Search

We investigate a robust equilibrium investment-reinsurance problem for n ambiguity-averse competitive insurers, n ≥ 2 . Each insurer is allowed to purchase proportional reinsurance and invest in a risk-free asset and a risky asset. Each insurer aims to maximize the expected utility of a weighted relative terminal wealth with respect to the other competitors. In this article, the risky asset is assumed to follow a general and flexible model: the square root factor process. Following the game theory approach, we derive the closed solutions of the robust equilibrium investment-reinsurance strategies. Moreover, the verification theorem is provided in this article. Finally, we demonstrate some numerical analyses and give the economic explanations as well. [ABSTRACT FROM AUTHOR]

Rare earth ion doped fluorescent powder, as a key material for the application of white light-emitting diodes (w-LEDs), green components often face the problem of poor thermal stability. Developing fluorescent powders with excellent thermal stability is of great significance. This article synthesized a series of Gd 5 Si 2 BO 13 :Tb3+ blue phosphors and non rare earth Bi3+ ion doped Gd 5 Si 2 BO 13 :Tb3+ green phosphors using a high-temperature solid-phase method. The phase structure and photoluminescence characteristics of the sample were analyzed in detail through XRD, excitation and emission spectra, as well as attenuation curves. The energy transfer from Bi3+ to Tb3+ was studied and confirmed through photoluminescence spectra and lifetime decay curves. Research has shown that the addition of Bi3+ significantly enhances the emission intensity of Tb3+ in the near ultraviolet range, and tunes the emission color of Gd 5 Si 2 BO 13 :Bi3+ and Tb3+ from blue to green, attributed to the energy transfer from Bi3+ to Tb3+. In addition, the addition of Bi3+ increased the thermal stability of single doped fluorescent powder Gd 5 Si 2 BO 13 :0.55Tb3+ from 88.21 % to 92.82 % at 150 °C, proving that the Gd 5 Si 2 BO 13 :Bi3+ and Tb3+ samples have good thermal stability. This study not only deepens our understanding of the new main material Gd 5 Si 2 BO 13 , but also provides a reference for the development of green phosphors with excellent thermal stability. [Display omitted] • A series of Gd 5 Si 2 BO 13 :Bi3+, Tb3+ phosphors were successfully synthesized. • The co-doped Gd 5 Si 2 BO 13 :Bi3+, Tb3+ phosphors have excellent emission intensity and thermal stability. • The Gd 5 Si 2 BO 13 :Bi3+, Tb3+ green phosphors is promising for use in high-power LED lighting devices and backlight displays. [ABSTRACT FROM AUTHOR]

[Display omitted] • The northwest area of the BTSSCP suffered severe dust-affected zones based on the dust flow trajectory. • The ESs in severe dust-affected areas were relatively poor. • ESs and the dust flow trajectory were integrated to identify ecological governance zones. • Governance suggestions were proposed for the ecological management zone combined with the driving forces. Achieving ecological conservation and governance based on ecosystem services (ESs) can balance regional ecological protection and development, which is of great significance for sustainable development. Existing research has mainly focused on the extraction of priority ecological conservation areas, thereby neglecting to consider the classification and management of ecological engineering areas. To improve regional ecological governance, we combine ESs and dust movement trajectory, using the Beijing-Tianjin Sandstorm Source Control Project (BTSSCP) as the research object to generate watersheds' ecological governance zones. Six ESs were assessed to determine ecological zones. Trajectory simulation of dust movement, using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and potential source contribution function, was used to determined zones affected by dust. By combining these two aspects, five main ecological governance clusters were identified. We found that: (1) the area with low ESs in the northwest of the BTSSCP suffered from severe dust impacts; (2) slight dust-affected zones were mainly distributed in the eastern of the BTSSCP, and in the area, ESs gradually decreased from south to north; (3) ESs in the region was primarily influenced by natural factors and the influencing factors of ESs vary among different zones. These findings will not only contribute to the overall planning and governance of the BTSSCP, but can offer general guidance for the formulation of targeted ecological protection and restoration measures in other areas. [ABSTRACT FROM AUTHOR]

