ESTIMATING A RUNNER\u27S STRIDE LENGTH AND FREQUENCY FROM A RACE VIDEO BY USING GROUND STITCHING

This study estimated stride length and frequency of runners in a 100 m race video. One method for measuring stride length and frequency is using infrared sensors. However, this method is not applicable to real races since numerous markers with infrared-reflective material must be attached to the runner’s entire body. Therefore, we proposed a method using a race video. We generated a panoramic image of the 100 m track to estimate the distance of each frame from the start line. We detected the positions of the runner’s steps from the movement of the leg joints. We projected every step to the overview image of the 100 m track. In the experiment, we applied our method to the video of an IAAF World Championship Track and Field 100 m race and obtained data from Usain Bolt. As a result, we can automatically estimate stride length and frequency of real races

BODY SHAPE AND CENTER OF MASS ESTIMATION USING MULTI-VIEW IMAGES

This study presents a method for estimating human 3D body shape in action. We propose a method for estimating 3D human body shape motion that uses multiple view images and visual hulls. Related methods necessitated lengthier preparations, such as camera calibration, which would require several tries before actually capturing the image. We solve this issue by combining state-of-the-art computer vision methods to automatically process the required inputs and parameters, so that camera images are the only resource needed for estimation. In our experiments, we applied our method to a video of human subject kicking a soccer ball to left and right side of a goal; we successfully acquired the subject’s 3D body shape. In addition, we verified that the application’s automatically obtained body shape successfully provides the subject’s center of mass

Experimental characterization and performance improvement evaluation of an electromagnetic transducer utilizing a tuned inerter

This research reports on the experimental verification of an enhanced energy conversion device utilizing a tuned inerter called a tuned inertial mass electromagnetic transducer (TIMET). The TIMET consists of a motor, a rotational mass, and a tuning spring. The motor and the rotational mass are connected to a ball screw and the tuning spring interfaced to the ball screw is connected to the vibrating structure. Thus, vibration energy of the structure is absorbed as electrical energy by the motor. Moreover, the amplified inertial mass can be realized by rotating relatively small physical masses. Therefore, by designing the tuning spring stiffness and the inertial mass appropriately, the motor can rotate more effectively due to the resonance effect, leading to more effective energy generation. The authors designed a prototype of the TIMET and conducted tests to validate the effectiveness of the tuned inerter for electromagnetic transducers. Through excitation tests, the property of the hysteresis loops produced by the TIMET is investigated. Then a reliable analytical model is developed employing a curve fitting technique to simulate the behavior of the TIMET and to assess the power generation accurately. In addition, numerical simulation studies on a structure subjected to a seismic loading employing the developed model are conducted to show the advantages of the TIMET over a traditional electromagnetic transducer in both vibration suppression capability and energy harvesting efficiency

Retrospective Study of Selective Submandibular Neck Dissection versus Radical Neck Dissection for N0 or N1 Necks in Level I Patients with Oral Squamous Cell Carcinoma

Objective. To evaluate the efficacy of selective submandibular neck dissection (SMND) in patients with oral squamous cell carcinoma (OSCC) with or without nodal metastasis. Patients. From a total of 384 patients with untreated OSCC who underwent radical excision, we identified 229 with clinically N0 necks and 68 with clinically N1 necks in level I. Main Outcome Measures. The Kaplan-Meier 5-year regional control and 5-year disease specific survival (DSS) were compared for SMND, radical neck dissection (RND), and modified radical neck dissection (MRND). Results. In clinically node-negative necks, the regional control rates were 85.2% with SMND and 83.3% with MRND (P = 0.89), and 5-year DSS rates were 86.5% and 87.0%, respectively, (P = 0.94). In clinically N1 necks, the regional control rates were 81.3% with SMND and 83.0% with RND (P = 0.72), and the DSS rates were 81.3% and 80.0%, respectively, (P = 0.94). Type of neck dissection was not significantly associated with regional control or DSS on either univariate or multivariate analysis using Cox's proportional hazard model. Conclusions. SMND can be effectively applied in elective and therapeutic management to patients with OSCC that are clinically assessed as N0 or N1 to level I of the neck

Clinical Study Retrospective Study of Selective Submandibular Neck Dissection versus Radical Neck Dissection for N0 or N1 Necks in Level I Patients with Oral Squamous Cell Carcinoma

