Personalized human mobility prediction for HuMob challenge

We explain the methodology used to create the data submitted to HuMob Challenge, a data analysis competition for human mobility prediction. We adopted a personalized model to predict the individual's movement trajectory from their data, instead of predicting from the overall movement, based on the hypothesis that human movement is unique to each person. We devised the features such as the date and time, activity time, days of the week, time of day, and frequency of visits to POI (Point of Interest). As additional features, we incorporated the movement of other individuals with similar behavior patterns through the employment of clustering. The machine learning model we adopted was the Support Vector Regression (SVR). We performed accuracy through offline assessment and carried out feature selection and parameter tuning. Although overall dataset provided consists of 100,000 users trajectory, our method use only 20,000 target users data, and do not need to use other 80,000 data. Despite the personalized model's traditional feature engineering approach, this model yields reasonably good accuracy with lower computational cost

Interpreting Grokked Transformers in Complex Modular Arithmetic

Grokking has been actively explored to reveal the mystery of delayed generalization. Identifying interpretable algorithms inside the grokked models is a suggestive hint to understanding its mechanism. In this work, beyond the simplest and well-studied modular addition, we observe the internal circuits learned through grokking in complex modular arithmetic via interpretable reverse engineering, which highlights the significant difference in their dynamics: subtraction poses a strong asymmetry on Transformer; multiplication requires cosine-biased components at all the frequencies in a Fourier domain; polynomials often result in the superposition of the patterns from elementary arithmetic, but clear patterns do not emerge in challenging cases; grokking can easily occur even in higher-degree formulas with basic symmetric and alternating expressions. We also introduce the novel progress measure for modular arithmetic; Fourier Frequency Sparsity and Fourier Coefficient Ratio, which not only indicate the late generalization but also characterize distinctive internal representations of grokked models per modular operation. Our empirical analysis emphasizes the importance of holistic evaluation among various combinations.Comment: Code: https://github.com/frt03/grok_mod_pol

Field Equations of Massless Fields in the New Interpretation of the Matrix Model

Recently, some of the authors have introduced a new interpretation of matrix models in which covariant derivatives on any curved space can be expressed by large-N matrices. It has been shown that the Einstein equation follows from the equation of motion of IIB matrix model in this interpretation. In this paper, we generalize this argument to covariant derivatives with torsion. We find that some components of the torsion field can be identified with the dilaton and the $B$-field in string theory. However, the other components do not seem to have string theory counterparts. We also consider the matrix model with a mass term or a cubic term, in which the equation of motion of string theory is exactly satisfied.Comment: 21 page

Adaptive challenges of curriculum implementation for enhancing medical student resilience at Showa University in Japan

It has been consistently reported that medical students experience a high rate of psychological morbidity, depersonalization, and low personal accomplishment around the world. Under the circumstances, resilience-enhancing programs have been gathering attention and partially implemented even in Japan. However, most of the programs just imitate resiliency programs in North America even though studies have indicated that there are cultural differences between East Asia and North America in the capacity to cope with a stressful situation. The presenters investigated what factors might affect the similarities or differences in the perception of resilience among experienced palliative care physicians in Canada and Japan in 2017-2018. This study showed that Japanese physicians are more likely to rely on “Relationships” with other persons such as family members, friends, mentors or colleagues; in contrast, Canadian physicians tended to be more focused on individual factors such as “Autonomy” and “Confidence”. As a result, the presenters at Showa University School of Medicine in Japan have implemented a progressively advancing resiliency program in a passed manner for the 1st through 6th year medical students as part of a new curriculum. This represents one of the most drastic revisions of curriculum in the school’s history. This presentation will introduce a course for resiliency programs as part of a new curriculum, including course description, course content, educational objectives, instructional strategies and the tips for the classroom teaching and learning. &nbsp

Obstetric pelvimetry by three-dimensional computed tomography in non-pregnant Japanese women: a retrospective single-center study

