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    13197 research outputs found

    An Exploratory Study of Donations to Individual Developers via GitHub Sponsors

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    奈良先端科学技術大学院大学修士(工学)master thesi

    カカンソクセイ シスウ ガ イチヨウ デ ナイ タニュウシュツリョクケイ ニ タイスル フィードバック ゴサ ガクシュウ

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    奈良先端科学技術大学院大学修士(工学)master thesi

    コウハンイ キンキョリ ムセン ツウシン ニ オケル フクスウ タンマツ セツゾクジ ノ カンド カイゼンホウ

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    奈良先端科学技術大学院大学修士(工学)master thesi

    Complicated Human Activity Recognition Based on Wearable Sensors Scenario

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    奈良先端科学技術大学院大学修士 (理学)master thesi

    Mechanics of Reversible Deformation during Leaf Movement and Regulation of Pulvinus Development in Legumes

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    Plant cell deformation is a mechanical process that is driven by differences in the osmotic pressure inside and outside of the cell and is influenced by cell wall properties. Legume leaf movements result from reversible deformation of pulvinar motor cells. Reversible cell deformation is an elastic process distinct from the irreversible cell growth of developing organs. Here, we begin with a review of the basic mathematics of cell volume changes, cell wall function, and the mechanics of bending deformation at a macro scale. Next, we summarize the findings of recent molecular genetic studies of pulvinar development. We then review the mechanisms of the adaxial/abaxial patterning because pulvinar bending deformation depends on the differences in mechanical properties and physiological responses of motor cells on the adaxial versus abaxial sides of the pulvinus. Intriguingly, pulvini simultaneously encompass morphological symmetry and functional asymmetry along the adaxial/abaxial axis. This review provides an introduction to leaf movement and reversible deformation from the perspective of mechanics and molecular genetics.review articl

    Identification of Single Yeast Budding Using Impedance Cytometry with a Narrow Electrode Span

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    Impedance cytometry is wildly used in single-cell detection, and its sensitivity is essential for determining the status of single cells. In this work, we focus on the effect of electrode gap on detection sensitivity. Through comparing the electrode span of 1 00B5mand500B5m and 5 00B5m, our work shows that narrowing the electrode span could greatly improve detection sensitivity. The mechanism underlying the sensitivity improvement was analyzed via numerical simulation. The small electrode gap (1 00B5m)allowstheelectricfieldtoconcentratenearthedetectionarea,resultinginahighsensitivityfortinyparticles.Thisfindingisalsoverifiedwiththemixturesuspensionof100B5m) allows the electric field to concentrate near the detection area, resulting in a high sensitivity for tiny particles. This finding is also verified with the mixture suspension of 1 00B5m and 3 00B5mpolystyrenebeads.Asaresult,theelectrodeswith100B5m polystyrene beads. As a result, the electrodes with 1 00B5m gap can detect more 1 00B5mbeadsinthesuspensionthanelectrodeswith500B5m beads in the suspension than electrodes with 5 00B5m gap. Additionally, for single yeast cells analysis, it is found that impedance cytometry with 1 00B5melectrodesgapcaneasilydistinguishbuddingyeastcells,whichcannotberealizedbytheimpedancecytometrywith500B5m electrodes gap can easily distinguish budding yeast cells, which cannot be realized by the impedance cytometry with 5 00B5m electrodes gap. All experimental results support that narrowing the electrode gap is necessary for tiny particle detection, which is an important step in the development of submicron and nanoscale impedance cytometry.journal articl

    Alleviating parameter-tuning burden in reinforcement learning for large-scale process control

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    Modern process controllers necessitate high quality models and remedial system re-identification upon performance degradation. Reinforcement Learning (RL) can be a promising replacement for those laborious manual procedures. However, in realistic scenarios time is limited, algorithms that can robustly learn with reduced human-agent interactions or self-exploration e.g. parameter tuning are desired. In practice, a great portion of time in setting up an RL algorithm to properly work is spent on those trial-and-error interactions. To reduce the interaction time, we propose a principled framework to ensure monotonic policy improvement even with underperforming parameters, enhancing the robustness of RL process against parameter setting. We incorporate key ingredients such as random features and factorial policy into monotonic improvement mechanism for learning cautiously in large-scale process control problems. We demonstrate in challenging control problems on the simulated vinyl acetate monomer process that the proposed method robustly learns meaningful policy within a short, fixed learning horizon given various parameter configurations that simulate the interactions, comparing to the other method that can only show good performance specific to a narrow range of parameters.journal articl

    Memory trace imbalance in reinforcement and punishment systems can reinforce implicit choices leading to obsessive-compulsive behavior

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    We may view most of our daily activities as rational action selections; however, we sometimes reinforce maladaptive behaviors despite having explicit environmental knowledge. In this study, we model obsessive-compulsive disorder (OCD) symptoms as implicitly learned maladaptive behaviors. Simulations in the reinforcement learning framework show that agents implicitly learn to respond to intrusive thoughts when the memory trace signal for past actions decays differently for positive and negative prediction errors. Moreover, this model extends our understanding of therapeutic effects of behavioral therapy in OCD. Using empirical data, we confirm that patients with OCD show extremely imbalanced traces, which are normalized by serotonin enhancers. We find that healthy participants also vary in their obsessive-compulsive tendencies, consistent with the degree of imbalanced traces. These behavioral characteristics can be generalized to variations in the healthy population beyond the spectrum of clinical phenotypes.journal articl

    Interplay between HTRA1 and classical signalling pathways in organogenesis and diseases

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    The high temperature requirement factor A1 (HTRA1) is a serine protease which modulates an array of signalling pathways driving basal biological processes. HTRA1 plays a significant role in cell proliferation, migration and fate determination, in addition to controlling protein aggregates through refolding, translocation or degradation. The mutation of HTRA1 has been implicated in a plethora of disorders and this has also led to its growing interest as drug therapy target. This review details the involvement of HTRA1 in certain signalling pathways, namely the transforming growth factor beta (TGF-β), canonical Wingless/Integrated (WNT) and NOTCH signalling pathways during organogenesis and various disease pathogenesis such as preeclampsia, age-related macular degeneration (AMD), small vessel disease and cancer. We have also explored possible avenues of exploiting the serine proteases for therapeutic management of these disorders.journal articl

    シンソウ ガクシュウ ニ モトズク IMU デッド レコニング オ モチイタ スイチュウ オドメトリ システム ノ カイハツ

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    奈良先端科学技術大学院大学修士(工学)master thesi

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