Early-spring soil warming partially offsets the enhancement of alpine grassland aboveground productivity induced by warmer growing seasons on the Qinghai-Tibetan Plateau

Aims The response of vegetation productivity to global warming is becoming a worldwide concern. While most reports on responses to warming trends are based on measured increases in air temperature, few studies have evaluated long-term variation in soil temperature and its impacts on vegetation productivity. Such impacts are especially important for high-latitude or high-altitude regions, where low temperature is recognized as the most critical limitation for plant growth

Responses of Community Structure, Productivity and Turnover Traits to Long-Term Grazing Exclusion in a Semiarid Grassland on the Loess Plateau of Northern China

Grazing exclusion has been widely used for restoration of degraded grassland all over the world. Based on over a 30-year (from 1982 to 2011) vegetation survey and a 2-year (from 2013 to 2014) field decomposition experiment in Yunwu Mountain Grassland Nature Reserve on the Loess Plateau of China, responses of community structure and productivity and decomposition traits of dominant Stipa species (Stipa bungeana, Stipa grandis and Stipa przewalskyi) litters were determined to reveal the ecosystem cyclic process. Results showed that grassland coverage, plant density, Shannon-Wiener index and aboveground productivity changed in a hump pattern with peaks in 2002. Productivity was significantly positively correlated with mean annual temperature. The direction and magnitude about effects of climatic changes on productivity depended on phonological stages of plant community. Warming in early stage of growing season (April–May) contributed the increase of productivity, while temperature rise after the growing season (September–March in the next following year) was negatively correlated with productivity in the following year. Leaf litters of three Stipa species (S. bungeana, S. grandis and S. przewalskyi) had higher decomposition rates in the growing season than that in the nongrowing season. Nutrient-releasing pattern in litters of three Stipa species followed a different pattern: S. bungeana > S.grandis>S. przewalskyi. Considering productivity and decomposition traits, grazing exclusion promotes carbon sequestration of semiarid grassland, while adjustments in nutrient cycling might explain fluctuations of community structure

Modification in Grassland Ecology under the Influence of Changing Climatic and Land Use Conditions

Grasslands are important terrestrial ecosystems in China, which are mainly distributed in arid and semiarid regions. Based on the multiyear field experiments in the semiarid grassland, the effects of land use practices on grassland above- and belowground community characteristics were investigated. In addition, how the annual climate factors regulate grassland productivity was also studied to detect critical periods for grass growth. Results showed that grazing exclusion increased grassland root biomass, root length density and root surface area with declining plant species richness. After grazing exclusion, with perennial bunchgrasses being predominant in root community all the time, proportion of perennial rhizome grasses increased and proportion of perennial forbs declined. Clipping significantly decreased the annual mean soil respiration and its components. The root respiration was more sensitive to clipping than microbial respiration. Temperature increments during the early stage of the growing season (April–May) were positively correlated with aboveground productivity. However, hot and dry summer (June–July) strongly inhibited aboveground productivity. Impacts of drought and heat in August on productivity were negligible. Increased temperature and precipitation during the senescence period (September–October) and a warmer dormancy phase (November–March) were negatively correlated with productivity in the following year, while precipitation during the dormancy period had no detectable effects

Vascular changes of the choroid and their correlations with visual acuity in diabetic retinopathy

ObjectiveTo investigate changes in the choroidal vasculature and their correlations with visual acuity in diabetic retinopathy (DR).MethodsThe cohort was composed of 225 eyes from 225 subjects, including 60 eyes from 60 subjects with healthy control, 55 eyes from 55 subjects without DR, 46 eyes from 46 subjects with nonproliferative diabetic retinopathy (NPDR), 21 eyes from 21 subjects with proliferative diabetic retinopathy (PDR), and 43 eyes from 43 subjects with clinically significant macular edema (CSME). Swept-source optical coherence tomography (SS-OCT) was used to image the eyes with a 12-mm radial line scan protocol. The parameters for 6-mm diameters of region centered on the macular fovea were analyzed. Initially, a custom deep learning algorithm based on a modified residual U-Net architecture was utilized for choroidal boundary segmentation. Subsequently, the SS-OCT image was binarized and the Niblack-based automatic local threshold algorithm was employed to calibrate subfoveal choroidal thickness (SFCT), luminal area (LA), and stromal area (SA) by determining the distance between the two boundaries. Finally, the ratio of LA and total choroidal area (SA + LA) was defined as the choroidal vascularity index (CVI). The choroidal parameters in five groups were compared, and correlations of the choroidal parameters with age, gender, duration of diabetes mellitus (DM), glycated hemoglobin (HbA1c), fasting blood sugar, SFCT and best-corrected visual acuity (BCVA) were analyzed.ResultsThe CVI, SFCT, LA, and SA values of patients with DR were found to be significantly lower compared to both healthy patients and patients without DR (P < 0.05). The SFCT was significantly higher in NPDR group compared to the No DR group (P < 0.001). Additionally, the SFCT was lower in the PDR group compared to the NPDR group (P = 0.014). Furthermore, there was a gradual decrease in CVI with progression of diabetic retinopathy, reaching its lowest value in the PDR group. However, the CVI of the CSME group exhibited a marginally closer proximity to that of the NPDR group. The multivariate regression analysis revealed a positive correlation between CVI and the duration of DM as well as LA (P < 0.05). The results of both univariate and multivariate regression analyses demonstrated a significant positive correlation between CVI and BCVA (P = 0.003).ConclusionChoroidal vascular alterations, especially decreased CVI, occurred in patients with DR. The CVI decreased with duration of DM and was correlated with visual impairment, indicating that the CVI might be a reliable imaging biomarker to monitor the progression of DR