Objective: Investigating the utility of serum exosomal markers CA125, HE4, and C5a, both individually and in combination, for distinguishing between benign and malignant ovarian tumors. Methods: In this study, we selected a total of 234 patients diagnosed with ovarian tumors, including 34 with malignant tumors, 10 with borderline ovarian tumors, and 190 with benign tumors. This study conducted comparisons of exosomal levels of CA125, HE4, and C5a among distinct groups, as well as making comparisons between serum and exosomal levels of CA125 and HE4. Furthermore, the diagnostic performance was assessed through Receiver Operating Characteristic (ROC) curve analysis. The Area Under the Curve (AUC) was computed, and a comparative evaluation of sensitivity and specificity was conducted to ascertain their effectiveness in determining the nature of ovarian tumors across different markers. Results: Serum CA125 and HE4 levels, the ROMA index, exosomal CA125, HE4, C5a levels, and their combined applied value (OCS value) were notably elevated in the ovarian non-benign tumor group compared to the benign tumor group, with statistical significance (P < 0.05). Exosomal and serum levels of CA125 and HE4 exhibited a positive correlation, with concentrations of these markers in serum surpassing those in exosomes. The combined OCS (AUC = 0.871) for CA125, HE4, and C5a in exosomes demonstrated superior sensitivity (0.773) and specificity (0.932) compared to serum tumor markers (CA125, HE4) and the ROMA index. The tumor stage represents an autonomous risk factor influencing the prognosis of individuals with ovarian malignancies. Conclusion: The stage of ovarian malignancy is an independent risk factor for its prognosis. The combination of exosomal CA125, HE4 and C5a has a higher clinical value for the identification of the nature of ovarian tumours. [ABSTRACT FROM AUTHOR]

The Drosophila hindgut is a classical model to study organogenesis. The adult hindgut originates from the precursor cells in the larval hindgut. However, the territory of these cells has still not been well determined. A ring of wingless (wg)-expressing cells lies at the anterior zone of both the larval and adult hindgut. The larval Wg ring was thought as a portion of precursor of the adult hindgut. By applying a cell lineage tracing tool (G-TRACE), we demonstrate that larval wg -expressing cells have no cell lineage contribution to the adult hindgut. Additionally, adult Wg ring cells do not divide and move posteriorly to replenish the hindgut tissue. Instead, we determine that the precursors of the adult pylorus and ileum are situated in the cubitus interruptus (ci)-expressing cells in the anterior zone, and deduce that the precursor stem cells of the adult rectum locate in the trunk region of the larval pylorus including hedgehog (hh)-expressing cells. Together, this research advances our understanding of cell lineage origins and the development of the Drosophila hindgut. [Display omitted] • Adult Wg ring cells do not divide and move posteriorly to replenish the hindgut tissue. • Larval Wg ring in the anterior zone of hindgut was not the precursors of adult hindgut. • The progenitors of the adult pylorus and ileum were situated in the ci expressing cells in the larval anterior zone. • The progenitors of the adult rectum were located in the trunk region of pylorus including hh expressing cells. [ABSTRACT FROM AUTHOR]

Shrub encroachment, characterized by the proliferation of shrubs into grasslands, is a challenge faced by grasslands worldwide that significantly impacts livestock production and ecosystem functions. Rapid and accurate estimation of shrub dominance is important for understanding changes in plant community structures and formulating grassland management policies. However, the limited spatial resolution of commonly used satellite imagery poses a challenge when estimating shrub dominance at the landscape scale. The rapid development of Unoccupied Aerial Vehicles (UAVs) has opened up new opportunities for cross-scale observations of shrub encroachment in grasslands by effectively bridging the scale gap between ground sampling and satellite image pixels while reducing the required groundwork. This study utilized ground reference data, UAV data (RGB, hyperspectral, and LiDAR), and satellite data (Sentinel-1 and Sentinel-2) to estimate shrub and total above-ground biomass (AGB) in temperate grasslands to map the shrub dominance. First, UAV data were applied at the plot scale for the classification of shrub and herbaceous vegetation using the maximum entropy model (MaxEnt), estimation of shrub AGB by employing the vegetation index weighted canopy volume model (CVM VI), and estimation of herbaceous AGB based on the partial least squares regression (PLSR). Second, UAV AGB mapping results were upscaled as samples at the landscape scale and integrated with satellite imagery to establish the shrub and total AGB models using the extreme gradient boosting (XGBoost). Finally, shrub dominance, represented as shrub AGB/total AGB, was mapped across the study area. We found that at the plot scale, the MaxEnt model achieved an overall accuracy of 0.990 for object-based classification. The CVM VI combined with canopy height model and narrow-band vegetation index achieved the highest accuracy for estimating shrub AGB (R2 = 0.821, RMSE = 30.1 g). The PLSR combined with features derived from all UAV data achieved the highest accuracy for estimating herbaceous AGB (R2 = 0.856, RMSE = 9.1 g/m2). At the landscape scale, the XGBoost achieved high accuracy for estimating both the shrub AGB (R2 = 0.719, RMSE = 4.2 g/m2) and total AGB (R2 = 0.961, RMSE = 5.0 g/m2). The high-precision mapping results further facilitate the generation of shrub dominance maps at a landscape scale. This study presents a more accurate and efficient framework for mapping shrub AGB, total AGB, and shrub dominance using multi-scale remote sensing data, which offers new approaches for large-scale grassland AGB mapping and monitoring of shrub encroachment in grasslands. • Multisensory UAV data were evaluated for shrub and herbaceous AGB estimation at the plot scale. • SAR and multispectral satellite data were used to map AGB and shrub dominance at the landscape scale. • Our multi-scale framework outperformed the traditional AGB estimation method. • Assessing shrub dominance is important for understanding shrub encroachment. [ABSTRACT FROM AUTHOR]

