Strong Support Research Articles

Investigation on the Lubrication Heat Transfer Mechanism of the Multilevel Gearbox by the Lattice Boltzmann Method

In a gear transmission system in a closed space, the heat transfer between gears and fluids presents highly nonlinear characteristics due to the complex physical processes involved in heat exchange and fluid motion, and constructing and solving the thermodynamic model of the gearbox becomes a task that involves considerable difficulty. This paper takes a conical–cylindrical two-stage gearbox as the research object, proposes a fluid–solid coupled dynamics model based on the lattice Boltzmann (LBM) combined with the large eddy simulation (LES) method, and the adopted lattice model is the D3Q27 velocity model, which is used to numerically simulate the distribution of the flow field inside the gearbox and undertake in-depth research on the fluid motion law of the complex gear transmission system in the enclosed space. The model is solved to reveal the laws determining the gear speed and the effects of the lubricant’s dynamic viscosity and thermal conductivity coefficient on the gear heat dissipation efficiency. By adopting the lattice Boltzmann method, we can simulate the fluid flow and heat transfer inside the gearbox more efficiently, which provides a new way to closely understand the thermodynamic behavior of closed complex gear transmission systems. The application of this method is expected to provide strong support for thermal performance optimization and the design of gear transmission systems.

The VMC survey. L. Type II Cepheids in the Magellanic Clouds: Period–luminosity relations in the near-infrared bands

Type II Cepheids (T2Cs) are the less frequently used counterparts of classical or type I Cepheids (CCs) which provide the primary calibration of the distance ladder for measuring the Hubble constant in the local Universe. In the era of the `Hubble tension', T2C variables together with the RR Lyrae stars and the tip of the red giant branch (TRGB) can potentially provide non-CC-dependent calibration of the cosmic distance ladder. Our goal is to provide an absolute calibration of the period--luminosity, period--luminosity--colour, and period--Wesenheit relations (PL, PLC, and PW, respectively) of T2Cs in the Large Magellanic Cloud (LMC), which traditionally serves as a crucial first anchor of the extragalactic distance ladder. We exploited time-series photometry in the near-infrared (NIR) $Y,\,J,$ and $K_s$ bands for a sample of approximately $320$ T2Cs in the Magellanic Clouds (MCs). These observations were acquired during 2009--2018 in the context of the VISTA survey of the Magellanic Clouds system (VMC), an ESO public survey. We supplemented the NIR photometry from the VMC survey with well-sampled optical light curves and accurate pulsation periods from the Optical Gravitational Lensing Experiment (OGLE) IV survey and the $Gaia$ mission. We used the best-quality NIR light curves to generate custom templates for modelling sparsely sampled light curves in $YJK_s$ bands. The best-fitting $YJK_s$ template light curves were used to derive accurate and precise intensity-averaged mean magnitudes and pulsation amplitudes of 277 and 62 T2Cs in the LMC and SMC, respectively. We used optical and NIR mean magnitudes for different T2C subclasses (BLHer, WVir, and RVTau) to derive PL/PLC/PW relations in multiple bands, which were calibrated with the geometric distance to the LMC as derived from eclipsing binaries and with the $Gaia$ parallaxes. We used our new empirical calibrations of PL and PW relations to obtain distances to 22 T2C-host Galactic globular clusters, which were found to be systematically smaller by $ $0.1 mag and 0.03--0.06 mag than in the literature when the zero points are calibrated with the distance of the LMC or $Gaia$ parallaxes, respectively. Better agreement is found between our distances and those based on RR Lyrae stars in globular clusters, providing strong support for using these population II stars together with the TRGB for future distance scale studies.

“We Want You!” Applying Social Network Analysis to Online Extremist Communities

ABSTRACT Current literature on online criminal and deviant groups recognizes the role of online forums in the transfer of knowledge and socialization of members, but debates on the role of the Internet in the socialization and radicalization processes in the context of online extremist groups. This study contributes to the discussion by examining online radicalization process through the use of social learning theory and social network analysis. This innovation allows for assessment on the impact of online interactions with forum members on radicalization process. Findings found strong support of differential association and differential reinforcement, but showed the possibility of other mechanisms, such as self-radicalization, at play. Findings from the study highlight the need to for theory integration, the inclusion of online peer association, and replication to address the complex phenomenon of online radicalization.

