Search

Mid-deep geothermal reinjection technology is crucial for the sustainable development of geothermal resources, which has garnered significant attention and rapid growth in recent years. Currently, various geothermal reinjection technologies lag behind, lacking effective integration to address issues like low reinjection rates and thermal breakthrough. This paper reviews the basic principles and development history of mid-deep geothermal reinjection technology, focusing on various technical methods used in the process and analyzing their applicability, advantages, and disadvantages under different geological conditions. It highlights the unique challenges posed by deep geothermal resources, including high temperature, high pressure, high stress, chemical corrosion, and complex geological structures. Additionally, it addresses challenges in equipment selection and durability, system stability and operation safety, environmental impact, and sustainable development. Finally, the paper explores future directions for mid-deep geothermal reinjection technology, highlighting key areas for further research and potential pathways for technological innovation. This comprehensive analysis aims to accelerate the advancement of geothermal reinjection technology, offering essential guidance for the efficient reinjection and sustainable development of geothermal resources.

Chemical kinetics is a branch of physical chemistry that constitutes an essential part of undergraduate education. In general, a complex and expensive experimental apparatus is indispensable for observing the kinetics of a chemical process owing to the continuity of chemical reactions. Thus, intuitive visualization of the chemical kinetics using a simple experimental apparatus is challenging. Herein, a portable flow reactor was designed and used to observe the chemical kinetics of a first-order process. Continuous chemical reactions were visualized via the flow reactor as static patterns with color gradients. The thermochromism of the rhodamine B salicylaldehyde hydrazone zinc(II) complex was visualized via the flow reactor and found to follow first-order kinetics. The color gradients of static reaction patterns were analyzed by comparing them with standard color cards, and the kinetic parameters, such as the reaction rate constants at different temperatures and the activation energy, were determined. By performing this experiment, students can learn about flow chemistry, photochromism, and thermochromism. The interesting experimental process and distinct color changes can hold the students' attention. The two calculation methods can help the students better understand the rate equation of a first-order reaction. The experimental apparatus is low cost and commercially available, which is beneficial for the widespread use of this experiment.

Objective: Cell dysfunction and death induced by lung ischaemia–reperfusion injury (LIRI) are the main causes of death in transplant patients. Activation of the cGAS-STING-induced immune response and death plays a critical role in multiple organ injuries. However, no study has yet investigated the role of the cGAS-STING pathway in LIRI after lung transplantation. Methods: Sprague-Dawley (SD) rats were subjected to left lung transplantation and administered inhibitors of cGAS and STING. The expression of cGAS-STING-TBK1-IRF3, histological injury, pulmonary permeability, and the levels of cytokines and pyroptotic proteins in transplanted lungs were tested. Endothelial cells were subjected to hypoxemia and reoxygenation and treated with inhibitors of cGAS and STING. Mitochondrial DNA (mtDNA), the cGAS-STING axis and cytokine levels in cells, cellular activity and death were evaluated. Moreover, after the administration of deoxyribonuclease (DNase) I, the reoxygenated endothelial cells were also examined for cellular function and inflammatory factor expression. Finally, we administered an agonist of STING and an inhibitor of cathepsin B to the normal endothelium and investigated pyroptosis and pyroptotic proteins. Results: After 24 h of reperfusion, the expression of cGAS-STING-TBK1-IRF3 and pyroptotic proteins was significantly increased, and inhibitors of cGAS or STING ameliorated lung injury and reduced pyroptotic protein levels. In vitro, the inhibition of cGAS and STING reduced the activation of TBK and IRF3 and reduced cellular injury and death. The activation of cGAS-STING and cellular inflammation were suppressed by DNase I. Cathepsin B and NLRP3 were upregulated by an agonist of STING, and an inhibitor of cathepsin B reduced NLRP3 levels. Conclusion: cGAS-STING participated in LIRI by promoting endothelial cell pyroptosis via cathepsin B.

