Long Short-Term Sample Distillation

In the past decade, there has been substantial progress at training increasingly deep neural networks. Recent advances within the teacher--student training paradigm have established that information about past training updates show promise as a source of guidance during subsequent training steps. Based on this notion, in this paper, we propose Long Short-Term Sample Distillation, a novel training policy that simultaneously leverages multiple phases of the previous training process to guide the later training updates to a neural network, while efficiently proceeding in just one single generation pass. With Long Short-Term Sample Distillation, the supervision signal for each sample is decomposed into two parts: a long-term signal and a short-term one. The long-term teacher draws on snapshots from several epochs ago in order to provide steadfast guidance and to guarantee teacher--student differences, while the short-term one yields more up-to-date cues with the goal of enabling higher-quality updates. Moreover, the teachers for each sample are unique, such that, overall, the model learns from a very diverse set of teachers. Comprehensive experimental results across a range of vision and NLP tasks demonstrate the effectiveness of this new training method.Comment: published as a conference paper at AAAI 202

Modeling and Prediction of Driving Behaviors Using a Nonparametric Bayesian Method with AR Models

To develop a new generation advanced driver assistance system that avoids a dangerous condition in advance, we need to predict driving behaviors. Since a nonparametric Bayesian method with a two-level structure successfully predicted the symbolized behaviors only, we applied a nonparametric Bayesian method with linear dynamical systems to predicting the driving behavior. The method called the beta process autoregressive hidden Markov model (BP-AR-HMM) segments driving behaviors into states each of which corresponds to an AR model and it predicts future behaviors using the estimated future state sequence and the dynamical systems therein. Here, the segmentation as well as the parameters of the dynamical systems are determined using given training data in an unsupervised way. We carried out experiments with real driving data and found that the BP-AR-HMM predicted driving behaviors better than other methods

リョウ チャネル ニ ゼンショリ オ モチイタ ステレオ エコー キャンセラ ノ シュウソク ソクド ノ カイセキ

修士(Master)工学(Engineering)奈良先端科学技術大学院大学修第5021

Estimated results.

A country’s industrial structure plays a pivotal role in determining its competitiveness, growth, and sustainability. Recently, many Asian countries have experienced significant economic upgradation and transformation and have emerged as major players in global trade. It is crucial to understand the factors contributing in upgradation of industrial structure of Asian economies for their continuous progress and it is little focused in literature. This study explores the effect of labor quality and digitalization on the upgradation of the industrial structure in 32 Asian countries covering the time period from 2010–2021. Multiple econometric techniques are applied for a comprehensive analysis of data, and the findings show that high-quality labor has a positive contribution to upgrading the industrial structure. Moreover, digitalization upgrades the industrial structure by improving connectivity, fostering collaboration, and enhancing productivity. Based on the findings of this study, Asian countries should prioritize investments in education and skill development to enhance human capital quality. Additionally, they should promote policies that facilitate digitalization, including investments in digital infrastructure, the development of digital skills, and the creation of a supportive regulatory environment. Thus, Asian countries can accelerate the upgradation of their industrial structure, leading to sustainable economic growth, increased competitiveness, and improved living standards.</div

Emerging Roles and Mechanism of m6A Methylation in Cardiometabolic Diseases

Cardiometabolic diseases (CMDs) are currently the leading cause of death and disability worldwide, and their underlying regulatory mechanisms remain largely unknown. N6-methyladenosine (m6A) methylation, the most common and abundant epigenetic modification of eukaryotic mRNA, is regulated by m6A methyltransferase, demethylase, and the m6A binding protein, which affect the transcription, cleavage, translation, and degradation of target mRNA. m6A methylation plays a vital role in the physiological and pathological processes of CMDs. In this review, we summarize the role played by m6A methylation in CMDs, including obesity, hypertension, pulmonary hypertension, ischemic heart disease, myocardial hypertrophy, heart failure, and atherosclerosis. We also describe mechanisms that potentially involve the participation of m6A methylation, such as those driving calcium homeostasis, circadian rhythm, lipid metabolism, autophagy, macrophage response, and inflammation. m6A methylation and its regulators are expected to be targets for the treatment of CMDs

Sample countries.

A country’s industrial structure plays a pivotal role in determining its competitiveness, growth, and sustainability. Recently, many Asian countries have experienced significant economic upgradation and transformation and have emerged as major players in global trade. It is crucial to understand the factors contributing in upgradation of industrial structure of Asian economies for their continuous progress and it is little focused in literature. This study explores the effect of labor quality and digitalization on the upgradation of the industrial structure in 32 Asian countries covering the time period from 2010–2021. Multiple econometric techniques are applied for a comprehensive analysis of data, and the findings show that high-quality labor has a positive contribution to upgrading the industrial structure. Moreover, digitalization upgrades the industrial structure by improving connectivity, fostering collaboration, and enhancing productivity. Based on the findings of this study, Asian countries should prioritize investments in education and skill development to enhance human capital quality. Additionally, they should promote policies that facilitate digitalization, including investments in digital infrastructure, the development of digital skills, and the creation of a supportive regulatory environment. Thus, Asian countries can accelerate the upgradation of their industrial structure, leading to sustainable economic growth, increased competitiveness, and improved living standards.</div

Mediating effects.