OBJECTIVE: While a basic understanding of pelvic size and typology is still important for obstetricians, pelvic measurement data for Japanese women are very scarce. To our best knowledge, no large-scale pelvimetry studies of Japanese women have been made for the past 50 years. This study aimed to investigate the accurate size, particularly the obstetric conjugate (OC) and transverse diameter of the pelvic inlet (TD), of modern Japanese women, using three-dimensional (3D) computed tomography (CT), and to obtain their reference values. METHODS: This retrospective, single-center observational study enrolled Japanese non-pregnant women aged between 20 and 40 years, who underwent pelvic CT examination from 2016 to 2021. CT was performed for various reasons, including acute abdomen, search for cancer metastases, and follow-up of existing disease. However, no cases were taken for pelvic measurements. Pelvimetry was performed retrospectively using a 3D workstation. The OC was measured on a strict lateral view and the TD was measured on an axial-oblique view. Other clinical data, such as age, height, and weight, were also extracted from the medical charts and analyzed. RESULTS: A total of 1, 263 patients were enrolled, with the mean age of 32.7 years (standard deviation [SD] 6.2). The mean height, weight, and body mass index were 158.8 cm (SD 5.8), 54.8 kg (SD 11.7), and 21.7 kg/m2 (SD 4.4), respectively. The mean OC length was 127.0 mm (SD 9.5, 95% confidence interval [CI] 126.5-127.5), while the mean TD length was 126.8 mm (SD 7.5, 95% CI 126.4-127.2). Both values were normally distributed. Height was significantly associated with OC (regression coefficient = 0.75 [95% CI 0.66-0.84], p < .001) and TD (regression coefficient = 0.63 [95% CI 0.56-0.70], p < .001). Age showed a weak but statistically significant positive association with TD (regression coefficient = 0.14 [95% CI 0.07-0.20], p < .001) and OC (regression coefficient = -0.10 [95% CI -0.18 to -0.01], p = .026). CONCLUSION: The 3D CT pelvimetry in 1, 263 non-pregnant Japanese women of childbearing age revealed the mean OC and TD of 127.0 mm, and 126.8 mm, which were 11.8 mm and 4.3 mm larger, respectively, than those in the survey in 1972. Our data will be referred to in clinical practice as the standard pelvic measurement values for the Japanese population

Case-based similar image retrieval for weakly annotated large histopathological images of malignant lymphoma using deep metric learning

In the present study, we propose a novel case-based similar image retrieval (SIR) method for hematoxylin and eosin (H&E)-stained histopathological images of malignant lymphoma. When a whole slide image (WSI) is used as an input query, it is desirable to be able to retrieve similar cases by focusing on image patches in pathologically important regions such as tumor cells. To address this problem, we employ attention-based multiple instance learning, which enables us to focus on tumor-specific regions when the similarity between cases is computed. Moreover, we employ contrastive distance metric learning to incorporate immunohistochemical (IHC) staining patterns as useful supervised information for defining appropriate similarity between heterogeneous malignant lymphoma cases. In the experiment with 249 malignant lymphoma patients, we confirmed that the proposed method exhibited higher evaluation measures than the baseline case-based SIR methods. Furthermore, the subjective evaluation by pathologists revealed that our similarity measure using IHC staining patterns is appropriate for representing the similarity of H&E-stained tissue images for malignant lymphoma

TRAIL Team Description Paper for RoboCup@Home 2023

Our team, TRAIL, consists of AI/ML laboratory members from The University of Tokyo. We leverage our extensive research experience in state-of-the-art machine learning to build general-purpose in-home service robots. We previously participated in two competitions using Human Support Robot (HSR): RoboCup@Home Japan Open 2020 (DSPL) and World Robot Summit 2020, equivalent to RoboCup World Tournament. Throughout the competitions, we showed that a data-driven approach is effective for performing in-home tasks. Aiming for further development of building a versatile and fast-adaptable system, in RoboCup @Home 2023, we unify three technologies that have recently been evaluated as components in the fields of deep learning and robot learning into a real household robot system. In addition, to stimulate research all over the RoboCup@Home community, we build a platform that manages data collected from each site belonging to the community around the world, taking advantage of the characteristics of the community

開心術前後における身体組成変動

Lean body mass decreases after a major operation such as open-heart surgery, which leads to postoperative complications, as a drastic loss of muscle mass is related to infections and longer hospital stays. The purpose of this study was to examine changes in lean body mass and muscle mass including body composition the perioperative phase until discharge in patients undergoing open-heart surgery. Body fluids, fat and lean body mass in 17 patients were determined before and 1 week after surgery, and at discharge using bioelectrical impedance analysis. In addition, the levels of hemoglobin, albumin, and C-reactive protein in blood were measured. Cardiac rehabilitation consisted of early mobilization and aerobic bicycle exercise was subsequently performed after confirmation of independent walking for 200 meters. Early mobilization after surgery was assisted by physical therapists experienced in cases of cardiovascular surgery. Early mobilization required no more than 3 delayed days and no major complications until discharge in any of the patients. Weight and body mass index were significantly lower at discharge than before and 1 week after surgery, while lean body mass, muscle mass, total body water, intracellular fluid, body protein, and body cell mass values were significantly lower at discharge than before surgery. The changes in body composition seen after cardiac surgery until discharge indicated continuous catabolic reactions in our patients and some cytokines have been suggested to influence this phenomenon. After receiving open-heart surgery, it is important for patients to receive nutritional therapy and begin resistance exercise as soon as possible. Aerobic exercise should produce muscle protein synthesis and increase muscle mass under adequate nutritional support including specific amino acid supplements. Our findings indicate that muscle mass and nutritional status should be monitored after discharge and followed consistently in patients after open-heart surgery