The Error Covariance Matrix Inflation in Ensemble Kalman Filter

The estimation accuracy of ensemble forecast errors is crucial to the assimilation results for all ensemble-based schemes. The ensemble Kalman filter (EnKF) is a widely used scheme in land surface data assimilation, without using the adjoint of a dynamical model. In EnKF, the forecast error covariance matrix is estimated as the sampling covariance matrix of the ensemble forecast states. However, past researches on EnKF have found that it can generally lead to an underestimate of the forecast error covariance matrix, due to the limited ensemble size, as well as the poor initial perturbations and model error. This can eventually result in filter divergence. Therefore, using inflation to further adjust the forecast error covariance matrix becomes increasingly important. In this chapter, a new structure of the forecast error covariance matrix is proposed to mitigate the problems with limited ensemble size and model error. An adaptive procedure equipped with a second-order least squares method is applied to estimate the inflation factors of forecast and observational error covariance matrices. The proposed method is tested on the well-known atmosphere-like Lorenz-96 model with spatially correlated observational systems. The experiment results show that the new structure of the forecast error covariance matrix and the adaptive estimation procedure lead to improvement of the analysis states

Soil Moisture Assimilation Using a Modified Ensemble Transform Kalman Filter Based on Station Observations in the Hai River Basin

Assimilating observations to a land surface model can further improve soil moisture estimation accuracy. However, assimilation results largely rely on forecast error and generally cannot maintain a water budget balance. In this study, shallow soil moisture observations are assimilated into Common Land Model (CoLM) to estimate the soil moisture in different layers. A proposed forecast error inflation and water balance constraint are adopted in the Ensemble Transform Kalman Filter to reduce the analysis error and water budget residuals. The assimilation results indicate that the analysis error is reduced and the water imbalance is mitigated with this approach

Targeting PRMT3 Impairs Methylation and Oligomerization of HSP60 to Boost Anti-tumor Immunity by Activating cGAS/Sting Signaling

Immune checkpoint blockade (ICB) has emerged as a promising therapeutic option for hepatocellular carcinoma (HCC), but resistance to ICB occurs and patient responses vary. Here, we uncover protein arginine methyltransferase 3 (PRMT3) as a driver for immunotherapy resistance in HCC. We show that PRMT3 expression is induced by ICB-activated T cells via an interferon-gamma (IFNγ)-STAT1 signaling pathway, and higher PRMT3 expression levels correlate with reduced numbers of tumor-infiltrating CD8+ T cells and poorer response to ICB. Genetic depletion or pharmacological inhibition of PRMT3 elicits an influx of T cells into tumors and reduces tumor size in HCC mouse models. Mechanistically, PRMT3 methylates HSP60 at R446 to induce HSP60 oligomerization and maintain mitochondrial homeostasis. Targeting PRMT3-dependent HSP60 methylation disrupts mitochondrial integrity and increases mitochondrial DNA (mtDNA) leakage, which results in cGAS/STING-mediated anti-tumor immunity. Lastly, blocking PRMT3 functions synergize with PD-1 blockade in HCC mouse models. Our study thus identifies PRMT3 as a potential biomarker and therapeutic target to overcome immunotherapy resistance in HCC

mechanismresponsibleforthecompletesuppressionofkrmnvortexinflowspastawavysquaresectioncylinder

The Kármán vortex shedding is totally suppressed in flows past a wavy square-section cylinder at a Reynolds number of 100 and the wave steepness of 0.025. Such a phenomenon is illuminated by the numerical simulations. In the present study, the mechanism responsible for it is mainly attributed to the vertical vorticity. The geometric disturbance on the rear surface leads to the appearance of spanwise flow near the base. The specific vertical vorticity is generated on the rear surface and convecting into the near wake. The wake flow is recirculated with the appearance of the pair of recirculating cells. The interaction between the upper and lower shear layers is weakened by such cells, so that the vortex rolls could not be formed and the near wake flow becomes stable

effectsofparticlesizeondiluteparticledispersioninakrmnvortexstreetflow

It is shown that in a Kármán vortex street flow, particle size influences the dilute particle dispersion. Together with an increase of the particle size, there is an emergence of a period-doubling bifurcation to a chaotic orbit, as well as a decrease of the corresponding basins of attraction. A crisis leads the attractor to escape from the central region of flow. In the motion of dilute particles, a drag term and gravity term dominate and result in a bifurcation phenomenon

PM2.5 concentrations based on near-surface visibility in the Northern Hemisphere from 1959 to 2022

