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Aims Perennial plants play important roles in maintaining ecosystem functions by forming fertile islands beneath their canopies. Little is known about how the fertile island effect varies among different patch types and across climatic gradients, or what drives the strength of its effect. Methods We assessed biotic (plants, biocrusts, litter) and abiotic (soil infiltrability, labile carbon, enzymes) fertile island effects beneath three plant patch types (tree, shrub and grass patches), and collected data on biotic (canopy size, grazing intensity) and abiotic (soil texture, electrical conductivity and pH) drivers at 150 sites along an extensive aridity gradient in eastern Australia. Results The fertile island effect was generally apparent beneath trees, shrubs and grasses, with biotic (plants) and abiotic (soils) attributes regulated differently by plant canopy size. The fertile island effect intensified with increasing aridity, with the greatest litter and soil resources accumulated beneath trees. Conclusions Our study provides evidence of the fertile island effect across the whole spectrum of the aridity gradient, with the effect depending on the target attribute and plant patch type. Forecasted increases in aridity will likely strengthen the fertile island effect beneath trees, reinforcing the importance of trees in drier environments to support critical ecosystem functions and services.

Aims Biocrusts are globally distributed and important for sustaining critical ecosystem functions. Little is known about their continental drivers and how smaller-scale microsite differences might affect biocrusts along aridity gradients. This limits our ability to manage biocrusts effectively under drier climates. Methods We collected data on biocrust cover, biotic (plants, litter, grazing intensity) and abiotic (soil texture, soil stability and integrity) attributes from four microsites (trees, shrubs, grasses, open) at 150 sites along an extensive aridity gradient in eastern Australia. Results At the sub-continental scale, average biocrust cover increased with declining litter cover, and crust cover became more variable with increasing aridity. Biocrust cover was greatest in open microsites and least under trees, and differences were related to the effects of soil texture, vegetation and grazing intensity, which either increased or declined with increasing aridity. Conclusions Our study reveals that biotic and abiotic effects on biocrust cover vary at different spatial scales along an aridity gradient. Predicted increases in aridity in eastern Australia will likely enhance biocrust cover whereas microsite-level effects are likely to be driven by land management actions such as vegetation removal and overgrazing.

BackgroundThe Internet has become a leading source of health information accessed by patients and the general public. It is crucial that this information is reliable and accurate.ObjectivesThe purpose of this systematic review was to evaluate the overall quality of online health information targeting patients and the general public.MethodsThe systematic review is based on a pre-established protocol and is reported according to the PRISMA statement. Eleven databases and Internet searches were performed for relevant studies. Descriptive statistics were used to synthesize data. The NIH Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies was used to assess the methodological quality of the included studies.ResultsOut of 3393 references, we included 153 cross-sectional studies evaluating 11,785 websites using 14 quality assessment tools. The quality level varied across scales. Using DISCERN, none of the websites received a category of excellent in quality, 37–79% were rated as good, and the rest were rated as poor quality. Only 18% of websites were HON Code certified. Quality varied by affiliation (governmental was higher than academic, which was higher than other media sources) and by health specialty (likely higher in internal medicine and anesthesiology).ConclusionThis comprehensive systematic review demonstrated suboptimal quality of online health information. Therefore, the Internet at the present time does not provide reliable health information for laypersons. The quality of online health information requires significant improvement which should be a mandate for policymakers and private and public organizations.

Despite the ability of combination antiretroviral therapy (cART) to increase the life expectancy of patients infected with human immunodeficiency virus (HIV), viral reservoirs persist during life-long treatment. Notably, two cases of functional cure for HIV have been reported and are known as the “Berlin Patient” and the “London Patient”. Both patients received allogeneic hematopoietic stem cell transplantation from donors with homozygous CCR5 delta 32 mutation for an associated hematological malignancy. Therefore, there is growing interest in creating an HIV-resistant immune system through the use of gene-modified autologous hematopoietic stem cells with non-functional CCR5 . Moreover, studies in CXCR4 -targeted gene therapy for HIV have also shown great promise. Developing a cure for HIV infection remains a high priority. In this review, we discuss the increasing progress of coreceptor-based hematopoietic stem cell gene therapy, cART, milder conditioning regimens, and shock and kill strategies that have important implications for designing potential strategies aiming to achieve a functional cure for the majority of people with HIV.

