As an important component of the hydrological and biogeochemical cycle, porewater discharge represents a significant pathway for releasing chemical solutes into coastal zones, particularly in highly ...permeable aquifers. In this study, a 222Rn advection-diffusion model was used to estimate the porewater discharge in a coastal aquifer (Shengsi Island, East China Sea) during November 2015. Porewater discharge was estimated to range from 7.4 to 25.8 (mean: 12.9 ± 5.8) cm d−1. Furthermore, the estimated porewater-derived nutrient fluxes (dissolved inorganic nitrogen (DIN), phosphorus (DIP) and silicon (DSi)) (mol m−2 d−1) were (1.7 ± 1.4) × 10−2, (2.1 ± 1.1) × 10−4 and (1.5 ± 1.3) × 10−2, respectively. The Si/N ratio of coastal seawater at Shengsi Island was ∼0.83, which is close to that of porewater along the coastal aquifers of Shengsi Island (∼0.92) but higher than that of the Yangtze River Estuary (∼0.68). Thus, porewater-derived Si flux with a higher Si/N ratio may mitigate the outbreak of non-siliceous algae (i.e., Prorocentrum dentatum) in adjacent waters of Shengsi Island. By comparing the SGD-derived nutrient fluxes worldwide, this study suggests that Si flux with a higher Si/N ratio through porewater discharge (or SGD) may strongly influence the Si budget and cycling because such porewater/SGD-derived Si can compensate for the dwindling Si flux from riverine sources due to human activity (i.e., dam construction, reservoirs). Our results are expected to increase our understanding of not only biogenic elements of cycling processes but also eco-environment processes such as the occurrences of harmful algal blooms alone river-influenced coasts.
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•Porewater discharge was estimated based on a 222Rn advection-diffusion model.•Higher porewater-derived nutrient fluxes may mitigate the eutrophication outbreak of non-siliceous algae.•Si flux with a higher Si/N ratio through porewater may influence the Si budget and cycling.
This paper investigates the issue of cooperative spectrum sensing with a crowd of low-end personal spectrum sensors (such as smartphones, tablets, and in-vehicle sensors), where the sensing data from ...crowd sensors that may be unreliable, untrustworthy, or even malicious. Moreover, due to either unexpected equipment failures or malicious behaviors, every crowd sensor could sporadically and randomly contribute with abnormal data, which makes the existing cooperative sensing schemes ineffective. To tackle these challenges, we first propose a generalized modeling approach for sensing data with an arbitrary abnormal component. Under this model, we then analyze the impact of general abnormal data on the performance of the cooperative sensing, by deriving closed-form expressions of the probabilities of global false alarm and global detection. To improve sensing data quality and enhance cooperative sensing performance, we further formulate an optimization problem as stable principal component pursuit, and develop a data cleansing-based robust spectrum sensing algorithm to solve it, where the under-utilization of licensed spectrum bands and the sparsity of nonzero abnormal data are jointly exploited to robustly cleanse out the potential nonzero abnormal data component from the original corrupted sensing data. Extensive simulation results demonstrate that the proposed robust sensing scheme performs well under various abnormal data parameter configurations.
It is a key issue to investigate the degradation law of ship propeller service performance and predict its residual fatigue in marine engineering. In this paper, the underwater test are carried out ...and fracture characteristics are detected to systematically analyze the failure mechanism of the ship propeller in operating states. Then, a feature fusion method based on adaptive popular learning algorithm is proposed, the redundant information in multi-domain characteristics set is eliminated, and the fusion characteristic index of propeller performance degradation trend is constructed according to the LLE method. Finally, based on the TV-HSMM method, the state transformation coefficient is optimized, and the propeller operating state recognition and residual fatigue life prediction are realized with the combined application of the feature fusion data. The research on propeller residual fatigue life prediction based on data fusion is of great significance to avoid major faults and ensure the operation safety of ships.
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•TV-HSMM model involving thee time varying state is employed to predict the residual fatigue life of propeller, the state transition coefficient and state transition probability are derived with the consideration of the degradation characteristics of propeller in three operating states.
