Objective Guidance Research Articles

User Acceptance and Sustainable Adoption of University Management Information Systems: a Cross-cultural Study

Objective: This study aims to enhance the quality of management information systems (MIS) in universities by investigating user acceptance and sustainable adoption across different cultural contexts.Method: A cross-cultural study was conducted utilizing the Technology Acceptance Model (TAM) as a theoretical framework. Key research variables were identified, including system performance, management information quality, system interactivity, social impact, educational culture, usage habits, perceived usefulness, perceived ease of use, user acceptance, sustained use intention, and sustained use behavior. A series of hypotheses were established and validated through experimental analysis.Results: The analysis revealed that system performance, management information quality, educational culture, and perceived usefulness significantly positively influenced user acceptance, with path coefficients of 0.256, 0.752, 0.607, and 0.368, respectively. Additionally, social influence, usage habits, perceived usefulness, and user acceptance positively impacted users' willingness to continue using the MIS, with path coefficients of 0.533, 0.532, 0.441, and 0.602, respectively.Conclusions: The findings indicate that cross-cultural research on user acceptance and sustainable adoption of MIS in universities is vital for understanding diverse user needs. The insights gained can serve as objective guidance for enhancing the management capabilities of universities globally.

CRITICAL INFRASTRUCTURE OF THE GROUND CONTROL COMPLEX FOR THE ORBITAL SATELLITE CONSTELLATION

The article is devoted to determining the priority of objects of the ground control complex of an orbital constellation of satellites as objects of critical infrastructure of the Russian Federation. The use of high-precision weapons, navigation, communications, control, and transport increasingly depends on the functioning of the orbital constellation of satellites. The ground control com- plex for the orbital constellation of satellites of the Russian Ministry of Defense includes a Mission Control Center and more than a dozen stationary command and measurement points. The equipment of the ground-based orbital constellation control complex requires strict reference to the spatial-temporal operating parameters, especially for the Global Navigation Satellite System, which, in turn, determines the effectiveness of high-precision weapons guidance, targeting, and location of objects, the functioning of communications, transportation systems and other means comprising corresponding navigation receivers. For spacecraft, and primarily for Global Navigation Satellite System satellites, the problem of having an onboard time scale of high stability is relevant, which is determined by the functioning of the unified time system, which is an integral part of both the ground control complex and the orbital constellation. In the most general terms, the basis of the unified time system of the ground-based control complex for the orbital satellite constellation is made up of time and frequency standards distributed throughout the territory of the Russian Federation, located mainly in ground-based command and measurement centers and measurement laboratories. The unified time system is the most secure technical system, which is formed as a composite measure at the highest level of the hierarchy of accuracy classes of frequency standards. Therefore, the most significant control objects of the orbital constellation are equipped with group standards, which can be considered a criterion for classifying the objects of the ground control complex of the orbital constellation of satellites as the critical infrastructure of the Russian Federation. It was determined that the hierarchical sequence of importance for the critical infrastructure of the Russian Federation of objects in the unified time system of the orbital constellation of the satellite control complex takes into account GLONASS objects, the standards of the State Service of Time and Frequency and determination of the parameters of the Earth’s rotation of the Russian Federation, as well as the standards of the «Quazar KTS» complex.

CSMDC: Exploring consistently context semantics for multi-view document clustering

Multi-view document clustering, which aims to discover clustering partitions based on multiple document views, has attracted increasing research interest. However, the potential advantages of incorporating context semantics to enhance multi-view document clustering are yet to be fully explored. To address the above limitation, we propose a deep multi-view document clustering model that explores consistent context semantics called CSMDC which consists of three modules. Specifically, a novel view-translator is designed to convert non-contextual document views into contextual views. With its help, all document views can be processed to obtain their semantic representations within the view-translator representation learning module. Then the data-based view consistency self-supervising module is developed to fine-tune the semantic representations of document views by jointly incorporating view-wise representation relevance and consistent clustering assignments. Additionally, the task-based document clustering module is employed to simultaneously improve the view semantic representations and document clustering results. To the best of our knowledge, this is the first study to explicitly apply consistent context semantics under the guidance of data-based and task-based objectives in multi-view document clustering. Comprehensive experimental results demonstrated the effectiveness of the proposed model.

