Function modeling, like other early-stage design tools, relies on subjective inputs from designers and is influenced by individual differences in designers. While research on function modeling has investigated topics such as modeling representations, model construction techniques, model use for conceptual design, and modeling behaviors, the role of individual differences is largely unexplored. This research aims to investigate how cognitive attributes and other individual differences influence the function modeling process and outcomes. Due to limited insight available about the nature of the relationship between individual attributes and function modeling, a theory building approach is adopted. An input-process-output framework is developed to systematically identify measures that will represent different aspects of function modeling. Four cognitive attribute measures are selected for testing: (1) systemizing quotient, (2) risk propensity, (3) goal orientation, and (4) concept design thinking style inventory. A two-part protocol study in conducted. Participants are first asked to complete the set of surveys intended to capture the input measures in the form of individual differences. Following that, a protocol study session is scheduled where a video recording of the function modeling activity is collected. A protocol analysis is used to code videos into structured data, which are subsequently analyzed to generate process measures. The finalized Function Structure model is converted into a bipartite graph, which is then used to calculate graph complexity metrics. These along with a rubric-based evaluation of the model are used as output measures. The input, process, and output measures are then compared using an exhaustive pairwise regression analysis and a multiple regression analysis. Correlations highlighted from the regression analyses are discussed. The learning goal orientation measure is found to be correlated with frequency of reading the problem statement, pointing towards a tendency to internalize the problem. Preference for different concept design thinking styles is found to correlate with different aspects of the modeling process. The “inquiring” thinking style is correlated with labeling flows, while the “exploring” thinking style is correlated with the number of modeling activities. Risk propensity is found to be inversely correlated with functions generated in the modeling process and directly correlated with the level of interconnection in the final model. Elements generated during the modeling process and the chaining methods used for introducing elements to the models are also correlated with the level of interconnection in the final model. Following a discussion of potential relationships observed, a targeted experiment is designed and conducted to investigate the relationship between risk propensity and level of interconnection in the final model. Results shows that risk propensity does not correlate with function model size but does affect the level of interconnection in the model. To conclude, the correlations found are summarized and limitations of the study are discussed. A theoretical model of function modeling is proposed using the relationships discovered in this research. Finally, five future research questions are identified, corresponding hypotheses are formulated, and potential experiments are discussed. Applications of the research methods to other design tools are also explored as future work

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field