Smartphone-integrated colorimetric sensor for rapid and highly selective detection of spermine in food based on the laccase-mimicking activity of flower-shaped Mn3O4 nanoparticles

Colorimetric methods have the benefits of rapid detection and easy operation in the detection of spermine (SPM). However, the existing colorimetric sensor for detecting SPM still face challenges in terms of performance stability, result reliability and safety of sensing materials. Herein, it was first found that flower-like Mn3O4 nanoparticles (Mnf) exhibit excellent laccase-mimicking activity. Since SPM can effectively inhibit this activity, a colorimetric sensor was developed to detect SPM in food. The addition of positive charged SPM will induce the aggregation of multiple Mnf with negative charge through electrostatic interactions. In this case, the specific surface area of Mnf is reduced, and some surface-active sites are occupied by SPM, leading to a decrease in the laccase-mimicking activity of Mnf. Consequently, the colorimetric sensor appears light pink. Furthermore, a smartphone was utilized to convert the color of the reaction solution into the corresponding G/B value, facilitating on-site and fast analysis of SPM quantity. The proposed colorimetric sensor exhibits outstanding sensitivity and selectivity, with a limit of detection (LOD) as low as 0.094 μg·mL−1. The colorimetric sensor also features stable performance, reliable results and environmentally friendly safety, all of which will provide strong support for the monitoring of SPM in the food industry.

A Hybrid Convolutional and Recurrent Neural Network for Multi-Sensor Pile Damage Detection with Time Series.

Machine learning (ML) algorithms are increasingly applied to structure health monitoring (SHM) problems. However, their application to pile damage detection (PDD) is hindered by the complexity of the problem. A novel multi-sensor pile damage detection (MSPDD) method is proposed in this paper to extend the application of ML algorithms in the automatic identification of PDD. The time-series signals collected by multiple sensors during the pile integrity test are first processed by the traveling wave decomposition (TWD) theory and are then input into a hybrid one-dimensional (1D) convolutional and recurrent neural network. The hybrid neural network can achieve the automatic multi-task identification of pile damage detection based on the time series of MSPDD results. Finally, the analytical solution-based sample set is utilized to evaluate the performance of the proposed hybrid model. The outputs of the multi-task learning framework can provide a detailed description of the actual pile quality and provide strong support for the classification of pile quality as well.

A Taxonomic Review of South African Indigenous Meliaceae Using Molecular Systematics and Anatomical Data

The Meliaceae are broadly distributed worldwide, with about 50 genera and over 1400 species. There are 11 genera in South Africa, with 13 indigenous and three naturalized species. Considering the diversity of the indigenous species of this family in South Africa and the lack of recent studies encompassing these species, a taxonomic revision of the South African indigenous species of Meliaceae is presented here. Phylogenetic analysis, anatomical data, herbarium collections, and online data sources were used in this study. The results confirm the monophyly of Melioideae and Swietenioideae. The incongruence of Turraea previously reported was resolved in this study. Most representative genera of South African Meliaceae were recovered monophyletic with strong support. However, multiple samplings of species and including more markers could provide a better understanding of the relationships among South African species of Meliaceae. The review of the taxonomy of the South African Meliaceae, and especially the study of diagnostic characters and hitherto recorded natural distributions, have value in providing an up-to-date inventory of the indigenous genera and species and an easy means of identifying the taxa. Anatomical characters may be of systematic value to explore higher-level relationships in the family. This study is a contribution to tropical botany and to a more comprehensive database for the Meliaceae.

Paving Their Own Road? Local Chinese and World Bank Aid and Foreign Direct Investment in Africa

Abstract China’s emergence as a major donor and economic partner to sub-Saharan Africa has prompted questions if the aims and impacts of China’s efforts in the region are driven by self-serving commercial motives. While there are strong reasons to think that the foreign aid may make a location more attractive to investment, generally, by improving the infrastructural, institutional, or human capital environment and/or by serving as a signal of a location’s risk, there is also reason to suspect that Chinese aid may be “paving the way” for investment by Chinese firms. To investigate, this paper uses spatial and temporal variations in localized, geo-referenced data to find a strong overall support that local aid boosts local foreign direct investment (FDI). However, we also find some evidence that Chinese aid boosts its own FDI compared to FDI from third-party countries; but this differential effect is also visible with the Chinese FDI’s response to the World Bank aid as well as in the relationship between both aid and FDI from the USA, suggesting that the Chinese FDI may simply be following any aid and that the relationship between its aid and FDI is not exceptional among bilateral donors.

