Optimization of a Heat Exchange System in a Process Plant

The purpose of this study is to propose an optimization procedure which is applicable to the optimization of the heat exchange system. Optimization of a heat exchange system is studied as a three stage problem: optimization of the heat exchangers, optimization of a heat exchange system for a fixed system configuration, and optimal synthesis of a heat exchange system. The Fibonacci search technique is used for the optimum design of a water cooler. The modified simplex method is used for the optimization of a heat exchanger system for a fixed system configuration. Optimal synthesis of the heat exchange system is developed by graphical analysis of a temperature-enthalpy flow rate diagram and a temperature-heat capacity flow rate diagram.Chemical Engineerin

Prediction of novel synthetic pathways for the production of desired chemicals

<p>Abstract</p> <p>Background</p> <p>There have been several methods developed for the prediction of synthetic metabolic pathways leading to the production of desired chemicals. In these approaches, novel pathways were predicted based on chemical structure changes, enzymatic information, and/or reaction mechanisms, but the approaches generating a huge number of predicted results are difficult to be applied to real experiments. Also, some of these methods focus on specific pathways, and thus are limited to expansion to the whole metabolism.</p> <p>Results</p> <p>In the present study, we propose a system framework employing a retrosynthesis model with a prioritization scoring algorithm. This new strategy allows deducing the novel promising pathways for the synthesis of a desired chemical together with information on enzymes involved based on structural changes and reaction mechanisms present in the system database. The prioritization scoring algorithm employing Tanimoto coefficient and group contribution method allows examination of structurally qualified pathways to recognize which pathway is more appropriate. In addition, new concepts of binding site covalence, estimation of pathway distance and organism specificity were taken into account to identify the best synthetic pathway. Parameters of these factors can be evolutionarily optimized when a newly proven synthetic pathway is registered. As the proofs of concept, the novel synthetic pathways for the production of isobutanol, 3-hydroxypropionate, and butyryl-CoA were predicted. The prediction shows a high reliability, in which experimentally verified synthetic pathways were listed within the top 0.089% of the identified pathway candidates.</p> <p>Conclusions</p> <p>It is expected that the system framework developed in this study would be useful for the <it>in silico </it>design of novel metabolic pathways to be employed for the efficient production of chemicals, fuels and materials.</p

DisCoHead: Audio-and-Video-Driven Talking Head Generation by Disentangled Control of Head Pose and Facial Expressions

For realistic talking head generation, creating natural head motion while maintaining accurate lip synchronization is essential. To fulfill this challenging task, we propose DisCoHead, a novel method to disentangle and control head pose and facial expressions without supervision. DisCoHead uses a single geometric transformation as a bottleneck to isolate and extract head motion from a head-driving video. Either an affine or a thin-plate spline transformation can be used and both work well as geometric bottlenecks. We enhance the efficiency of DisCoHead by integrating a dense motion estimator and the encoder of a generator which are originally separate modules. Taking a step further, we also propose a neural mix approach where dense motion is estimated and applied implicitly by the encoder. After applying the disentangled head motion to a source identity, DisCoHead controls the mouth region according to speech audio, and it blinks eyes and moves eyebrows following a separate driving video of the eye region, via the weight modulation of convolutional neural networks. The experiments using multiple datasets show that DisCoHead successfully generates realistic audio-and-video-driven talking heads and outperforms state-of-the-art methods. Project page: https://deepbrainai-research.github.io/discohead/Comment: Accepted to ICASSP 202

Necrotizing sialometaplasia: a malignant masquerade but questionable precancerous lesion, report of four cases

Abstract Background Necrotizing sialometaplasia (NSM) is an extremely rare benign lesion with an uncertain pathogenesis. The differential diagnosis of this lesion is challenging due to little familiarity with this entity and histologic similarity with carcinomas, especially mucoepidermoid carcinoma (MEC). The purpose of this study is to raise awareness about NSM, which is often overlooked or misdiagnosed as malignancy in a small biopsy. Methods We reviewed all biopsy materials taken from the oral cavity in a single institution in Korea from 2012 to 2018 and found 4 cases of NSM out of 726. Clinicopathologic characteristics and comparison with other lesions were discussed. Results Unlike previous reports, patients in our series were relatively young, and NSM was not related to smoking and not associated with malignancies, although one patient was misdiagnosed with MEC on the basis of the initial biopsy. High-grade squamous dysplasia was observed in one patient; however, all four patients showed excellent prognoses without further management. Conclusions A conservative approach is recommendable for necrotizing lesions of the palate in young adults to avoid unnecessary treatment. However, careful monitoring is also required due to uncertainty of premalignant potential

The way forward

The attached file contains files from a presentation that was part of the panel disccussion "Condensed Matter Nuclear Science - The Way Forward" at the ICCF 18. The panel will explore the problems and prospects of the future course of the CMNS field in the various countries, emphasizing the importance of applying established scientific methodology to understand the intriguing anomalous nuclear phenomena

234 Genome Informatics 15(2): 234–243 (2004) Knowledge Representation Model for Systems-Level Analysis of Signal Transduction Networks

A Petri-net based model for knowledge representation has been developed to describe as explicitly and formally as possible the molecular mechanisms of cell signaling and their pathological implications. A conceptual framework has been established for reconstructing and analyzing signal transduction networks on the basis of the formal representation. Such a conceptual framework renders it possible to qualitatively understand the cell signaling behavior at systems-level. The mechanisms of the complex signaling network are explored by applying the established framework to the signal transduction induced by potent proinflammatory cytokines, IL-1β and TNF-α The corresponding expert-knowledge network is constructed to evaluate its mechanisms in detail. This strategy should be useful in drug target discovery and its validation