The social phenomenon of university students learning agriculture rather than pursuing it, understanding agriculture rather than choosing agriculture, is a major challenge for the sustainable development of agricultural talents in China. This research paper investigates the impact and mechanism of practical education in agricultural schools on students’ intention to start agricultural businesses using OLS, Probit, and mediation effect models. Data from a survey of 1612 Chinese students from Sichuan Agricultural University, Nanjing Agricultural University and other 6 agricultural universities was analyzed, with instrumental variable probit model (IV-Probit) utilized to tackle endogeneity issues. The results showed that (1) The implementation of rural social practice, volunteer service, entrepreneurship competition, and agricultural labor education by universities can significantly boost university students’ interest in starting their agricultural businesses. Additionally, for every additional type of practical education students receive, they are 11.0% more likely to want to start business in agriculture. (2) Practical education will affect individual entrepreneurial effectiveness perception, including economic benefit perception, social status perception and professional value perception. Among these, the mediating effect of professional value perception is the strongest, with a ratio of 16.1%. (3) The results suggest that entrepreneurship support policy play a role in moderating the connection between individuals’ economic benefit, social status perceptions and their intentions. (4) The intentions of university students to start agricultural businesses are significantly correlated with their control variables, including major selection, students cadre experience, agricultural cognition, household registration, and family members’ occupation. Therefore, it is suggested that there should be a focus on enhancing practical education in agricultural universities, fostering students’ confidence in agricultural entrepreneurship, and optimizing sustainable policy support for university students’ entrepreneurial endeavors.

Digital nucleic acid amplification tests enable absolute quantification of nucleic acids, but the generation of uniform compartments and reading of the fluorescence requires specialized instruments that are costly, limiting their widespread applications. Here, the authors report deep learning‐enabled polydisperse emulsion‐based digital loop‐mediated isothermal amplification (deep‐dLAMP) for label‐free, low‐cost nucleic acid quantification. deep‐dLAMP performs LAMP reaction in polydisperse emulsions and uses a deep learning algorithm to segment and determine the occupancy status of each emulsion in images based on precipitated byproducts. The volume and occupancy data of the emulsions are then used to infer the nucleic acid concentration based on the Poisson distribution. deep‐dLAMP can accurately predict the sizes and occupancy status of each emulsion and provide accurate measurements of nucleic acid concentrations with a limit of detection of 5.6 copies µl‐1 and a dynamic range of 37.2 to 11000 copies µl‐1. In addition, deep‐dLAMP shows robust performance under various parameters, such as the vortexing time and image qualities. Leveraging the state‐of‐the‐art deep learning models, deep‐dLAMP represents a significant advancement in digital nucleic acid tests by significantly reducing the instrument cost. We envision deep‐dLAMP would be readily adopted by biomedical laboratories and be developed into a point‐of‐care digital nucleic acid test system. Droplet digital PCR requires sophisticated instruments for droplet generation and reading, limiting their widespread applications. In this article, polydisperse emulsions are generated and read using common instruments, and deep learning is adopted to analyze the occupancy and volumes of the emulsions for nucleic acid quantification.