Summary: Background: Ovarian cancer has the highest mortality rate among gynaecological malignancies and is initially screened using ultrasound. Owing to the high complexity of ultrasound images of ovarian masses and the anatomical characteristics of the deep pelvic cavity, subjective assessment requires extensive experience and skill. Therefore, detecting the ovaries and ovarian masses and diagnose ovarian cancer are challenging. In the present study, we aimed to develop an automated deep learning framework, the Ovarian Multi-Task Attention Network (OvaMTA), for ovary and ovarian mass detection, segmentation, and classification, as well as further diagnosis of ovarian masses based on ultrasound screening. Methods: Between June 2020 and May 2022, the OvaMTA model was trained, validated and tested on a training and validation cohort including 6938 images and an internal testing cohort including 1584 images which were recruited from 21 hospitals involving women who underwent ultrasound examinations for ovarian masses. Subsequently, we recruited two external test cohorts from another two hospitals. We obtained 1896 images between February 2024 and April 2024 as image-based external test dataset, and further obtained 159 videos for the video-based external test dataset between April 2024 and May 2024. We developed an artificial intelligence (AI) system (termed OvaMTA) to diagnose ovarian masses using ultrasound screening. It includes two models: an entire image-based segmentation model, OvaMTA-Seg, for ovary detection and a diagnosis model, OvaMTA-Diagnosis, for predicting the pathological type of ovarian mass using image patches cropped by OvaMTA-Seg. The performance of the system was evaluated in one internal and two external validation cohorts, and compared with doctors’ assessments in real-world testing. We recruited eight physicians to assess the real-world data. The value of the system in assisting doctors with diagnosis was also evaluated. Findings: In terms of segmentation, OvaMTA-Seg achieved an average Dice score of 0.887 on the internal test set and 0.819 on the image-based external test set. OvaMTA-Seg also performed well in ovarian mass detection from test images, including healthy ovaries and masses (internal test area under the curve [AUC]: 0.970; external test AUC: 0.877). In terms of classification diagnosis prediction, OvaMTA-Diagnosis demonstrated high performance on image-based internal (AUC: 0.941) and external test sets (AUC: 0.941). In video-based external testing, OvaMTA recognised 159 videos with ovarian masses with AUC of 0.911, and is comparable to the performance of senior radiologists (ACC: 86.2 vs. 88.1, p = 0.50; SEN: 81.8 vs. 88.6, p = 0.16; SPE: 89.2 vs. 87.6, p = 0.68). There was a significant improvement in junior and intermediate radiologists who were assisted by AI compared to those who were not assisted by AI (ACC: 80.8 vs. 75.3, p = 0.00015; SEN: 79.5 vs. 74.6, p = 0.029; SPE: 81.7 vs. 75.8, p = 0.0032). General practitioners assisted by AI achieved an average performance of radiologists (ACC: 82.7 vs. 81.8, p = 0.80; SEN: 84.8 vs. 82.6, p = 0.72; SPE: 81.2 vs. 81.2, p > 0.99). Interpretation: The OvaMTA system based on ultrasound imaging is a simple and practical auxiliary tool for screening for ovarian cancer, with a diagnostic performance comparable to that of senior radiologists. This provides a potential tool for screening ovarian cancer. Funding: This work was supported by the National Natural Science Foundation of China (Grant Nos. 12090020, 82071929, and 12090025) and the R&D project of the Pazhou Lab (Huangpu) (Grant No. 2023K0605).

This paper focuses on the study of the evolutionary mechanism governing the temperature field of geothermal reservoir under low-temperature tailwater reinjection conditions, which is crucial for the sustainable geothermal energy management. With advancing exploitation of geothermal resources deepens, precise understanding of this mechanism becomes paramount for devising effective reinjection strategies, optimizing reservoir utilization, and bolstering the economic viability of geothermal energy development. The article presents a comprehensive review of temperature field evolution across diverse heterogeneous thermal reservoirs under low-temperature tailwater reinjection conditions, and analyzes key factors influencing this evolution. It evaluates existing research methods, highlighting their strengths and limitations. The study identifies gaps in the application of rock seepage and heat transfer theories on a large scale, alongside the need for enhanced accuracy in field test results, particularly regarding computational efficiency of fractured thermal reservoir models under multi-well reinjection conditions. To address these shortcomings, the study proposes conducting large-scale rock seepage and heat transfer experiments, coupled with multi-tracer techniques for field testing, aimed at optimizing fractured thermal reservoir models' computational efficiency under multi-well reinjection conditions. Additionally, it suggests integrating deep learning methods into research endeavors. These initiatives are of significance in deepening the understanding of the evolution process of the temperature field in deep thermal reservoirs and enhancing the sustainability of deep geothermal resource development.

