Effect of Root-Zone Temperature on Growth and Quality of Hydroponically Grown Red Leaf Lettuce (Lactuca sativa L. cv. Red Wave)

Soil temperature influences crop growth and quality under field and greenhouse conditions;however, precise investigation using controlled cultivation systems is largely lacking. We investigated effects of root-zone temperatures on growth and components of hydroponically grown red leaf lettuce (Lactuca sativa L. cv. Red Wave) under a controlled cultivation system at 20&degC. Compared with ambient root-zone temperature exposure, a 7-day low temperature exposure reduced leaf area, stem size, fresh weight, and water content of lettuce. However, root-zone heating treatments produced no significant changes in growth parameters compared with ambient conditions. Leaves under low root-zone temperature contained higher anthocyanin, phenols, sugar, and nitrate concentrations than leaves under other temperatures. Root oxygen consumption declined with low temperature root exposure, but not with root heating. Leaves of plants under low rootzone temperature showed hydrogen peroxide production, accompanied by lipid peroxidation. Therefore, low temperature root treatment is suggested to induce oxidative stress responses in leaves, activating antioxidative secondary metabolic pathways.

Effects of Alternative Partial Root-zone Irrigation and Nitrogen Fertilizer on Plukenetia volubilis Seedlings

This study was aimed to investigate the effects of alternative partial rootzone irrigation and nitrogen fertilizer on the potted seedlings of Plukenetia volubilis.A total of 7 treatments were designed with three factors, i.e., irrigation amount, irrigation mode and nitrogen fertilizer. The growth, photosynthesis and water use efficiency were analyzed. The results showed that compared with those under full irrigation, the biomass and water consumption under alternative partial root-zone irrigation were reduced by 5% and 75%, respectively, and the water use efficiency was increased by 60%. Under severe drought conditions, the root cap ratio in the nitrogen fertilizer treatment group was increased by 30%; the leaf area index, photosynthetic rate and biomass under alternative partial root-zone irrigation were reduced by 38%, 9% and 18%, respectively. It indicates that under severe drought conditions, alternative partial root-zone irrigation is not suitable to be matched with application of nitrogen fertilizer. In short, under moderate drought conditions, alternative partial root-zone irrigation could reduce transpiration and improve water use efficiency, and it is an effective water-saving irrigation technology for the plantation of P.volubilis plants.

Effect of Partial Root-Zone Irrigating Deuterium Oxide on the Properties of Water Transportation and Distribution in Young Apple Trees

Partial root-zone irrigation （PRI） has been proved to be an optimal water-saving irrigation technology, however, few studies were done on water transportation and distribution under PRI. The present study was performed to investigate the water transportation and distribution among the wet and dry root-zones and the shoot using deuterium water （D2O） in 1/4 root-zone PRI experiment. It also aimed to determine and analyze the D2O relative abundance within different types of roots and shoots. The results indicated that water could be transported from roots in wet root-zone to roots in dry root-zone and shoots within 2 h after irrigation. Water transportation in roots of wet-zone was carried out by absorbing root, 1-2 mm root, 2-5 mm root, and〉5 mm root progressively, while through a reverse process in three dry root-zones. In shoots, water was transported to trunk, central trunk, annual branches, shoot and leaf progressively. Thus in the young apple trees subjected to PRI, water was distributed ifrst in the roots, including the roots in the wet and dry root-zones, to satisfy the water need of roots itself, and then transported to the shoot within hours of irrigation.

Root Morphology, Plant Growth, Nitrate Accumulation and Nitrogen Metabolism of Temperate Lettuce Grown in the Tropics with Elevated Root-Zone CO2 at Different Root-Zone Temperatures

