Study on the methods for predicting the performance of a hybrid solar-assisted ground-source heat pump system

It is critical to find suitable setting parameters for designing a hybrid solar-assisted ground-source heat pump system in the practical engineering application, but the heat pump performance is unpredictable after many years of operation. This paper used 2000 sets of performance data collected from solar-assisted GSHP systems that keep operating over 20 years to simulate long term used heat pump with a professional software called GeoStar. Adopted the classification and regression tree (CART) method, the design of solar energy collector areas can be predicted. The multi-linear regression is also utilized to predict average monthly per meter borehole heat exchange. Seasonal factor decomposition and exponential smoothing are used to analyze the average monthly temperature of the circulating fluid, circulating fluid inlet and outlet temperatures of the heat pump after 20 years when we perform the time series prediction. Experimental results demonstrate that CART, multi-linear regression, seasonal factor decomposition and exponential smoothing are promising for practical applications

Research on control methods of roof radiant cooling system

Taking the capillary ceiling radiation air conditioning system in radiation cooling Laboratory of comprehensive experimental building in Shandong Jianzhu University as an example, research the two different control methods which are room temperature control and water temperature control. The roof cooling model was established by using TRNSYS simulation software, two typical summer days were selected to explore the stability of the room temperature and the supply and return water temperature, research the comfort of human body and system energy consumption under two control methods. The results show that the indoor temperature of the two control methods can be stable at the design temperature of 27℃ under outdoor high temperature environment in summer. When the maximum outdoor temperature does not exceed 30℃, the temperature stability of the room temperature control method is better, the comfort of the two control methods can meet the requirements, but the water temperature control method is more comfortable. The room temperature control method is 20% ~ 25% energy saving than the water temperature control method in the two typical selected days, and is 40.5% energy saving in the whole cooling season

Research on the cooling characteristics in building interior zones using displacement ventilation system

The outdoor low temperature fresh air can be used as a free cold source to eliminate waste heat for the building interior zones during the transition season and winter. This paper takes a project in Hunan as an example, and the project building interior zones is 25m×7m×3.9m(L×W×H). Using Fluent software to simulate the temperature field and velocity field both the interior and exterior zones of the engineering offices. The simulation results show that using the displacement ventilation system to take the outdoor air into inner rooms not only cooling but also improving the air quality and adding comfort. According to the simulation results and outdoor air dry bulb temperature and enthalpy values, the h − d diagram is divided into three air conditioning conditions (summer, winter, transition season), and three different operation adjustment methods have been proposed corresponding to each air conditioning condition, which will reduce the energy consumption of air conditioning system

High CD8+tumor-infiltrating lymphocytes indicate severe exhaustion and poor prognosis in angioimmunoblastic T-cell lymphoma

BackgroundExhaustion of CD8+ tumor-infiltrating lymphocytes (TILs), characterized by the overexpression of immune checkpoints (IC), is a major impediment to anti-tumor immunity. However, the exhaustion status of CD8+TILs in angioimmunoblastic T cell lymphoma (AITL) remains unclear. Therefore, we aimed to elucidate the exhaustion status of CD8+TILs in AITL and its influence on prognosis.MethodsThe correlation between CD8+TILs and IC expression in AITL was analyzed using single-cell RNA sequencing (n = 2), flow cytometry (n = 20), and RNA sequencing (n = 20). Biological changes related to CD8+TILs exhaustion at different cytotoxic T lymphocyte (CTL) levels (mean expression levels of CD8A, CD8B, GZMA, GZMB, and PRF1) in AITL were evaluated using RNA sequencing (n = 20) and further validated using the GEO dataset (n = 51). The impact of CD8 protein expression and CTL levels on patient prognosis was analyzed using flow cytometry and RNA sequencing, respectively.ResultsOur findings demonstrated that the higher the infiltration of CD8+TILs, the higher was the proportion of exhausted CD8+TILs characterized by the overexpression of multiple IC. This was accompanied by extensive exhaustion-related biological changes, which suggested severe exhaustion in CD8+TILs and may be one of the main reasons for the poor prognosis of patients with high CD8+TILs and CTL.ConclusionOur study comprehensively reveals the exhaustion status of CD8+TILs and their potential negative impact on AITL prognosis, which facilitates further mechanistic studies and is valuable for guiding immunotherapy strategies

Impact of the Storm Sewer Network Complexity on Flood Simulations According to the Stroke Scaling Method

For urban watersheds, the storm sewer network provides indispensable data for flood modeling but often needs to be simplified to balance the conflict between the large amount of data and current computing power. The sensitivity of a flood simulation to the data precision of a storm sewer network needs to be explored to develop reasonable generalization strategies. In this study, the impact of using the stroke scaling method to generalize a storm sewer network on a flood simulation was analyzed in terms of the total inflow of the outfalls and flood results. The results of the three study basins showed that different complexities of a sewer network did not have a significant effect on the outfall’s total inflow for an area with a single drainage system but did for an area with multiple drainage systems. In addition, serious flooding was mainly distributed at the backbone pipes, which can be identified with the simplified sewer network. Several effective generalization strategies were developed for sewer networks that consider the distribution characteristics of the drainage system and application requirements. This study is theoretically important for better understanding the data sensitivity of flood modeling and simulation and practically important for improving the modeling efficiency and the accuracy of urban flood simulation

