Evidence of Carbon Uptake Associated with Vegetation Greening Trends in Eastern China

Persistent and widespread increase of vegetation cover, identified as greening, has been observed in areas of the planet over late 20th century and early 21st century by satellite-derived vegetation indices. It is difficult to verify whether these regions are net carbon sinks or sources by studying vegetation indices alone. In this study, we investigate greening trends in Eastern China (EC) and corresponding trends in atmospheric CO₂ concentrations. We used multiple vegetation indices including NDVI and EVI to characterize changes in vegetation activity over EC from 2003 to 2016. Gap-filled time series of column-averaged CO₂ dry air mole fraction (XCO₂) from January 2003 to May 2016, based on observations from SCIAMACHY, GOSAT, and OCO-2 satellites, were used to calculate XCO₂ changes during growing season for 13 years. We derived a relationship between XCO₂ and surface net CO₂ fluxes from two inversion model simulations, CarbonTracker and Monitoring Atmospheric Composition and Climate (MACC), and used those relationships to estimate the biospheric CO₂ flux enhancement based on satellite observed XCO₂ changes. We observed significant growing period (GP) greening trends in NDVI and EVI related to cropland intensification and forest growth in the region. After removing the influence of large urban center CO₂ emissions, we estimated an enhanced XCO₂ drawdown during the GP of −0.070 to −0.084 ppm yr⁻¹. Increased carbon uptake during the GP was estimated to be 28.41 to 46.04 Tg C, mainly from land management, which could offset about 2–3% of EC’s annual fossil fuel emissions. These results show the potential of using multi-satellite observed XCO₂ to estimate carbon fluxes from the regional biosphere, which could be used to verify natural sinks included as national contributions of greenhouse gas emissions reduction in international climate change agreements like the UNFCC Paris Accord

Fast and Efficient Boolean Matrix Factorization by Geometric Segmentation

Boolean matrix has been used to represent digital information in many fields, including bank transaction, crime records, natural language processing, protein-protein interaction, etc. Boolean matrix factorization (BMF) aims to find an approximation of a binary matrix as the Boolean product of two low rank Boolean matrices, which could generate vast amount of information for the patterns of relationships between the features and samples. Inspired by binary matrix permutation theories and geometric segmentation, we developed a fast and efficient BMF approach, called MEBF (Median Expansion for Boolean Factorization). Overall, MEBF adopted a heuristic approach to locate binary patterns presented as submatrices that are dense in 1's. At each iteration, MEBF permutates the rows and columns such that the permutated matrix is approximately Upper Triangular-Like (UTL) with so-called Simultaneous Consecutive-ones Property (SC1P). The largest submatrix dense in 1 would lie on the upper triangular area of the permutated matrix, and its location was determined based on a geometric segmentation of a triangular. We compared MEBF with other state of the art approaches on data scenarios with different density and noise levels. MEBF demonstrated superior performances in lower reconstruction error, and higher computational efficiency, as well as more accurate density patterns than popular methods such as ASSO, PANDA and Message Passing. We demonstrated the application of MEBF on both binary and non-binary data sets, and revealed its further potential in knowledge retrieving and data denoising

Cumulative live birth rates and birth outcomes after IVF/ICSI treatment cycles in young POSEIDON patients: A real-world study

ObjectiveThe aim of this study was to describe the cumulative live birth rates (CLBRs) of young women with or without low prognosis according to the POSEIDON criteria after IVF/ICSI cycles and to investigate whether the diagnosis of low prognosis increases the risk of abnormal birth outcomes.DesignRetrospective study.SettingA single reproductive medicine center.PopulationFrom January 2016 to October 2020, there were 17,893 patients (<35 years) involved. After screening, 4,105 women were included in POSEIDON group 1, 1,375 women were included in POSEIDON group 3, and 11,876 women were defined as non-POSEIDON.Intervention(s)Baseline serum AMH level was measured on the D2–D3 of menstrual cycle before IVF/ICSI treatment.Main outcome measure(s)Cumulative live birth rate (CLBR), birth outcomes.Result(s)After four stimulation cycles, the CLBRs in POSEIDON group 1, POSEIDON group 3, and non-POSEIDON group reached 67.9% (95% CI, 66.5%–69.3%), 51.9% (95% CI, 49.2%–54.5%), and 79.6% (95% CI, 78.9%–80.3%), respectively. There was no difference in gestational age, preterm delivery, cesarean delivery, and low birth weight infants between the three groups, but macrosomia was significantly higher in non-POSEIDON group, after adjusting for maternal age and BMI.Conclusion(s)The POSEIDON group shows lower CLBRs than the non-POSEIDON group in young women, while the risk of abnormal birth outcomes in the POSEIDON group will not increase

Morphological diversity of single neurons in molecularly defined cell types.