This paper investigated the effects of root-zone (RZ) CO2 concentration ([CO2]) on root morphology and growth, nitrate (NO3-) uptake and assimilation of lettuce plants at different root-zone temperatures (RZT). Elevated RZ [CO2] stimulated root development, root and shoot growth compared to ambient RZ [CO2]. The greatest increase in root growth was observed in plants grown under elevated RZ [CO2] of 50,000 ppm. However, RZ [CO2] of 10,000 ppm was sufficient to achieve the maximal leaf area and shoot productivity. Lettuce plants exhibited faster shoot and root growth at 20°C-RZT than at ambient (A)-RZT. However, under elevated RZ [CO2], the magnitude of increased growth was greater at A-RZT than at 20°C-RZT. Compared to RZ [CO2] of 360 ppm, elevated RZ [CO2] of 10,000 ppm increased NO3- accumulation and nitrate reductase activity (NRA) in both leaves and roots. NO3- concentrations of leaf and root were higher at 20°C-RZT than at A-RZT in all plants. NRA was higher in root than in leaf especially under A-RZT. The total reduced nitrogen (TRN) concentration was significantly higher in plants grown under elevated RZ [CO2] of 10,000 ppm than under ambient RZ [CO2] of 360 ppm with greater concentration in 20°C-RZT plants than in A-RZT plants. These results imply that elevated RZ [CO2] significantly affected root morphology, root and shoot growth and N metabolism of temperate lettuce with greater impacts at A-RZT than at 20°C-RZT. These findings have practical significance to vegetable production by growing the vegetable crops at cool-RZT with elevated RZ [CO2] to enhance its productivity.

Yield Response to Deficit Irrigation and Partial Root-Zone Drying in Processing Tomato （Lycopersicon esculentum Mill,）

Due to the global expansion of irrigated areas and the limited availability of irrigation water, it is necessary to optimize water use in order to maximize crop yields under water deficit conditions. To evaluate the yield response of two processing tomato hybrids （Ercole and Genius） grown under different irrigation treatments, a field trial was conducted during the 2008 growing season in Southern Italy. Three irrigation treatments were used： the restitution of 70% of maximum evapotranspiration （ETc） both under ＂Deficit Irrigation＂ （70DI） and ＂Partial Root-zone Drying＂ （70PRD） strategies; full irrigated （FI： 100% ETc）. The two water deficit irrigation treatments （DI and PRD） showed stomatal conductance values lower than FI treatment and saved a substantial amount of water maintaining reasonable marketable yield. Moreover, PRD strategy showed slightly higher ＂Water Use Efficiency＂ （WUE） values than DI. Finally, ＂yield response factor＂ （Ky） showed always values less than unity, indicating the possibility to adopt, within certain limited condition, both DI and PRD in field-grown processing tomato cultivated in Southern Italy. In conclusion, in our experimental conditions, deficit irrigation practices seem to be acceptable relatively to processing tomato yield aspects and Ky could be promoted as a useful indicator for irrigation in water deficit conditions.

Effect of fertigation frequency on soil nitrogen distribution and tomato yield under alternate partial root-zone drip irrigation

Alternate partial root-zone drip fertigation (ADF) is a combination of alternating irrigation and drip fertigation,with the potential to save water and increase nitrogen (N) fertilizer efficiency.A 2-year greenhouse experiment was conducted to evaluate the effect of different fertigation frequencies on the distribution of soil moisture and nutrients and tomato yield under ADF.The treatments included three ADF frequencies with intervals of 3 days (F3),6 days (F6) and 12 days (F12),and conventional drip fertigation as a control (CK),which was fertilized once every 6 days.For the ADF treatments,two drip tapes were placed 10 cm away on each side of the tomato row,and alternate drip irrigation was realized using a manual valve on the distribution tapes.For the CK treatment,a drip tape was located close to the roots of the tomato plants.The total N application rate of all treatments was 180 kg ha^(-1).The total irrigation amounts applied to the CK treatment were450.6 and 446.1 mm in 2019 and 2020,respectively;and the irrigation amounts applied to the ADF treatments were 60%of those of the CK treatment.The F3 treatment resulted in water and N being distributed mainly in the 0–40-cm soil layer with less water and N being distributed in the 40–60-cm soil layer.The F6 treatment led to 21.0 and 29.0%higher 2-year average concentration of mineral N in the 0–20 and 20–40-cm soil layer,respectively and a 23.0%lower N concentration in the 40–60-cm soil layer than in the CK treatment.The 2-year average tomato yields of the F3,F6,F12,and CK treatments were 107.5,102.6,87.2,and 98.7 t ha^(-1),respectively.The tomato yield of F3 was significantly higher (23.3%) than that in the F12 treatment,whereas there was no significant difference between the F3 and F6 treatment.The F6 treatment resulted in yield similar to the CK treatment,indicating that ADF could maintain tomato yield with a 40%saving in water use.Based on the distribution of water and N,and tomato yield,a fertigation frequency of 6 days under ADF should be considered as a water-saving strategy for greenhouse tomato production.