Real-Time Epidemiology and Acute Care Need Monitoring and Forecasting for COVID-19 via Bayesian Sequential Monte Carlo-Leveraged Transmission Models.

COVID-19 transmission models have conferred great value in informing public health understanding, planning, and response. However, the pandemic also demonstrated the infeasibility of basing public health decision-making on transmission models with pre-set assumptions. No matter how favourably evidenced when built, a model with fixed assumptions is challenged by numerous factors that are difficult to predict. Ongoing planning associated with rolling back and re-instituting measures, initiating surge planning, and issuing public health advisories can benefit from approaches that allow state estimates for transmission models to be continuously updated in light of unfolding time series. A model being continuously regrounded by empirical data in this way can provide a consistent, integrated depiction of the evolving underlying epidemiology and acute care demand, offer the ability to project forward such a depiction in a fashion suitable for triggering the deployment of acute care surge capacity or public health measures, and support quantitative evaluation of tradeoffs associated with prospective interventions in light of the latest estimates of the underlying epidemiology. We describe here the design, implementation, and multi-year daily use for public health and clinical support decision-making of a particle-filtered COVID-19 compartmental model, which served Canadian federal and provincial governments via regular reporting starting in June 2020. The use of the Bayesian sequential Monte Carlo algorithm of particle filtering allows the model to be regrounded daily and adapt to new trends within daily incoming data-including test volumes and positivity rates, endogenous and travel-related cases, hospital census and admissions flows, daily counts of dose-specific vaccinations administered, measured concentration of SARS-CoV-2 in wastewater, and mortality. Important model outputs include estimates (via sampling) of the count of undiagnosed infectives, the count of individuals at different stages of the natural history of frankly and pauci-symptomatic infection, the current force of infection, effective reproductive number, and current and cumulative infection prevalence. Following a brief description of the model design, we describe how the machine learning algorithm of particle filtering is used to continually reground estimates of the dynamic model state, support a probabilistic model projection of epidemiology and health system capacity utilization and service demand, and probabilistically evaluate tradeoffs between potential intervention scenarios. We further note aspects of model use in practice as an effective reporting tool in a manner that is parameterized by jurisdiction, including the support of a scripting pipeline that permits a fully automated reporting pipeline other than security-restricted new data retrieval, including automated model deployment, data validity checks, and automatic post-scenario scripting and reporting. As demonstrated by this multi-year deployment of the Bayesian machine learning algorithm of particle filtering to provide industrial-strength reporting to inform public health decision-making across Canada, such methods offer strong support for evidence-based public health decision-making informed by ever-current articulated transmission models whose probabilistic state and parameter estimates are continually regrounded by diverse data streams.

A short review of medical-grade stainless steel: Corrosion resistance and novel techniques

Due to its exceptional quality as a biomedical metal, stainless steel is often utilized to produce a broad range of medical tools. The resistance of stainless steel to corrosion is a key indicator of how long and how effective it will serve its intended purpose, and it is an important factor in determining the biocompatibility of the material. However, due to the complex physiological environment within the human body, the corrosion management of medical-grade stainless steel is facing several challenges. In this article, an overview of the factors that influence the corrosion performance of medical-grade stainless steel is provided, and new technologies and methods that have been developed in recent years to improve the corrosion resistance are discussed. These cutting-edge methods are expected to improve the corrosion resistance and longevity of medical-grade stainless steel, providing strong support for the increased applicability of the material in the medical industry.

Eggs - a scoping review for Nordic Nutrition Recommendations 2023.

