With the wide application of the Internet and smart systems, data centers (DCs) have become a hot spot of global concern. The energy saving for data centers is at the core of the related works. The thermal performance of a data center directly affects its total energy consumption, as cooling consumption accounts for nearly 50% of total energy consumption. Superior power distribution is a reliable method to improve the thermal performance of DCs. Therefore, analyzing the effects of different power distribution on thermal performance is a challenge for DCs. This paper analyzes the thermal performance numerically and experimentally in DCs with different power distribution. First, it uses Fluent simulate the temperature distribution and flow field distribution in the room, taking the cloud computing room as the research object. Then, it summarizes a formula based on the computing power distribution in a certain range by the numerical and experimental analysis. Finally, it calculates an optimal cooling power by analyzing the cooling power distribution. The results shows that it reduces the maximum temperature difference between the highest temperature of the cabinet from 5-7k to within 1.2k. In addition, the cooling energy consumption is reduced by more than 5%.

This paper proposes to apply a microfluidic chip combining DSC, DTA, and PCR-like functions for studying synthesis and selection of precursors of the genetic code carriers at hydrothermal conditions including those in natural high frequency fields (such as magnetosphere emission, atmospherics, auroras and lightings).

Heat transfer fluids (HTFs) are critical in numerous industrial processes, enabling efficient heat exchange and precise temperature control. HTF degradation, primarily from thermal cracking and oxidation, negatively impacts system performance, reducing fluid lifespan and increasing operational costs, thus necessitating regular monitoring and proactive management. This review assesses optimal sampling frequencies for organic and synthetic HTFs, considering degradation mechanisms, relevant analytical parameters, and the economic advantages of proactive monitoring. The objective of this review is to examine HTF degradation mechanisms, compare organic and synthetic fluid properties and their impact on sampling frequency, and discuss strategies for optimising system performance and extending fluid life through effective HTF condition management. The article highlights the importance of fluid management, including appropriate fluid selection, to optimise system and fluid health, which is crucial for maximising their lifespans, ensuring safe operation, and minimising costs.

This document outlines the advancements in AI- accelerated frame generation utilizing Neural Processing Units (NPU) in mobile devices. The integration of NPU technology enhances the processing efficiency of mobile graphics, enabling real-time frame generation that significantly improves video and image quality. By leveraging specialized hardware designed for AI computations, the system reduces latency and optimizes power consumption, making it ideal for demanding applications such as gaming and augmented reality. This paper discusses the underlying architecture of NPUs, their role in accelerating frame generation, and the potential impacts on user experience in mobile environments. The findings illustrate how NPU-driven solutions can transform mobile graphics, offering a more immersive and responsive experience while efficiently managing resources.

This paper presents a numerical method for solving a nonlinear age-structured population model based on a set of piecewise constant orthogonal functions. The block-pulse functions (BPFs) method is applied to determine the numerical solution of a non-classic type of partial differential equation with an integral boundary condition. BPFs duo to the simple structure can efficiently approximate the solution of systems with local or non-local boundary conditions. Numerical results reveal the accuracy of the proposed method even for the long term simulations.

In this study, a computational fluid dynamics (CFD) model is developed for a radio frequency (RF) plasma system designed for powder spheroidization. The electric field is generated analytically by solving the RF coil system, and then the resulting equations are implemented as user-defined functions (UDF) to the CFD model. UDF codes were created and defined in the Fluent program to generate RF plasma. Electromagnetic fields and fluid flow have been modelled in numerical analysis studies, and temperature and velocity distributions were obtained. The effect of this plasma environment on titanium particle temperature is investigated using various particle-feeding gas flow rates. As a result, it is observed that an optimal powder-feeding rate could be determined. It is seen that high particle velocities prevent the attainment of the necessary temperature for melting, while low velocities may cause the temperature to exceed the boiling point. These results conclude that the feeding gas flow rate could be determined for a specific powder size range to obtain the powder temperatures within the melting and boiling temperatures.