An uncertainty investigation of RCM downscaling ratios in nonstationary extreme rainfall IDF curves

Designed for rainstorms and flooding, hydrosystems are largely based on local rainfall Intensity–Duration–Frequency (IDF) curves which include nonstationary components accounting for climate variability. IDF curves are commonly calculated using downscaling outputs from General Circulation Models (GCMs) or Regional Circulation Models (RCMs). However, the downscaling procedures used in most studies are based on one specific time scale (e.g., 1 h) and generally ignore scale-driven uncertainty. This study analyzes the uncertainties in IDF curves stemming from RCM downscaling ratios for four representative weather stations in the United Kingdom. We constructed a series of IDF curves using distribution-based scaling bias-correction technology and a statistical downscaling method to explore the scale-driven uncertainty of IDF curves. The results revealed considerable scale-induced uncertainty of IDF curves for short durations and long return periods; however, there was no clear correlation with the mean storm intensity of the IDF curves of different RCM ensemble members for each duration and return period. The scale-driven uncertainty of IDF curves, which may be propagated or enhanced through hydrometeorological applications, is critical and cannot be ignored in the hydrosystem design process; therefore, a multi-scale method to derive IDF curves must be developed

Long lead-time radar rainfall nowcasting method incorporating atmospheric conditions using long short-term memory networks

High-resolution radar rainfall data have great potential for rainfall predictions up to 6 h ahead (nowcasting); however, conventional extrapolation approaches based on in-built physical assumptions yield poor performance at longer lead times (3–6 h), which limits their operational utility. Moreover, atmospheric factors in radar estimate errors are often ignored. This study proposed a radar rainfall nowcasting method that attempts to achieve accurate nowcasting of 6 h using long short-term memory (LSTM) networks. Atmospheric conditions were considered to reduce radar estimate errors. To build radar nowcasting models based on LSTM networks (LSTM-RN), approximately 11 years of radar, gauge rainfall, and atmospheric data from the UK were obtained. Compared with the models built on optical flow (OF-RN) and random forest (RF-RN), LSTM-RN had the lowest root-mean-square errors (RMSE), highest correlation coefficients (COR), and mean bias errors closest to 0. Furthermore, LSTM-RN showed a growing advantage at longer lead times, with the RMSE decreasing by 17.99% and 7.17% compared with that of OF-RN and RF-RN, respectively. The results also revealed a strong relationship between LSTM-RN performance and weather conditions. This study provides an effective solution for nowcasting radar rainfall at long lead times, which enhances the forecast value and supports practical utility

Strange Quasar Candidates with Abnormal Astrometric Characteristics from Gaia EDR3 and SDSS (SQUAB-II): Optical Identifications

There are some strange quasars with multiple Gaia detections or observed with abnormal astrometric characteristics, such as with large proper motions or significant astrometric noises. Those strange quasars could be potential candidates of quasar-star pairs, dual quasars (DQs), or lensed quasars (LQs). Searching for both DQs and LQs is of great importance in many fields of astrophysics. Here in this work, we select 143 SDSS spectroscopically confirmed quasars that have multiple Gaia EDR3 detections within 1 arcsec of the SDSS quasar' position. We apply several optical identification methods to classify this sample. We firstly exclude 65 quasar-star pairs via their stellar features including their parallaxes and proper motions, stellar features in the SDSS spectra, or via the colour-colour diagram. Based on the spectral-fitting results, we find 2 DQ candidates, one of which presents a double-peaked [O III] emission line feature and the other shows a broad $H_{\beta}$ velocity offset ($\sim$ 870 $km s^{-1}$) relative to the [O III] $\lambda$5007 line. Via the colour difference method, we further find 56 LQ candidates with similar colours in their multiple images. We also cross-match 143 objects with the HST archive and find 19 targets with archival HST images. Our classification results of those 19 targets are mainly consistent with previous works.Comment: 18 pages, 11figures, accepted for publication in MNRA

HMGB1: a double-edged sword and therapeutic target in the female reproductive system

HMGB1 that belongs to the High Mobility Group-box superfamily, is a nonhistone chromatin associated transcription factor. It is present in the nucleus of eukaryotes and can be actively secreted or passively released by kinds of cells. HMGB1 is important for maintaining DNA structure by binding to DNA and histones, protecting it from damage. It also regulates the interaction between histones and DNA, affecting chromatin packaging, and can influence gene expression by promoting nucleosome sliding. And as a DAMP, HMGB1 binding to RAGE and TLRs activates NF-κB, which triggers the expression of downstream genes like IL-18, IL-1β, and TNF-α. HMGB1 is known to be involved in numerous physiological and pathological processes. Recent studies have demonstrated the significance of HMGB1 as DAMPs in the female reproductive system. These findings have shed light on the potential role of HMGB1 in the pathogenesis of diseases in female reproductive system and the possibilities of HMGB1-targeted therapies for treating them. Such therapies can help reduce inflammation and metabolic dysfunction and alleviate the symptoms of reproductive system diseases. Overall, the identification of HMGB1 as a key player in disease of the female reproductive system represents a significant breakthrough in our understanding of these conditions and presents exciting opportunities for the development of novel therapies