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Understanding the impact of climate and land use change on soil erosion is particularly important to the development and management of ecosystems. The purpose of this research was to differentiate the impacts of climate and land use alterations on soil erosion by using the InVEST model in the Anning River basin. The findings indicated a rise in average soil erosion from 42.78 t ha−1·a−1 to 49.84 t ha−1·a−1 over the decade from 2010 to 2020, with climate change accounting for 99.71% of the increase and land use change contributing 0.28%. The findings also indicated that the process of urbanization and the implementation of the Returning Grain to Forestry and Grass (RGFG) strategy were effective in decreasing soil erosion by 1.29 t ha−1·a−1 and 6.60 t ha−1·a−1, respectively. Four management measures were developed based on our results. The results of this study are not only of great significance for the environmental protection of a specific region, but also provide references for the mitigation of soil erosion in other regions of the world.

Fractures play a crucial role in tight sandstone gas reservoirs with low permeability and low effective porosity. If open, they not only significantly increase the permeability of the reservoir but also serve as channels connecting the storage space. Among numerous fracture identification methods, seismic data provide unique advantages for fracture identification owing to the provision of three-dimensional information between wells. How to accurately identify the development of fractures in geological bodies between wells using seismic data is a major challenge. In this study, a tight sandstone gas reservoir in the Kuqa Basin (China) was used as an example for identifying reservoir fractures using deep-learning-based method. First, a feasibility analysis is necessary. Intersection analysis between the fracture density and seismic attributes (the characteristics of frequency, amplitude, phase, and other aspects of seismic signals) indicates that there is a correlation between the two when the fracture density exceeds a certain degree. The development of fractures is closely related to the lithology and structure, indirectly affecting differences in seismic attributes. This indicates that the use of seismic attributes for fracture identification is feasible and reasonable. Subsequently, the effective fracture density data obtained from imaging logging were used as label data, and the optimized seismic attribute near the well data were used as feature data to construct a fracture identification sample dataset. Based on a feed-forward neural network algorithm combined with natural fracture density and effectiveness control factor constraints, a trained identification model was obtained. The identification model was applied to seismic multi-attribute data for the entire work area. Finally, the accuracy of the results from the training, testing, and validation datasets were used to determine the effectiveness of the method. The relationship between the fracture identification results and the location of the fractures in the target reservoir was used to determine the reasonableness of the results. The results indicate that there is a certain relationship between multiple seismic attributes and fracture development, which can be established using deep learning models. Furthermore, the deep-learning-based seismic data fracture identification method can effectively identify fractures in the three-dimensional space of reservoirs.

ObjectivesShanghai witnessed an unprecedented outbreak of COVID-19 and experienced a strict lockdown from March 28, 2022 to May 31, 2022. Most studies to date are on the first lockdown after the outbreak in December 2019. This study aimed to examine the impact of lockdown on delivery and neonatal outcomes among uninfected pregnant women in the new phase of the COVID-19 outbreak.MethodsA retrospective analysis was conducted in the Obstetrics and Gynecology Hospital of Fudan University. Pregnant women without COVID-19 who delivered from March 28, 2022 to May 31, 2022 (lockdown group) and the same period in 2021 (non-lockdown group) were recruited for this study. Logistic regression models and 1 : 1 propensity score matching (PSM) were used to assess the effect of lockdown on delivery outcomes.ResultsA total of 2,962 patients were included in this study, 1,339 of whom were from the lockdown group. Compared with the non-lockdown group, pregnant women giving birth during lockdown had an increased risk of term prelabor rupture of membranes (TPROM) (aOR = 1.253, 95% CI: 1.026–1.530), and decreased risks of postpartum hemorrhage (PPH) (aOR = 0.362, 95% CI: 0.216–0.606) and fetal malformation (aOR = 0.309, 95% CI: 0.164–0.582). The risk of large for gestational age (LGA) (aOR = 0.802, 95% CI: 0.648–0.992) and rate of admission to the neonatal intensive care unit (NICU) (aOR = 0.722, 95% CI: 0.589–0.885) also significantly declined. After 1 : 1 PSM, the impact of lockdown on the risk of TPROM (aOR = 1.501, 95% CI: 1.083–2.080), PPH (aOR = 0.371, 95% CI: 0.211–0.654), fetal malformation (aOR = 0.332, 95% CI: 0.161–0.684), LGA (aOR = 0.749, 95% CI: 0.594–0.945) and rate of admission to the NICU (aOR = 0.700, 95% CI: 0.564–0.869) all remained. There were no other delivery or neonatal outcomes affected by the lockdown after the COVID-19 outbreak.ConclusionThis study indicated a significant increase in the risk of term PROM, significant decreases in the risk of PPH, fetal malformation and LGA, and a marked decline in the rate of admission to the NICU during Shanghai Lockdown.

