Effect of supply air temperature on air distribution in a room with radiant heating and mechanical ventilation

The present study focused on the effect of supply air temperature on air distribution in a room with floor heating (FH) or ceiling heating (CH) and mixing ventilation (MV) or displacement ventilation (DV). The vertical distribution of airtemperature and velocity in the occupied zone and the horizontal distribution of containment concentration in the breathing zone were measured as the supply air temperature ranged from 15.0°C (59°F)to 19.0°C (66.2°F). The results showed that the vertical air temperature differences were less than 0.3°C (32.5°F) with FH+MV or CH+MV and between 1.9°C (35.4°F) and 4.2°C (39.6°F) with FH+DV or CH+DV. The turbulence intensity varied from 12.5% to 15.5% with FH+MV or CH+MV and from 6.0% to 10.8% with FH+DV or CH+DV. The air-distribution effectiveness was close to 1.0 with FH+MV or CH+MV and between 1.06 and 1.16 with FH+DV or CH+DV. The results in this paper are relevant to the designand control of the hybrid systems with radiant heating systems and mechanical ventilation systems

A miR-137-XIAP axis contributes to the sensitivity of TRAIL-induced cell death in glioblastoma

Glioblastoma (GBM) is the most lethal primary brain tumor in the central nervous system with limited therapeutic strategies to prolong the survival rate in clinic. TNF-related apoptosis-inducing ligand (TRAIL)-based strategy has been demonstrated to induce cell death in an extensive spectrum of tumor cells, including GBM, while a considerable proportion of malignant cells are resistant to TRAIL-induced apoptosis. MiR-137 is highly expressed in the brain, but significantly decreases with advanced progression of GBM. However, the functional link between miR-137 and TRAIL-induced apoptosis in GBM cells has not been established. Here, GBM cells were transfected with miR-137, and gene expression levels were examined by qRT-PCR and western blot. Apoptotic cells were measured by Annexin-V staining and TUNEL assay. Our data showed that miR-137 sensitizes GBM cells to the TRAIL-mediated apoptosis. Mechanistically, we identified that XIAP is a bona fide target of miR-137, which is essential for miR-137-regulated sensitivity of TRAIL-induced cell death in GBM cells. Finally, in a xenograft model, combined utilization of miR-137 and TRAIL potently suppresses tumor growth in vivo. Collectively, we demonstrate that a miR-137-XIAP axis is required for the sensitivity of TRAIL-induced cell death and shed a light on the avenue for the treatment of GBM

Research on High Precision Angle Measurement and Compensation Technology Based on Circular Grating

Abstract In this paper, the angle measurement method of high-precision circular grating is studied. The principle analysis of circular grating angle measurement, the principle analysis of multi reading head, and the design of rotary servo control system are carried out. After analyzing the error model of circular grating angle measurement, the research based on harmonic compensation model is carried out respectively. Aiming at the problem of zero crossing oscillation of compensation algorithm, the piecewise compensation strategy is designed, which fully demonstrates the application value of circular grating angle measurement method in high-precision angle measurement system.</jats:p

Sequence-to-Sequence Prescription Recommendation Model Based on Chinese Medicine Keywords

Taking the traditional Chinese medicine prescription recommendation task as an entry point, a keyword-aware model for traditional Chinese medicine based on a sequence-to-sequence framework is proposed. This is done to address the problems of existing prescription recommendation models that ignore domain knowledge information, such as herb compatibility, which can lead to poor recommendation effects and deviation of recommended prescriptions from the reality. A keyword-aware network is added to the symptom sequence information mining part to expand the multi-branch structure of the model, and prescription monarch medicine serves as the keyword embedding vector to mine the prescription dispensing information to enhance the model's ability to represent the deep knowledge features and improve the recommendation quality. A cross-propagation mechanism is proposed to reduce the feature dimensions that are over-attended in the attention accumulation process, ensuring that the accumulation result can focus on the unattended region, and reducing the probability of recommended prescription repetition. A hybrid soft loss function is also proposed to further improve the results by increasing the gap between different distributions and penalizing repeated attention to the same location behavior. The model is tested on two public clinical traditional Chinese medicine prescription datasets. The experimental results show that, compared with other deep learning models such as TPGen and Herb-Know, the model can effectively enhance the quality of recommended prescriptions and improve the repetition problem in the model generation process. It also improves the quality of recommended prescriptions compared with the best baseline model in terms of Precision, Recall, and F1 value by 8, 5, and 6 percentage points, respectively. In addition, the results of ablation experiments demonstrate the effectiveness of the modules