Search

Background: Cerebral protection strategies in type A aortic dissection (TAAD) surgery are critical yet inconclusive. We propose an integrated cerebral protection protocol. This study aimed to evaluate the effectiveness of this protocol. Methods: From January 2020 to December 2022, 85 patients were treated with an integrated protocol incorporating bilateral antegrade cerebral perfusion (ACP) and moderate hypothermia, with measures to prevent the shedding of thrombus or endothelial debris (BACP group), while traditional protocols were applied to 273 additional patients (UACP group). Inverse probability treatment weighting (IPTW) was performed to balance baseline characteristics. Three logistic regression models were used to evaluate the relationship between the two cerebral protection strategies and neurologic complications. Stepwise logistic regression was further employed to identify risk factors for cerebral complications. Results: Baseline characteristics were balanced after IPTW adjustment. The BACP group had a significantly shorter operative time (364.79 vs. 397.61 min, P = 0.022), significantly fewer neurologic complications (5.6% vs. 15.9%, P = 0.032), and transient neurologic injury (3.0% vs. 12.5%, P = 0.035). Binary multivariable logistic regression analysis showed that the cerebral complication risk was 3.14 times greater with the traditional protocol compared to the integrated protocol (odds ratio[OR]:3.14, 95%confidence interval[CI]:1.19–8.27, P = 0.020). Stepwise logistic regression confirmed that cerebral complications were dramatically increased with unilateral ACP (OR:2.99, 95%CI:1.14–7.82, P = 0.025), while bilateral ACP had a significant impact on decreasing cerebral complications. Conclusions: Our integrated protocol effectively minimizes postoperative cerebral complications. Moderate hypothermia combined with BACP and measures to prevent brain debris could be adopted as an effective strategy for cerebral protection in TAAD surgery. [ABSTRACT FROM AUTHOR]

Background: The global burden of respiratory diseases such as influenza, tuberculosis, and viral pneumonia necessitates rapid, accurate diagnostic tools to improve healthcare responses. Current methods, including RT-PCR and chest radiography, face limitations in accuracy, speed, accessibility, and cost-effectiveness, especially in resource-constrained settings, often delaying treatment and increasing transmission. Methods: This study introduces an Enhanced Multi-Model Deep Learning (EMDL) approach to address these challenges. EMDL integrates an ensemble of five pre-trained deep learning models (VGG-16, VGG-19, ResNet, AlexNet, and GoogleNet) with advanced image preprocessing (histogram equalization and contrast enhancement) and a novel multi-stage feature selection and optimization pipeline (PCA, SelectKBest, Binary Particle Swarm Optimization (BPSO), and Binary Grey Wolf Optimization (BGWO)). Results: Evaluated on two independent chest X-ray datasets, EMDL achieved high accuracy in the multiclass classification of influenza, pneumonia, and tuberculosis. The combined image enhancement and feature optimization strategies significantly improved diagnostic precision and model robustness. Conclusions: The EMDL framework provides a scalable and efficient solution for accurate and accessible pulmonary disease diagnosis, potentially improving treatment efficacy and patient outcomes, particularly in resource-limited settings. [ABSTRACT FROM AUTHOR]

