Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
1,675
result(s) for
"Li, Xiang-Yu"
Sort by:
On the Prediction of Aerosol‐Cloud Interactions Within a Data‐Driven Framework
Aerosol‐cloud interactions (ACI) pose the largest uncertainty for climate projection. Among many challenges of understanding ACI, the question of whether ACI can be deterministically predicted has not been explicitly answered. Here we attempt to answer this question by predicting cloud droplet number concentration Nc${N}_{c}$from aerosol number concentration Na${N}_{a}$and ambient conditions using a data‐driven framework. We use aerosol properties, vertical velocity fluctuations, and meteorological states from the ACTIVATE field observations (2020–2022) as predictors to estimate Nc${N}_{c}$ . We show that the campaign‐wide Nc${N}_{c}$can be successfully predicted using machine learning models despite the strongly nonlinear and multi‐scale nature of ACI. However, the observation‐trained machine learning model fails to predict Nc${N}_{c}$in individual cases while it successfully predicts Nc${N}_{c}$of randomly selected data points that cover a broad spatiotemporal scale. This suggests that, within a data‐driven framework, the Nc${N}_{c}$prediction is uncertain at fine spatiotemporal scales. Plain Language Summary Ambient aerosol particles act as seeds for ice crystals and cloud droplets that form clouds. Both aerosols and clouds regulate the energy and water budgets of the Earth via radiative and cloud micro/macro‐processes. This is the so‐called aerosol‐cloud interactions (ACI). ACI remains the source of the largest uncertainty for accurate climate projections, due to incomplete understanding of nonlinear multi‐scale processes, limited observations across various cloud regimes, and insufficient computational power to resolve them in models. Quantifying the relation between the cloud droplet Nc$\\left({N}_{c}\\right)$and aerosol Na$\\left({N}_{a}\\right)$number concentration has been a central challenge of understanding and representing ACI. In this work, we tackle this challenge by predicting Nc${N}_{c}$from observations made during the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) using machine learning models. We show that the climatological Nc${N}_{c}$can be successfully predicted despite the strongly nonlinear and multi‐scale nature of ACI. However, the observation‐trained machine learning model fails to predict Nc${N}_{c}$at fine spatiotemporal scales. Key Points Three‐year in situ measurements (179 flights) provide adequate data to train and validate a random forest model (RFM) to study aerosol‐cloud interactions The RFM can successfully predict cloud droplet number concentration Nc${N}_{c}$and identify importance of key predictors Data‐driven Nc${N}_{c}$prediction in individual cases shows strong dependency on sampling strategy
Journal Article
High-efficiency reinforcement learning with hybrid architecture photonic integrated circuit
Reinforcement learning (RL) stands as one of the three fundamental paradigms within machine learning and has made a substantial leap to build general-purpose learning systems. However, using traditional electrical computers to simulate agent-environment interactions in RL models consumes tremendous computing resources, posing a significant challenge to the efficiency of RL. Here, we propose a universal framework that utilizes a photonic integrated circuit (PIC) to simulate the interactions in RL for improving the algorithm efficiency. High parallelism and precision on-chip optical interaction calculations are implemented with the assistance of link calibration in the hybrid architecture PIC. By introducing similarity information into the reward function of the RL model, PIC-RL successfully accomplishes perovskite materials synthesis task within a 3472-dimensional state space, resulting in a notable 56% improvement in efficiency. Our results validate the effectiveness of simulating RL algorithm interactions on the PIC platform, highlighting its potential to boost computing power in large-scale and sophisticated RL tasks.
The Authors present a universal framework that utilizes photonic integrated circuits (PIC) to enhance the efficiency of reinforcement learning (RL). Leveraging the advantages of the hybrid architecture PIC (HyArch PIC), the PIC-RL experiment demonstrates a remarkable 56% improvement in efficiency for synthesizing perovskite materials.
Journal Article
Different degeneration patterns of paraspinal muscles in degenerative lumbar diseases: a MRI analysis of 154 patients
Study designA retrospective study.ObjectiveTo evaluate the different degeneration patterns of paraspinal muscles in degenerative lumbar diseases and their correlation with lumbar spine degeneration severity.Summary of background dataThe degeneration characteristics of different paraspinal muscles in degenerative lumbar diseases remain unclear.Methods78 patients diagnosed with single-level degenerative lumbar spondylolisthesis (DLS) and 76 patients with degenerative lumbar kyphosis (DLK) were included as DLS and DLK groups. Paraspinal muscle parameters of psoas major (PS), erector spinae (ES) and multifidus muscle (MF) were measured, including fatty infiltration (FI) and relative cross-sectional area (rCSA), namely the ratio of the paraspinal muscle CSA to the CSA of the vertebrae of the same segment. Sagittal parameters including lumbar lordosis (LL) and sagittal vertical axis (SVA) were measured. The paraspinal muscle parameters and ES/MF rCSA ratio were compared between the two groups. Paraspinal muscles parameters including rCSA and FI were also compared between each segments from L1 to L5 in both DLS and DLK groups. In order to determine the influence of sagittal spinal alignment on paraspinal muscle parameters, correlation analysis was conducted between the MF, ES, PS rCSA and FI and the LL in DLS and DLK group.ResultMF atrophy is more significant in DLS patients compared with DLK. Also, MF fatty infiltration in the lower lumbar spine of DLS patients was greater compared to DLK patients. DLK patients showed more significant atrophy of ES and heavier ES fatty infiltration. MF FI was significantly different between all adjacent segments in both DLS and DLK groups. In DLS group, ES FI was significantly different between L2/L3 to L3/L4 and L4/L5 to L5/S1, while in DLK group, the difference of ES FI between all adjacent segments was not significant, and ES FI was found negatively correlated with LL.ConclusionsParaspinal muscles show different degeneration patterns in degenerative lumbar diseases. MF degeneration is segmental in both DLS and DLK patients, while ES degenerated diffusely in DLK patients and correlated with the severity of kyphosis. MF degeneration is more significant in the DLS group, while ES degeneration is more significant in DLK patients. MF is the stabilizer of the lumbar spine segments, while the ES tends to maintain the spinal sagittal balance.