As an increasingly prevalent form of human activity, roads drive the taxonomic homogenization of mountain plant assemblages, threatening global biodiversity. However, little is known about how mountain roads impact functional and phylogenetic beta diversity and how these effects are related to taxonomic homogenization. To understand the mechanism of taxonomic homogenization triggered by mountain roads, we used species absence/presence data from 76 plots (2 m*50 m) and values for 12 traits measured on 978 species from the interior and roadside communities in the Qionglai mountain range, one of the temperate regions with the highest plant species richness in the world. We used a structural equation modeling approach (SEM) to consider several surrogates of road disturbance (changes in soil physicochemical properties and the presence or absence of roads) and the causal relationship between three facets of beta diversity (taxonomic beta diversity, TBD; functional beta diversity, FBD and phylogenetic beta diversity, PBD). The results suggest that TBD, FBD and PBD respond inconsistently to mountain roads, despite strong positive correlations between the three facets of plant beta diversity in the study area. Compared with the interior community, the βtotal.tax and βtotal.func of the roadside community decreased by 2.54% and 2.22%, respectively, which were related to the reduction of species and trait richness differences and replacements; however, we did not find the same results when assessing the changes in βtotal.phy, which represents tip-weighted PBD (twPBD). Furthermore, the largest effect of roads on beta diversity was reflected in basal-weighted PBD (bwPBD), which decreased by 9.97%, indicating that those species with fewer extant relatives and longer evolutionary histories are more sensitive to mountain roads. Therefore, it is necessary to take targeted protection measures for ancient species in roadside communities. In addition, we believe that it is still necessary to take measures to prevent the further dispersal of nonnative species, although the presence of non-native species in roadside plots has led to small changes in three facets of beta diversity. There were causal relationships between the three facets of beta diversity, but their intensity and sign different in the SEM of different components of beta diversity (i.e., richness difference and replacement). Our findings suggest that the homogenization of community species composition at the landscape scale arises by a combination of adaptive responses of the functional traits of organisms to environmental consistency (e.g., reduced the differences in soil variables) caused by roads and resorting or reassembly of community clades composition due to environmental filtering. These results contribute to our comprehensive understanding of the impact of mountain roads on plant diversity, which highlights the complex relationship between human pressure and biodiversity loss.

A comprehensive understanding of the effects of mountain roads on plant diversity is critical to finding the most effective solutions for managing this particular driver. Little is known, however, about the simultaneous effects that road have on the multiple facets of biodiversity, although roads are considered to be one of the major disturbances in the Qionglai mountain range. In this study, we analyzed the impact of roads on the multiple facets of plant diversity (taxonomic, functional and phylogenetic diversity) in the study area using Hill numbers by comparing plant diversity between roadside and interior plots at the landscape scale, then, we used linear mixed models to analyze the effect of mountain roads on the multiple facets of plant diversity along an elevational gradient. The results showed that the roadside plots lacked 29.45% of the total number of species with particular functional traits (such as a relatively high specific leaf area (SLA), a relatively low leaf dry matter content (LDMC) and relatively old clades) and exclusively contained 14.62% of the total number of species. Compared with the interior community, the taxonomic, functional and phylogenetic diversity of roadside community decreased by no more than 26.78%, 24.90% and 16.62%, respectively. Taxonomic and functional diversity of dominant and common species showed greater changes to road disturbances, while rare species showed the greatest change in phylogenetic diversity. Taxonomic homogenization of roadside communities was accompanied by functional and phylogenetic homogenization. Additionally, the impact of roads on these three facets of plant diversity showed the characteristics of peak clipping along the elevation gradient. Our findings highlight the negative impact of roads on the taxonomic, functional and phylogenetic diversity of the Qionglai mountain range, as roads promote communities that are more similar in taxonomic, functional, and phylogenetic composition, and to a greater extent contributed to compositional evenness. These effects tend to be functionally and phylogenetically non-random, and species in some clades or with some functional traits are at higher risk of loss. Our results are important for the conservation and management of nature reserves, especially for local governments aiming to create new infrastructure to connect natural mountainous areas.

Flavones predominantly accumulate as O- and C-glycosides in kumquat plants. Two catalytic mechanisms of flavone synthase II (FNSII) support the biosynthesis of glycosyl flavones, one involving flavanone 2-hydroxylase (which generates 2-hydroxyflavanones for C-glycosylation) and another involving the direct catalysis of flavanones to flavones for O-glycosylation. However, FNSII has not yet been characterized in kumquats. In this study, we identified two kumquat FNSII genes (FcFNSII-1 and FcFNSII-2), based on transcriptome and bioinformatics analysis. Data from in vivo and in vitro assays showed that FcFNSII-2 directly synthesized apigenin and acacetin from naringenin and isosakuranetin, respectively, whereas FcFNSII-1 showed no detectable catalytic activities with flavanones. In agreement, transient overexpression of FcFNSII-2 in kumquat peels significantly enhanced the transcription of structural genes of the flavonoid-biosynthesis pathway and the accumulation of several O-glycosyl flavones. Moreover, studying the subcellular localizations of FcFNSII-1 and FcFNSII-2 demonstrated that N-terminal membrane-spanning domains were necessary to ensure endoplasmic reticulum localization and anchoring. Protein–protein interaction analyses, using the split-ubiquitin yeast two-hybrid system and bimolecular fluorescence-complementation assays, revealed that FcFNSII-2 interacted with chalcone synthase 1, chalcone synthase 2, and chalcone isomerase-like proteins. The results provide strong evidence that FcFNSII-2 serves as a nucleation site for an O-glycosyl flavone metabolon that channels flavanones for O-glycosyl flavone biosynthesis in kumquat fruits. They have implications for guiding genetic engineering efforts aimed at enhancing the composition of bioactive flavonoids in kumquat fruits.