Elevated Root-Zone Temperature Modulates Growth and Quality of Hydroponically Grown Carrots

Air and soil temperatures strongly influence the growth and quality of crops. However, in root vegetables, such as carrot, few experiments aimed at regulating growth and quality by manipulating root-zone temperature have been reported. We investigated the effect of root-zone temperatures (20&degC, 25&degC, 29&degC, and 33&degC) on carrot growth and components using a hydroponic system. High root-zone temperatures for 14 days reduced shoot and rootgrowth and water content. In contrast, total phenolic compounds and soluble-solid content increased in tap roots under high-temperature treatment. Root oxygen consumption was upregulated after 7 days under high-temperature treatment. These results suggest that high root-zone temperatures induce drought-like stress responses that modulate carrot biomass and components. High root-zone temperature treatments administered to hydroponically grown crops may be a valuable tool for improving and increasing the quality and value of crops.

Effects of Root-Zone Temperature on Photosynthesis, Productivity and Nutritional Quality of Aeroponically Grown Salad Rocket (Eruca sativa) Vegetable

Although tropical high ambient temperature and humidity severely reduced the productivity of temperate plants, temperate vegetable crops such as lettuce have been successfully grown in Singapore by only cooling its root-zone. In this paper, a cool Meditteranean vegetable, Eruca sativa, was studied to understand how different RZTs can impact its shoot productivity, photosynthesis and nutritional quality. All plants were cultivated using aeroponic systems in a tropical greenhouse under hot ambient conditions where roots were subjected to four different root-zone temperatures (RZTs) of 20°C-RZT, 25°C-RZT, 30°C-RZT and fluctuating ambient temperatures ranged from 25°C to 38°C [25°C/38°C (ambient)]-RZT. Parameters studied include shoot fresh weight (FW), photosynthetic gas exchange, midday chlorophyll (Chl) fluorescence Fv/Fm ratio, Chl fluorescence photochemical quenching (qP), non-photochemical quenching (qN) and electron transport rate (ETR), total phenolic compounds and mineral content such as potassium (K), calcium (Ca), magnesium (Mg) and iron (Fe). Among the 4 different RZT treatments, E. sativa plants grown under ambient-RZT (25/38°C-RZT) had the lowest shoot and root FW while those plants grown under 20°C-RZT had highest productivity of shoot and root. However, there were no significant differences in shoot and root FW in plants grown at 25°C- and 30°C-RZT. Compared to plants grown under 25°C/38°C (ambient-RZT), light-saturated photosynthetic CO2 assimilation rate (Asat) and stomatal conductance (gssat) were similarly higher in 20°C-, 25°C- and 30°C-RZT. All plants had midday Chl fluorescence Fv/Fm ratio lower than <0.8 ranged from 0.785 to 0.606 with the highest and lowest ratios recorded in 20°C-RZT and ambient-RZT plants, respectively. These results indicate that cooling the RZ of E. sativa plants protected their PS II from photoinactivation during midday in the greenhouse. There were no significant differences observed in photochemical quenching (qP), non-photochemical quenching (qN) and electron transport rate among plants grown under 20°C-, 25°C- and 30°C-RZT. However, plants grown under ambient-RZT had lower qP, qN and ETR compared to all other plants. E. sativa at 20°C-RZT with the best developed roots had the highest dietary mineral (K, Mg, Ca and Fe) contents but lower total phenolics content. In contrast, ambient-RZT, plants with poorly developed roots had the lowest mineral content but highest total phenolic content. The results of this study suggest that cooling of roots is a feasible method for the cultivation of E. sativa in the tropic, which enhances the content of dietary minerals in shoots.

Validity,Reliability,and Measurement Invariance of the Thai Smartphone Application-Based Addiction Scale and Bergen Social Media Addiction Scale

Background:In recent years,there has been increased research interest in both smartphone addiction and social media addiction as well as the development of psychometric instruments to assess these constructs.However,there is a lack of psychometric evaluation for instruments assessing smartphone addiction and social media addiction in Thailand.The present study evaluated the psychometric properties and gender measurement invariance of the Thai version of the Smartphone Application-Based Addiction Scale(SABAS)and Bergen Social Media Addiction Scale(BSMAS).Method:A total of 801 Thai university students participated in an online survey from January 2022 to July 2022 which included demographic information,SABAS,BSMAS,and the Internet Gaming Disorder Scale-Short Form(IGDS9-SF).Results:Confirmatory Factor Analyses(CFAs)found that both the SABAS and BSMAS had a one-factor structure.Findings demonstrated adequate psychometric properties of both instruments and also supported measurement invariance across genders.Moreover,scores on the SABAS and BSMAS were correlated with scores on the IGDS9-SF.Conclusion:The results indicated that the SABAS and BSMAS are useful psychometric instruments for assessing the risk of smartphone addiction and social media addiction among Thai young adults.