Objective. To evaluate the efficacy of selective submandibular neck dissection (SMND) in patients with oral squamous cell carcinoma (OSCC) with or without nodal metastasis. Patients. From a total of 384 patients with untreated OSCC who underwent radical excision, we identified 229 with clinically N0 necks and 68 with clinically N1 necks in level I. Main Outcome Measures. The Kaplan-Meier 5-year regional control and 5-year disease specific survival (DSS) were compared for SMND, radical neck dissection (RND), and modified radical neck dissection (MRND). Results. In clinically node-negative necks, the regional control rates were 85.2% with SMND and 83.3% with MRND (P = 0.89), and 5-year DSS rates were 86.5% and 87.0%, respectively, (P = 0.94). In clinically N1 necks, the regional control rates were 81.3% with SMND and 83.0% with RND (P = 0.72), and the DSS rates were 81.3% and 80.0%, respectively, (P = 0.94). Type of neck dissection was not significantly associated with regional control or DSS on either univariate or multivariate analysis using Cox's proportional hazard model. Conclusions. SMND can be effectively applied in elective and therapeutic management to patients with OSCC that are clinically assessed as N0 or N1 to level I of the neck

DOCK2 is involved in the host genetics and biology of severe COVID-19

「コロナ制圧タスクフォース」COVID-19疾患感受性遺伝子DOCK2の重症化機序を解明 --アジア最大のバイオレポジトリーでCOVID-19の治療標的を発見--. 京都大学プレスリリース. 2022-08-10.Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge. Here we conducted a genome-wide association study (GWAS) involving 2, 393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3, 289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2 associated with the risk allele in these younger patients. DOCK2 expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n = 61 individuals) identified cell-type-specific downregulation of DOCK2 and a COVID-19-specific decreasing effect of the risk allele on DOCK2 expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target

The whole blood transcriptional regulation landscape in 465 COVID-19 infected samples from Japan COVID-19 Task Force

「コロナ制圧タスクフォース」COVID-19患者由来の血液細胞における遺伝子発現の網羅的解析 --重症度に応じた遺伝子発現の変化には、ヒトゲノム配列の個人差が影響する--. 京都大学プレスリリース. 2022-08-23.Coronavirus disease 2019 (COVID-19) is a recently-emerged infectious disease that has caused millions of deaths, where comprehensive understanding of disease mechanisms is still unestablished. In particular, studies of gene expression dynamics and regulation landscape in COVID-19 infected individuals are limited. Here, we report on a thorough analysis of whole blood RNA-seq data from 465 genotyped samples from the Japan COVID-19 Task Force, including 359 severe and 106 non-severe COVID-19 cases. We discover 1169 putative causal expression quantitative trait loci (eQTLs) including 34 possible colocalizations with biobank fine-mapping results of hematopoietic traits in a Japanese population, 1549 putative causal splice QTLs (sQTLs; e.g. two independent sQTLs at TOR1AIP1), as well as biologically interpretable trans-eQTL examples (e.g., REST and STING1), all fine-mapped at single variant resolution. We perform differential gene expression analysis to elucidate 198 genes with increased expression in severe COVID-19 cases and enriched for innate immune-related functions. Finally, we evaluate the limited but non-zero effect of COVID-19 phenotype on eQTL discovery, and highlight the presence of COVID-19 severity-interaction eQTLs (ieQTLs; e.g., CLEC4C and MYBL2). Our study provides a comprehensive catalog of whole blood regulatory variants in Japanese, as well as a reference for transcriptional landscapes in response to COVID-19 infection

Optimizing Sensor Position with Virtual Sensors in Human Activity Recognition System Design

Human activity recognition (HAR) systems combined with machine learning normally serve users based on a fixed sensor position interface. Variations in the installing position will alter the performance of the recognition and will require a new training dataset. Therefore, we need to understand the role of sensor position in HAR system design to optimize its effect. In this paper, we designed an optimization scheme with virtual sensor data for the HAR system. The system is able to generate the optimal sensor position from all possible locations under a given sensor number. Utilizing virtual sensor data, the training dataset can be accessed at low cost. The system can help the decision-making process of sensor position selection with great accuracy using feedback, as well as output the classifier at a lower cost than a conventional training model

Estimation of grip strength using monocular camera for home-based hand rehabilitation

Grip strength exercises are commonly used rehabilitation methods for recovery of hand function. They are easy to perform even without the direct support of a healthcare professional. However, without objective feedback, the patient may not be fully engaged in the rehabilitation process. To solve this problem, we developed a system for measuring grip strength in real time using a soft ball and a monocular camera. The system estimates the grip strength using the modelled relationship between the finger joint angles extracted from the camera image and the person's grip strength. A patient can get the feedback as numbers or movements displayed on the screen. Experimental results showed that there is a correlation between the finger joint angles and the air pressure of a ball when squeezed. The average estimation error was 16.1 hPa, and the average measurement range was 100–230 hPa. The estimation error was about 12% of the measurement range. They also showed that there is a correlation between the air pressure of a ball and the applied force