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Ancient manganese (Mn) deposits are primarily characterized by the presence of Mn(II) carbonates that likely formed by the diagenetic reduction of precursor Mn(IV) oxides. As such, Precambrian sedimentary Mn deposits have been used as a line of evidence for the evolution of oxygen in Earth's surface environments. However, recent studies have shown that these Mn(II)-carbonates have the ability to directly accumulate within anoxic water columns, where free oxygen does not play a role in their formation. This alternative pathway casts uncertainty on the robustness of using ancient Mn deposits to constrain the redox fabric of the past marine water columns. Here, we investigate the Wafangzi Mn and Fe ore deposit from the 1.45 billion-year-old Tieling Formation, North China. The deposit contains Mn(II,III) mineral phases (hausmannite, braunite) as inclusions, or unreacted residues, trapped within Mn(II) carbonate (Ca-rhodochrosite). Some nodules and oolites of Mn(II) and Fe(II)-carbonate phases are also present and display a banded structure with concentric rings. Mn(III) oxide (manganite) is present in a paragenetic assemblage along with hematite and replacement textures with braunite. The negative carbon isotope composition (δ13C, –7‰ to –4‰) from Mn(II) carbonate samples in the Wafangzi Mn deposit which are distinct from that of contemporaneous seawater (~0‰), along with petrographic and speciation analyses, collectively suggest that the Mn(II,III)- and Fe(II)-bearing mineral phases formed through the diagenetic reduction of primary Mn(IV)/Fe(III) minerals coupled to the oxidation of organic matter. Therefore, the Wafangzi Mn deposit suggests the presence of sufficiently oxygenated marine waters, overlying anoxic ferruginous deeper waters with a transitional manganous water layer that could have driven the redox cycling of Mn, Fe, and C. Given the contemporaneous economic Mn deposits in the 1.45 Ga Ullawarra Formation in Western Australia, our findings imply the existence of a transient, and perhaps widespread, pulsed oxygenation event in the mid-Proterozoic oceans. [ABSTRACT FROM AUTHOR]

In tropical regions, lack of moisture-damage-resistant fillers in flexible pavements poses significant challenges for infrastructure development and maintenance. Hence, this study examined sawdust ash (SDA) for such purposes. SDA is abundant as agricultural waste in rice-producing countries like India and China. Durability assessment of SDA-enriched bituminous concrete (BC) against moisture damage is considered as state-of-art in this investigation. To implement this study, numerous laboratory tests were carried out. First, the Marshall test was carried out to estimate the optimal bitumen content (OBC) and several Marshall properties, including Marshall volumetric properties. After that, a modified Marshall immersion test, energy loss ratio test, ultrasonic pulse velocity (UPV) test, indirect tensile strength test (ITS), resilient modulus ratio test, and rutting resistance test were done to execute this investigation. Furthermore, the morphological characteristics of the studied filler were investigated by atomic force microscopy (AFM). The experimental result shows that the 8% SDA-enriched BC mix may be applied in low-volume roads in tropical regions like India with 86.94% structural integrity for the presence of ample amounts of calcium oxide (CaO), silicon oxide (SiO2), ferric oxide (Fe2O3), and higher loss on ignition value in that ash. Moreover, the results have shown that the mixes containing 8% SDA perform exceptionally well against moisture damage with the highest energy loss ratio (63.27%) and dynamic modulus (12.1 MPa) after 14 days of immersion. Similarly, this type of mix delivers the highest tensile strength ratio (96.27%) and resilient modulus ratio (89.21%), with minimum rutting depth (9.55 mm), and performs not only in terms of moisture resistance but also in its ability to withstand rutting deformation significantly. These results make it a promising choice for asphalt pavements, to mitigate the detrimental effects of both rutting and moisture on the overall durability and longevity of the road. [ABSTRACT FROM AUTHOR]

Changes in tree species composition are one of the key aspects of forest succession. In recent decades, significant changes have occurred in the tree species composition of subtropical forests in China, with a decrease in coniferous trees and an increase in broad-leaved trees. This study focuses on Zhejiang Province, located in the subtropical region of China, and utilizes seven inventories from the National Continuous Forest Inventory (NCFI) System spanning 30 years (1989-2019) for modeling and analysis. We categorized tree species into three groups: pine, fir, and broadleaf. We used the proportion of biomass in a sample plot as a measure of the relative abundance of each tree species group. A novel nonlinear difference equation system (NDES) model was proposed. A NDES model was established based on two consecutive survey datasets. A total of six models were established in this study. The results indicated that during the first two re-examination periods (1989-1994, 1994-1999), there was significant fluctuation in the trend of tree species abundance, with no consistent pattern of change. During the latter four re-examination periods (1999-2004, 2004-2009, 2009-2014, 2014-2019), a consistent trend was observed, whereby the abundance of the pine group and the fir group decreased while the abundance of the broad-leaved group increased. Moreover, over time, this pattern became increasingly stable. Although the abundances of the pine group and the fir group have been steadily declining, neither group is expected to become extinct. The NDES model not only facilitates short-term, medium-term, and even long-term predictions but also employs limit analysis to reveal currently obscure changing trends in tree species composition. [ABSTRACT FROM AUTHOR]

