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In cognitive radio networks (CRNs), primary users (PUs) have the highest priority in channel resource allocation. Secondary users (SUs) can generally only utilize temporarily unused channels of PUs, share channels with PUs, or cooperate with PUs to gain priority through the interweave, underlay, and overlay modes. Traditional optimization schemes for channel resource allocation often lead to structural wastage of channel resources, whereas approaches such as reinforcement learning—though effective—require high computational power and thus exhibit poor adaptability in industrial deployments. Moreover, existing works typically optimize a single performance metric with limited scenario scalability. To address these limitations, this paper proposes a CR network algorithm based on the hybrid users (HU) concept, which links the Interweave and Underlay modes through an adaptive threshold for mode switching. The algorithm employs the Hungarian method for SU channel allocation and applies a multi-level power adjustment strategy when PUs and SUs share the same channel to maximize channel resource utilization. Simulation results under various parameter settings show that the proposed algorithm improves the average signal to interference plus noise ratio (SINR) of SUs while ensuring PU service quality, significantly enhances network energy efficiency, and markedly improves Jain’s fairness among SUs in low-power scenarios.

Nowadays, computer vision and machine learning are widely applied in vehicle detection. The technique of object detection is also of necessity in this realm. However, due to the large variety of models in object detection, it is important to find the most specifically suitable model for detecting vehicles in many situations. In this paper, we focus on comparing and summarizing Faster R-CNN, YOLOv3 and YOLOv5 applied in vehicle detection. We would introduce the models in relative detail and design an experiment to verify the models’ performances. The methodology for the experiment is to train the three models using the same dataset of vehicles, compare the different attributes of these results and find the most suitable application scenario for vehicle detection for each model.

Natural processes are substantially impacted by human activity, and assessing human activity has significant ramifications for regional ecological conservation. The study developed an extended human footprint (HF) assessment model based on the theory of ecological effects and human pressures to evaluate human disturbances in the urban agglomerations of the Yellow River Basin using data from 2005 to 2020, revealing the spatiotemporal pattern in the region. The conclusions show that the HF value of urban agglomeration in the Yellow River Basin has steadily increased from 2005 to 2020, primarily driven by mining intensity and road construction. High HF areas are primarily concentrated in urban areas in the south-central of the region, with a tendency to spread outward. Medium HF areas are mainly distributed in the eastern part of the study area, and the spatial distribution increases year by year, extending outward from the center area. The moderately low and HF areas are mostly found in the mountainous areas of the northwest. Among the urban agglomerations in the Yellow River Basin, the Central Plains UA and Shandong Peninsula UA are the areas most heavily affected by human disturbance. The conclusions are instructive for the high-quality development of urban agglomerations in the Yellow River Basin.

Background Stroke is a leading cause of death worldwide, with oxidative stress and calcium overload playing significant roles in the pathophysiology of the disease. Ozone, renowned for its potent antioxidant properties, is commonly employed as an adjuvant therapy in clinical settings. Nevertheless, it remains unclear whether ozone therapy on parthanatos in cerebral ischemia–reperfusion injury (CIRI). This study aims to investigate the impact of ozone therapy on reducing parthanatos during CIRI and to elucidate the underlying mechanism. Methods Hydrogen peroxide (H 2 O 2 ) was utilized to mimic the generation of reactive oxygen species (ROS) in SH-SY5Y cell reperfusion injury in vitro, and an in vivo ischemic stroke model was established. Ozone saline was introduced for co-culture or intravenously administered to mice. Apoptosis and oxidative stress were assessed using flow cytometry and immunofluorescence. Western blotting was utilized to examine the expression of parthanatos signature proteins. The mechanism by which ozone inhibits parthanatos was elucidated through inhibiting PPARg or Nrf2 activity. Results The findings demonstrated that ozone mitigated H 2 O 2 -induced parthanatos by either upregulating nuclear factor erythroid 2-related factor 2 (Nrf2) or activating peroxisome proliferator-activated receptorg (PPARg). Furthermore, through the use of calcium chelators and ROS inhibitors, it was discovered that ROS directly induced parthanatos and facilitated intracellular calcium elevation. Notably, a malignant feedback loop between ROS and calcium was identified, further amplifying the induction of parthanatos. Ozone therapy exhibited its efficacy by increasing PPARg activity or enhancing the Nrf2 translation, thereby inhibiting ROS production induced by H 2 O 2 . Concurrently, our study demonstrated that ozone treatment markedly inhibited parthanatos in stroke-afflicted mice. Additionally, ozone therapy demonstrated significant neuroprotective effects on cortical neurons, effectively suppressing parthanatos. Conclusions These findings contribute valuable insights into the potential of ozone therapy as a therapeutic strategy for reducing parthanatos during CIRI, highlighting its impact on key molecular pathways associated with oxidative stress and calcium regulation.