Reducing farmland abandonment is important to address food security issues. China is accelerating its transition into an aging society, and this change in the labor force structure may have an impact on farmland abandonment. This study is based on the China Labor Force Survey conducted in 2012, 2014, 2016, and 2018 and collects data from 29,704 valid farmer samples in 29 provinces and cities across the nation. We investigate how farmer aging affects farmland abandonment from the viewpoints of information, mutual aid, and factor substitution using the Tobit and mediation effect models. The core conclusions are as follows: (1) There is a significant positive correlation between aging and abandoned farmland, that is, the higher the degree of aging in rural households, the more likely it is that farmland will be abandoned and the larger the area of abandoned farmland. (2) Aging has a multi-level impact on abandoned farmland, that is, aging will aggravate the abandonment of farmland from the perspectives of household head characteristics, family characteristics, and village characteristics. (3) Using the mediation effect model, aging will increase the abandonment of farmland due to less use of the Internet, agricultural cooperatives, and mechanization. This conclusion provides a basis for policy intervention, indicating that improving agricultural digitalization and modernization and increasing policy subsidies may be an effective way to slow down land abandonment.

With the development of higher education, college students have become a new and important group for environmentally sustainable development. How to evaluate and strengthen the practical effect of ecological education is of great significance. Based on the survey data of 1579 university students, this study constructed a systematic index system of ecological education by using a hierarchical evaluation method. Moreover, OLS (Ordinary Least Squares), Oprobit, and intermediary effect models were used to analyze the influence relationship and mechanism of the two empirically and IV-Oprobit was used to solve the endogeneity problem. The results show the following: (1) Ecological education can effectively promote the sustainable behavior of university students, and the probability of university students implementing sustainable behavior increases by 10.7% with each unit increase in the level of ecological education. (2) Environmental value perception such as in individual economic value perception, social value perception, and health value perception are all important mediating channels of ecological education, among which health value perception has the strongest mediating effect. (3) Particulate Matter 2.5 (PM2.5) exposure positively moderates the impact of university students’ environmental value perception on their sustainable behavior. (4) There is a significant correlation between university students’ household registration, participation in environmental associations and hometown social networks, and sustainable behaviors. (5) The influence of ecological education on students’ behaviors shows heterogeneity in family household registration. Students from rural families have a higher level of environmental behavior and value perception than those from urban families. Moreover, they are more likely to exhibit behaviors under the influence of ecological education. The above results provide reference suggestions for the ecological education policy system and offer theoretical support and policy inspiration for promoting sustainable behaviors among global college students and enhancing the efficiency of ecological education in universities.

Predicting community evolution in dynamic social networks is crucial for relevant authorities to understand trends and implement safety measures in advance. Most existing algorithms for predicting community evolution rely on extracting community state features to forecast evolutionary events. However, in highly interactive social networks, such as corporate collaboration networks in financial markets, extracting high-quality community state features is extremely challenging. This study proposes a community evolution prediction method based on feature change patterns, aiming to explore the changing features during community evolution, and designs an algorithm to learn the rules of feature changes, thereby obtaining the feature change pattern of the community. Compared to traditional methods that rely on static state features, our proposed approach captures richer dynamic information and more accurately reflects community evolution trends. Additionally, we have designed a parallel learning strategy with parameter sharing, based on the consistency of community environments. Experimental results show that our method, based on feature change patterns, achieves approximately 25% improvement in maximum predictive performance on the AS, DBLP, and Facebook datasets compared to baseline methods (TNSEP, GNAN, and MF-PSF). Additionally, the parallel learning mechanism reduces training time by nearly half.

Scale management has become an essential form of modern agricultural production. However, it is still unclear how farm size influences farmers’ pesticide packaging waste recycling behavior (FPPWRB). Based on the data from the China Rural Revitalization Survey 2020, this study quantitatively explores the impact of farm size on FPPWRB. This study found that (1) the ratio for FPPWRB is low, with only about 41.7% of the sample farmers expressing participation in recycling. (2) The empirical results show that for every 1% increase in farm size, the probability of FPPWRB increases by 3.59%. (3) Farmers in urban suburbs or younger farmers are more inclined to FPPWRB. (4) Farm size can improve FPPWRB by enhancing farmers’ environmental cognition levels. The research in this study provides insights into the improper disposal of pesticide packaging waste and offers references for formulating policies related to the resource utilization of pesticide packaging waste. Thus, the findings of this study can help provide a reference for the introduction of policies to manage pesticide packaging waste, which, in turn, can help promote sustainable agricultural development.