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Effects of different concentrations of biogas slurry (BS) were evaluated relative to vegetable cultivation. Five concentration levels of BS were used as organic fertilizer to grow Chinese cabbages (CA) by drip irrigation to study the effect of BS on the yield and quality. Each level was replicated three times and BS was used seven times. Results showed that the average plant height, fresh weight, dry weight, and soluble sugars and protein contents of Chinese cabbage under the T1 (BS 25%) treatment were optimal. Among them, dry weight per plant (3.53g), soluble sugar content (0.41%), and soluble protein content (0.0039%) were 1.74 times, 1.41 times, and 1.14 times more than under the CK treatment, respectively. In addition, the application of biogas slurry improved the physical and chemical properties of soil. Soil total nitrogen (TN) and available phosphorus (AP) content increased after the use of biogas slurry, and the soil total nitrogen and available phosphorus content increased with the increase in the concentration of the applied biogas slurry. The available potassium (AK) content of soil fluctuated with the concentration of biogas slurry. In addition, biogas slurry can properly improve soil pH. In conclusion, BS 25% was the best for the growth of CA and its quality, which provided scientific basis for biogas slurry as fertilizer.

Effects of different concentrations of biogas slurry (BS) were evaluated relative to vegetable cultivation. Five concentration levels of BS were used as organic fertilizer to grow Chinese cabbages (CA) by drip irrigation to study the effect of BS on the yield and quality. Each level was replicated three times and BS was used seven times. Results showed that the average plant height, fresh weight, dry weight, and soluble sugars and protein contents of Chinese cabbage under the T1 (BS 25%) treatment were optimal. Among them, dry weight per plant (3.53g), soluble sugar content (0.41%), and soluble protein content (0.0039%) were 1.74 times, 1.41 times, and 1.14 times more than under the CK treatment, respectively. In addition, the application of biogas slurry improved the physical and chemical properties of soil. Soil total nitrogen (TN) and available phosphorus (AP) content increased after the use of biogas slurry, and the soil total nitrogen and available phosphorus content increased with the increase in the concentration of the applied biogas slurry. The available potassium (AK) content of soil fluctuated with the concentration of biogas slurry. In addition, biogas slurry can properly improve soil pH. In conclusion, BS 25% was the best for the growth of CA and its quality, which provided scientific basis for biogas slurry as fertilizer.

Abstract Although perovskite light-emitting diodes (PeLEDs) have seen unprecedented development in device efficiency over the past decade, they suffer significantly from poor operational stability. This is especially true for blue PeLEDs, whose operational lifetime remains orders of magnitude behind their green and red counterparts. Here, we systematically investigate this efficiency-stability discrepancy in a series of green- to blue-emitting PeLEDs based on mixed Br/Cl-perovskites. We find that chloride incorporation, while having only a limited impact on efficiency, detrimentally affects device stability even in small amounts. Device lifetime drops exponentially with increasing Cl-content, accompanied by an increased rate of change in electrical properties during operation. We ascribe this phenomenon to an increased mobility of halogen ions in the mixed-halide lattice due to an increased chemically and structurally disordered landscape with reduced migration barriers. Our results indicate that the stability enhancement for PeLEDs might require different strategies from those used for improving efficiency. Graphical Abstract

Abstract Background Children of mothers with gestational diabetes mellitus (GDM) are more prone to acquire type 2 diabetes and obesity as adults. Due to this link, early intervention strategies that alter the gut microbiome may benefit the mother and kid long-term. This work uses metagenomic and transcriptome sequencing to investigate how probiotics affect gut microbiota dysbiosis and inflammation in GDM. Methods GDM and control metagenomic sequencing data were obtained from the SRA database. This metagenomic data helped us understand gut microbiota abundance and function. KEGG detected and extracted functional pathway genes. Transcriptome sequencing data evaluated GDM-related gene expression. Finally, GDM animal models were given probiotics orally to evaluate inflammatory response, regulatory immune cell fractions, and leptin protein levels. Results GDM patients had more Fusobacteria and Firmicutes, while healthy people had more Bacteroidetes. Gut microbiota composition may affect GDM by altering the L-aspartate and L-asparagine super pathways. Mannan degradation and the super pathway of L-aspartate and L-asparagine synthesis enhanced in GDM mice with leptin protein overexpression. Oral probiotics prevent GDM by lowering leptin. Oral probiotics increased Treg, Tfr, and Breg cells, which decreased TNF-α and IL-6 and increased TGF-β and IL-10, preventing inflammation and preserving mouse pregnancy. Conclusion Dysbiosis of the gut microbiota may increase leptin expression and cause GDM. Oral probiotics enhance Treg, Tfr, and Breg cells, which limit the inflammatory response and assist mice in sustaining normal pregnancy. Thus, oral probiotics may prevent GDM, enabling targeted gut microbiota modulation and maternal and fetal health.