Toward Constructing Frameworks for Task- and Design-Optimized Visualizations.

Visualization is crucial to augment and enhance human understanding and decision-making in today's data-driven world. However, the way data are visualized can influence and drastically change the conclusions people draw using data. The findings around visualization effectiveness are nuanced, and guidelines for effective visualization design depend on the visual channels used, chart types, and analysis tasks. This points to a significant need to understand the intersection of these factors to create optimized visualizations. We need a framework to define this intersection that fills the gap by providing a task-optimized visualization design for better quality and higher decision-making confidence that gives designers objective guidance. A task-optimized visualization design framework strategically integrates visual channels, visualization types, and specific low-level tasks to enhance data interpretation and optimize user task performance. We discuss constructing a visualization framework that considers both human perception for encoding techniques and the task being performed, enabling optimizing visualization design to maximize efficiency. Furthermore, we highlight a task-optimized framework's impact and potential applications.

Comparison of Weekly Paclitaxel Regimens in Recurrent Platinum-Resistant Ovarian Cancer: A Single Institution Retrospective Study.

Weekly paclitaxel (WP) is a chemotherapeutic cornerstone in the management of patients with platinum-resistant ovarian carcinoma. Multiple WP dosing regimens have been used clinically and studied individually. However, no formal comparison of these regimens is available to provide objective guidance in clinical decision making. The primary objective of this study was to compare the cumulative dose of paclitaxel delivered using 80 mg/m2/week, administered using either a 3 weeks out of 4 (WP3) or a 4 weeks out of 4 (WP4) regimen. The secondary objective was to evaluate the clinical outcomes associated with both regimens, including efficacy and toxicity parameters. Our retrospective cohort comprised 149 patients harboring platinum-resistant ovarian cancer treated at the CHU de Québec from January 2012 to January 2023. WP3 and WP4 reached a similar cumulative dose (1353.7 vs. 1404.2 mg/m2; p = 0.29). No significant differences in the clinical outcomes were observed. The frequency of dose reduction was significantly higher for WP4 than WP3 (44.7% vs. 4.9%; p < 0.01), mainly due to treatment intolerance from toxicity (34.0% vs. 3.9%; p < 0.01). Our data suggest that a WP3 regimen delivers a similar cumulative dose to WP4, hence offering a better tolerability profile without compromising efficacy.

University Management Information Systems: a Cross-cultural Study

Management Information System (MIS) is an important support for the planning and management of information resources in universities. In different cultural backgrounds, users’ understanding and application of MIS may vary due to the language and cultural symbols they use, which can affect the actual application of the system. In order to improve the quality of management information in universities and understand different user needs, this article conducted a cross-cultural study on the user acceptance and sustainable adoption of MIS in universities. It constructed a theoretical research model using the Technology Acceptance Model (TAM), and then established system performance, management information quality, system interactivity, social impact, educational culture, usage habits, perceived usefulness, perceived ease of use, user acceptance, sustained use intention, and sustained use behavior as research variables. On this basis, a research hypothesis was constructed and finally validated through experimental analysis. The results show that system performance, management information quality, educational culture, and perceived usefulness had a significant positive impact on user acceptance, with path coefficients of 0,256, 0,752, 0,607, and 0,368, respectively. Social influence, usage habits, perceived usefulness, and user acceptance had a significant positive impact on user willingness to continue using, with path coefficients of 0,533, 0,532, 0,441, and 0,602, respectively. The conclusion indicates that cross-cultural research on user acceptance and sustainable adoption of MIS in universities can help understand user needs in different cultural backgrounds and provide objective guidance for improving the management level of universities

A deep learning framework for predicting endometrial cancer from cytopathologic images with different staining styles.