Cardiovascular diseases (CVD), type 2 diabetes (T2D), and cancer are a significant public health burden in the Nordic and Baltic countries. High intake of eggs, mainly due to its high cholesterol content, has been suggested to have adverse health effects. The purpose of this scoping review is to describe the evidence related to the impact of egg intake on health. A literature search identified 38 systematic reviews and meta-analyses on egg consumption in relation to health outcomes published between 2011 and 30 April 2022. Overall, current evidence from systematic reviews of randomized clinical trials indicates that higher egg intake may increase serum total cholesterol concentration and the ratio of low-density lipoprotein to high-density lipoprotein cholesterol, but with substantial heterogeneity in the response. However, recent evidence from observational studies does not provide strong support for a detrimental role of moderate egg consumption (up to one egg/day) on the risk of CVD, especially in the European studies. The overall evidence from observational studies indicates that egg consumption is not associated with increased risk of mortality or T2D in European study populations. There is also little support for a role of egg consumption in cancer development, although a weak association with higher risk of certain cancers has been found in some studies, mainly case-control studies. Again, no associations with cancer risk have been observed in European studies. Systematic reviews and meta-analyses of egg consumption in relation to other health-related outcomes are scarce. There are also limited data available on the associations between the consumption of more than one egg/day and risk of diseases. Based on the available evidence, one egg/day is unlikely to adversely affect overall disease risk.

Ectopic expression of an Old Yellow Enzyme (OYE3) gene from Saccharomyces cerevisiae increases the tolerance and phytoremediation of 2-nitroaniline in rice

2-nitroaniline (2-NA) is an environmental pollutant and has been extensively used as intermediates in organic synthesis. The presence of 2-NA in the environment is not only harmful for aquatic life but also mutagenic for human beings. In this study, we constructed transgenic rice expressing an Old Yellow Enzyme gene, ScOYE3, from Saccharomyces cerevisiae. The ScOYE3 transgenic plants were comprehensively investigated for their biochemical responses to 2-NA treatment and their 2-NA phytoremediation capabilities. Our results showed that the rice seedlings exposed to 2-NA stress, showed growth inhibition and biomass reduction. However, the transgenic plants exhibited strong tolerance to 2-NA stress compared to wild-type plants. Ectopic expression of ScOYE3 could effectively protect transgenic plants against 2-NA damage, which resulted in less reactive oxygen species accumulation in transgenic plants than that in wild-type plants. Our phytoremediation assay revealed that transgenic plants could eliminate more 2-NA from the medium than wild-type plants. Moreover, omics analysis was performed in order to get a deeper insight into the mechanism of ScOYE3-mediated 2-NA transformation in rice. Altogether, the function of ScOYE3 during 2-NA detoxification was characterized for the first time, which serves as strong theoretical support for the phytoremediation potential of 2-NA by Old Yellow Enzyme genes.

Stringent sustainability regulations for global supply chains are supported across middle-income democracies

Expanded international trade and globalised production networks are increasing the environmental and social impacts in middle-income countries (GNI per capita $1,136-$13,845). High-income countries (>$13,845) are seeking to mitigate the negative impacts of domestic consumption by imposing new sustainability regulations on global supply chains. Recent evidence suggests that these regulations are broadly supported across high-income countries. However, it remains unclear whether citizens of middle-income countries support aligning domestic sustainability regulations with the measures developed by high-income countries. Concerns about economic competitiveness and foreign imposition could increase public resistance toward such alignment. Alternatively, desires for continued market access in high-income countries and aspirations for strengthening local environmental and labour regulations could foster support for alignment. Based on survey-embedded experiments in the three largest democratic non-OECD economies (Brazil, India, Indonesia), we find surprisingly strong support for domestic-based measures that are aligned with emerging global supply chain sustainability regulations. Our findings suggest that support is largely driven by positive impact expectations, where the future benefits of alignment are perceived as outweighing concerns about increased costs. These results bode well for initiatives to install stricter sustainability regulations for global supply chains that are acceptable not only in high-income economies but also in non-OECD countries.

Gas‐phase Smiles rearrangement of ortho‐nitro‐substituted diaryliodonium cations and their mechanistic insights