Dendritic and axonal morphology reflects the input and output of neurons and is a defining feature of neuronal types1,2, yet our knowledge of its diversity remains limited. Here, to systematically examine complete single-neuron morphologies on a brain-wide scale, we established a pipeline encompassing sparse labelling, whole-brain imaging, reconstruction, registration and analysis. We fully reconstructed 1,741 neurons from cortex, claustrum, thalamus, striatum and other brain regions in mice. We identified 11 major projection neuron types with distinct morphological features and corresponding transcriptomic identities. Extensive projectional diversity was found within each of these major types, on the basis of which some types were clustered into more refined subtypes. This diversity follows a set of generalizable principles that govern long-range axonal projections at different levels, including molecular correspondence, divergent or convergent projection, axon termination pattern, regional specificity, topography, and individual cell variability. Although clear concordance with transcriptomic profiles is evident at the level of major projection type, fine-grained morphological diversity often does not readily correlate with transcriptomic subtypes derived from unsupervised clustering, highlighting the need for single-cell cross-modality studies. Overall, our study demonstrates the crucial need for quantitative description of complete single-cell anatomy in cell-type classification, as single-cell morphological diversity reveals a plethora of ways in which different cell types and their individual members may contribute to the configuration and function of their respective circuits

Developmental pathways of depressive symptoms via parenting, self-evaluation and peer relationships in young people from 3 to 17 years old: evidence from ALSPAC.

PURPOSE: Self-evaluation and interpersonal factors are theoretically and empirically linked to depression in young people. An improved understanding of the multifactorial developmental pathways that explain how these factors predict depression could inform intervention strategies. METHODS: Using structural equation modeling, this study explored whether self-evaluation and interpersonal factors were associated with adolescent depressive symptoms in a population-based sample (n = 11,921; Avon Longitudinal Study of Parents and Children, ALSPAC), across four development stages: early and late childhood plus early and middle adolescence from 3 to 17 years old. RESULTS: Early good parenting practices predicted self-esteem, fewer peer difficulties, good friendships and fewer depressive symptoms in late childhood development outcomes. Higher self-esteem and less negative self-concept mediated the effect of early good parenting practice on reduced depressive symptoms in middle adolescence. The hypothesized erosion pathway from depressive symptoms in late childhood via higher levels of negative self-concept in early adolescence to depressive symptoms in middle adolescence was also confirmed. Additionally, peer difficulties played a mediation role in developing depressive symptoms. Contrary to the hypothesis, poor friendships predicted fewer depressive symptoms. The analysis supported a developmental pathway in which good parenting practices in early childhood led to fewer peer difficulties in late childhood and to less negative self-concept in early adolescence, which in turn predicted fewer depressive symptoms in middle adolescence. CONCLUSION: The social-developmental origin of youth depressive symptoms was supported via the effect of peer relationships in late childhood on self-evaluation in early adolescence

Codes_and_data.zip

The codes and data used for creating figures.</p

Challenges and opportunities of chemiresistors based on microelectromechanical systems for chemical olfaction

Microelectromechanical-system (MEMS)-based semiconductor gas sensors are considered one of the fastest-growing, interdisciplinary high technologies during the post-Moore era. Modern advancements within this arena include wearable electronics, Internet of Things, and artificial brain-inspired intelligence, among other modalities, thus bringing opportunities to drive MEMS-based gas sensors with higher performance, lower costs, and wider applicability. However, the high demand for miniature and micropower sensors with unified processes on a single chip imposes great challenges. This review focuses on recent developments and pitfalls in MEMS-based micro- and nanoscale gas sensors and details future trends. We also cover the background of the topic, seminal efforts, current applications and challenges, and opportunities for next-generation systems.Agency for Science, Technology and Research (A*STAR)Ministry of Education (MOE)Submitted/Accepted versionThe authors gratefully acknowledge financial support from the National Natural Science Foundation of China (62074123), the PetroChina Innovation Foundation (2019D-5007-0410), the Singapore Agency for Science, Technology and Research (A*STAR) under the Manufacturing, Trade and Connectivity Individual Research Grant (M21K2c0105), and the Ministry of Education Singapore under its Academic Research Funds (RG3/21 and MOET2EP10120-0003)