Endometrial cancer screening is crucial for clinical treatment. Currently, cytopathologists analyze cytopathology images is considered a popular screening method, but manual diagnosis is time-consuming and laborious. Deep learning can provide objective guidance efficiency. But endometrial cytopathology images often come from different medical centers with different staining styles. It decreases the generalization ability of deep learning models in cytopathology images analysis, leading to poor performance. This study presents a robust automated screening framework for endometrial cancer that can be applied to cytopathology images with different staining styles, and provide an objective diagnostic reference for cytopathologists, thus contributing to clinical treatment. We collected and built the XJTU-EC dataset, the first cytopathology dataset that includes segmentation and classification labels. And we propose an efficient two-stage framework for adapting different staining style images, and screening endometrial cancer at the cellular level. Specifically, in the first stage, a novel CM-UNet is utilized to segment cell clumps, with a channel attention (CA) module and a multi-level semantic supervision (MSS) module. It can ignore staining variance and focus on extracting semantic information for segmentation. In the second stage, we propose a robust and effective classification algorithm based on contrastive learning, ECRNet. By momentum-based updating and adding labeled memory banks, it can reduce most of the false negative results. On the XJTU-EC dataset, CM-UNet achieves an excellent segmentation performance, and ECRNet obtains an accuracy of 98.50%, a precision of 99.32% and a sensitivity of 97.67% on the test set, which outperforms other competitive classical models. Our method robustly predicts endometrial cancer on cytopathologic images with different staining styles, which will further advance research in endometrial cancer screening and provide early diagnosis for patients. The code will be available on GitHub.

Quantitative Analysis of Primary Compressive Trabeculae Distribution in the Proximal Femur of the Elderly.

As osteoporosis progresses, the primary compressive trabeculae (PCT) in the proximal femur remains preserved and is deemed the principal load-bearing structure that links the femoral head with the femoral neck. This study aims to elucidate the distribution patterns of PCT within the proximal femur in the elderly population, and to assess its implications for the development and optimization of internal fixation devices used in hip fracture surgeries. This is a retrospective cohort study conducted from March 2022 to April 2023. A total of 125 patients who underwent bilateral hip joint CT scans in our hospital were enrolled. CT data of the unaffected side of the hip were analyzed. Key parameters regarding the PCT distribution in the proximal femur were measured, including the femoral head's radius (R), the neck-shaft angle (NSA), the angle between the PCT-axis and the head-neck axis (α), the distance from the femoral head center to the PCT-axis (δ), and the lengths of the PCT's bottom and top boundaries (L-bottom and L-top respectively). The impact of gender differences on PCT distribution patterns was also investigated. Student's t-test or Mann-Whitney U test were used to compare continuous variables between genders. The relationship between various variables was investigated through Pearson's correlation analysis. PCT was the most prominent bone structure within the femoral head. The average NSA, α, and δ were 126.85 ± 5.85°, 37.33 ± 4.23°, and 0.39 ± 1.22 mm, respectively, showing no significant gender differences (p > 0.05). Pearson's correlation analysis revealed strong correlations between α and NSA (r = -0.689, p < 0.001), and R and L-top (r = 0.623, p < 0.001), with mild correlations observed between δ and NSA (r = -0.487, p < 0.001), and R and L-bottom (r = 0.427, p < 0.001). Importantly, our study establishes a method to accurately localize PCT distribution in true anteroposterior (AP) radiographs of the hip joint, facilitating precise screw placement in proximal femur fixation procedures. Our study provided unprecedented insights into the distribution patterns of PCT in the proximal femur of the elderly population. The distribution of PCT in the proximal femur is predominantly influenced by anatomical and geometric factors, such as NSA and femoral head size, rather than demographic factors like gender. These insights have crucial implications for the design of internal fixation devices and surgical planning, offering objective guidance for the placement of screws in hip fracture treatments.