High-salt printing and dyeing wastewater is a difficult industrial wastewater to treat. Coal-based activated carbon (CBAC) can be used as an adsorbent to treat high-salt printing and dyeing ...wastewater and realize the resource utilization of CBAC. In this study, simulated wastewater that contained methylene blue (MB) was used as the research object, and CBAC was used as the adsorbent. The effects of CBAC dosage, NaCl concentration, coexisting ions, adsorption time, MB concentration, humic acid concentration, and solution pH on the adsorption performance of CBAC with MB were discussed. The results showed that when the CBAC dosage was 0.6 g/L, the solution pH was greater than 6, the adsorption time was 8 h, the adsorption temperature was 308 K, and the MB concentration was 10 mg/L. Thus, the maximum adsorption capacity of CBAC with MB was obtained. The maximum adsorption capacity and removal rate were 15.5 mg/L and 90%, respectively. High-salt wastewater can inhibit the adsorption of methylene blue by coal-based activated carbon. In addition, 20 g/L of NaCl reduced the adsorption capacity of coal-based activated carbon by 1.8 mg/g. Compared to the other coexisting ions, the influence of the presence of Cu2+ and Fe3+ on the removal of methylene blue was greater. However, when Cu2+, Fe3+ and high-salt wastewater coexist, the inhibition effect decreases.
A progressive damage model for aramid honeycomb cutting was proposed to reveal its cutting damage mechanism. It established the relationship between the mesoscale failure modes and the macroscale ...cutting damage types of the aramid honeycomb. The proposed model addressed the material assignment problem of impregnated honeycomb by developing a material calculation method that simulates the real manufacturing process of the aramid honeycomb. Cutting experiment of aramid honeycomb specimen was conducted concerning on the cutting forces response and cutting damages, which validated that the proposed method was effective for investigating the cutting process and mechanism for the aramid honeycomb. Predicted cutting mechanism results show that: (a) cutting process of the aramid honeycomb can be divided into three stages with four characteristic states—initial state, cut-in state, cut-out state and final state; (b) cell wall bending in the cutting direction relieves the cutting force, and strong plasticity of the aramid fiber makes it hard to break, which lead to uncut fiber and burr damages; (c) using sharp tip cutting tool to reduce cutting force and bonding both top and bottom of the honeycomb to make it stiffer are beneficial to obtain good cutting quality with less damages.
This article investigates the problem of distributed channel selection for opportunistic spectrum access systems, where multiple cognitive radio (CR) users are spatially located and mutual ...interference only emerges between neighboring users. In addition, there is no information exchange among CR users. We first propose a MAC-layer interference minimization game, in which the utility of a player is defined as a function of the number of neighbors competing for the same channel. We prove that the game is a potential game with the optimal Nash equilibrium (NE) point minimizing the aggregate MAC-layer interference. Although this result is promising, it is challenging to achieve a NE point without information exchange, not to mention the optimal one. The reason is that traditional algorithms belong to coupled algorithms which need information of other users during the convergence towards NE solutions. We propose two uncoupled learning algorithms, with which the CR users intelligently learn the desirable actions from their individual action-utility history. Specifically, the first algorithm asymptotically minimizes the aggregate MAC-layer interference and needs a common control channel to assist learning scheduling, and the second one does not need a control channel and averagely achieves suboptimal solutions.
Programmed cell death （PCD） is of fundamental importance to development and defense in animals and plants. In plants, a well-recognized form of PCD is hypersensitive response （HR） triggered by ...pathogens, which involves the generation of reactive oxygen species （ROS） and other signaling molecules. While the mitochondrion is a master reg- ulator of PCD in animals, the chloroplast is known to regulate PCD in plants. Arabidopsis Mosaic Death 1 （MOD1）, an enoyl-acyl carrier protein （ACP） reductase essential for fatty acid biosynthesis in chloroplasts, negatively regulates PCD in Arabidopsis. Here we report that PCD in modl results from accumulated ROS and can be suppressed by mu- tations in mitochondrial complex I components, and that the suppression is confirmed by pharmaceutical inhibition of the complex 1-generated ROS. We further show that intact mitochondria are required for full HR and optimum disease resistance to the Pseudomonas syringae bacteria. These findings strongly indicate that the ROS generated in the electron transport chain in mitochondria plays a key role in triggering plant PCD and highlight an important role of the communication between chloroplast and mitochondrion in the control of PCD in plants.