Serum creatinine (Cr) and albumin (Alb) are important predictors of mortality in individuals with various diseases, including acute pancreatitis (AP). However, most previous studies have only examined the relationship between single Cr or Alb levels and the prognosis of patients with AP. To our knowledge, the association between short- and long-term all-cause mortality in patients with AP and the blood creatinine to albumin ratio (CAR) has not been investigated. Therefore, this study aimed to evaluate the short- and long-term relationships between CAR and all-cause mortality in patients with AP. We conducted a retrospective study utilizing data from the Medical Information Market for Intensive Care (MIMIC-IV) database. The study involved analyzing various mortality variables and obtaining CAR values at the time of admission. The X-tile software was used to determine the optimal threshold for the CAR. Kaplan-Meier (K-M) survival curves and multivariate Cox proportional hazards regression models were used to assess the relationship between CAR and both short- and long-term all-cause mortality. The predictive power, sensitivity, specificity, and area under the curve (AUC) of CAR for short- and long-term mortality in patients with AP after hospital admission were investigated using Receiver Operating Characteristic analysis. Additionally, subgroup analyses were conducted. A total of 520 participants were included in this study. The CAR ideal threshold, determined by X-tile software, was 0.446. The Cox proportional hazards model revealed an independent association between CAR≥0.446 and all-cause mortality at 7-day (d), 14-d, 21-d, 28-d, 90-d, and 1-year (y) before and after adjustment for confounders. K-M survival curves showed that patients with CAR≥0.446 had lower survival rates at 7-d, 14-d, 21-d, 28-d, 90-d, and 1-y. Additionally, CAR demonstrated superior performance, with higher AUC values than Cr, Alb, serum total calcium, Glasgow Coma Scale, Systemic Inflammatory Response Syndrome score, and Sepsis-related Organ Failure Assessment score at 7-d, 14-d, 21-d, 28-d, 90-d, and 1-y intervals. Subgroup analyses showed that CAR did not interact with a majority of subgroups. The CAR can serve as an independent predictor for short- and long-term all-cause mortality in patients with AP. This study enhances our understanding of the association between serum-based biomarkers and the prognosis of patients with AP.

Innate immunity to nucleic acids forms the backbone for anti-viral immunity and several inflammatory diseases. Upon sensing cytosolic viral RNA, retinoic acid-inducible gene-I-like receptors (RLRs) interact with the mitochondrial antiviral signaling protein (MAVS) and activate TANK-binding kinase 1 (TBK1) to induce type I interferon (IFN-I). TRAF3-interacting protein 3 (TRAF3IP3, T3JAM) is essential for T and B cell development. It is also well-expressed by myeloid cells, where its role is unknown. Here we report that TRAF3IP3 suppresses cytosolic poly(I:C), 5’ppp-dsRNA, and vesicular stomatitis virus (VSV) triggers IFN-I expression in overexpression systems and Traf3ip3 −/− primary myeloid cells. The mechanism of action is through the interaction of TRAF3IP3 with endogenous TRAF3 and TBK1. This leads to the degradative K48 ubiquitination of TBK1 via its K372 residue in a DTX4-dependent fashion. Mice with myeloid-specific gene deletion of Traf3ip3 have increased RNA virus-triggered IFN-I production and reduced susceptibility to virus. These results identify a function of TRAF3IP3 in the regulation of the host response to cytosolic viral RNA in myeloid cells. RNA viruses can be detected by immune cell pattern recognition receptors, such as RLRs, resulting in MAVS-TBK1-IRF3 signalling and production of antiviral type 1 interferons. Here the authors show that macrophage TRAF3-interacting protein 3 regulates this signalling pathway by interacting with TRAF3 and TBK1 to suppress interferon responses.