An rs-fMRI based neuroimaging marker for adult absence epilepsy

ObjectiveApproximately 20–30 % of epilepsy patients exhibit negative findings on routine magnetic resonance imaging, and this condition is known as nonlesional epilepsy. Absence epilepsy (AE) is a prevalent form of nonlesional epilepsy. This study aimed to investigate the clinical diagnostic utility of regional homogeneity (ReHo) assessed through the support vector machine (SVM) approach for identifying AE. MethodsThis research involved 102 healthy individuals and 93 AE patients. Resting-state functional magnetic resonance imaging was employed for data acquisition in all participants. ReHo analysis, coupled with SVM methodology, was utilized for data processing. ResultsCompared to healthy control individuals, AE patients demonstrated significantly elevated ReHo values in the bilateral putamen, accompanied by decreased ReHo in the bilateral thalamus. SVM was used to differentiate patients with AE from healthy control individuals based on rs-fMRI data. A composite assessment of altered ReHo in the left putamen and left thalamus yielded the highest accuracy at 81.64 %, with a sensitivity of 95.41 % and a specificity of 69.23 %. SignificanceAccording to the results, altered ReHo values in the bilateral putamen and thalamus could serve as neuroimaging markers for AE, offering objective guidance for its diagnosis.

Constructing A Model of the Impact of Human Capital and Social Capital on the Employment Quality of Chinese University Graduates: Based on the Mediating Role of Career Development

Introduction: This article is based on the theories of human capital, social capital, social interaction, and collaborative governance. From the dual perspectives of human capital and social capital, combined with the mediating role of career development, it studies the factors that affect the quality of employment for university students and constructs a conceptual model to determine the mediating role of career development between human capital, social capital, and the quality of employment for university graduates. Through a large amount of literature and previous research theories, suitable employment quality indicators, human capital indicators, social capital indicators, and career development indicators were selected. This article reveals the influencing factors of improving the employment quality of university graduates, providing ideas for improving the employment quality of university graduates and promoting the improvement of the higher education system and the stable development of the social economy. Objective: It introduces a novel perspective on career development and explores the mediating role of career development in the impact of human capital and social capital on the employment quality of university graduates. This not only provides more objective and scientific guidance for university graduates' job values, self-awareness, and planning but also helps them better develop and cultivate their own human capital and social capital capability providing effective practical guidance. At the same time, it can provide objective analytical data for the reform of major settings in university education, the establishment of career courses, and the fair and reasonable formulation of employment policies, providing a new research perspective for studying the quality of employment of university graduates. Theoretical Framework: In the developmental stage, at least four economists have made outstanding contributions: Theodore W. Schultz and Gary Becker, Jacob Mincer and Edward Denison, respectively from different angles in different fields for the formation of the basic framework of the foundation, the modern sense of human capital theory was born, not only laid the theoretical foundation for the western education economics but also opened up a new field of western economics research. Method: The research of domestic and foreign scholars on the career development of university students is similar. Due to the differences in the focus, attention topics, and research methods, the dimensions of career development of university students are also defined differently. Results and Discussion: The theories of human capital and social capital have received attention and recognition from scholars as the basis for studying the quality of employment for university graduates. The impact of human capital and social capital on the quality of employment for university graduates is also significant. However, in existing research, there are not many studies that focus on the quality of employment for university graduates from the perspectives of schools and social governance, based on social interaction theory and collaborative governance theory. Specifically, there is a lack of systematic theoretical support and empirical exploration in exploring the impact of major differences and career development on the quality of employment for university graduates, and overall, it is still in the exploratory stage. Research Implications: The research results indicate that there is a significant correlation between career development, human capital, social capital, and the quality of employment for university graduates Originality/Value: This model is not yet tested in Chinese contexts.