How can researchers best measure infants' motor experiences in the home? Body position—whether infants are held, supine, prone, sitting, or upright—is an important developmental experience. However, the standard way of measuring infant body position, video recording by an experimenter in the home, can only capture short instances, may bias measurements, and conflicts with physical distancing guidelines resulting from the COVID-19 pandemic. Here, we introduce and validate an alternative method that uses machine learning algorithms to classify infants' body position from a set of wearable inertial sensors. A laboratory study of 15 infants demonstrated that the method was sufficiently accurate to measure individual differences in the time that infants spent in each body position. Two case studies showed the feasibility of applying this method to testing infants in the home using a contactless equipment drop-off procedure.

Social media platforms increasingly give users the option of ephemerality through settings that delete or hide posted content after a set period of time. Many individuals apply these settings to manage their posting history and, in turn, reduce concerns about self-presentation. Despite the growing popularity of this feature, few studies have empirically explored it. This study examines the Time Limit setting on WeChat Moments as an example and investigates how users using the Time Limit setting differ from nonusers in terms of personal characteristics (demographics, personality traits, psychological factors, and previous behavioral patterns) and social characteristics (audience size and audience diversity). Compared with nonusers, users using Time Limit setting scored significantly higher on posting frequency and privacy setting use and scored significantly lower on audience size. We also examine how personal and social characteristics vary between user groups with different degrees of ephemerality (i.e., low, medium, or high). Our findings show that users using the Time Limit setting who scored higher on measures of life changes, self-monitoring, posting frequency, and audience size and lower on perceived stress were more likely to opt for the low (i.e., 6months) rather than the medium (i.e., 1month) or high (i.e., 3days) degree of ephemerality. Our work contributes to the understanding of ephemerality settings on social media platforms and provides insights that help practitioners design more effective platforms.

As an increasingly prevalent form of human activity, roads drive the taxonomic homogenization of mountain plant assemblages, threatening global biodiversity. However, little is known about how mountain roads impact functional and phylogenetic beta diversity and how these effects are related to taxonomic homogenization. To understand the mechanism of taxonomic homogenization triggered by mountain roads, we used species absence/presence data from 76 plots (2 m*50 m) and values for 12 traits measured on 978 species from the interior and roadside communities in the Qionglai mountain range, one of the temperate regions with the highest plant species richness in the world. We used a structural equation modeling approach (SEM) to consider several surrogates of road disturbance (changes in soil physicochemical properties and the presence or absence of roads) and the causal relationship between three facets of beta diversity (taxonomic beta diversity, TBD; functional beta diversity, FBD and phylogenetic beta diversity, PBD). The results suggest that TBD, FBD and PBD respond inconsistently to mountain roads, despite strong positive correlations between the three facets of plant beta diversity in the study area. Compared with the interior community, the ⓰total.tax and βtotal.func of the roadside community decreased by 2.54% and 2.22%, respectively, which were related to the reduction of species and trait richness differences and replacements; however, we did not find the same results when assessing the changes in βtotal.phy, which represents tipweighted PBD (twPBD). Furthermore, the largest effect of roads on beta diversity was reflected in basal-weighted PBD (bwPBD), which decreased by 9.97%, indicating that those species with fewer extant relatives and longer evolutionary histories are more sensitive to mountain roads. Therefore, it is necessary to take targeted protection measures for ancient species in roadside communities. In addition, we believe that it is still necessary to take measures to prevent the further dispersal of nonnative species, although the presence of non-native species in roadside plots has led to small changes in three facets of beta diversity. There were causal relationships between the three facets of beta diversity, but their intensity and sign different in the SEM of different components of beta diversity (i.e., richness difference and replacement). Our findings suggest that the homogenization of community species composition at the landscape scale arises by a combination of adaptive responses of the functional traits of organisms to environmental consistency (e.g., reduced the differences in soil variables) caused by roads and resorting or reassembly of community clades composition due to environmental filtering. These results contribute to our comprehensive understanding of the impact of mountain roads on plant diversity, which highlights the complex relationship between human pressure and biodiversity loss. [ABSTRACT FROM AUTHOR]