Aboveground biomass (AGB) in grasslands directly reflects the net primary productivity, making it a sensitive indicator of grassland resource quality and ecological degradation. Accurately estimating AGB over large regions to reveal long-term AGB evolution trends remains a formidable challenge. In this study, we divided Inner Mongolia Autonomous Region (IMAR) grasslands into three study regions based on their spatial distribution of grassland types. We combined remote sensing data with ground-based sample data collected over the past 19 years from 6114 field plots using the Google Earth Engine platform. We constructed random forest (RF) and traditional regression AGB inversion models for each region and selected the best-performing model through accuracy assessment to estimate IMAR grassland AGB for the period 2000–2022. We also examined the trends in AGB changes and identified the driving forces affecting IMAR grasslands through the application of Theil-Sen estimation, Mann-Kendall trend analysis, and the Geodetector model. The main findings are as follows: (1) Compared with the univariate parametric traditional regression model, the AGB monitoring accuracy of the multivariate non-parametric RF model in the three study regions increased by 5.94%, 5.08% and 19.14%, respectively. (2) The average AGB per unit area of IMAR grasslands from 2000 to 2022 was 731.41 kg/hm2, with alpine meadow having the highest average AGB (1271.70 kg/hm2) and temperate grassland desertification having the lowest (469.06 kg/hm2). IMAR grasslands exhibited an overall increasing trend in AGB over the past 23 years (6.01 kg/hm2•yr), with the increasing trend covering 83.52% of the grassland area and the decreasing trend covering 16.48%. (3) Spatially, IMAR grassland AGB showed a gradual decline from northeast to southwest and exhibited an increasing trend with increasing longitude (45.423 kg/hm2 per degree) and latitude (71.9 kg/hm2 per degree). (4) Meteorological factors were the most significant factors affecting IMAR grassland AGB, with precipitation (five-year average q value of 0.61) being the most prominent. In the western part of IMAR, where precipitation is consistently limited throughout the year, the primary drivers of influence were human activities, with particular emphasis on the number of livestock (with a five-year average q value of 0.44). It is evident that reducing human activity disturbance and pressure in fragile grassland areas or implementing near-natural restoration measures will be beneficial for the sustainable development of grassland ecosystems. The results of this research hold substantial reference importance for the protection and restoration of grasslands, the supervision and administration of grassland resources, as well as the development of policies related to grassland management. [Display omitted] • The aboveground biomass (AGB) of grasslands in IMAR increased over the past 23 years. • IMAR grassland AGB shows an upward trend with increasing longitude and latitude. • Precipitation is the main factor affecting grassland AGB in IMAR. • Human activities have a greater impact on the grassland AGB in western IMAR. [ABSTRACT FROM AUTHOR]

• NDVI represents photosynthetic phenology only in deciduous trees. • Gcc tracks photosynthetic phenology more accurately than GRVI at the canopy scale. • ɸ NPQ and ɸ f,D have great influences on the spectral signal changes of NIRv and PRI. • Good consistency was found between NIRv and PRI for predicting A max. Vegetation photosynthetic phenology is an important indicator to characterize the biological responses of terrestrial carbon cycle to climate change. Remote sensing-derived spectral indices have been used to estimate photosynthetic phenology of terrestrial ecosystems, yet there are large uncertainties due to differences in leaf structure and canopy function between evergreen and deciduous trees. In this study, we used in-situ measured meteorology, the maximum rate of leaf-level CO 2 assimilation (A max), chlorophyll fluorescence and canopy color changes in evergreen and deciduous species to evaluate and compare the abilities of spectral indices for photosynthetic phenology modeling. Seasonal variation in A max is used as a proxy for photosynthetic phenology. Several indices were used, including the normalized difference vegetation index (NDVI), near-infrared reflectance vegetation index (NIRv), photochemical reflectance index (PRI), chlorophyll/carotenoid index (CCI), green-red vegetation index (GRVI), and green chromaticity coordinates (Gcc). We found that NIRv and PRI estimated phenological periods for Cedrus deodara and three deciduous trees all differed from A max by less than 5 days, and all were linearly related to A max (R2 > 0.6). CCI had less potential for A max modeling, while NDVI had the largest error in predicting A max. Gcc was a more accurate proxy for photosynthetic phenology than GRVI at the canopy scale. In addition, we found that the variability of different spectral indices in tracking photosynthetic phenology of evergreen and deciduous species was related to non-photochemical quenching processes. Especially for the fraction of absorbed light quenched by dynamic NPQ (ɸ NPQ) and the fraction of absorbed light quenched by sustained NPQ (ɸ f,D), they contribute more than 40 % to the variations of the NIRv and PRI spectral signals. Therefore, NIRv and PRI provide powerful tools for monitoring photosynthetic phenology, and future exploration of NIR v and PRI at larger spatial scales will favor the global plant phenology and carbon uptake modeling. [ABSTRACT FROM AUTHOR]