Crop phenology indicators provide essential information on crop growth phases, which are highly required for agroecosystem management and yield estimation. Previous crop phenology studies were mainly conducted using coarse-resolution (e.g., 500 m) satellite data, such as the moderate resolution imaging spectroradiometer (MODIS) data. However, precision agriculture requires higher resolution phenology information of crops for better agroecosystem management, and this requirement can be met by long-term and fine-resolution Landsat observations. In this study, we generated the first national maize phenology product with a fine spatial resolution (30 m) and a long temporal span (1985–2020) in China, using all available Landsat images on the Google Earth Engine (GEE) platform. First, we extracted long-term mean phenological indicators using the harmonic model, including the v3 (i.e., the date when the third leaf is fully expanded) and the maturity phases (i.e., when the dry weight of maize grains first reaches the maximum). Second, we identified the annual dynamics of phenological indicators by measuring the difference in dates when the vegetation index in a specific year reaches the same magnitude as its long-term mean. The derived maize phenology datasets are consistent with in situ observations from the agricultural meteorological stations and the PhenoCam network. Besides, the derived fine-resolution phenology dataset agrees well with the MODIS phenology product regarding the spatial patterns and temporal dynamics. Furthermore, we observed a noticeable difference in maize phenology temporal trends before and after 2000, which is likely attributable to the changes in temperature and precipitation, which further altered the farming activities. The extracted maize phenology dataset can support precise yield estimation and deepen our understanding of the future agroecosystem response to global warming. The data are available at 10.6084/m9.figshare.16437054 (Niu et al., 2021). [ABSTRACT FROM AUTHOR]

Background: This study aimed to assess brain oxygenation status and cerebral autoregulation function in subjects with cognitive dysfunction. Methods: The Montreal Cognitive Assessment (MoCA) was applied to divide the subjects into three groups: cognitive impairment (Group CI, 72.50 ± 10.93 y), mild cognitive impairment (Group MCI, 72.02 ± 9.90 y), and normal cognition (Group NC, 70.72 ± 7.66 y). Near-infrared spectroscopy technology and a non-invasive blood pressure device were used to simultaneously measure changes in cerebral tissue oxygenation signals in the bilateral prefrontal lobes (LPFC/RPFC) and arterial blood pressure (ABP) signals from subjects in the resting state (15 min). The coupling between ABP and cerebral oxyhemoglobin concentrations (Δ [O2Hb]) was calculated in very-low-frequency (VLF, 0.02–0.07 Hz) and low-frequency (LF, 0.07–0.2 Hz) bands based on the dynamical Bayesian inference approach. Pearson correlation analyses were used to study the relationships between MoCA scores, tissue oxygenation index, and strength of coupling function. Results: In the interval VLF, Group CI (p = 0.001) and Group MCI (p = 0.013) exhibited significantly higher coupling strength from ABP to Δ [O2Hb] in the LPFC than Group NC. In the interval LF, coupling strength from ABP to Δ [O2Hb] in the LPFC was significantly higher in Group CI than in Group NC (p = 0.001). Pearson correlation results showed that MoCA scores had a significant positive correlation with the tissue oxygenation index and a significant negative correlation with the coupling strength from ABP to Δ [O2Hb]. Conclusion: The significantly increased coupling strength may be evidence of impaired cerebral autoregulation function in subjects with cognitive dysfunction. The Pearson correlation results suggest that indicators of brain oxygenation status and cerebral autoregulation function can reflect cognitive function. This study provides insights into the mechanisms underlying the pathophysiology of cognitive impairment and provides objective indicators for screening cognitive impairment in the elderly population. [ABSTRACT FROM AUTHOR]

Understanding the spatio-temporal variations of temperature and precipitation in the arid and semiarid region of China (ASRC) is of great significance for promoting regional eco-environmental protection and policy-making. In this study, the annual and seasonal spatio-temporal patterns of change in average temperature and precipitation and their influencing factors in the ASRC were analyzed using the Mann-Kendall test, linear tendency estimation, accumulative anomaly and the Pearson's correlation coefficient. The results showed that both annual average temperature and average annual precipitation increased in the ASRC during 1951–2019. The temperature rose by about 1.93°C and precipitation increased by about 24 mm. The seasonal average temperature presented a significant increase trend, and the seasonal precipitation was conspicuous ascension in spring and winter. The spatio-temporal patterns of change in temperature and precipitation differed, with the southwest area showing the most obvious variation in each season. Abrupt changes in annual and seasonal average temperature and precipitation occurred mainly around the 1990s and after 2000, respectively. Atmospheric circulation had an important effect on the trends and abrupt changes in temperature and precipitation. The East Asian summer monsoon had the largest impact on the trend of average annual temperature, as well as on the abrupt changes of annual average temperature and precipitation. Temperature and precipitation changes in the ASRC were influenced by long-term and short-term as well as direct and indirect anthropogenic and natural factors. This study identifies the characteristics of spatio-temporal variations in temperature and precipitation in the ASRC and provides a scientific reference for the formulation of climate change responses. [ABSTRACT FROM AUTHOR]