A country’s industrial structure plays a pivotal role in determining its competitiveness, growth, and sustainability. Recently, many Asian countries have experienced significant economic upgradation and transformation and have emerged as major players in global trade. It is crucial to understand the factors contributing in upgradation of industrial structure of Asian economies for their continuous progress and it is little focused in literature. This study explores the effect of labor quality and digitalization on the upgradation of the industrial structure in 32 Asian countries covering the time period from 2010–2021. Multiple econometric techniques are applied for a comprehensive analysis of data, and the findings show that high-quality labor has a positive contribution to upgrading the industrial structure. Moreover, digitalization upgrades the industrial structure by improving connectivity, fostering collaboration, and enhancing productivity. Based on the findings of this study, Asian countries should prioritize investments in education and skill development to enhance human capital quality. Additionally, they should promote policies that facilitate digitalization, including investments in digital infrastructure, the development of digital skills, and the creation of a supportive regulatory environment. Thus, Asian countries can accelerate the upgradation of their industrial structure, leading to sustainable economic growth, increased competitiveness, and improved living standards.</div

Dynamic Simulation Method of High-Speed Railway Engineering Construction Processes Based on Virtual Geographic Environment

The spatial conflicts in the construction of high-speed railways not only reduce project efficiency, but also lead to serious accidents. To address these key issues, this paper presents a dynamic simulation method for constructions processes based on a virtual geographic environment. This approach can facilitate the identification of conflicts in the construction scheme through accurately expressing and analysing the intricate spatio-temporal relations among railway facility components, construction equipment and the surrounding environment. First, a high-precision virtual geographic scene in which the construction process and methods can be visualized and modelled intuitively is established with terrain, imagery, and engineering 3D models. Then, the overall construction processes can be accurately simulated by a sequential display of the railway components and the behaviour of construction equipment. To simulate the behaviour of construction equipment, the linkage relations between each joint of construction machinery are accurately modelled and animation control parameters are extracted. Finally, a construction simulation of a high-speed railway bridge was performed, and the experimental results show that the proposed method can provide a scientific basis for the optimization of complex engineering construction schemes, safety hazard assessments, and related full life cycle tasks

Effects of Moderate-Intensity Continuous Training and High-Intensity Interval Training on Testicular Oxidative Stress, Apoptosis and m6A Methylation in Obese Male Mice

Exercise is an effective way to improve reproductive function in obese males. Oxidative stress and apoptosis are important pathological factors of obesity-related male infertility. Accumulating studies have demonstrated that N6-methyladenosine (m6A) methylation is associated with obesity and testicular reproductive function. Our study aimed to investigate and compare the effect of 8 weeks of moderate-intensity continuous training (MICT) and high-intensity interval training (HIIT) on testicular oxidative stress, apoptosis and m6A methylation in obese male mice. Male C57BL/6 mice were randomly allocated into the four groups: normal diet (ND) group, high-fat diet (HFD) group, high-fat diet with moderate-intensity continuous training (HFD-MICT) group and high-fat diet with high-intensity interval training (HFD-HIIT) group. Mice in the HFD-MICT and HFD-HIIT groups were subjected to 8 weeks of MICT or HIIT treadmill protocols after 12 weeks of HFD feeding. We found that MICT and HIIT increased the protein expression of Nrf2, HO-1 and NQO-1 in the testes of obese mice, and HIIT increased it more than MICT. The Bax/Bcl-2 ratio, Cleaved Caspase-3 protein expression and TUNEL-positive cells were consistently up-regulated in the testes of obese mice, but MICT and HIIT restrained these HFD-induced effects. In addition, HFDs increased m6A levels and the gene expression of METTL3, YTHDF2 and FTO in the testes, but these effects were reversed by MICT and HIIT. However, HIIT was more effective than MICT in reducing m6A methylation in the testes of obese mice. These results demonstrate that both MICT and HIIT protected against HFD-induced oxidative stress, apoptosis and m6A methylation in testicular tissues; as a result, testicular morphological and functional impairment improved. In particular, HIIT was more beneficial than MICT in increasing the mRNA expression of steroidogenic enzymes and testicular antioxidant capacity and decreasing m6A methylation in the testes of HFD-fed mice