The specific root exudate, tripropylene glycol monomethyl ether (TPM), was significantly increased under the maize and peanut intercropping system. Exploring its effects on the growth and metabolic physiology of peanut plants could provide reference for exploring effective substances regulating the growth and development of peanut and promoting the quality and yield improvement of peanut. In this study, Qinghua No.6 peanut variety was used as experimental material, and the same volume of sterile water was added as control (CK). The dry matter accumulation, maximum photochemical efficiency, carbon and nitrogen metabolism enzyme activity and antioxidant properties of peanut plants under three tripropylene glycol monomethyl ether (TPM) adding gradient (T1:10.23μL/pot, T2:20.46μL/pot, T3: 40.92 μL/pot) were studied. The results showed that, compared with CK, T1 and T3 significantly reduced the above-ground dry matter weight of peanut plants. All TPM treatments significantly reduced the dry matter weight of underground part and maximum photochemical efficiency (Fv/Fm) of PSII. TPM supplementation significantly increased the activity of carbon and nitrogen metabolizing enzymes in peanut functional leaves, for detail, the activities of nitrate reductase (NR), sucrose synthetase (SS) and phosphate sucrose synthetase (SPS) in T1 treatment were increased by 6.49%-203.24% compared with CK, and Glutamine synthetase (GS) activity in T3 treatment was significantly increased by 39.81% compared with CK. The supplementation of TPM had stress effect on peanut plants. The content of malondialdehyde (MDA) was significantly increased by 17.32%-34.65% compared with CK. The activities of superoxide dismutase (SOD) and catalase (CAT) under T3 treatment were decreased by 75.82% and 75.74% compared with CK, respectively. The peroxidase (POD) activity under T1 treatment was significantly decreased by 30.43% compared with CK. According to the histochemical localization, T3 treatment significantly induced the accumulation of H2O2 and O2- in peanut plant functional leaves, and the content of O2- was significantly increased by 83.39% compared with CK. In conclusion, TPM can inhibit the growth of peanut plants, especially the underground part, reduce the potential maximum photosynthetic capacity (Fv/Fm) of leaves and inhibit the activities of antioxidant enzymes such as SOD, CAT and POD. However, peanut plants can reduce the damage caused by TPM by improving the activities of carbon and nitrogen metabolic enzymes such as NR, SS, SPS and GS. In this study, TPM is not suitable for peanut production. [ABSTRACT FROM AUTHOR]

This paper exploits the three eastward expansions of NATO after the Cold War as a quasi‐natural experiment to investigate the relationship between military alliance and trade. To identify the impact of alliance membership on trade, we adopt the difference‐in‐differences method to estimate a gravity model with global bilateral trade data from 1995 to 2015. The results show that joining NATO has a positive effect on new member countries' exports, as well as an enhancing effect on both imports and exports between old and new members. Further analysis of subdivided data reveals that formal alliance between old and new members boosts bilateral trade of security‐sensitive products, facilitates specialisation and helps mitigate trade disputes, suggesting that deepening of mutual strategic trust is a possible channel of influence. [ABSTRACT FROM AUTHOR]

A paradoxical phenomenon in China's transitional economy is that markets developed under predominant public ownership, which nevertheless has declined with the development of markets. Previous studies reveal that initial political and economic conditions of reform and fiscal decentralization gave rise to local public enterprises' leading role in early marketization. This paper explains the subsequent fall of such a role. Building and expanding on recent studies of privatization, we argue that market development and competition have constrained the abilities of local public enterprises to address revenue and employment imperatives, whereas local governments' sales-oriented growth strategies have exacerbated governance problems. Panel data are analyzed to provide provisional test of pertinent hypotheses. Key words--property rights, fiscal revenue, employment, governance problem, China, Asia

A lossy substrate model is developed to accurately simulate the measured RF noise of 80-nm super-100-GHz [f.sub.T] n-MOSFETs. A substrate RLC network built in the model plays a key role responsible for the nonlinear frequency response of noise in 1-18-GHz regime, which did not follow the typical thermal noise theory. Good match with the measured S-parameters, Y-parameters, and noise parameters before deembedding proves the lossy substrate model. The intrinsic RF noise can be extracted easily and precisely by the lossy substrate deembedding using circuit simulation. The accuracy has been justified by good agreement in terms of [I.sub.d], [g.sub.m], Y-parameters, and [f.sub.T] under a wide range of bias conditions and operating frequencies. Both channel thermal noise and resistance induced excess noises have been implemented in simulation. A white noise [gamma] factor extracted to be higher than 2/3 accounts for the velocity saturation and channel length modulation effects. The extracted intrinsic [NF.sub.min] as low as 0.6-0.7 dB at 10 GHz indicates the advantages of super-100 GHz [f.sub.T] offered by the sub-100-nm multifinger n-MOSFETs. The frequency dependence of noise resistance [R.sub.n] suggests the bulk RC coupling induced excess channel thermal noise apparent in 1-10-GHz regime. The study provides useful guideline for low noise and low power design by using sub-100-nm RF CMOS technology. Index Terms--Lossy substrate, noise, RF CMOS, RLC network.