<jats:p>Abstract. Long-term PM2.5 data are essential for the atmospheric environment, human health, and climate change. PM2.5 measurements are sparsely distributed and of short duration. In this study, daily PM2.5 concentrations are estimated using a machine learning method for the period from 1959 to 2022 in the Northern Hemisphere based on near-surface atmospheric visibility. They are extracted from the Integrated Surface Database (ISD). Daily continuous monitored PM2.5 concentration is set as the target, and near-surface atmospheric visibility and other related variables are used as the inputs. A total of 80 % of the samples of each site are the training set, and 20 % are the testing set. The training result shows that the slope of linear regression with a 95 % confidence interval (CI) between the estimated PM2.5 concentration and the monitored PM2.5 concentration is 0.955 [0.955, 0.955], the coefficient of determination (R2) is 0.95, the root mean square error (RMSE) is 7.2 µg m−3, and the mean absolute error (MAE) is 3.2 µg m−3. The test result shows that the slope within a 95 % CI between the predicted PM2.5 concentration and the monitored PM2.5 concentration is 0.864 [0.863, 0.865], the R2 is 0.79, the RMSE is 14.8 µg m−3, and the MAE is 7.6 µg m−3. Compared with a global PM2.5 concentration dataset derived from a satellite aerosol optical depth product with 1 km resolution, the slopes of linear regression on the daily (monthly) scale are 0.817 (0.854) from 2000 to 2021, 0.758 (0.821) from 2000 to 2010, and 0.867 (0.879) from 2011 to 2022, indicating the accuracy of the model and the consistency of the estimated PM2.5 concentration on the temporal scale. The interannual trends and spatial patterns of PM2.5 concentration on the regional scale from 1959 to 2022 are analyzed using a generalized additive mixed model (GAMM), suitable for situations with an uneven spatial distribution of monitoring sites. The trend is the slope of the Theil–Sen estimator. In Canada, the trend is −0.10 µg m−3 per decade, and the PM2.5 concentration exhibits an east–high to west–low pattern. In the United States, the trend is −0.40 µg m−3 per decade, and PM2.5 concentration decreases significantly after 1992, with a trend of −1.39 µg m−3 per decade. The areas of high PM2.5 concentration are in the east and west, and the areas of low PM2.5 concentration are in the central and northern regions. In Europe, the trend is −1.55 µg m−3 per decade. High-concentration areas are distributed in eastern Europe, and the low-concentration areas are in northern and western Europe. In China, the trend is 2.09 µg m−3 per decade. High- concentration areas are distributed in northern China, and the low-concentration areas are distributed in southern China. The trend is 2.65 µg m−3 per decade up to 2011 and −22.23 µg m−3 per decade since 2012. In India, the trend is 0.92 µg m−3 per decade. The concentration exhibits a north–high to south–low pattern, with high-concentration areas distributed in northern India, such as the Ganges Plain and Thar Desert, and the low-concentration area in the Deccan Plateau. The trend is 1.41 µg m−3 per decade up to 2013 and −23.36 µg m−3 per decade from 2014. The variation in regional PM2.5 concentrations is closely related to the implementation of air quality laws and regulations. The daily site-scale PM2.5 concentration dataset from 1959 to 2022 in the Northern Hemisphere is available at the National Tibetan Plateau/Third Pole Environment Data Center (https://doi.org/10.11888/Atmos.tpdc.301127) (Hao et al., 2024). </jats:p&gt

A colorimetric sensor based on citrate-stabilized AuNPs for rapid pesticide residue detection of terbuthylazine and dimethoate

A new colorimetric sensor based on citrate-stabilized AuNPs was proposed for the rapid pesticide residue detection of both terbuthylazine (TBA) and dimethoate (DMT) with ultra-sensitivities and high selectivities. The detection mechanisms have been verified via FT-IR, UV-vis spectra, Zeta Potential, TEM and DLS. Under the optimized experimental conditions, 30 kinds of potential environmental pollutants have no interference on the TBA or DMT detection indicating the high selectivities of our AuNP-based colorimetric sensor. The limit of detections (LODs) of TBA and DMT by eye vision are respectively 0.3 mu M and 20 nM, and those based on calculation (3 sigma/S) are 0.02 mu M and 6.2 nM, respectively. The minimum detectable concentrations of TBA or DMT are much lower than the maximum residue limit (MRL) regulated by the governments of EU and China. The linear relationships of the UV-vis spectrometry demonstrate that our AuNP-based colorimetric sensor can be used for the quantitative analysis of TBA in the range of 0.1-0.9 mu M, and DMT in the range of 1-40 nM. Finally, our AuNP-based colorimetric sensor is also verified to have a good practical applicability for TBA or DMT detection in the real environmental samples. (C) 2017 Elsevier B.V. All rights reserved

Dual‐Responsive Supramolecular Polymeric Nanomedicine for Self‐Cascade Amplified Cancer Immunotherapy

