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      • Cooling control based on model predictive control using temperature information of IT equipment for modular data center utilizing fresh-air

        Masatoshi Ogawa,Hiroshi Endo,Hiroyuki Fukuda,Hiroyoshi Kodama,Toshio Sugimoto,Takeshi Horie,Tsugito Maruyama,Masao Kondo 제어로봇시스템학회 2013 제어로봇시스템학회 국제학술대회 논문집 Vol.2013 No.10

        A cooling control method based on a model predictive control (MPC) for a modular datacenter utilizing the fresh-air is proposed. The proposed method reduces the total energy consumption of information technology (IT) equipment and cooling facilities in the data center, while considering a relationship between energy-savings and the temperature information of IT equipment. This method based on MPC controls the central processing unit (CPU) temperature in servers by facility fans for cooling. To design the proposed method, it is developed a prediction model that represents the CPU temperature by the revolution speed of facility fans, the fresh-air temperature, utilization of servers, and other factors. Furthermore, the proposed control method is applied to the actual modular data center. The energy consumption of the proposed method is compared with that of a traditional method, which has controlled the temperature difference between the inlet and outlet of the server racks based on proportional integral (PI) control. Actual comparison experiments with traditional method are provided to validate effectiveness of the proposed method. The results show that the proposed method realizes energy-savings of more than 20% compared to the traditional control method in the actual modular datacenter.

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        Evaluation and Prediction of Post-Hepatectomy Liver Failure Using Imaging Techniques: Value of Gadoxetic Acid-Enhanced Magnetic Resonance Imaging

        Sofue Keitaro,Shimada Ryuji,Ueshima Eisuke,Komatsu Shohei,Yamaguchi Takeru,Yabe Shinji,Ueno Yoshiko,Hori Masatoshi,Murakami Takamichi 대한영상의학회 2024 Korean Journal of Radiology Vol.25 No.1

        Despite improvements in operative techniques and perioperative care, post-hepatectomy liver failure (PHLF) remains the most serious cause of morbidity and mortality after surgery, and several risk factors have been identified to predict PHLF. Although volumetric assessment using imaging contributes to surgical simulation by estimating the function of future liver remnants in predicting PHLF, liver function is assumed to be homogeneous throughout the liver. The combination of volumetric and functional analyses may be more useful for an accurate evaluation of liver function and prediction of PHLF than only volumetric analysis. Gadoxetic acid is a hepatocyte-specific magnetic resonance (MR) contrast agent that is taken up by hepatocytes via the OATP1 transporter after intravenous administration. Gadoxetic acid-enhanced MR imaging (MRI) offers information regarding both global and regional functions, leading to a more precise evaluation even in cases with heterogeneous liver function. Various indices, including signal intensity-based methods and MR relaxometry, have been proposed for the estimation of liver function and prediction of PHLF using gadoxetic acid-enhanced MRI. Recent developments in MR techniques, including high-resolution hepatobiliary phase images using deep learning image reconstruction and whole-liver T1 map acquisition, have enabled a more detailed and accurate estimation of liver function in gadoxetic acid-enhanced MRI.

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