Developing a mentoring program to support the next generation of immunologists.

Mentorship refers to the guidance given by a mentor to a less experienced individual to enhance their professional and personal development. For graduate research students, seeking independent mentors external to their institution offers the rewarding opportunity to obtain objective guidance on a variety of work, study and life matters. This article outlines the steps taken to develop a professional society-based, international mentoring program of over 70 participants. This 6-month program aimed to connect graduate research students with more senior academic scientists in response to the limited networking opportunities imposed by the coronavirus disease 2019 (COVID-19) pandemic in Australia. Outlined here are the resources used to maximize the potential of this successful program, which include (1) an 'Introduction to Mentoring' workshop, (2) the use of a mentoring software or communication strategy to maintain program momentum and (3) the integration of in-person networking events. Overall, the program was a great success, with a high satisfaction rating (8.7/10) and a large number of participants reported that they would maintain their mentoring relationship. All participants stated that they would recommend the program to a peer, and thus reiterations of the program would likely be similarly well-received and beneficial to the Australasian immunology community.

Enhancing urban blue-green landscape quality assessment through hybrid genetic algorithm-back propagation (GA-BP) neural network approach: a case study in Fucheng, China

This study employs an artificial neural network optimization algorithm, enhanced with a Genetic Algorithm-Back Propagation (GA-BP) network, to assess the service quality of urban water bodies and green spaces, aiming to promote healthy urban environments. From an initial set of 95 variables, 29 key variables were selected, including 17 input variables, such as water and green space area, population size, and urbanization rate, six hidden layer neurons, such as patch number, patch density, and average patch size, and one output variable for the comprehensive value of blue-green landscape quality. The results indicate that the GA-BP network achieves an average relative error of 0.94772%, which is superior to the 1.5988% of the traditional BP network. Moreover, it boasts a prediction accuracy of 90% for the comprehensive value of landscape quality from 2015 to 2022, significantly outperforming the BP network’s approximate 70% accuracy. This method enhances the accuracy of landscape quality assessment but also aids in identifying crucial factors influencing quality. It provides scientific and objective guidance for future urban landscape structure and layout, contributing to high-quality urban development and the creation of exemplary living areas.

Ecological Security Patterns Research Based on Ecosystem Services and Circuit Theory in Southwest China

The rapid economic development in the Chengdu–Chongqing Economic Circle (CCEC) has exerted significant pressure on the ecological environment of the Sichuan–Chongqing Region in China. Balancing ecological protection and economic development has become an imperative challenge that needs to be addressed. In this study, we employed land use/cover data and environmental threat factors to construct Ecological Security Patterns (ESPs) for the CCEC using the InVEST model and Circuit Theory. The research findings revealed the following key outcomes: (1) The total area of suitable habitat in the CCEC was 208,728.3 km2, accounting for 87.14% of the study area. Habitat quality exhibited regional variations, with higher quality habitats predominantly found in the western and northeastern parts, and lower quality habitats in the central region. (2) The CCEC consisted of areas with low, medium, high, and optimal habitat quality, spanning 140,912.18 km2, 15,341.89 km2, 15,578.38 km2, and 36,895.85 km2, respectively. These areas accounted for 58.83%, 6.40%, 6.50%, and 15.40% of the study area, respectively. (3) The ESPs in the CCEC encompassed 22 ecological nodes, 36 clusters of ecological corridors, and 136 ecological sources. Ecological corridors served as radial connections, linking each ecological node and ecological source along mountain ranges, forested areas, river networks, and valleys. (4) The core ecological regions forming the ESPs of the CCEC included the Qionglai–Minshan–Longquan Mountains in the west, Tiefeng–Fangdou–Qiyue–Wushan Mountains in the east and northeast, and Dalou Mountain in the southeast. These regional-scale findings provide valuable insights for policymakers to implement targeted measures for ecological protection and promote green development. They offer objective guidance and constraints for managing urban expansion and anthropogenic activities, ultimately enhancing the ecological security level of the CCEC.