An inverse analysis of fluid flow through granular media using differentiable lattice Boltzmann method

This study presents a method for the inverse analysis of fluid flow problems.The focus is put on accurately determining boundary conditions and characterizing the physical properties of granular media,such as permeability,and fluid components,like viscosity.The primary aim is to deduce either constant pressure head or pressure profiles,given the known velocity field at a steady-state flow through a conduit containing obstacles,including walls,spheres,and grains.The lattice Boltzmann method(LBM)combined with automatic differentiation(AD)(AD-LBM)is employed,with the help of the GPU-capable Taichi programming language.A lightweight tape is used to generate gradients for the entire LBM simulation,enabling end-to-end backpropagation.Our AD-LBM approach accurately estimates the boundary conditions for complex flow paths in porous media,leading to observed steady-state velocity fields and deriving macro-scale permeability and fluid viscosity.The method demonstrates significant advantages in terms of prediction accuracy and computational efficiency,making it a powerful tool for solving inverse fluid flow problems in various applications.

Making the case for the evolving role of social media in health professions education and a literature review on the application of some in ophthalmology

Background and Objective:Social media(SoMe)has emerged as a tool in health professions education(HPE),particularly amidst the challenges posed by the coronavirus disease 2019(COVID-19)pandemic.Despite the academia’s initial skepticism SoMe has been gaining traction in supporting learning communities,and offering opportunities for innovation in HPE.Our study aims to explore the integration of SoMe in HPE.Four key components were outlined as necessary for a successful integration,and include designing learning experiences,defining educator roles,selecting appropriate platforms,and establishing educational objectives.Methods:This article stemmed from the online Teaching Skills Series module on SoMe in education from the Ophthalmology Foundation,and drew upon evidence supporting learning theories relevant to SoMe integration and models of education.Additionally,we conducted a literature review considering Englishlanguage articles on the application of SoMe in ophthalmology from PubMed over the past decade.Key Content and Findings:Early adopters of SoMe platforms in HPE have leveraged these tools to enhance learning experiences through interaction,dialogue,content sharing,and active learning strategies.By integrating SoMe into educational programs,both online and in-person,educators can overcome time and geographical constraints,fostering more diverse and inclusive learning communities.Careful consideration is,however,necessary to address potential limitations within HPE.Conclusions:This article lays groundwork for expanding SoMe integration in HPE design,emphasizing the supportive scaffold of various learning theories,and the need of furthering robust research on examining its advantages over traditional educational formats.Our literature review underscores an ongoing multifaceted,random application of SoMe platforms in ophthalmology education.We advocate for an effective incorporation of SoMe in HPE education,with the need to comply with good educational practice.

Retraction:YEATS domain containing 4 promotes gastric cancer cell proliferation and mediates tumor progression via activating the Wnt/β-Catenin signaling pathway

Following the publication,concerns have been raised about a number of figures in this article.An unexpected area of similarity was identified in terms of the cellular data,where the results from differently performed experiments were intended to have been shown,although the areas immediately surrounding this area featured comparatively different distributions of cells.In addition,the western blots in this article were presented with atypical,unusually shaped and possibly anomalous protein bands in many cases.