RationaleDiaryliodonium salts are useful electrophilic reagents in organic chemistry, finding extensive applications in arylations and photo‐induced polymerizations. However, comprehensive mechanistic investigations, particularly concerning the mass spectrometric behaviors of diaryliodonium salts, are relatively scarce in the literature.MethodsDiaryliodonium salts could be readily ionized using electrospray ionization mass spectrometry (ESI‐MS) to give [Ar1‐I+‐Ar2], and high‐resolution ESI‐tandem mass spectrometry (MS/MS) experiments were conducted to investigate their gas‐phase chemical reactions.ResultsInvestigations on ESI‐MS/MS of [Ar1‐I+‐Ar2] revealed two major fragmentation patterns: (1) reductive elimination resulting in the diaryl coupling product ion [Ar1‐Ar2]+• by the loss of I; (2) generation of aryl cations [Ar1]+ or [Ar2]+ through cleavage of the C–I bonds. We revealed that the introduction of NO2 into Ar2 of [Ar1‐I+‐Ar2] could lead to an unexpected fragmentation ion [Ar1O]+ in MS/MS, arising from an O‐atom transfer process from NO2 to Ar1. Particularly, when NO2 was ortho‐positioned to the iodine in Ar2, the [Ar1O]+ sometimes exhibited dominant behavior.ConclusionsComprehensive ESI‐MS/MS studies and theoretical calculations provided strong support for the O‐atom transfer mechanistic pathway: [Ar1‐I+‐(o‐NO2‐Ar2)] initially underwent a Smiles rearrangement to the intermediate [Ar1‐O‐(o‐NO‐Ar2I)]+, which subsequently dissociated to [Ar1O]+ or [o‐NO‐Ar2I]+•. Herein, we proposed an unexpected “ortho effect” in the gas‐phase fragmentation reaction of [Ar1‐I+‐(o‐NO2‐Ar2)], in which the crucial determinant factor for the aryl migration was identified as the Smiles rearrangement reaction.

Assessing pragmatic language difficulties using the Revised Children's Communication Checklist-2. Exploratory structural equation modeling and associations with restricted and repetitive behaviors.

In this paper, we investigated the psychometric properties of the Child Communication Checklist-Revised (CCC-R) for the first time with an English-speaking sample. We used a confirmatory application of exploratory structural equation modeling (ESEM) to re-evaluate the CCC-R's psychometric properties. We found strong support for its use as an assessment for pragmatic and structural language. Our second main aim was to explore associations between pragmatic and structural language and restricted and repetitive behaviors (RRBs), two hallmark characteristics of autism. We used the CCC-R and Repetitive Behavior Questionnaire (RBQ-2) to investigate these associations in a diverse non-clinical sample of children, taking a transdiagnostic approach. We intentionally excluded autism and other neurodevelopmental diagnoses to test, (1) the CCC-R in a broad sample and (2) the association between pragmatic language and RRB in children not already selected for that association. The sample comprised two groups of children, one was community sampled (n = 123) and the other (n = 143) included children with non-specific behavioral, emotional and/or cognitive difficulties referred to an assessment unit by schools. We found clear associations between pragmatic language difficulties and RRBs in both groups. Regression analysis showed that pragmatic language was the only significant contributor to RRBs even after Grammatical-Semantic score, age, sex, and socioeconomic status were controlled. The pattern was the same for both recruitment groups. However, the effects were stronger for the school-referred group which also had more pragmatic difficulties, grammatical-semantic difficulties and RRBs. A robust link between pragmatic language and RRBs, established in autism, has continuity across the broader non-clinical population.

Strong Bipartisan Support for Controlled Psilocybin Use as Treatment or Enhancement in a Representative Sample of US Americans: Need for Caution in Public Policy Persists

The psychedelic psilocybin has shown promise both as treatment for psychiatric conditions and as a means of improving well-being in healthy individuals. In some jurisdictions (e.g., Oregon, USA), psilocybin use for both purposes is or will soon be allowed and yet, public attitudes toward this shift are understudied. We asked a nationally representative sample of 795 US Americans to evaluate the moral status of psilocybin use in an appropriately licensed setting for either treatment of a psychiatric condition or well-being enhancement. Showing strong bipartisan support, participants rated the individual’s decision as morally positive in both contexts. These results can inform effective policy-making decisions around supervised psilocybin use, given robust public attitudes as elicited in the context of an innovative regulatory model. We did not explore attitudes to psilocybin use in unsupervised or non-licensed community or social settings.

Assessing and prioritizing drivers and strategies for transition to a green energy for sustainable development in China

This study addresses the critical global challenge of climate change, primarily caused by the overconsumption of fossil fuels. Recognizing the urgent need for a transition to green energy (GE) sources such as wind, solar, hydro, and biomass, this research focuses on identifying effective strategies for fostering a sustainable and low-carbon energy future in China. The study employs a combination of the Analytical Hierarchy Process (AHP) and fuzzy Decision-making Trial and Evaluation Laboratory (DEMATEL), both well-established multi-criteria decision-making (MCDM) methods, to analyze various drivers, sub-drivers, and strategies crucial for this transition. Through an extensive literature review, we identified several key drivers and strategies aiding the shift towards GE for sustainable development. The AHP method was applied to evaluate and rank the major drivers and sub-drivers, such as policy, financing, and infrastructure and innovation, that are crucial for China's successful transition to GE. Simultaneously, fuzzy DEMATEL was utilized to prioritize vital strategies, including public awareness and education, financial incentives and support mechanisms, and policy and regulatory frameworks. The findings reveal that, in addition to strong policy and financial support, public awareness and education are critical for advancing GE development in China. This study underscores the importance of integrating various drivers and strategies for effective green energy development, aiming to mitigate the environmental impacts of fossil fuel use.

