Improving the indoor thermal environment with ceiling radiant terminals

A CFD (computational Fluid Dynamics) simulation model of the porous ceiling radiant air-conditioning system was established to study the influence of the ceiling temperature and envelope temperature (including the temperature of the walls and the floor of a room) on the thermal environment in the room equipped with such a system. The results showed that, for the summer condition, higher ceiling temperatures would result in higher indoor air temperature and higher Predicted Percentage Dissatisfied (PPD), which meant potential discomfort of occupants in the room. For the winter condition, however, a higher ceiling temperature within 28°C would result in a lower PPD, thus improved the thermal comfort. Considering the energy-conservation, the thermal comfort could be assured if the ceiling temperature was not more than 28°C. As for the effect of envelope temperature, the result showed that the increase in the envelope temperature during summer could result in a higher indoor air temperature, but the thermal comfort of occupants could still be ensured under such condition. Considering both the thermal comfort and the energyconservation, a ceiling temperature of 18°C (underside surface temperature of the ceiling) and an envelope temperature between 26°C and 32°C were proved appropriate for the summer. Similarly, based on the simulation results, a ceiling temperature of 26°C, and an envelope temperature between 8°C and 11°C were found appropriate for the winter. The results indicated that for the porous ceiling radiant air-conditioning system, ceiling temperature should be controlled to increase the ratio of radiant heat transfer in the summer, and the envelope temperature should be lowered to improve the energy-conservation of the system. In the winter, the heat transfer by radiation of the porous ceiling would account for a larger ratio, therefore the system showed good heating capacity and energyconservation performance in winter.publishedVersio

Acoustic Scene Clustering Using Joint Optimization of Deep Embedding Learning and Clustering Iteration

Recent efforts have been made on acoustic scene classification in the audio signal processing community. In contrast, few studies have been conducted on acoustic scene clustering, which is a newly emerging problem. Acoustic scene clustering aims at merging the audio recordings of the same class of acoustic scene into a single cluster without using prior information and training classifiers. In this study, we propose a method for acoustic scene clustering that jointly optimizes the procedures of feature learning and clustering iteration. In the proposed method, the learned feature is a deep embedding that is extracted from a deep convolutional neural network (CNN), while the clustering algorithm is the agglomerative hierarchical clustering (AHC). We formulate a unified loss function for integrating and optimizing these two procedures. Various features and methods are compared. The experimental results demonstrate that the proposed method outperforms other unsupervised methods in terms of the normalized mutual information and the clustering accuracy. In addition, the deep embedding outperforms many state-of-the-art features.Comment: 9 pages, 6 figures, 11 tables. Accepted for publication in IEEE TM

Data-Driven Modeling of Landau Damping by Physics-Informed Neural Networks

Kinetic approaches are generally accurate in dealing with microscale plasma physics problems but are computationally expensive for large-scale or multiscale systems. One of the long-standing problems in plasma physics is the integration of kinetic physics into fluid models, which is often achieved through sophisticated analytical closure terms. In this study, we successfully construct a multi-moment fluid model with an implicit fluid closure included in the neural network using machine learning. The multi-moment fluid model is trained with a small fraction of sparsely sampled data from kinetic simulations of Landau damping, using the physics-informed neural network (PINN) and the gradient-enhanced physics-informed neural network (gPINN). The multi-moment fluid model constructed using either PINN or gPINN reproduces the time evolution of the electric field energy, including its damping rate, and the plasma dynamics from the kinetic simulations. For the first time, we introduce a new variant of the gPINN architecture, namely, gPINN$p$ to capture the Landau damping process. Instead of including the gradients of all the equation residuals, gPINN$p$ only adds the gradient of the pressure equation residual as one additional constraint. Among the three approaches, the gPINN$p$-constructed multi-moment fluid model offers the most accurate results. This work sheds new light on the accurate and efficient modeling of large-scale systems, which can be extended to complex multiscale laboratory, space, and astrophysical plasma physics problems.Comment: 11 pages, 7 figure

Arp2/3 Complex Regulates Asymmetric Division and Cytokinesis in Mouse Oocytes

Mammalian oocyte meiotic maturation involves oocyte polarization and a unique asymmetric division, but until now, the underlying mechanisms have been poorly understood. Arp2/3 complex has been shown to regulate actin nucleation and is widely involved in a diverse range of processes such as cell locomotion, phagocytosis and the establishment of cell polarity. Whether Arp2/3 complex participates in oocyte polarization and asymmetric division is unknown. The present study investigated the expression and functions of Arp2/3 complex during mouse oocyte meiotic maturation. Immunofluorescent staining showed that the Arp2/3 complex was restricted to the cortex, with a thickened cap above the meiotic apparatus, and that this localization pattern was depended on actin. Disruption of Arp2/3 complex by a newly-found specific inhibitor CK666, as well as by Arpc2 and Arpc3 RNAi, resulted in a range of effects. These included the failure of asymmetric division, spindle migration, and the formation and completion of oocyte cytokinesis. The formation of the actin cap and cortical granule-free domain (CGFD) was also disrupted, which further confirmed the disruption of spindle migration. Our data suggest that the Arp2/3 complex probably regulates oocyte polarization through its effect on spindle migration, asymmetric division and cytokinesis during mouse oocyte meiotic maturation