Abstract Led by the National Space Science Center of the Chinese Academy of Sciences, we have built a Chinese dual auroral radar network in northern China, which is called the CN‐DARN. The CN‐DARN consists of three pairs of high‐frequency coherent scattering radar facilities and is one of the key parts of the Chinese Meridian Project Phase II. It has been fully constructed and started trial operations at the end of 2023. The detection range of the radar network extends longitudinally over approximately 9 hr of local times and covers the middle to high latitudes of the entire Asia region above 40°. In this paper, we present the basic design of the CN‐DARN and its preliminary observations of ionospheric irregularities, subauroral polarization streams (SAPSs) and traveling ionospheric disturbances (TIDs). We also investigate its contribution to the ionospheric convection pattern of the Northern Hemisphere derived from Super Dual Auroral Radar Network (SuperDARN) observations. The results indicate that the CN‐DARN provides excellent measurements and better specifications of flows in the Asian sector, improving our understanding of the global‐scale ionospheric convection pattern in the Northern Hemisphere. These encouraging results lead us to believe that the CN‐DARN will play an important role in studies on the evolution of ionospheric irregularities, the characteristics and evolution of SAPSs, the propagation of TIDs, and global‐scale ionospheric convection dynamics.

In this study, the dynamic process of a droplet moving with a substrate until blocked by air flow is investigated experimentally and theoretically. A sequence of experiments has been conducted to investigate the impacts of wetting properties, droplet volumes, air flow velocities, and droplet velocities. The substrate is driven by a linear motion motor to ensure the droplet moves at a certain velocity alongside the substrate. The air flow that is vertically injected from the nozzles toward the substrate is known as an impinging jet. After the air flow impacts the substrate, it will blow horizontally. When the direction of air flow is opposite to that of the droplet movement, a force will be exerted on the surface of the droplet. This action incurs the deformation of the droplet and the cessation of its movement, eventually resulting in an equilibrium state. The droplet shape and motion processes are recorded by a high-speed camera. A mathematical model considering the effect of droplet contact angle, droplet size, droplet moving velocity, and air flow velocity is established in the state of equilibrium. Correlation factors are used in the model for the drag coefficient and air average velocity acting on the droplet. It is found that the air flow rate required to stop the motion of the droplet increases with the droplet moving velocity and the droplet size but reduces with the increase in the static contact angle. The mathematical model, when equipped with suitable correlation factors, exhibits good agreement with experimental data and could potentially be utilized as a predictor of critical velocity for the cessation of the droplet motion.

Cells are the most basic structural and functional unit of living organisms. In recent years, people have paid more attention to cell heterogeneity. In order to characterize the heterogeneity of cells and prevent the life information in an individual cell from being overwhelmed by the average level of the population gained from traditional cell biology research, many new analytical techniques have been developed for single-cell analysis. However, single-cell analysis is extremely challenging due to the minimal cell volume, low content and wide variety of analytes in single cells, some of analytes change rapidly in cells and others may interfere with each other during analysis. Mass spectrometry has gradually become an ideal tool for single-cell analysis due to its high sensitivity, high resolution and high selectivity. In this review, several techniques of single-cell analysis based on mass spectrometry in the recent five years were systematically summarized and discussed including electrospray ionization mass spectrometry (ESI-MS), laser desorption ionization mass spectrometry (LDI-MS), secondary ion mass spectrometry (SIMS) and inductively coupled plasma mass spectrometry (ICP-MS). Finally, this review also looked into future developments of these mass spectrometry-based techniques. With the development of cell biology, the requirement for single-cell analysis technology is increasing as well. In the meanwhile, single-cell analysis, which focuses on studying the mechanisms of cellular and molecular behavior, has aroused more and more attention from various branches of life sciences in recent years. Although higher spatial resolution and detection sensitivity have become the development trends for single-cell mass spectrometry, none of these mass spectrometry-based techniques can be recognized flawless, which means they all have certain flaws to some extent. Consequently, single-cell analysis technology based on mass spectrometry is developing towards methodological diversification. On the one hand, it is of great importance to choose one suitable mass spectrometry-based technique according to the research purpose and actual conditions. On the other hand, it should be also emphasized that different methods can complement each other and jointly provide a more comprehensive analysis environment for single-cell mass spectrometry, thereby improving and innovating existing single-cell analysis techniques based on mass spectrometry. This review will provide insights into better understanding on and development of single-cell analysis by mass spectrometry.

Underground Thermal Energy Storage (UTES) store unstable and non-continuous energy underground, releasing stable heat energy on demand. This effectively improve energy utilization and optimize energy allocation. As UTES technology advances, accommodating greater depth, higher temperature and multi-energy complementarity, new research challenges emerge. This paper comprehensively provides a systematic summary of the current research status of UTES. It categorized different types of UTES systems, analyzes the applicability of key technologies of UTES, and evaluate their economic and environmental benefits. Moreover, this paper identifies existing issues with UTES, such as injection blockage, wellbore scaling and corrosion, seepage and heat transfer in cracks, etc. It suggests deepening the research on blockage formation mechanism and plugging prevention technology, improving the study of anticorrosive materials and water treatment technology, and enhancing the investigation of reservoir fracture network characterization technology and seepage heat transfer. These recommendations serve as valuable references for promoting the high-quality development of UTES.