The Federal Reserve’s responses to the post-Covid period of high inflation

In the face of the COVID-19 pandemic in March 2020, the Federal Reserve committed to using its full range of tools to support the U.S. economy. Over the next year and a half, with progress on vaccinations and strong policy support, indicators of economic activity and employment strengthened while inflation moved higher. Faced with a tight labor market and elevated inflation, the Federal Open Market Committee (FOMC) began a process of unwinding the very accommodative stance of monetary policy and moving to a restrictive policy stance to address inflation pressures. Here we review the sequence of actions taken by the Committee between late 2020 and mid-2023 as well as discuss some issues it contemplated along the way; the table provides a chronological list of key events over this period.

Partnership Status, Health, and Mortality: Selection or Protection?

Married individuals have better health and lower mortality than nonmarried people. Studies show that when cohabitants are distinguished from other nonmarried groups, health differences between partnered and nonpartnered individuals become even more pronounced. Some researchers have argued that partnered individuals have better health and lower mortality because a partnership offers protective effects (protection); others have posited that partnered people have better health and lower mortality because healthy persons are more likely to form a union and less likely to dissolve it (selection). This study contributes to this debate by investigating health and mortality by partnership status in England and Wales and analyzing the causes of mortality differences. We use combined data from the British Household Panel Survey and the UK Household Longitudinal Study and apply a simultaneous-equations hazard model to control for observed and unobserved selection into partnerships. We develop a novel approach to identify frailty based on self-rated health. Our analysis shows that partnered individuals have significantly lower mortality than nonpartnered people. We observe some selection into and out of unions on unobserved health characteristics, but the mortality differences by partnership status persist. The study offers strong support for the marital protection hypothesis and extends it to nonmarital partnerships.

Effect of Cr Segregation on Mechanical Behavior and Deformation Mechanism of Ni─Co─Cr Alloy

AbstractNi─Co alloys have attracted extensive attention from materials researchers in recent years because of their excellent properties. The effect of solute segregation on the properties of the alloy is studied by molecular dynamics simulation. The results show that the yield strength increases from 2.8 to 3.5 GPa when the solute atom Cr is introduced into the grain boundary. Under the action of stress, the disorder of segregation grain boundary is enhanced, which hinders the growth of grain, produces less layer fault structure, and the peak number of HCP (Hexagonal Close Packed) atom decreases from 50 000 to 37 000. The introduction of solute atoms provides a strong support for the grain boundary and has a similar skeleton structure, which improves the deformation resistance of the lattice. In addition, the improved grain boundary stability leads to the difficulty of nucleation of the dislocation, because the obstruction of the grain boundary makes it difficult to activate the dislocation source in the adjacent grain, and the maximum reduction of the perfect dislocation is 74%. In general, the microscopic mechanism of solute segregation strengthening is discussed from dislocation, phase structure, and energy, which provides guidance for plastic deformation of solid‐solution alloys.

Student Development Activities in Chinese Higher Education Institutions: From Assessment to An Enhancement Program

This study takes Chinese higher education institutions as an example to investigate students to investigate the student development activities from assessment to strengthening plan, and to explore the influencing factors and current situation of student development activities in Chinese higher education institutions. In addition, on the basis of investigation and analysis, the development plan to enhance students' multifaceted ability.By means of questionnaire analysis and interview, this paper collects, collates and analyzes the relevant data of student development activities in Chinese higher education institutions through a questionnaire survey of 100 teachers and 200 students. This enables local researchers to better understand students' needs and challenges, thereby providing strong support for improving students' developmental experiences and learning outcomes. At the same time, the data analysis results can provide an important basis for formulating targeted strengthening plans and improvement strategies, so as to promote the sustainable development of student development activities in China's higher education institutions.