Integrity Assessment Research Articles

Effect of Various Notch Shapes on Lamb Wave Scattering Behavior in a Bent Plate

Abstract The application of guided waves to investigate commonly used plate shapes in the aerospace, mechanical, and civil industries is plates with bend shapes. This article investigates the interaction of fundamental Lamb waves with notches in bent plates, commonly found in aerospace, mechanical, and civil engineering applications. These areas are particularly susceptible to failure due to defects such as cracks and notches, which often manifest as semicircular corrosion patches or 90-deg notches. The presence of notches affects stress distribution, necessitating thorough analysis to prevent accidents. Accordingly, this article focuses on the interaction of fundamental Lamb waves through two types of notches that could be present inside a bent metal plate section. To explore this, a hybrid numerical framework is employed which combines semianalytical finite elements (SAFEs) with the finite element method (FEM). A bent plate section with various notch types is simulated using FEM, while SAFEs facilitate the definition of wave propagation through healthy regions of the plate. The study analyzes the scattering behavior of Lamb waves for different notch configurations and examines both fundamental modes over a specified frequency range. With a change in the interrogation signal parameters, there is a noticeable difference in the sensitivity of scattered waves with different notch types. Formulating a strategy for identifying and locating a notch inside a bent plate may need careful consideration of the important conclusions drawn. Understanding these interactions, the aim of the article is to enhance the integrity assessment of structural components subject to such defects.

MESSAGEix-Materials v1.1.0: representation of material flows and stocks in an integrated assessment model

Abstract. Extracting raw materials and processing them into products used in industry constitute a substantial source of CO2 emissions, which are currently lacking process detail in many integrated assessment models (IAMs). To broaden the space of climate change mitigation options to include material-oriented strategies such as the circular-economy and material efficiency measures in IAM scenario analysis, we develop the MESSAGEix-Materials module, representing material flows and stocks within the MESSAGEix-GLOBIOM IAM framework. We provide a fully open-source model that can assess different industry decarbonization options under various climate targets for the most energy- and emissions-intensive industries: aluminum, iron and steel, cement, and petrochemicals. We illustrate the model's operation with a baseline and mitigation 2-degrees (2 °C) scenario setup and validate base year results for 2020 against historical datasets. We also discuss the industry decarbonization pathways and material stocks of the electricity generation technologies resulting from the new model features. The next steps are to extend the model to other sectors, end uses and materials, as well as the combined modeling of various supply- and demand-side measures.

Annular cement sheath characterization and hydraulic aperture assessment through single- and two-phase seepage tests

The integrity of well barriers is critical throughout the life cycle of oil and gas wells, with annular cement as a key component in maintaining the structural integrity of the barrier system. In this study, an annular cemented section with a well-defined microannulus was systematically constructed and characterized, and both single- and two-phase seepage tests were conducted to gain a deeper understanding of how relative permeability impacts the estimation of hydraulic aperture in potential leakage pathways. The test cell design allows modification of the microannulus gap size by changing the pressure applied inside the inner casing. This enables studying different microannulus sizes throughout the conducted tests. The single-phase seepage tests showed consistent measurements of hydraulic aperture for both gas and water, despite variations in fluid type and applied pressure, with surface roughness likely affecting the non-linear behavior of the hydraulic aperture under stress. The two-phase seepage tests demonstrated a clear relationship between breakthrough pressure and microannulus size, with the van Genuchten model providing a better fit for relative permeability and capillary pressure data. Breakthrough time experiments revealed that initial permeability estimations were significantly lower than those obtained from single-phase tests; however, once relative permeability at breakthrough was accounted for, the estimated absolute permeability values aligned closely with the single-phase experimental data. These findings offer valuable insights into the complex interactions between cement sheath integrity and gas migration, potentially contributing to developing new well integrity assessment technologies, including tracer gas below the well barrier element, as well as insights relevant for both gas migration and sustained casing pressure analysis.

An Explore the Government Expenditure, Income Per Capita, Investment, and Poverty Impact to Integrity Assessment Survey (SPI) In Indonesia

An Explore the Government Expenditure, Income Per Capita, Investment, and Poverty Impact to Integrity Assessment Survey (SPI) In Indonesia

Effect of strain and excitation conditions on magneto acoustic emission signals in Q235 steel using maximal overlap discrete wavelet transform

ABSTRACT This study explores the effect of strain on Magneto Acoustic Emission (MAE) characteristics in Q235 steel plates under various excitation frequencies and voltages. Using Maximal Overlap Discrete Wavelet Transform (MODWT), we processed envelope energy signals derived from MAE signals generated from samples subjected to incremental tensile forces revealing critical variations in features extracted from AC and DC components such as RMS, mean bias and energy distribution. The results demonstrate the significant impact of strain on MAE signal characteristics, particularly under higher excitation frequencies and voltages, which enhances the detection of subtle plastic deformations. Our approach provides a refined methodology for enhancing MAE-based Non-Destructive Testing (NDT) practices, crucial for the reliable assessment of material integrity in engineering applications.