BackgroundThis study aimed to investigate the effects of adjuvant beam radiation therapy (ABRT) on overall survival (OS) in patients with primary single intracranial atypical meningioma (AM), with a focus on age-related outcomes.MethodsWe conducted a retrospective study using data from SEER database. Our cohort consisted of patients diagnosed with a primary single intracranial AM tumor and had undergone surgery. The primary endpoint was OS. For survival analysis, univariable and multivariable Cox regression analysis were performed. A multivariable additive Cox model was used to assess the functional relationship between age and OS in patients with or without ABRT.ResultsOf the 2,759 patients included, 1,650 underwent gross total resection and 833 received ABRT. Multivariable Cox analysis indicated that ABRT did not significantly influence OS across the entire cohort. According to the multivariable generalized additive Cox model, the relative risk of all-cause mortality increased with advancing age in both ABRT-yes and ABRT-no group. ABRT-yes had a lower relative risk than ABRT-no when age ≤ 55 years old while a higher relative risk when age > 55 years old. Subsequent multivariable Cox analysis showed that ABRT was associated with a significant lower risk for all-cause mortality in patients with age ≤ 55 years old while a significant higher risk in patients with age > 55 years old.ConclusionOur study found that ABRT enhanced OS in younger primary single intracranial AM patients. But we also revealed a negative correlation between OS and ABRT in older patients.

Abstract Multiple objectives optimization of frequency selective surface (FSS) structures is challenging in electromagnetic wave filter design. For example, one of the sub-objectives, the sidelobe level (SLL), is critical to directional anti-interference, which is complicated and becomes the bottleneck for radar design. Here, we established a dynamic algorithm for fitness function to automatically adjust the weights of multiple objectives in the optimization process of FSS structures. The dynamic algorithm could efficiently evaluate the achieving probability of sub-objectives according to the statistical analysis of the latest individual distribution so that the fitness function could automatically adjusted to focus on the sub-objective difficult to optimize, such as SLL. Computational results from the dynamic algorithm showed that the efficiency of multi-objective optimization was greatly improved by 213%, as compared to the fixed-weighted algorithm of the fitness function. Specifically for SLL, the efficiency rate increased even better, up to 315%. More interestingly, the FSS structures were most improved while picking median value or golden section value as the reference value. Taken together, the current study indicated that the dynamic algorithm with fitness function might be a better choice for FSS structural optimization with SLL suppression and potentially for the better design of lower SLL radar.

The forward-reverse framework based on machine learning for MASnxPb1-xI3 perovskite solar cells is reported. The practicability of bandgap model revealing asymmetrically-bowing shape and optimized Sn:Pb ratio are verified by experiments.

Up-conversion lasing actions are normally difficult to realize in light-emitting materials due to small multi-photon absorption cross section and fast dephasing of excited states during multi-photon excitation. This paper reports an easily accessible up-conversion amplified spontaneous emission (ASE) in organic-inorganic hybrid perovskites (MAPbBr3) films by optically exciting broad gap states with sub-bandgap laser excitation. The broad absorption was optimized by adjusting the grain sizes in the MAPbBr3 films. At low sub-bandgap pumping intensities, directly exciting the gap states leads to 2-photon, 3-photon, and 4-photon up-conversion spontaneous emission, revealing a large optical cross section of multi-photon excitation occurring in such hybrid perovskite films. At moderate pumping intensity (1.19 mJ/cm2) of 700 nm laser excitation, a significant spectral narrowing phenomenon was observed with the full width at half maximum (FWHM) decreasing from 18 nm to 4 nm at the peak wavelength of 550 nm, simultaneously with a nonlinear increase on spectral peak intensity, showing an up-conversion ASE realized at low threshold pumping fluence. More interestingly, the up-conversion ASE demonstrated a giant magnetic field effect, leading to a magneto-ASE reaching 120%. In contrast, the up-conversion photoluminescence (PL) showed a negligible magnetic field effect (< 1%). This observation provides an evidence to indicate that the light-emitting states responsible for up-conversion ASE are essentially formed as spatially extended states. The angular dependent spectrum results further verify the existence of spatially extended states which are polarized to develop coherent in-phase interaction. Clearly, using broad gap states with spatially extended light-emitting states presents a new approach to develop up-conversion ASE in organic-inorganic hybrid perovskites.