Remote control of gene function by local translation

The subcellular position of a protein is a key determinant of its function. Mounting evidence indicates that RNA localization, where specific mRNAs are transported subcellularly and subsequently translated in response to localized signals, is an evolutionarily conserved mechanism to control protein localization. On-site synthesis confers novel signaling properties to a protein and helps to maintain local proteome homeostasis. Local translation plays particularly important roles in distal neuronal compartments, and dysregulated RNA localization and translation cause defects in neuronal wiring and survival. Here, we discuss key findings in this area and possible implications of this adaptable and swift mechanism for spatial control of gene function

Research on performance Evaluation method to promote sustainable development of opening government affairs

Open government affairs (OGA) play an important role in promoting national governance system and capacity. In order to realize an open and efficient government, it is necessary to scientifically evaluate the performance of government. The effect of OGA can be improved continuously through the feedback from evaluation, which is beneficial for the sustainable development of OGA. However, with the continuous development of OGA, the existing methods of evaluation are faced with such problems as poor-timeliness, high-cost and subjective uncertainty, which are difficult to satisfy the demands of performance evaluation of OGA. Therefore, this paper puts forward a performance evaluation method based on T-S fuzzy neural network. Our method has a strong ability of data processing, which can simplify the work flow. The T-S fuzzy neural network was trained and tested through using the performance evaluation data of all districts and counties in Shandong Province, China. Finally, the evaluation results offered by our method are highly accurate. Hence, our method is suitable for the performance evaluation of OGA, it can continuously enhance the improvement of government’s performance management and capacity building so as to promote the sustainable development of OGA

Recent Advances in Nanoparticle-Based Optical Sensors for Detection of Pesticide Residues in Soil

The excessive and unreasonable use of pesticides has adversely affected the environment and human health. The soil, one of the most critical natural resources supporting human survival and development, accumulates large amounts of pesticide residues. Compared to traditional spectrophotometry analytical methods, nanoparticle-based sensors stand out for their simplicity of operation as well as their high sensitivity and low detection limits. In this review, we focus primarily on the functions that various nanoparticles have and how they can be used to detect various pesticide residues in soil. A detailed discussion was conducted on the properties of nanoparticles, including their color changeability, Raman enhancement, fluorescence enhancement and quenching, and catalysis. We have also systematically reviewed the methodology for detecting insecticides, herbicides, and fungicides in soil by using nanoparticles

Improving Output Power of InGaN Laser Diode Using Asymmetric In0.15Ga0.85N/In0.02Ga0.98N Multiple Quantum Wells

Herein, the optical field distribution and electrical property improvements of the InGaN laser diode with an emission wavelength around 416 nm are theoretically investigated by adjusting the relative thickness of the first or last barrier layer in the three In0.15Ga0.85N/In0.02Ga0.98N quantum wells, which is achieved with the simulation program Crosslight. It was found that the thickness of the first or last InGaN barrier has strong effects on the threshold currents and output powers of the laser diodes. The optimal thickness of the first quantum barrier layer (FQB) and last quantum barrier layer (LQB) were found to be 225 nm and 300 nm, respectively. The thickness of LQB layer predominantly affects the output power compared to that of the FQB layer, and the highest output power achieved 3.87 times that of the reference structure (symmetric quantum well), which is attributed to reduced optical absorption loss as well as the reduced vertical electron leakage current leaking from the quantum wells to the p-type region. Our result proves that an appropriate LQB layer thickness is advantageous for achieving low threshold current and high output power lasers

Improving the indoor thermal environment with ceiling radiant terminals

A CFD (computational Fluid Dynamics) simulation model of the porous ceiling radiant air-conditioning system was established to study the influence of the ceiling temperature and envelope temperature (including the temperature of the walls and the floor of a room) on the thermal environment in the room equipped with such a system. The results showed that, for the summer condition, higher ceiling temperatures would result in higher indoor air temperature and higher Predicted Percentage Dissatisfied (PPD), which meant potential discomfort of occupants in the room. For the winter condition, however, a higher ceiling temperature within 28°C would result in a lower PPD, thus improved the thermal comfort. Considering the energy-conservation, the thermal comfort could be assured if the ceiling temperature was not more than 28°C. As for the effect of envelope temperature, the result showed that the increase in the envelope temperature during summer could result in a higher indoor air temperature, but the thermal comfort of occupants could still be ensured under such condition. Considering both the thermal comfort and the energyconservation, a ceiling temperature of 18°C (underside surface temperature of the ceiling) and an envelope temperature between 26°C and 32°C were proved appropriate for the summer. Similarly, based on the simulation results, a ceiling temperature of 26°C, and an envelope temperature between 8°C and 11°C were found appropriate for the winter. The results indicated that for the porous ceiling radiant air-conditioning system, ceiling temperature should be controlled to increase the ratio of radiant heat transfer in the summer, and the envelope temperature should be lowered to improve the energy-conservation of the system. In the winter, the heat transfer by radiation of the porous ceiling would account for a larger ratio, therefore the system showed good heating capacity and energyconservation performance in winter