The triglyceride-glucose (TyG) index is a novel marker of insulin resistance that has been strongly associated with many diseases related to metabolic disorders, such as diabetes, coronary heart disease, myocardial infarction, obesity, nonalcoholic fatty liver disease, and stroke. However, whether the TyG index is associated with the prevalence of gallstones has not been determined. Therefore, the purpose of this study was to evaluate the relationship between the TyG index and the prevalence of gallstones in American adults, as well as the age at which adults in America undergo their first gallstone surgery. We selected individuals from the National Health and Nutrition Examination Survey (NHANES) database from 2017 to March 2020. Based on the goal of our study, comprehensive inclusion and exclusion criteria were created. A logistic regression analysis, dose–response curve, and subgroup analysis were computed to assess the relationship between the TyG index and gallstone prevalence and age at first surgery for gallstone. A total of 3905 participants aged > 20 years were included in our study, of whom 421 had a self-reported history of gallstones. A total of 1884 (48.2%) males and 2021 (51.8%) females were included. After confounders adjustment, it was found single-unit increases in the TyG index were linked with a 25.0% increase in gallstone prevalence (odds ratio [OR] = 1.25, 95% confidence interval [95%CI]: 1.04, 1.51). After conversion of the TyG index values from continuous to categorical variables with tertiles, a marked 48% increase in gallstone incidence was found in tertile 3 relative to tertile 1 (OR = 1.48, 95% CI: 1.09, 1.99). The dose–response curve results indicated positive associations between gallstone prevalence and the TyG index, while the latter was negatively associated with age at first gallstone surgery. Based on subgroup analysis, the positive association between TyG index and high-incidence of gallstones was more significant in females (OR = 1.39, 95% CI: 1.09, 1.77), age < 40 years (OR = 2.02, 95% CI: 1.23, 3.29), and other race (OR = 1.46, 95% CI: 1.06, 2.02). A higher TyG index is associated with a higher incidence of gallstones and may lead to an earlier age of first gallstone surgery. However, a causal relationship between TyG and gallstones cannot be established.

The Carbonate rock weathering Carbon Sink (CCS) and Silicate rock weathering Carbon Sink (SCS) play a significant role in the carbon cycle and global climate change. However, the spatial‐temporal patterns and trends of the CCS and SCS from 1950 to 2099 have not been systematically quantified. Thus, Supported by long‐term hydrometeorological data under the RCP8.5, we use the accepted Suchet and Hartmann models to determine the following. First, we found except for the difference in their weathering rates, the SCS covers 37.2 million km2 more area than the CCS. The CCS Flux (CCSF) and SCS Flux (SCSF) are 5.36 and 1.22 t/km2/yr, respectively. Similarly, the Full CCS (FCCS, 0.3 Pg/yr) is more than the Full SCS (FSCS, 0.08 Pg/yr). Furthermore, the CCS (7.01 kg/km2) and SCS (3.95 kg/km2) are in a state of overall increase. In addition, the mid‐to‐high latitudes of the northern hemisphere are aggravated by warming (0.03°C) and humidity (0.65 mm), while the decrease in runoff in the mid‐latitudes of the southern hemisphere reduces karstification. Specifically, by 2099, the CCSF in the mid‐latitudes of the southern hemisphere will decrease by 5.72%. Instead, the CCSF in the northern hemisphere and lower latitudes of the southern hemisphere will exhibit a gentle upward slope. Particularly, the peak regions of the global FCCS (65.63 Tg/yr) and FSCS (33.01 Tg/yr) are the tropical zone. In conclusion, this study contributes a high‐resolution and long‐time series CS datasets for the CCS and SCS. We provide data and a theory for solving terrestrial carbon sink loss. Plain Language Summary The carbon cycle and global‐climate change cannot ignore the Carbonate and Silicate rocks weathering Carbon Sink (CCS and SCS). However, the spatial‐temporal patterns and trends of CCS and SCS from 1950 to 2099 have not been quantified. We use the accepted Suchet and Hartmann models to determine the following. First, we found except for the difference in their weathering rates, the SCS covers 37.2 million km2 more area than the CCS. The CCS Flux (CCSF) and SCS Flux (SCSF) are 5.36 and 1.22 t/km2/yr, respectively. Similarly, the Full CCS (FCCS, 0.3 Pg/yr) is more than the Full SCS (FSCS, 0.08 Pg/yr). Furthermore, the CCS (7.01 kg/km2) and SCS (3.95 kg/km2) are in a state of overall increase. In addition, the mid‐to‐high latitudes of the northern hemisphere are aggravated by warming (0.03°C) and humidity (0.65 mm), while the decrease in runoff in the mid‐latitudes of the southern hemisphere reduces karstification. Specifically, by 2099, the CCSF in the mid‐latitudes of the southern hemisphere will decrease by 5.72%. Instead, the CCSF in the northern hemisphere and lower latitudes of the southern hemisphere will exhibit a gentle upward slope. In conclusion, this study contributes a high‐resolution data set for solving carbon sink loss. Key Points High‐resolution data set for global carbonate and spatial diversification carbon sinks was established Carbon cycle can't ignore CCS (5.36 t/km2/yr) and SCS (1.22 t/km2/yr). Especially CCS (7.01 kg/km2) and SCS (3.95 kg/km2) increased significantly The peak regions of the global FCCS (65.63 Tg/yr) and FSCS (33.01 Tg/yr) are the tropical zone