Abstract Poyang Lake Basin is of great importance to maintain regional ecological balance. However, fish biodiversity in this basin has rapidly declined as the result of anthropogenic habitat alteration, such as dam construction, sand mining, and water pollution. Here, we aimed to analyze the temporal and spatial changes in biodiversity patterns of fish in Poyang Lake Basin over the last 37 years. The number of fish species underwent a significant decrease in the current period. In particular, 36.7% of the migration of fish was extirpated. Twenty‐seven fish species have been formally assessed using the Chinese Red List were currently listed as Critically Endangered (9), Endangered (3), Vulnerable (10), and Near Threatened (5). Alpha and gamma diversity revealed that fish diversity had also decreased, and beta diversity showed significant composition dissimilarity in two periods. PCoA showed that the historical fish composition dissimilarity was significantly different from that of the current period. We found a significant effect of the geographical distance on the spatial turnover component for the historical and current periods. In addition, the nestedness component was the main contributor to beta diversity, which indicated one large protected area should be established in Poyang Lake and the Ganjiang River Basin with higher species richness. These results indicated that fish biodiversity declined in the current period likely caused by anthropogenic habitat alteration and other threatened factors. Therefore, we suggest that the habitat reconstruction and biodiversity conservation for fish have become imperative in this basin, and a complete management plan should be carried out.

Summary: This paper reports a new method to generate stable and high-brightness electroluminescence (EL) by subsequently growing large/small grains at micro/nano scales with the configuration of attaching small grains on the surfaces of large grains in perovskite (MAPbBr3) films by mixing two precursor solutions (PbBr2 + MABr and Pb(Ac)2·3H2O + MABr). Consequently, the small and large grains serve, respectively, as passivation agents and light-emitting centers, enabling self-passivation on the defects located on the surfaces of light-emitting large grains. Furthermore, the light-emitting states become linearly polarized with maximal polarization of 30.8%, demonstrating a very stable light emission (49,119 cd/m2 with EQE = 11.31%) and a lower turn-on bias (1.9 V) than the bandgap (2.25V) in the perovskite LEDs (ITO/PEDOT:PSS/MAPbBr3/TPBi[50 nm]/LiF[0.7 nm]/Ag). Therefore, mixing large/small grains with the configuration of attaching small grains on the surfaces of large grains by mixing two precursor solutions presents a new strategy to develop high-performance perovskite LEDs. : Materials Characterization; Optical Materials; Surface Subject Areas: Materials Characterization, Optical Materials, Surface

Abstract Understanding the feasibility to couple semiconducting and magnetic properties in metal halide perovskites through interface design opens new opportunities for creating the next generation spin‐related optoelectronics. In this work, a fundamentally new phenomenon of optically induced magnetization achieved by coupling photoexcited orbital magnetic dipoles with magnetic spins at perovskite/ferromagnetic interface is discovered. The depth‐sensitive polarized neutron reflectometry combined with in situ photoexcitation setup, constitutes key evidence of this novel effect. It is demonstrated that a circularly polarized photoexcitation induces a stable magnetization signal within the depth up to 7.5 nm into the surface of high‐quality perovskite (MAPbBr3) film underneath a ferromagnetic cobalt layer at room temperature. In contrast, a linearly polarized light does not induce any detectable magnetization in the MAPbBr3. The observation reveals that photoexcited orbital magnetic dipoles at the surface of perovskite are coupled with the spins of the ferromagnetic atoms at the interface, leading to an optically induced magnetization within the perovskite’s surface. The finding demonstrates that perovskite semiconductor can be bridged with magnetism through optically controllable method at room temperature in this heterojunction design. This provides the new concept of utilizing spin and orbital degrees of freedom in new‐generation spin‐related optoelectronic devices.