Abstract Insufficient tumor immunogenicity and immune escape from tumors remain common problems in all tumor immunotherapies. Recent studies have shown that pyroptosis, a form of programmed cell death that is accompanied by immune checkpoint inhibitors, can induce effective immunogenic cell death and long‐term immune activation. Therapeutic strategies to jointly induce pyroptosis and reverse immunosuppressive tumor microenvironments are promising for cancer immunotherapy. In this regard, a dual‐responsive supramolecular polymeric nanomedicine (NCSNPs) to self‐cascade amplify the benefits of cancer immunotherapy is designed. The NCSNPs are formulated by β‐cyclodextrin coupling nitric oxide (NO) donor, a pyroptosis activator, and NLG919, an indoleamine 2,3‐dioxygenase (IDO) inhibitor, and self‐assembled through host–guest molecular recognition and hydrophobic interaction to obtain nanoparticles. NCSNPs possess excellent tumor accumulation and bioavailability attributed to ingenious supramolecular engineering. The study not only confirms the occurrence of NO‐triggered pyroptosis in tumors for the first time but also reverses the immunosuppressive microenvironment in tumor sites via an IDO inhibitor by enhancing the infiltration of cytotoxic T lymphocytes, to achieve remarkable inhibition of tumor proliferation. Thus, this study provides a novel strategy for cancer immunotherapy

Role of the Early Miocene Jinhe-Qinghe Thrust Belt in the building of the Southeastern Tibetan Plateau topography

International audienceUnderstanding the role of southeastern Tibetan thrust faults in the development of plateau topography is key to our assessment of the geodynamic processes shaping continental topography. Detailed structural analysis along the ~400 km long Jinhe-Qinghe thrust belt (JQTB) indicates post Late Eocene thrust motion with a minor leftlateral component, inducing ~0.6 to 3.6 km of apparent vertical offset across the fault. The exhumation history of the Baishagou granite, based on thermal modeling of new apatite (U-Th)/He and fission-track results, suggests an accelerated exhumation rate (~0.4 km/Myr) between 20 and 16 Ma, corresponding to ~1.7-2.4 km of exhumation. We interpret this fast exhumation as a manifestation of the activation of the Nibi thrust, a northern branch of the JQTB, resulting in the creation of significant relief across the JQTB in the Early Miocene. When compared with previous studies, our findings show that Cenozoic exhumation and relief creation in southeastern Tibet cannot be explained by a single mechanism. Rather, at least three stages of relief creation should be invoked. The first phase is Eocene NE-SW compression partly coeval with Eocene sedimentation. During the Late Oligocene to Early Miocene and coeval with the extrusion of Indochina, the second thrusting phase occurred along the Yulong and Longmenshan thrust belts, and then migrated to the JQTB at 20-16 Ma. The third phase involved the activation of the Xianshuihe fault and the re-activation of the Longmenshan thrust belt and the Muli thrust. Uplift in the hanging wall of thrust belts appears to explain most of the present-day relief in the southeastern Tibetan Plateau

Paleoelevations in the Jianchuan Basin of the southeastern Tibetan Plateau based on stable isotope and pollen grain analyses

The southeastern margin of the Tibetan Plateau (TP) is a key region for understanding the region's surface uplift mechanisms. This study focused on the Jiuziyan and Shuanghe Formations (Fms) in the Jianchuan Basin, both of which include lacustrine calcareous mudstones and marls. Ostracods of the genus Austrocypris found within the Jiuziyan and Shuanghe Fms constrain the age of strata to the Late Eocene. This study used two different proxies, i.e. fossil pollen coexistence and the δ^(18)O (VPDB) values of carbonate (δ^(18)O_c), to reconstruct paleoelevation and the extant paleoenvironment from lacustrine calcareous mudstones and marls preserved in the Eocene stratigraphy of the Jianchuan Basin. The coexistence approach (CA) using pollen data from the Shuanghe Fm indicates a paleoelevation of 1.3–2.6 km above sea level (asl), which would most probably have been associated with a vegetation cover consisting of tropical-subtropical, deciduous, coniferous, broadleaf forests. The reconstructed mean annual air temperature (MAAT) had a value of 16.8–21.7 °C, warmer than today's MAAT (~6 °C). Oxygen isotope results from the Jiuziyan Fm, with/without modification between Eocene and modern Myanmar sea level, suggested that the surface of the Jianchuan Basin was at a paleoelevation between 0.5^(+0.8)_(–0.5) km asl and 2.5 ± 0.7 km asl (δ^(18)Omw: −8.9 ± 1.3‰, 2σ). During the Shuanghe Fm sedimentation the paleoelevation was between 0.9^(+0.7)_(–0.7) km asl and 2.9 ± 0.6 km asl (δ^(18)O_(mw): −9.5 ± 1.1‰, 2σ). Our results suggest that a stepwise uplift of Jianchuan Basin and crustal thickening initiated during the Eocene was the cause of passive surface uplift of the southeastern Tibetan Plateau (TP) rather than Miocene lower crustal flow