Journal Article
Central nervous system Cryptococcoma mimicking demyelinating disease: a case report
Background
Cerebral cryptococcomas is a rare form of central nervous system cryptococcosis. Most previous cases were mistaken for neoplasm before surgery. We present a case of cerebral cryptococcomas whose radiological profiles resembled demyelinating disease, especially tumefactive demyelinating lesion.
Case presentation
A 40-year-old male was admitted for 1-week-long unconsciousness. Brain MRI revealed a rim-enhanced mass within the corpus callosum body. Central nervous system demyelinating disease was suspected. Empirical corticosteroid treatment led to some improvement, but his condition deteriorated 2 months later. Brain MRI revealed punctate new foci.
Cryptococcus neoformans
was detected in cerebrospinal fluid. Cryptococcus antigen test was positive in his current and previous cerebrospinal fluid samples. The patient died despite standard antifungal treatment.
Conclusion
Diagnosis of cerebral cryptococcomas is challenging. It may mimic demyelinating diseases.
Journal Article
Lycium barbarum polysaccharide attenuates diabetic testicular dysfunction via inhibition of the PI3K/Akt pathway-mediated abnormal autophagy in male mice
Testicular dysfunction is one of the serious secondary complications in diabetes. Lycium barbarum polysaccharide (LBP) has long been considered to possess a wide range of beneficial properties including antiaging, anticancer and reproductive-enhancing. Abnormal autophagy was reported to play a significant role in accelerating diabetic reproductive injury. However, the autophagy regulation mechanism of LBP on diabetic testicular dysfunction is incompletely understood. We investigate the protective effects of LBP on diabetic testicular dysfunction and its underlying mechanism with different approaches. Protective effects of LBP (40 mg/kg) on testicular functions were assessed through the use of sperm parameters, testosterone levels and hematoxylin and eosin staining. Antioxidant capacity and serum malondialdehyde levels were determined using assay kits. Immune intensity of Beclin-1 and LC3I in testes was detected by immunofluorescence staining. Western blot analysis was used to detect expressions of p-PI3K, Akt, p-Akt, Beclin-1, LC3I and LC3II proteins. Q-PCR was used to evaluate Beclin-1 and LC3I mRNA expressions in testis. Administration of LBP (40 mg/kg) considerably recovered testicular function, obviously improved testicular histopathologic structure and significantly increased antioxidant enzyme activities. Immunofluorescence staining showed that immune intensity of Beclin-1 and LC3I significantly decreased in the LBP 40 mg/kg group. The results of Q-PCR and western blot analysis showed that LBP 40 mg/kg significantly downregulated Beclin-1 and LC3I protein expressions upregulated p-PI3K and p-Akt protein expressions and decreased Beclin-1 and LC3I mRNA expressions compared with diabetic mice. In conclusion, inhibition of PI3K/Akt pathway-mediated testicular excessive autophagy may be a target for protective effects of LBP on diabetic testicular dysfunction.
Journal Article
Understanding aerosol–cloud interactions using a single-column model for a cold-air outbreak case during the ACTIVATE campaign
Marine boundary layer clouds play a critical role in Earth's energy balance. Their microphysical and radiative properties are highly impacted by ambient aerosols and dynamic forcings. In this study, we evaluate the representation of these clouds and related aerosol–cloud interaction processes in the single-column version of the E3SM climate model (SCM) against field measurements collected during the NASA ACTIVATE campaign over the western North Atlantic, as well as intercompare results with high-resolution process level models. We show that E3SM SCM reproduces the macrophysical properties of post-frontal boundary layer clouds in a cold-air outbreak (CAO) case well. However, it generates fewer but larger cloud droplets compared to aircraft measurements. Further sensitivity tests show that the underestimation of both aerosol number concentration and vertical velocity variance contributes to this bias. Aerosol–cloud interactions are examined by perturbing prescribed aerosol properties in E3SM SCM with fixed dynamics. Higher aerosol number concentration or hygroscopicity leads to more numerous but smaller cloud droplets, resulting in a stronger cooling via shortwave cloud forcing. This apparent Twomey effect is consistent with prior climate model studies. The cloud liquid water path shows a weakly positive relation with cloud droplet number concentration due to precipitation suppression. This weak aerosol effect on cloud macrophysics may be attributed to the dominant impact of strong dynamical forcing associated with the CAO. Our findings indicate that the SCM framework is a key tool to bridge the gap between climate models, process level models, and field observations to facilitate process level understanding.