The Yangtze River Basin (Changjiang Basin) hosts one of the most diverse freshwater mussel assemblages on Earth. However, due to human activities this fauna is dramatically imperiled in this region, highlighting the need for urgent conservation measures. To better protect and conserve these taxa, it is crucial to understand the main drivers that control the diversity patterns, as well as the anthropogenic influence on these patterns. Here, we estimated distinct diversity metrics (i.e. species richness and alpha, gamma, and beta diversity) to analyze the spatial freshwater mussel diversity changes across 16 tributaries and lakes from the middle and lower Yangtze River Basin, in two periods: past 1962–2012 and present. For the past, mussel records were compiled from previous studies, for the present, we surveyed 565 sites for freshwater mussel presence and abundance within the 16 selected areas. We also assessed several climatic and geographical parameters to try to identify the main factors that modulate species composition across the study area. We show that from the historical to the present periods, species diversity experienced a significant decrease, registering, per river/lake, an average of 5.4 extirpations of species native to China and 3.9 of the Yangtze River Basin endemics. The gamma diversity of the whole study area and the alpha diversity of each of the studied rivers and lakes have also decreased during this period. The beta diversity values indicated a significant trend towards taxonomic homogenization over the last decades. Poyang and Dongting Lakes should be considered for protection given due to their high diversity and species loss given that nestedness in these lakes represented the main component of beta diversity.

The Luoxiao Mountains play an important role in maintaining and supplementing the fish diversity of the Yangtze River Basin, which is also a biodiversity hotspot in China. However, fish biodiversity has declined rapidly in this area as the result of human activities and the consequent environmental changes. Beta diversity was a key concept for understanding the ecosystem function and biodiversity conservation. Beta diversity patterns are evaluated and important information provided for protection and management of fish biodiversity in the Luoxiao Mountains. The results showed that the spatial turnover component was the main contributor to beta diversity of Hemiramphidae, Amblycipitidae, Catostomidae, Clariidae, Balitoridae and Percichthyidae in the Luoxiao Mountains, which indicated that a number of protected areas would be necessary to conserve fish biodiversity and that these families would need conservation measures. Most protected areas are currently limited to some regions; therefore, in order to protect fish diversity, conservation efforts must target an increase in the number of protected areas which should be spread across each of the regions.

The Ganjiang River has abundant fish resources, which plays a significant role in maintaining and replenishing the fish resources in Poyang Lake and the Yangtze River, and contains important habitat for migratory fish. However, fish diversity has rapidly declined in the Ganjiang River, especially migratory fish. In this study, 107 fish species (including 43 Chinese endemic species) were found in the middle and lower reaches of the Ganjiang River. However, only 91 fish species were found in the main channel of the Ganjiang River, which was lower than the 108 fish species historically found there. According to the Chinese Red List, 85 Least Concern, two Critically Endangered, three Vulnerable, one Near Threatened and 16 Data Deficient fish species were found in the Ganjiang River. In addition, the species number, diversity and CPUE in the channel were all greater than in the reservoir. The Bray-Curtis resemblance matrix and non-metric multidimensional scaling (NMDS) showed that the habitats of the Ganjiang River were divided into three areas. The analysis of RDA showed that turbidity, dissolved oxygen and water depth significantly affected fish distributions and assemblage composition. These results indicated that dam construction and other human activities have seriously destroyed the fish habitat and led to the decline in fish diversity. Therefore, the conservation of fish has become urgent in the Ganjiang River, and an integrated management plan should be developed and effectively implemented.

The utilization of the large pretrained model (LPM) based on Transformer has emerged as a prominent research area in various fields, owing to its robust computational capabilities. However, there remains a need to explore how LPM can be effectively employed in the agricultural domain. This research aims to enhance agricultural pest detection with limited samples by leveraging the strong generalization performance of the LPM. Through extensive research, this study has revealed that in tasks involving the counting of a small number of samples, complex agricultural scenes with varying lighting and environmental conditions can significantly impede the accuracy of pest counting. Consequently, accurately counting pests in diverse lighting and environmental conditions with limited samples remains a challenging task. To address this issue, the present research suggests a unique approach that integrates the outstanding performance of the segment anything model in class-agnostic segmentation with the counting network. Moreover, by intelligently utilizing a straightforward TopK matching algorithm to propagate accurate labels, and drawing inspiration from the GPT model while incorporating the forgetting mechanism, a more robust model can be achieved. This approach transforms the problem of matching instances in different scenarios into a problem of matching similar instances within a single image. Experimental results demonstrate that our method enhances the accuracy of the FamNet baseline model by 69.17% on this dataset. Exploring the synergy between large models and agricultural scenes warrants further discussion and consideration.