日本のフレイル高齢者におけるKohzuki Exercise Program(KEP)の適用と効果検証

要約のみTohoku University上月　正博課

AN INTEGRATIVE MACHINE LEARNING APPROACH FOR SMALL SAMPLES AND HIGH-DIMENSIONAL IMBALANCED DATA IN PSYCHOLOGICAL EXPERIMENT

Machine learning for classification may not be immediately useful for many contexts seen in psychology. Psychological data often limit its efficacy due to small sample size, high dimensionality, and class imbalance. The current study presents an integrative machine learning approach that can be a useful solution to the challenges encountered when the aforementioned issues are inherent in psychological data. The tested approach consists of three consecutive steps – feature selection, minority oversampling, and predictive modeling. To begin with, feature selection tackles high dimensionality and extracts important features out of original predictors, using elastic net logistic regression. Then, synthetic minority oversampling technique addresses class imbalance, generating new observations primarily for the minority class. Finally, supervised machine learning algorithms build predictive models, using the oversampled feature set. The algorithms employed in this study include support vector machine, extreme gradient boosting, deep neural network, and logistic regression. They fully exploit the small sample with leave-one-out cross-validation. The current study demonstrates the utility of the integrative classification approach with an empirical analysis on predicting suicide attempt by a sample of patients diagnosed with bipolar I disorder, using their event-related potentials (ERPs). The study shows how prediction can be improved by the integrative modeling as the first two analytical steps being added to the generic process of predictive modeling.Master of Art

Global-Local Aggregation with Deformable Point Sampling for Camouflaged Object Detection

The camouflaged object detection (COD) task aims to find and segment objects that have a color or texture that is very similar to that of the background. Despite the difficulties of the task, COD is attracting attention in medical, lifesaving, and anti-military fields. To overcome the difficulties of COD, we propose a novel global-local aggregation architecture with a deformable point sampling method. Further, we propose a global-local aggregation transformer that integrates an object's global information, background, and boundary local information, which is important in COD tasks. The proposed transformer obtains global information from feature channels and effectively extracts important local information from the subdivided patch using the deformable point sampling method. Accordingly, the model effectively integrates global and local information for camouflaged objects and also shows that important boundary information in COD can be efficiently utilized. Our method is evaluated on three popular datasets and achieves state-of-the-art performance. We prove the effectiveness of the proposed method through comparative experiments

Efficient Conversion of Acetate to 3-Hydroxypropionic Acid by Engineered Escherichia coli

Acetate, which is an abundant carbon source, is a potential feedstock for microbial processes that produce diverse value-added chemicals. In this study, we produced 3-hydroxypropionic acid (3-HP) from acetate with engineered Escherichia coli. For the efficient conversion of acetate to 3-HP, we initially introduced heterologous mcr (encoding malonyl-CoA reductase) from Chloroflexus aurantiacus. Then, the acetate assimilating pathway and glyoxylate shunt pathway were activated by overexpressing acs (encoding acetyl-CoA synthetase) and deleting iclR (encoding the glyoxylate shunt pathway repressor). Because a key precursor malonyl-CoA is also consumed for fatty acid synthesis, we decreased carbon flux to fatty acid synthesis by adding cerulenin. Subsequently, we found that inhibiting fatty acid synthesis dramatically improved 3-HP production (3.00 g/L of 3-HP from 8.98 g/L of acetate). The results indicated that acetate can be used as a promising carbon source for microbial processes and that 3-HP can be produced from acetate with a high yield (44.6% of the theoretical maximum yield).11Ysciescopu

Pixel-Level Equalized Matching for Video Object Segmentation

Feature similarity matching, which transfers the information of the reference frame to the query frame, is a key component in semi-supervised video object segmentation. If surjective matching is adopted, background distractors can easily occur and degrade the performance. Bijective matching mechanisms try to prevent this by restricting the amount of information being transferred to the query frame, but have two limitations: 1) surjective matching cannot be fully leveraged as it is transformed to bijective matching at test time; and 2) test-time manual tuning is required for searching the optimal hyper-parameters. To overcome these limitations while ensuring reliable information transfer, we introduce an equalized matching mechanism. To prevent the reference frame information from being overly referenced, the potential contribution to the query frame is equalized by simply applying a softmax operation along with the query. On public benchmark datasets, our proposed approach achieves a comparable performance to state-of-the-art methods