A low-carbon and energy-saving sintering process with uniform temperature distribution has been developed to address several issues associated with the sintering of drill bits in medium-frequency ...furnaces, namely, the large circumferential temperature differences, uneven heating of the mold, and low energy utilization. Theoretical calculations indicated that the output energy of the conventional drill bit sintering process was 12.7 kW·h, with an energy loss of 8.84 kW·h. The low-carbon sintering process achieved an output energy of 4.2 kW·h, with an energy loss of only 0.26 kW·h. Consequently, the energy utilization rates for the two processes were 30.4% and 93.8%, respectively. It was observed through the experiment that when sintering 76/49 mm drill bits at insulation temperatures of 900 °C and 1080 °C, the circumferential temperature differences in the mold were 43.7 °C and 48 °C, respectively, in the conventional drill bit sintering process. In contrast, the circumferential temperature differences in the mold were reduced to 8.7 °C and 11.3 °C, respectively, in the low-carbon and energy-saving sintering process with uniform temperature. This indicates that the average circumferential temperature difference in the mold can be reduced by 81.61% at 900 °C and by 76.46% at 1080 °C, leading to improved drill bit quality.
The Arabidopsis immune receptor FLS2 perceives bacterial flagellin epitope flg22 to activate defenses through the central cytoplasmic kinase BIK1. The heterotrimeric G proteins composed of the ...non-canonical Gα protein XLG2, the Gβ protein AGB1, and the Gγ proteins AGG1 and AGG2 are required for FLS2-mediated immune responses through an unknown mechanism. Here we show that in the pre-activation state, XLG2 directly interacts with FLS2 and BIK1, and it functions together with AGB1 and AGG1/2 to attenuate proteasome-mediated degradation of BIK1, allowing optimum immune activation. Following the activation by flg22, XLG2 dissociates from AGB1 and is phosphorylated by BIK1 in the N terminus. The phosphorylated XLG2 enhances the production of reactive oxygen species (ROS) likely by modulating the NADPH oxidase RbohD. The study demonstrates that the G proteins are directly coupled to the FLS2 receptor complex and regulate immune signaling through both pre-activation and post-activation mechanisms.
Purpose
Cuprotosis is a newly discovered form of non-apoptotic regulated cell death and is characterized by copper-dependent and associated with mitochondrial respiration. However, the prognostic ...significance and function of cuprotosis-related genes (CRGs) in hepatocellular carcinoma (HCC) are unknown. This study aims to develop cuprotosis-mediated patterns-related gene (CMPRG) prediction models for the prognosis of patients with HCC, exploring the functional underlying the CRGs on the influence of tumor microenvironment (TME) features.
Experimental design
This study obtained transcriptome profiling and the corresponding clinical information from the TCGA and GEO databases. Besides, the Cox regression model with LASSO was implemented to build a multi-gene signature, which was then validated in an internal validation set and two external validation sets through Kaplan-Meier, DCA, and ROC analyses.
Results
According to the LASSO analysis, we screened out a cuprotosis-mediated pattern 5-gene combination (including PBK; MMP1; GNAZ; GPC1 and AKR1D1). A nomogram was constructed for the presentation of the final model. The ROC curve assessed the model’s predictive ability, which resulted in an area under the curve (AUC) values ranging from 0.604 to 0.787 underwent internal and two external validation sets. Meanwhile, the risk score divided the patients into two groups of high and low risk, and the survival rate of high-risk patients was significantly lower than that of low-risk patients (P<0.01). The risk score could be an independent prognostic factor in the multifactorial Cox regression analysis (P<0.01). Functional analysis revealed that immune status, mutational loads, and drug sensitivity differed between the two risk groups.
Conclusions
In summary, we identified three cuprotosis-mediated patterns in HCC. And CMPRGs are a promising candidate biomarker for HCC early detection, owing to their strong performance in predicting HCC prognosis and therapy. Quantifying cuprotosis-mediated patterns in individual samples may help improve the understanding of multiomic characteristics and guide the development of targeted therapy for HCC.
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