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Rising atmospheric CO 2 ( C a ) can increase tree radial growth by increasing intrinsic water-use efficiency (iWUE). However, the effects of age on the response remain unknown, particularly for forests in remote areas such as China’s Tianshan Mountains. Here, we assessed age-dependent growth trends of Picea schrenkiana using tree-ring data from low and high elevations and two detrending methods to detect robust long-term trends. We developed age-dependent relationships between basal area increment (BAI) and iWUE based on size-class isolation and separated the contributions of climate variables and iWUE to radial growth. The juvenile trees showed growth increases over time, versus growth reductions in two older age classes. An overall negative trend existed for combined data from all age classes and elevations. iWUE increased in response to increasing C a for trees in all age groups at low and high elevations, with higher values in near-mature and mature trees (100 yr < age ≤ 160 yr) at the lower sites. However, age affected radial growth and its responses to climate and iWUE. For juvenile trees (≤60 yr), BAI increased during the study period, temperature in May-July and iWUE all have positive effects on the radial growth with significantly high contribution variance from iWUE. The smaller hydraulic constraints in juvenile trees may permit higher photosynthetic rates, reduced climatic sensitivity, and increased growth by CO 2 fertilization. For older trees, BAI decreased, possibly due to stomatal closure caused by warmer temperatures and decreasing hydraulic efficiency with increasing tree age; thus, increased iWUE could not outweigh environmental stresses. The trees at high and low elevations responded consistently to environmental changes, but with different response intensity. Thus, climate and cambial age together determined whether increased iWUE could increase radial growth and the potential CO 2 fertilization effect. These age-dependent growth responses should be accounted for when assessing responses of forest dynamics to climate change. [ABSTRACT FROM AUTHOR]

Stable hydrogen isotope ratios (δD) in tree rings are an attractive but still rarely explored terrestrial archive of past climatic information. Because the preparation of the cellulose nitrate for δD measurements requires more wood and a longer preparation time than preparation techniques for other isotopes in cellulose (δ 18 O or δ 13 C), it is challenging to obtain high-resolution records, especially for slow-growing trees at high elevations and in boreal regions. Here, we tested whether annually pooled samples of Qinghai spruce ( Picea crassifolia Kom.) trees from northwestern China provided results similar to those derived as the mean of individual measurements of the same trees and whether the resulting chronologies recorded useful climate information. Inter-tree variability of δD was higher than that of measured ring width for the same trees. We found higher and significant coherence between pooled and mean isotope chronologies than that among the individual series. It showed a logarithmic relationship between ring mass and δD; however, accounting for the influence of ring mass on δD values only slightly improved the strength of climatic signals in the pooled records. Tree-ring δD was significantly positively correlated with the mean, maximum, and minimum temperatures during the previous winter and with maximum temperature during the current August, and significantly negatively correlated with precipitation in the previous November to January and the current July. The winter climate signal seems to dominate tree-ring δD through the influence of large-scale atmospheric circulation patterns, i.e. the Arctic Oscillation. These results will facilitate reconstruction of winter atmospheric circulation patterns over northwestern China based on a regional tree-ring δD networks. [ABSTRACT FROM AUTHOR]

Smart speakers are becoming increasingly popular and permeate many aspects of human life. To improve the security of smart speakers, voice commands transmitted over a network are encrypted; however, user privacy issues related to smart speakers continue to emerge. In fact, attackers are still able to infer the content of a user's specific voice commands from encrypted traffic through machine learning methods to obtain private information for advertising or to carry out malicious attacks. This traffic analysis attack is referred to as a voice command fingerprinting attack. In recent years, research on improving the accuracy of voice command fingerprinting attacks has become a hot topic and remains a challenging task. To improve the accuracy of voice command fingerprinting attacks, we design a new method in this paper. We use an adaptive and dilated residual network to process spatial features. In addition, we find that using temporal features helps improve fingerprinting attack accuracy, and therefore design an attention-based bidirectional gated recurrent unit. Then, we effectively combine the two models. Our method achieves an accuracy greater than 93.36% in a closed-world scenario, which exceeds those of other state-of-the-art methods (2020 WiSec Wang et al.). In a more realistic open-world setting, our model is still effective, obtaining a true-positive rate of 99.50% and a false-positive rate of 0.1% compared to Sirinam et al.'s rates of 90.66% and 0.1%, respectively. We also demonstrate that our model has good generalizability, as our model can also be applied to website fingerprinting and outperforms 2018 CCS Sirinam et al. [ABSTRACT FROM AUTHOR]