Journal Article
Condensational and Collisional Growth of Cloud Droplets in a Turbulent Environment
We investigate the effect of turbulence on the combined condensational and collisional growth of cloud droplets by means of high-resolution direct numerical simulations of turbulence and a superparticle approximation for droplet dynamics and collisions. The droplets are subject to turbulence as well as gravity, and their collision and coalescence efficiencies are taken to be unity. We solve the thermodynamic equations governing temperature, water vapor mixing ratio, and the resulting supersaturation fields together with the Navier–Stokes equation. We find that the droplet size distribution broadens with increasing Reynolds number and/or mean energy dissipation rate. Turbulence affects the condensational growth directly through supersaturation fluctuations, and it influences collisional growth indirectly through condensation. Our simulations show for the first time that, in the absence of the mean updraft cooling, supersaturation-fluctuation-induced broadening of droplet size distributions enhances the collisional growth. This is contrary to classical (nonturbulent) condensational growth, which leads to a growing mean droplet size, but a narrower droplet size distribution. Our findings, instead, show that condensational growth facilitates collisional growth by broadening the size distribution in the tails at an early stage of rain formation. With increasing Reynolds numbers, evaporation becomes stronger. This counteracts the broadening effect due to condensation at late stages of rain formation. Our conclusions are consistent with results of laboratory experiments and field observations, and show that supersaturation fluctuations are important for precipitation.
Journal Article
A multi-center investigation of breast-conserving surgery based on data from the Chinese Society of Breast Surgery (CSBrS-005)
Although breast-conserving surgery is one of the standard treatments for breast cancer, few studies have assessed its recent implementation in China. We aimed to clarify the current real-world status of breast-conserving surgery in China.
This cross-sectional survey relied on data collected by the Chinese Society of Breast Surgery (CSBrS) to examine patients who underwent this surgery between January 2018 and December 2018. The survey was conducted using a uniform electronic questionnaire to collect information, including clinical and pathological data on these patients.
Overall, 4459 breast-conserving surgeries were performed in 34 member units of CSBrS, accounting for 14.6% of all breast cancer surgeries performed in these units during the study period. In patients who underwent breast-conserving surgery with information on tumor size available, more than half (61.2%) of the tumors were smaller than 2 cm in diameter, and only 87 (3.2%) tumors were larger than 4 cm in diameter. Among patients who underwent breast-conserving surgeries, 457 (10.2%) patients received neoadjuvant therapy before the surgery. Among patients with a reported margin width, 34 (2.0%) patients had a margin of ≤2 mm, and 1530 (88.2%) of them had a margin of >5 mm.
This study demonstrated the rates of breast-conserving surgery in member units of the CSBrS, and introduced the characteristics and surgical margins of patients who underwent this surgery. This information helps describe the real-world status of breast-conserving surgery in China.
chictr.org.cn, ChiCTR1900026841; http://www.chictr.org.cn/showproj.aspx?proj=42783.
Journal Article
Relationship between TIA minus C0-7 angle and C2-7 SVA: analysis of 113 symptomatic patients
Background
Measurement of T1 slope (T1S) can be difficult due to the anatomical positioning of the shoulders. And thoracic inlet angle (TIA) was a morphological parameter and not changed by the position. We proposed a new parameter, TIA minus C0-7 angle (TIA-C07), to evaluate C2-7 SVA in order to overcome the T1S imperfection.
Methods
This was a retrospective radiological analysis of symptomatic subjects. The following cervical parameters were measured: Cervical lordosis angle (CL), C0-7 angle (C0-7), occiput-C2 lordosis angle (O-C2), C2-7 sagittal vertical axis (C2–7 SVA), TIA and TIA-C07. The Pearson correlation test was calculated, and the stepwise multiple regression analysis was conducted to determine the best predictor for C2-7 SVA. A paired sample t test was used to compare the predicted and measured C2-7 SVA.
Results
The mean age of 113 patients was 60.02 ± 9.67. The average O-C2, CL, C0-7, TIA, TIA-C07 and C2-C7 SVA was 29.24 ± 8.48°, 13.67 ± 11.22°, 42.91 ± 11.44°, 76.07 ± 9.54°, 33.16 ± 13.18° and 21.34 ± 11.42 mm. The predictive formula was founded: C2-7 SVA = 2.80 + 0.56 * (TIA—C07) (
R
= 0.645, R2 = 0.416). There was no statistical difference between the predicted and the measured C2-7 SVA (t = 0.085,
P
= 0.933).
Conclusions
TIA and C0-7 mismatch may significantly impact cervical alignment, and a greater T1A-C07 was related to a greater degree of C2-7 SVA. TIA-C07 may be a more important predictor for C2-7 SVA.
Journal Article