Atherosclerosis is a chronic inflammatory disease with high morbidity and mortality rates worldwide. Doublecortin‐like kinase 1 (DCLK1), a microtubule‐associated protein kinase, is involved in neurogenesis and human cancers. However, the role of DCLK1 in atherosclerosis remains undefined. In this study, we identified upregulated DCLK1 in macrophages in atherosclerotic lesions of ApoE −/− mice fed an HFD and determined that macrophage‐specific DCLK1 deletion attenuates atherosclerosis by reducing inflammation in mice. Mechanistically, RNA sequencing analysis indicated that DCLK1 mediates oxLDL‐induced inflammation via NF‐κB signaling pathway in primary macrophages. Coimmunoprecipitation followed by LC–MS/MS analysis identified IKKβ as a binding protein of DCLK1. We confirmed that DCLK1 directly interacts with IKKβ and phosphorylates IKKβ at S177/181, thereby facilitating subsequent NF‐κB activation and inflammatory gene expression in macrophages. Finally, a pharmacological inhibitor of DCLK1 prevents atherosclerotic progression and inflammation both in vitro and in vivo. Our findings demonstrated that macrophage DCLK1 promotes inflammatory atherosclerosis by binding to IKKβ and activating IKKβ/NF‐κB. This study reports DCLK1 as a new IKKβ regulator in inflammation and a potential therapeutic target for inflammatory atherosclerosis. Syopsis Macrophage DCLK1 promotes inflammatory atherosclerosis by directly binding to IKKβ and activating IKKβ/NF‐κB signal. DCLK1 is a new regulator of IKKβ and a potential therapeutic target for atherosclerosis. Macrophage‐specific deletion or pharmacological inhibition of DCLK1 attenuates inflammatory atherosclerosis in mice. Blockage of DCLK1 alleviates oxLDL‐induced inflammation by inhibiting NF‐κB activation in macrophages. DCLK1 directly binds to IKKβ to induce IKKβ phosphorylation at S177/181, resulting in NF‐κB activation. Graphical Abstract Macrophage DCLK1 promotes inflammatory atherosclerosis by directly binding to IKKβ and activating IKKβ/NF‐κB signal. DCLK1 is a new regulator of IKKβ and a potential therapeutic target for atherosclerosis.

Silicate rock weathering maintains a stable and long‐term absorption of CO2. However, the magnitude, spatial pattern, and evolution characteristics of global silicate rock weathering carbon sink (SCS) remain unclear. To solve this problem, based on high‐precision hydrometeorological data (1996–2017) and CMIP5 data (2041–2060), using the Celine model, we calculated the global silicate rock weathering carbon sink flux (SCSF) magnitude and spatio‐temporal distribution for 1996–2017. We also predicted the SCSF under two future greenhouse gas emission scenarios (RCP 4.5 and RCP 8.5). Then, we produced a spatial data set (0.5 × 0.5) of global SCSF from 1996 to 2017 and found that the global average annual SCSF was 1.67 t/km2/yr, and the SCS was 127.11 Tg/yr. In particular, Brazil's silicate rock contribution accounts for nearly a quarter of the global SCS (24.41%). Although the GEM‐CO2 model is now widely used, the SCSF, without considering the temperature, may be overestimated by 5.4%, and the maximum contribution of temperature to it can reach 240 kg/km2/yr. Moreover, the global SCS is now showing a downward trend, but the global emission of greenhouse gases in the future (2041–2060) will continue to increase the carbon sink capacity (23.8%) due to temperature changes. In summary, we have produced a set of high‐resolution spatiotemporal data of the past and the future. The above results fill up the large‐scale data gap of SCSF and provide a scientific basis for quantitatively assessing the impact of climate change on SCS. Key Points Silicate rock carbon sink is expanded to global scale with high spatial resolution There is huge spatial heterogeneity in global silicate rock carbon sink flux From 2041 to 2060, silicate rock carbon sink will rise in response to global warming