The Impact of Social Media on Dietary Behaviors and Body Image of College Students: A Qualitative Approach

Background: The use of social media platforms for health and nutrition information has become popular among college students. Although social media made information readily accessible in different formats, nutritional misinformation promoted by influencers and non-experts caused negative impact on diet behavior and perception of body image. Previous research indicated that extensive use of social media was positively linked to disordered eating behaviors. Social media platforms like Facebook and Instagram that allow users to follow celebrities intensified exposure to influencers’ messages and images and resulted in negative moods and body dissatisfaction. Objective: This paper aims to explore the impact of social media on college students’ dietary behaviors and body image. Participants: 18 undergraduate students from a public university in the Southern United States were recruited through a mass email. Methods: A cross-sectional qualitative study of three focus groups was conducted. The focus groups were based on guiding open-ended questions. Atlas.ti was used to code and analyze the data using inductive and deductive codes. Results: Three main themes were identified. The conditions theme included elements that explain why and how social media influences the participants’ actions. The actions theme included eating behavior, physical activity, and dietary supplement intake. The consequences theme describes anticipated or actual outcomes of actions such as body image and ideal weight. Conclusions: Social media has had a negative influence on diet behaviors and a positive influence on physical activity. Evidence-based nutrition and weight management information is needed to thwart potential misinformation.

Potential use of large language models for mitigating students’problematic social media use:ChatGPT as an example

The problematic use of social media has numerous negative impacts on individuals'daily lives,interpersonal relationships,physical and mental health,and more.Currently,there are few methods and tools to alleviate problematic social media,and their potential is yet to be fully realized.Emerging large language models(LLMs)are becoming increasingly popular for providing information and assistance to people and are being applied in many aspects of life.In mitigating problematic social media use,LLMs such as ChatGPT can play a positive role by serving as conversational partners and outlets for users,providing personalized information and resources,monitoring and intervening in problematic social media use,and more.In this process,we should recognize both the enormous potential and endless possibilities of LLMs such as ChatGPT,leveraging their advantages to better address problematic social media use,while also acknowledging the limitations and potential pitfalls of ChatGPT technology,such as errors,limitations in issue resolution,privacy and security concerns,and potential overreliance.When we leverage the advantages of LLMs to address issues in social media usage,we must adopt a cautious and ethical approach,being vigilant of the potential adverse effects that LLMs may have in addressing problematic social media use to better harness technology to serve individuals and society.

Associations between Social Media Use and Sleep Quality in China:Exploring the Mediating Role of Social Media Addiction

Sleep quality is closely linked to people’s health,and during the COVID-19 pandemic,the sleep patterns of residents in China were notably poor.The lockdown in China led to an increase in social media use,prompting questions about its impact on sleep.Therefore,this study investigates the association between social media use and sleep quality among Chinese residents during the COVID-19 outbreak,highlighting the potential mediating role of social media addiction.Data were collected via questionnaires through a cross-sectional survey with 779 valid responses.Variance analysis was used to test for differences in social media use among different demographic variables.Bivariate correlation analysis was employed to explore the relationships between variables,while regression analysis investigated the correlations between various media factors and sleep quality.Additionally,Bootstrap sampling was utilized to analyze the potential mediating influence of social media addiction in the relationship between social media use and sleep.The study's findings reveal a significant correlation between social media use,particularly before bedtime,and sleep quality(p<0.01),with pre-sleep activity notably linked to poorer overall sleep scores(β=0.141,p=0.004).Although the daily use of social media did not directly impact most individuals’sleep quality,specific platforms like news apps,short video apps,dating apps,and content community platforms were associated with higher levels of social media addiction,subsequently negatively affecting sleep quality.Specifically,the use of news apps(B=0.068,95%CI[0.000,0.019]),short video apps(B=0.112,95%CI[0.001,0.031]),dating apps(B=0.147,95%CI[0.000,0.028]),and content community platforms(B=0.106,95%CI[0.001,0.028])was found to increase the risk of social media addiction,subsequently leading to adverse effects on sleep quality.The study underscores a notable link between social media use and sleep quality,suggesting that mindful social media habits,particularly before bedtime,and reducing addiction-associated apps could enhance sleep quality.

Porous-DeepONet:Learning the Solution Operators of Parametric Reactive Transport Equations in Porous Media

Reactive transport equations in porous media are critical in various scientific and engineering disciplines,but solving these equations can be computationally expensive when exploring different scenarios,such as varying porous structures and initial or boundary conditions.The deep operator network(DeepONet)has emerged as a popular deep learning framework for solving parametric partial differential equations.However,applying the DeepONet to porous media presents significant challenges due to its limited capability to extract representative features from intricate structures.To address this issue,we propose the Porous-DeepONet,a simple yet highly effective extension of the DeepONet framework that leverages convolutional neural networks(CNNs)to learn the solution operators of parametric reactive transport equations in porous media.By incorporating CNNs,we can effectively capture the intricate features of porous media,enabling accurate and efficient learning of the solution operators.We demonstrate the effectiveness of the Porous-DeepONet in accurately and rapidly learning the solution operators of parametric reactive transport equations with various boundary conditions,multiple phases,and multiphysical fields through five examples.This approach offers significant computational savings,potentially reducing the computation time by 50–1000 times compared with the finite-element method.Our work may provide a robust alternative for solving parametric reactive transport equations in porous media,paving the way for exploring complex phenomena in porous media.