Introduction We designed and implemented a patient-centered, data-driven, holistic care model with evaluation of its impacts on clinical outcomes in patients with young-onset type 2 diabetes (T2D) for which there is a lack of evidence-based practice guidelines.Research design and methods In this 3-year Precision Medicine to Redefine Insulin Secretion and Monogenic Diabetes-Randomized Controlled Trial, we evaluate the effects of a multicomponent care model integrating use of information and communication technology (Joint Asia Diabetes Evaluation (JADE) platform), biogenetic markers and patient-reported outcome measures in patients with T2D diagnosed at ≤40 years of age and aged ≤50 years. The JADE-PRISM group received 1 year of specialist-led team-based management using treatment algorithms guided by biogenetic markers (genome-wide single-nucleotide polymorphism arrays, exome-sequencing of 34 monogenic diabetes genes, C-peptide, autoantibodies) to achieve multiple treatment goals (glycated hemoglobin (HbA1c)

Background/Aims Finite nucleos(t)ide analog (NA) therapy has been proposed as an alternative treatment strategy for chronic hepatitis B (CHB), but biomarkers for post-treatment monitoring are limited. We investigated whether measuring hepatitis B core-related antigen (HBcrAg) after NA cessation may stratify the risk of subsequent clinical relapse (CR). Methods This retrospective multicenter analysis enrolled adults with CHB who were prospectively monitored after discontinuing entecavir or tenofovir with negative HBeAg and undetectable HBV DNA at the end of treatment (EOT). Patients with cirrhosis or malignancy were excluded. CR was defined as serum alanine aminotransferase > two times the upper limit of normal with recurrent viremia. We applied time-dependent Cox proportional hazard models to clarify the association between HBcrAg levels and subsequent CR. Results The cohort included 203 patients (median age, 49.8 years; 76.8% male; 60.6% entecavir) who had been treated for a median of 36.9 months (interquartile range [IQR], 36.5–40.1). During a median post-treatment follow-up of 31.7 months (IQR, 16.7–67.1), CR occurred in 104 patients with a 5-year cumulative incidence of 54.8% (95% confidence interval [CI], 47.1–62.4%). Time-varying HBcrAg level was a significant risk factor for subsequent CR (adjusted hazard ratio [aHR], 1.53 per log U/mL; 95% CI, 1.12–2.08) with adjustment for EOT HBsAg, EOT anti-HBe, EOT HBcrAg and time-varying HBsAg. During follow-up, HBcrAg

Glycerol has been evaluated as a safe and promising animal feed. It can replace traditional energy foods and reduce competition with major animal husbandry systems. In this study, 40 fattening Kazakh ewes (18 months of age) were selected to investigate the dynamic response of growth performance, serum biochemical indexes, fat deposition, carcass traits and meat quality to different levels of glycerol (0, 1%, 7%, and 12% DM). The results showed that glycerol could improve sheep growth performance, increase fat deposition, increase carcass dressing percentage and improve meat quality. Among them, the Gly7% group had significant positive effects (P

This paper focuses on the re-entry phase of lunar return spacecraft and addresses the design optimization of their re-entry trajectories in real-world conditions. Considering various constraints of re-entry flights, this study introduces a refined superior control theory, drawing from Xuesen Qian’s descriptions in engineering control theory, and presents a specific superior control algorithm. The designed superior control algorithm and the traditional weighted optimal control algorithm were employed to simulate the lunar return and re-entry processes. Two representative trajectories were selected for a comparative analysis to obtain various parameters. Results indicate that the trajectory optimized using the weighted optimal control algorithm can only ensure that multiple performance indexes are optimized according to preset weights but cannot achieve superior performance in all metrics. In contrast, trajectories optimized using the superior control algorithm effectively leverage the permissible floating range of performance indexes without exceeding the maximum limit, thereby ensuring superior performance in all metrics. This paper is the first to refine the superior control theory proposed by Xuesen Qian, to design a specific algorithm theory for superior control, and to apply it to aerospace re-entry trajectory optimization—providing a theoretical foundation for future non-weighted control algorithm developments.