Above-Curie-temperature ultrafast terahertz emission and spin current generation in a 2D superlattice (Fe3GeTe2/CrSb)3

The increasing demand for denser information storage and faster data processing has fueled a keen interest in exploring spin currents up to terahertz (THz) frequencies. Emergent 2D intrinsic magnetic materials constitute a novel and highly controllable platform to access such femtosecond spin dynamics at atomic layer thickness. However, the function of 2D van der Waals magnets are limited by their Curie temperatures, which are usually low. Here, in a 2D superlattice (Fe3GeTe2/CrSb)3, we demonstrate ultrafast laser-induced spin current generation and THz radiation at room temperature, overcoming the challenge of the Curie temperature of Fe3GeTe2 being only 206 K. In tandem with time-resolved magneto-optical Kerr effect measurements and first-principles calculations, we further elucidate the origin of the spin currents—a laser-enhanced proximity effect manifested as a laser-induced reduction of interlayer distance and enhanced electron exchange interactions, which causes transient spin polarization in the heterostructure. Our findings present an innovative, magnetic-element-free route for generating ultrafast spin currents within the 2D limit, underscoring the significant potential of laser THz emission spectroscopy in investigating laser-induced extraordinary spin dynamics

Precursor prioritization for p-cymene production through synergistic integration of biology and chemistry

The strategy of synergistic application of biological and chemical catalysis is an important approach for efficiently converting renewable biomass into chemicals and fuels. In particular, the method of determining the appropriate intermediate between the two catalytic methods is critical. In this work, we demonstrate p-cymene production through the integration of biosynthesis and heterogenous catalysis and show how a preferred biologically derived precursor could be determined. On the biological side, we performed the limonene and 1,8-cineole production through the mevalonate pathway. Titers of 0.605 g/L and a 1.052 g/L were achieved, respectively. This difference is in agreement with the toxicity of these compounds toward the producing microorganisms, which has implications for subsequent development of the microbial platform. On the heterogeneous catalysis side, we performed the reaction with both biological precursors to allow for direct comparison. Using hydrogenation/dehydrogenation metals on supports with acid sites, both limonene and 1,8-cineole were converted to p-cymene with similar yields under equivalent reaction conditions. Thus, we could determine that the most promising strategy would be to target 1,8-cineole, the higher titer and lower toxicity bio-derived precursor with subsequent catalytic conversion to p-cymene. We further optimized the biological production of 1,8-cineole via fed-batch fermentation and reached the titer of 4.37 g/L which is the highest known 1,8-cineole titer from microbial production. This work provides a valuable paradigm for early stage considerations to determine the best route for the high-efficiency production of a target biobased molecule using an integration of biology and chemistry

The Habitat of Astragalus adsurgens PALL. Populations Indigenous to Yunwu Mountain in the Loess Plateau, North-west China

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Transmission Roles of Symptomatic and Asymptomatic COVID-19 Cases: A Modelling Study

Coronavirus disease 2019 (COVID-19) asymptomatic cases are hard to identify, impeding transmissibility estimation. The value of COVID-19 transmissibility is worth further elucidation for key assumptions in further modelling studies. Through a population-based surveillance network, we collected data on 1342 confirmed cases with a 90-days follow-up for all asymptomatic cases. An age-stratified compartmental model containing contact information was built to estimate the transmissibility of symptomatic and asymptomatic COVID-19 cases. The difference in transmissibility of a symptomatic and asymptomatic case depended on age and was most distinct for the middle-age groups. The asymptomatic cases had a 66.7% lower transmissibility rate than symptomatic cases, and 74.1% (95% CI 65.9–80.7) of all asymptomatic cases were missed in detection. The average proportion of asymptomatic cases was 28.2% (95% CI 23.0–34.6). Simulation demonstrated that the burden of asymptomatic transmission increased as the epidemic continued and could potentially dominate total transmission. The transmissibility of asymptomatic COVID-19 cases is high and asymptomatic COVID-19 cases play a significant role in outbreaks

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Modelling the Effects of Climatic Factors on the Biomass and Rodent Distribution in a Tibetan Grassland Region in China

To identify the main climatic factors from 2007 to 2009 that influence biomass and rodent distribution, 576 fixed sample plots within 81 million km2 of different climatic grassland in Tibet were monitored. The aboveground biomass, the total burrows, the active burrows, the burrow index, and the rodent density in the plots were measured yearly in October. The monthly precipitation and the average temperatures from April to November were obtained for four successive years (2006-2009). Correlative and modelling analyses between the aboveground biomass, the rodent density, and the climatic factors were performed. The results showed that biomass and rodent density were significantly correlated with the climatic factors. Using ridge regression analyses, models of the biomass and rodent density with respect to the monthly precipitations and average temperatures of the previous year were developed. The raw testing data demonstrated that the models can be used approximately to predict biomass and rodent density