RADIO: Reference-Agnostic Dubbing Video Synthesis

One of the most challenging problems in audio-driven talking head generation is achieving high-fidelity detail while ensuring precise synchronization. Given only a single reference image, extracting meaningful identity attributes becomes even more challenging, often causing the network to mirror the facial and lip structures too closely. To address these issues, we introduce RADIO, a framework engineered to yield high-quality dubbed videos regardless of the pose or expression in reference images. The key is to modulate the decoder layers using latent space composed of audio and reference features. Additionally, we incorporate ViT blocks into the decoder to emphasize high-fidelity details, especially in the lip region. Our experimental results demonstrate that RADIO displays high synchronization without the loss of fidelity. Especially in harsh scenarios where the reference frame deviates significantly from the ground truth, our method outperforms state-of-the-art methods, highlighting its robustness. Pre-trained model and codes will be made public after the review.Comment: Under revie

Effects of a smart phone-based game on balance ability and dizziness in healthy adult individuals

Many people use smartphone these days. There are many studies on the effects of smartphones on our bodies, but there is a lack of research on balance and dizziness. The purpose of this study was to determine how a healthy person’s balance and dizziness is affected by using smart devices. Twenty four healthy adults in their twenties were assigned to the 10-minute and 20-minute group based on the duration of the smartphone game. To evaluate the effects of smartphone games on the balance and dizziness of the participants, we evaluated their balance and dizziness before and after playing the smartphone game. Balance was measured using a force plate (Wii Balance Board, Balancia version 2.0, Mintosys Inc., Seoul, KR) and dizziness was measured using the Simulator sickness Questionnaire (SSQ). There was a significant difference in balance among both groups before and after playing the smartphone game (p .05). Regarding dizziness, the SSQ score indicated minimal symptoms in the 10-minute group, while it revealed significant symptoms in the 20-minute group. In this study, playing a smartphone game for 10 minutes and 20 minutes was found to affect balance. Further, it was found that playing a smartphone game for 20 minutes may lead to a significant level of dizziness

Age-Dependent Association of Height Loss with Incident Fracture Risk in Postmenopausal Korean Women

Background Height loss is a simple clinical measure associated with increased fracture risk. However, limited data exists on the association between height loss and fracture risk in postmenopausal Korean women. It is unknown whether this association varies with age. Methods Data on height loss over a 6-year period were collected from a community-based longitudinal follow-up cohort (Ansung cohort of the Korean Genome and Epidemiology Study). Incident fractures were defined based on self-reported fractures after excluding those due to severe trauma or toes/fingers. The association between incident fractures and height loss was investigated using a Cox proportional hazards model. Results During a median follow-up of 10 years after the second visit, 259/1,806 participants (median age, 64 years) experienced incident fractures. Overall, a 1 standard deviation (SD) decrease in height (1.6 cm/median 5.8 years) was associated with 9% increased risk of fracture (hazard ratio [HR], 1.09; P=0.037), which lost statistical significance after adjustment for covariates. When stratified into age groups (50–59, 60–69, 70 years or older), a 1 SD decrease in height remained a robust predictor of fracture in the 50 to 59 years age group after adjusting for covariates (adjusted hazard ratio [aHR], 1.52; P=0.003), whereas height loss was not an independent predictor of fracture in the 60 to 69 (aHR, 1.06; P=0.333) or the 70 years or older age groups (aHR, 1.05; P=0.700; P for interaction <0.05, for all). Conclusion Height loss during the previous 6 years was associated with an increased 10-year fracture risk in postmenopausal women in their 50s