8 Opportunities in enteric methane emissions mitigation in beef cattle

Abstract Enteric fermentation is the largest source of methane emissions in the United States, with beef cattle representing 71 percent of total enteric methane emissions in 2021. Approximately 87% of the enteric methane produced from US beef cattle comes from animals not housed in feedlots, thus significantly opportunity lies in development and delivery of mitigation solutions to grazing situations. Mitigating methane emissions can be expressed in two ways: on an emissions intensity basis (i.e., methane per kg of beef) or in absolute terms (i.e., methane emissions from the entire beef system). Mitigation solutions that reduce absolute or total emissions consistently are currently limited or in the case of higher concentrate diets in finishing cattle, already widely used. Genetic selection is a promising solution to mitigate enteric methane emissions; however, standardization of phenotype collection is required, as methane emissions estimates can be influenced by a wide array of measurement errors and methodological choices by investigators. Economically viable, practical, and scalable solutions are needed. Researchers and extension professionals should provide objective guidance to cattle producers and others in the cattle industry on the costs and benefits of the variety of potential enteric methane mitigation solutions.

Principal Component Analysis Method Application for Inventory Related Decisions-Making

This research aims to analyze the importance of inventory control and management, especially regarding the components used in industrial machinery maintenance. The methodology used was based on a quantitative approach, descriptive scope, and non-experimental cross-sectional design. Principal Component Analysis (PCA) and Clustering techniques were employed to evaluate both the quantities consumed and the frequency of usage, to efficiently categorize the components according to their distinctive attributes. This approach is proposed as an objective guidance that will significantly contribute to improving effectiveness and sustainability in the overall management of spare parts inventories. The developed methodology allowed for a detailed description of spare parts behavior; 1,753 references of spare parts used in the maintenance of industrial equipment in a food factory during the period from the second half of 2021 to the first half of 2022. The highest production peaks were recorded during this time, highlighting consumed quantities and usage frequencies, guiding the material management teams in making decisions about spare parts storage.

Strategy for Building Digital Studio Based on Cloud Computing

With the rapid development of studio informatization, the traditional era of studio construction is gradually entering digitalization. In recent years, the rapid development of cloud computing technology in the field of education has greatly changed the way teachers teach and students learn. The main goal of the digital studio cloud platform is to improve the teaching efficiency and quality of teachers, and provide students with a more convenient platform. At present, education cloud platforms are still in the early stages of development, and many designs focus on functionality while ignoring the core needs of users, leading to difficulties in user operation and hindering the comprehensive promotion of education cloud platforms. This article proposed a digital studio construction strategy based on cloud computing, using systematic and intelligent methods to improve the traditional studio teaching mode, strengthen objective evaluation and data guidance functions, and explore the standardized and systematic teaching mode of studios. This article constructed the ZStack private cloud platform to achieve flexible resource allocation and efficient utilization, and evaluated performance under different workloads through experiments, providing important reference for the optimization of future education cloud platforms.

Research on the Multimodal Teaching Model of Spoken English in Colleges and Universities by Counting and ANN Modeling

Abstract Spoken English teaching is a teaching scenario characterized by multimodality, which requires teachers’ verbal and nonverbal to cooperate. In the context of the high degree of integration of artificial intelligence and educational technology, the construction of an English speaking multimodal assessment method is of great significance for English speaking training and teaching. This paper constructs a multimodal teaching model of spoken English based on three modalities: audio, text, and video. Taking the English speech of Chinese college students as the research object, we improve the traditional computerized English pronunciation quality evaluation method, consider the multi-parametric evaluation indexes such as pitch, speech rate, rhythm and intonation, and convert the recognition problem into a scoring problem by utilizing the soft classification property of the ANN model. The confidence probability output value of the ANN model is used as the metric for evaluation results. Through experiments, it is proved that the accurate agreement rate of the spoken English assessment method in this paper is 89.87% and R 2 is 0.528 under the gold standard, and the data results prove that the assessment method is credible. It can give learners of spoken English timely, accurate and objective evaluation and feedback guidance and help learners find out the differences between their pronunciation and the standard pronunciation so as to improve the efficiency of spoken English learning.

