Generative Model for Constructing Reaction Path from Initial to Final States

Mapping out reaction pathways and their corresponding activation barriers is a significant aspect of molecular simulation. Given their inherent complexity and nonlinearity, even generating a initial guess of these paths remains a challenging problem. Presented in this paper is an innovative approach that utilizes neural networks to generate initial guess for these reaction pathways. The proposed method is initiated by inputting the coordinates of the initial state, followed by progressive alterations to its structure. This iterative process culminates in the generation of the approximate representation of the reaction path and the coordinates of the final state. The application of this method extends to complex reaction pathways illustrated by organic reactions. Training was executed on the Transition1x dataset, an organic reaction pathway dataset. The results revealed generation of reactions that bore substantial similarities with the corresponding test data. The method's flexibility allows for reactions to be generated either to conform to predetermined conditions or in a randomized manner

Si及びSiCの酸化のダイナミクスを再現する電荷移動型原子間ポテンシャルの開発と酸化メカニズムの解明

学位の種別: 課程博士審査委員会委員 : （主査）東京大学教授 泉 聡志, 東京大学特任教授 酒井 信介, 東京大学教授 吉川 暢宏, 東京大学准教授 梅野 宜崇, 東京大学准教授 澁田 靖University of Tokyo(東京大学

Acupuncture for attention deficit hyperactivity disorder (ADHD): study protocol for a randomised controlled trial

<p>Abstract</p> <p>Background</p> <p>Attention-deficit/hyperactivity disorder (ADHD) is a common neuro-psychiatric problem, affecting 7-9% of children. Pharmacological interventions are widely used with behavioral treatments in ADHD. Still, the origin of ADHD is unclear, limiting pharmacological effectiveness and making adverse effects common. The use of complementary and alternative medicine (CAM) has increased, especially for developmental and behavioral disorders, such as ADHD. CAM is used by 60-65% of parents of children with ADHD to relieve ADHD-associated symptoms and to avoid the side effects of conventional medication. Acupuncture has been widely used to treat patients with ADHD, but the available evidence of its effectiveness is insufficient. Our aim was to evaluate the effectiveness and safety of acupuncture in patients (both and each treatment naive and conventional therapy children) with ADHD (any subtype) compared to the waitlist control.</p> <p>Methods/Design</p> <p>This study is a waitlist controlled open trial. We used a computer generated randomization scheme. This randomised, controlled trial had two parallel arms (acupuncture, and waitlist group). Each arm consisted of 40 participants. The acupuncture group received acupuncture treatment two times per week for a total of 12 sessions over 6 weeks. Post-treatment follow-up was performed 3 weeks later to complement the 12 acupuncture sessions. Participants in the waitlist group did not receive acupuncture treatments during the first six weeks but were only required to be assessed. After 6 weeks, the same treatments given to the acupuncture group were provided to the waitlist group. The primary outcome of this trial included differences in Korean version of ADHD-Rating Scale (K-ADHD-RS) before randomization, 3 weeks and 6 weeks after randomization, and 3 weeks after completing the treatment.</p> <p>Discussion</p> <p>Subjective measurements, like K-ADHD-RS, are commonly used in ADHD. Although these measurements have adequate reliability and validity, lack of objective assessment in ADHD may lead to some disputes, like parental placebo effects. More objective measurements, like Computerized Neurocognitive function Test (CNT) in this study, are needed in ADHD trials. Furthermore, this trial will provide evidence for the effectiveness of acupuncture as a treatment for ADHD.</p> <p>Trial Registration</p> <p>Clinical Research Information Service (CRiS) KCT0000019</p

pfnet-research/torch-dftd: v0.4.0 release

&lt;p&gt;This is the release note of v0.4.0.&lt;/p&gt; &lt;h1&gt;Highlights&lt;/h1&gt; &lt;ul&gt; &lt;li&gt;Proper ONNX export, and optimizing peak memory usage and execution speed on some ONNX inference engine&lt;ul&gt; &lt;li&gt;Split c6 computation to reduce peak memory usage #17&lt;/li&gt; &lt;li&gt;Fix tracing batch size #18&lt;/li&gt; &lt;li&gt;Reduce Gather op when ONNX-exported #20&lt;/li&gt; &lt;/ul&gt; &lt;/li&gt; &lt;/ul&gt; &lt;h1&gt;Others&lt;/h1&gt; &lt;ul&gt; &lt;li&gt;Update CI #19&lt;/li&gt; &lt;/ul&gt

High-throughput investigation of stability and Li diffusion of doped solid electrolytes via neural network potential without configurational knowledge

Abstract Solid electrolytes hold substantial promise as vital components of all-solid-state batteries. Enhancing their performance necessitates simultaneous improvements in their stability and lithium conductivity. These properties can be calculated using first-principles simulations, provided that the crystal structure of the material and the diffusion pathway through the material are known. However, solid electrolytes typically incorporate dopants to enhance their properties, necessitating the optimization of the dopant configuration for the simulations. Yet, performing such calculations via the first-principles approach is so costly that existing approaches usually rely on predetermined dopant configurations informed by existing knowledge or are limited to systems doped with only a few atoms. The proposed method enables the optimization of the dopant configuration with the support of neural network potential (NNP). Our approach entails the use of molecular dynamics to analyze the diffusion after the optimization of the dopant configuration. The application of our approach to Li $${_{10}}$$ 10 MP $${_{2}}$$ 2 S $${_{12-x}}$$ 12 - x O $${_{x}}$$ x (M = Ge, Si, or Sn) reproduce the experimental results well. Furthermore, analysis of the lithium diffusion pathways suggests that the activation energy of diffusion undergoes a percolation transition. This study demonstrates the effectiveness of NNPs in the systematic exploration of solid electrolytes