Seasonal variability of sea surface pCO2 and air-sea CO2 flux in a high turbidity coastal ocean in the vicinity of the East China Sea

The sea surface partial pressure of CO2 (pCO2) and air-sea carbon flux in estuarine and bay areas, influenced by both natural and anthropogenic factors, remain poorly understood and inadequately assessed. This study, based on seasonal underway observations conducted in 2024, analyzed the seasonal variations in surface seawater pCO2 and air-sea CO2 flux in the high-turbidity coastal waters of Zhejiang, including Hangzhou Bay (HZB), Xiangshan Bay (XSB), Sanmen Bay (SMB), and the nearshore waters (NSW). The results indicate that the pCO2 in the study area ranged from 194 to 739 μatm throughout the year, exhibiting significant spatiotemporal heterogeneity. In HZB, the lowest pCO2 was observed in winter, averaging 453 μatm, whereas the values in spring and summer were around 600 μatm, with a subsequent decline to 481 μatm in autumn. In XSB, pCO2 reached its minimum in winter (194 μatm), attributed to vigorous biological activity, and peaked in spring, averaging 639 μatm. In SMB, pCO2 was relatively lower in autumn and winter (~470 μatm), and higher in spring and summer (~640 μatm). In the NSW, pCO2 was lower in winter and spring (~445 μatm), and increased to ~510 μatm in summer and autumn. The pCO2 was predominantly regulated by sea surface temperature and horizontal mixing, while other factors like biological activity also had significant impacts. The annual average CO2 flux was 6.0±3.7 mmol m-2 d-1 in HZB, 1.2±2.3 mmol m-2 d-1 in XSB, 7.0±3.2 mmol m-2 d-1 in SMB and 5.2±5.9 mmol m-2 d-1 in the NSW. Higher wind speeds in autumn and winter, coupled with elevated the pCO2 difference between the surface water and the atmosphere (ΔpCO2) in spring and summer, collectively drove the seasonal variations in CO2 flux. On an annual scale, both the estuarine and bay areas and the nearshore regions functioned as carbon sources

Titanium and zirconium complexes bearing new tridentate [OSO] bisphenolato-based ligands: synthesis, characterization and catalytic properties for alkene polymerization

Titanium and zirconium complexes with new tridentate [OSO] ligands were synthesized and studied as catalysts for olefin polymerization reactions.</p

Assessment of Vigilance Level during Work: Fitting a Hidden Markov Model to Heart Rate Variability

This study aimed to enhance the real-time performance and accuracy of vigilance assessment by developing a hidden Markov model (HMM). Electrocardiogram (ECG) signals were collected and processed to remove noise and baseline drift. A group of 20 volunteers participated in the study. Their heart rate variability (HRV) was measured to train parameters of the modified hidden Markov model for a vigilance assessment. The data were collected to train the model using the Baum–Welch algorithm and to obtain the state transition probability matrix A^ and the observation probability matrix B^. Finally, the data of three volunteers with different transition patterns of mental state were selected randomly and the Viterbi algorithm was used to find the optimal state, which was compared with the actual state. The constructed vigilance assessment model had a high accuracy rate, and the accuracy rate of data prediction for these three volunteers exceeded 80%. Our approach can be used in wearable products to improve their vigilance level assessment functionality or in other fields that have key positions with high concentration requirements and monotonous repetitive work