Selection of media tools for community planning:A study from the perspective of communicative planning

In community planning,due to the lack of evidence regarding the selection of media tools,this study examines how a common but differentiated ideal speech situation can be created as well as how more appropriate media tools can be defined and selected in the community planning process.First,this study describes the concept and theoretical basis of media used in community planning from the perspectives of the multiple effects of media evolution on communicative planning.Second,the classification criteria and typical characteristics of media tools used to support community planning are clarified from three dimensions:acceptability,cost effectiveness,and applicability.Third,strategies for applying media tools in the four phases of communicative planning-namely,state analysis,problem identification,contradictory solution and optimization-are described.Finally,trends in the development of media tools for community planning are explored in terms of multistakeholder engagement,supporting scientific decision-making and multiple-type media integration.The results provide a reference for developing more inclusive,effective,and appropriate media tools for enhancing decision-making capacity and modernizing governance in community planning and policy-making processes.

Analyzing topics in social media for improving digital twinning based product development

Digital twinning enables manufacturers to create digital representations of physical entities,thus implementing virtual simulations for product development.Previous efforts of digital twinning neglect the decisive consumer feedback in product development stages,failing to cover the gap between physical and digital spaces.This work mines real-world consumer feedbacks through social media topics,which is significant to product development.We specifically analyze the prevalent time of a product topic,giving an insight into both consumer attention and the widely-discussed time of a product.The primary body of current studies regards the prevalent time prediction as an accompanying task or assumes the existence of a preset distribution.Therefore,these proposed solutions are either biased in focused objectives and underlying patterns or weak in the capability of generalization towards diverse topics.To this end,this work combines deep learning and survival analysis to predict the prevalent time of topics.We propose a specialized deep survival model which consists of two modules.The first module enriches input covariates by incorporating latent features of the time-varying text,and the second module fully captures the temporal pattern of a rumor by a recurrent network structure.Moreover,a specific loss function different from regular survival models is proposed to achieve a more reasonable prediction.Extensive experiments on real-world datasets demonstrate that our model significantly outperforms the state-of-the-art methods.

Social Media-Based Surveillance Systems for Health Informatics Using Machine and Deep Learning Techniques:A Comprehensive Review and Open Challenges

Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic outbreaks.This review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their performance.Since,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by SM.This paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic outbreaks.DL has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation results.In recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM analysis.This paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM analysis.Finally,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.

Integrating Neighborhood Geographic Distribution and Social Structure Influence for Social Media User Geolocation

Geolocating social media users aims to discover the real geographical locations of users from their publicly available data,which can support online location-based applications such as disaster alerts and local content recommen-dations.Social relationship-based methods represent a classical approach for geolocating social media.However,geographically proximate relationships are sparse and challenging to discern within social networks,thereby affecting the accuracy of user geolocation.To address this challenge,we propose user geolocation methods that integrate neighborhood geographical distribution and social structure influence(NGSI)to improve geolocation accuracy.Firstly,we propose a method for evaluating the homophily of locations based on the k-order neighbor-hood geographic distribution(k-NGD)similarity among users.There are notable differences in the distribution of k-NGD similarity between location-proximate and non-location-proximate users.Exploiting this distinction,we filter out non-location-proximate social relationships to enhance location homophily in the social network.To better utilize the location-proximate relationships in social networks,we propose a graph neural network algorithm based on the social structure influence.The algorithm enables us to perform a weighted aggregation of the information of users’multi-hop neighborhood,thereby mitigating the over-smoothing problem of user features and improving user geolocation performance.Experimental results on real social media dataset demonstrate that the neighborhood geographical distribution similarity metric can effectively filter out non-location-proximate social relationships.Moreover,compared with 7 existing social relationship-based user positioning methods,our proposed method can achieve multi-granularity user geolocation and improve the accuracy by 4.84%to 13.28%.