The Effect of Soft Tissue and Bone Morphology on the Stresses in the Foot and Ankle

The foot and ankle interface with the ground, thus they absorb reaction forces and initiate load distribution through the body. The plantar fascia (PF) is a flexible structure that absorbs reaction forces and distributes loading across the foot. It is frequently a source of foot pain especially when people have plantar fasciitis and/or diabetes mellitus. Finite element (FE) models of the foot and ankle were created to examine the function however, the plantar fascia is frequently modeled as a 1D tension only spring, which does not represent variations caused by injury and/or disease. As models move toward being patient specific, understanding what components of a model can be generic versus what should be patient specific is critical when minimizing the time to create and simulate results. The purpose of this dissertation was to develop 3D finite element foot and ankle models including different thickness of 3D solid plantar fascia (i.e., 3mm, 4mm, and 5mm) and different ankle positions (i.e., neutral position, 10° dorsiflexion, and 10° plantarflexion). Additionally, the effect of different thicknesses of cartilage (i.e., 0.5mm, 1.0mm, and 1.7mm) and bone morphology (health and injured) was investigated in a model of the talocrural joint. As the thickness of plantar fascia increased, the strains of plantar fascia were increased, and the peak plantar pressure moved from hindfoot to forefoot. Also, the peak plantar pressures were highest when the foot was in 10° of plantarflexion and lowest in the neutral position. Finally, contact area decreased with decreasing cartilage thickness, with a greater decrease in contact area in healthy ankles. In 3 models, contact stress increased as cartilage thickness decreased. The fourth model had little decrease in contact area, thus the contact pressures may have been affected more by bone morphology. In conclusion, in models of the foot and ankle, the plantar fascia can be generic if it is less than 4 mm thick, a variety of foot positions should be considered, and specific bone morphologies should be included in the ankle if there is a known pathology

The Effect of Bone and Ligament Morphology of Ankle Joint Loading in the Neutral Position

Computational modeling of joints is used to investigate the effect of injuries, to plan surgeries, and to answer questions about joints that cannot be answered experimentally. Existing models of the ankle joint are moving toward being able to model specific patients, however, they do not include all of the anatomy (e.g., bones and/or ligaments) and have restrictive boundary conditions. These simplification in anatomy are made to minimize pre-processing and computation time. Because biomechanical modeling is increasingly focused on the implementation of patient specific cases, the effects of including more anatomical structures and determining how they affect the model results is necessary. Therefore, the purpose of this study was to develop a 3D Finite Element (FE) model of the ankle joint complex (i.e., tibia, fibula, talus, and calcaneus) with 13 major ligaments, and to determine how modeling the structure of the ligaments and the number of bone affected the contact stress in the talocrural joint (i.e., the joint between the tibia/fibula and the talus). A finite element model was developed in FEBio (FEBio, Salt Lake City, UT) from the CT data obtained from one cadaver. The model included bones, cartilage, and ligaments. Ligaments were modeled as tension-only linear springs, and applied for more than one spring for each of 13 major ligaments. Morphology of the spring was set as parallel or X configuration. The stress in the joint between the tibia and talus showed differences with the different number of bones. Especially, the stress of the three bone FE model was higher than ankle complex configuration with the same number of ligaments. The stresses were measured in Talocrural Joint 2 including tibia, talus, and 6 springs and Talocrural Joint 3 including tibia, talus, fibula, calcaneus, and 12 springs from 2.0541 MPa to 2.3077 MPa. The big difference between the models was the existence/non-existence of calcaneus. It demonstrates that the stress contour of Talocrural Joint 3 was had the most similar pattern with the Novel pressure data obtained from experiment

Look at the First Sentence: Position Bias in Question Answering

Many extractive question answering models are trained to predict start and end positions of answers. The choice of predicting answers as positions is mainly due to its simplicity and effectiveness. In this study, we hypothesize that when the distribution of the answer positions is highly skewed in the training set (e.g., answers lie only in the k-th sentence of each passage), QA models predicting answers as positions can learn spurious positional cues and fail to give answers in different positions. We first illustrate this position bias in popular extractive QA models such as BiDAF and BERT and thoroughly examine how position bias propagates through each layer of BERT. To safely deliver position information without position bias, we train models with various de-biasing methods including entropy regularization and bias ensembling. Among them, we found that using the prior distribution of answer positions as a bias model is very effective at reducing position bias, recovering the performance of BERT from 37.48% to 81.64% when trained on a biased SQuAD dataset.Comment: 13 pages, EMNLP 202

Strategic alliances in a veto game:An experimental study

In a veto game, we investigate the effects of “buyout” which allows non-veto players strategically form an intermediate coalition. First, our experimental findings show that the proportion of intermediate coalition formation is much lower than predicted by theory, regardless of the relative negotiation power between veto and non-veto players. Second, allowing coalition formation among non-veto players does not affect the surplus distribution between veto and non- veto players, which diverges from core allocations. These findings contrast to the literature, which views the ability to form an intermediate coalition as a valuable asset for non-veto players in increasing their bargaining power

Anatomy of Scientific Evolution

The quest for historically impactful science and technology provides invaluable insight into the innovation dynamics of human society, yet many studies are limited to qualitative and small-scale approaches. Here, we investigate scientific evolution through systematic analysis of a massive corpus of digitized English texts between 1800 and 2008. Our analysis reveals great predictability for long-prevailing scientific concepts based on the levels of their prior usage. Interestingly, once a threshold of early adoption rates is passed even slightly, scientific concepts can exhibit sudden leaps in their eventual lifetimes. We developed a mechanistic model to account for such results, indicating that slowly-but-commonly adopted science and technology surprisingly tend to have higher innate strength than fast-and-commonly adopted ones. The model prediction for disciplines other than science was also well verified. Our approach sheds light on unbiased and quantitative analysis of scientific evolution in society, and may provide a useful basis for policy-making.Comment: Supplementary material attache

Simple Questions Generate Named Entity Recognition Datasets

Recent named entity recognition (NER) models often rely on human-annotated datasets requiring the vast engagement of professional knowledge on the target domain and entities. This work introduces an ask-to-generate approach, which automatically generates NER datasets by asking simple natural language questions to an open-domain question answering system (e.g., "Which disease?"). Despite using fewer training resources, our models solely trained on the generated datasets largely outperform strong low-resource models by 20.8 F1 score on average across six popular NER benchmarks. Our models also show competitive performance with rich-resource models that additionally leverage in-domain dictionaries provided by domain experts. In few-shot NER, we outperform the previous best model by 5.2 F1 score on three benchmarks and achieve new state-of-the-art performance.Comment: Code available at https://github.com/dmis-lab/GeNE

日常生活下における実時間での心理・行動データの収集 : エコロジカルモメンタリーアセスメントの有用性

学位の種別:課程博士University of Tokyo(東京大学