Novel technology for industrial VOCs exhaust treatment under dual-carbon target based on multivariate statistical analysis

Abstract Against the background of the dual-carbon target, the treatment of volatile organic compounds (VOCs) emissions in the industrial sector, especially in the chemical industry, has become an urgent environmental issue. To provide scientific and objective guidance for technology selection, this study constructs a comprehensive evaluation model based on the combination of entropy weighting method and hierarchical analysis method for the complete progress of VOCs treatment technologies, taking into account the four main factors of environment, economy, management and technology and the thirteen secondary factors under them. The model provides in-depth quantitative analysis and evaluation of ten common VOCs end-of-pipe treatment technologies. The evaluation results show that thermal combustion, catalytic combustion, adsorption-concentration-combustion, and photocatalysis exhibit high comprehensive efficacy in VOCs emission treatment, with relative weight values of 0.1273, 0.1252, 0.1214, and 0.1184, respectively. These findings provide essential references and guidance for chemical companies in selecting suitable VOCs treatment technologies, which help to realize the win-win situation of environmental protection and economic development. This study fills the gap in evaluating VOCs emission management technologies and provides a practical decision-making tool for relevant decision makers.

Система синхронизации радиоимпульсной последовательности при управлении движением объектов

Based on recurrent algorithms for filtration of Markov sequences, an algorithm for the operation of a synchronization system of a sequence of quasi-periodic radio pulses that occurs in the receiver of an infrared coordinator of an object guidance’s command system with modulated tracer radiation has been synthesized. The analysis of the synthesized algorithms was carried out, during which the quality influence of synchronization by a sequence of pulses on the accuracy of object guidance into a given region of space was determined.

On the NASA GEDI and ESA CCI biomass maps: aligning for uptake in the UNFCCC global stocktake

Earth Observation data are uniquely positioned to estimate forest aboveground biomass density (AGBD) in accordance with the United Nations Framework Convention on Climate Change (UNFCCC) principles of ‘transparency, accuracy, completeness, consistency and comparability’. However, the use of space-based AGBD maps for national-level reporting to the UNFCCC is nearly non-existent as of 2023, the end of the first global stocktake (GST). We conduct an evidence-based comparison of AGBD estimates from the NASA Global Ecosystem Dynamics Investigation and ESA Climate Change Initiative, describing differences between the products and National Forest Inventories (NFIs), and suggesting how science teams must align efforts to inform the next GST. Between the products, in the tropics, the largest differences in estimated AGBD are primarily in the Congolese lowlands and east/southeast Asia. Where NFI data were acquired (Peru, Mexico, Lao PDR and 30 regions of Spain), both products show strong correlation to NFI-estimated AGBD, with no systematic deviations. The AGBD-richest stratum of these, the Peruvian Amazon, is accurately estimated in both. These results are remarkably promising, and to support the operational use of AGB map products for policy reporting, we describe targeted ways to align products with Intergovernmental Panel on Climate Change (IPCC) guidelines. We recommend moving towards consistent statistical terminology, and aligning on a rigorous framework for uncertainty estimation, supported by the provision of open-science codes for large-area assessments that comprehensively report uncertainty. Further, we suggest the provision of objective and open-source guidance to integrate NFIs with multiple AGBD products, aiming to enhance the precision of national estimates. Finally, we describe and encourage the release of user-friendly product documentation, with tools that produce AGBD estimates directly applicable to the IPCC guideline methodologies. With these steps, space agencies can convey a comparable, reliable and consistent message on global biomass estimates to have actionable policy impact.