Integration of National Chemical Hazards Monitoring, Total Diet Study, and Human Biomonitoring Programmes for Food Safety Exposure Assessment in Singapore

Food safety and food security can impact the quality of human life, and these two aspects are interrelated alongside many influencing external factors. Global stressors such as climate change, recent pandemic, and geopolitical tensions have demonstrated tangible impacts on food security and safety. Food and food system innovation is a key strategy towards feeding the world in a more sustainable and climate-resilient manner. This paper highlights the use of a science-based risk assessment and management in Singapore’s food safety system, specifically in the integration of exposure assessment approaches to support evidence-based food safety risk analysis and decision-making. The use of complementary top-down and bottom-up exposure assessment approaches through the market monitoring programme, total diet study and human biomonitoring forms a comprehensive integrated exposure assessment strategy which can ultimately inform policy and measures in ensuring and securing a supply of safe food. The discussion on such application for chemical food safety in Singapore offers additional insights into the synergistic inter-relationships contributing to the exposure assessment associated with chemicals in food.

Simultaneous Structural Monitoring over Optical Ground Wire and Optical Phase Conductor via Chirped-Pulse Phase-Sensitive Optical Time-Domain Reflectometry.

Optimizing the use of existing high-voltage transmission lines demands real-time condition monitoring to ensure structural integrity and continuous service. Operating these lines at the current capacity is limited by safety margins based on worst-case weather scenarios, as exceeding these margins risks bringing conductors dangerously close to the ground. The integration of optical fibers within modern transmission lines enables the use of Distributed Fiber Optic Sensing (DFOS) technology, with Chirped-Pulse Phase-Sensitive Optical Time-Domain Reflectometry (CP-ΦOTDR) proving especially effective for this purpose. CP-ΦOTDR measures wind-induced vibrations along the conductor, allowing for an analysis of frequency-domain vibration modes that correlate with conductor length and sag across spans. This monitoring system, capable of covering distances up to 40 km from a single endpoint, enables dynamic capacity adjustments for optimized line efficiency. Beyond sag monitoring, CP-ΦOTDR provides robust detection of external threats, including environmental interference and mechanical intrusions, which could compromise cable stability. By simultaneously monitoring the Optical Phase Conductor (OPPC) and Optical Ground Wire (OPGW), this study offers the first comprehensive, real-time evaluation of both structural integrity and potential external aggressions on overhead transmission lines. The findings demonstrate that high-frequency data offer valuable insights for classifying mechanical intrusions and environmental interferences based on spectral content, while low-frequency data reveal the diurnal temperature-induced sag evolution, with distinct amplitude responses for each cable. These results affirm CP-ΦOTDR's unique capacity to enhance line safety, operational efficiency, and proactive maintenance by delivering precise, real-time assessments of both structural integrity and external threats.

Dynamics of markers of oxidative stress during the complex use of therapeutic physical factors in patients with true eczema associated with metabolic syndrome

BACKGROUND: Among various pathological conditions associated with true eczema, metabolic syndrome occupies a special place, the high social significance of which is determined by its dominant influence on the main demographic indicators — life expectancy and mortality of the population. AIM: Assessment of the dynamics of parameters of pro- and antioxidant systems in patients with true eczema in combination with metabolic syndrome during the course application of broadband medium-wave phototherapy, mesodiencephalic modulation and their combination. MATERIALS AND METHODS: A prospective, controlled, comparative, randomized study was performed involving 115 patients with true eczema combined with metabolic syndrome, who were divided into 4 groups using simple randomization. The first group (control) received only basic drug therapy. In the second (comparison 1), third (comparison 2), and fourth (main) groups, patients additionally underwent courses of broadband medium-wave phototherapy, mesodiencephalic modulation, and their combination, respectively. The results of the course application of physiofactors were assessed by the dynamics of pro- and antioxidant system indices before and after the end of therapy. RESULTS: When comparing the main markers of oxidative stress between the group of healthy people and patients with true eczema in combination with metabolic syndrome, a pronounced imbalance in the "prooxidants-antioxidants" system was established, which indicates the development of oxidative stress. Conducting complex therapy had a corrective effect on the parameters of the lipid peroxidation process. More pronounced shifts in lipid peroxide metabolism indicators were revealed in the groups with the additional use of physiotherapeutic factors. The maximum corrective effect in relation to oxidative stress was established in the group with the complex use of physiofactors. An integrative assessment of the dynamics of oxidative stress markers using the antioxidant protection coefficient confirmed the results obtained. CONCLUSION: The use of therapeutic physical factors in the therapy of true eczema and metabolic syndrome is largely based on their ability to act as redox regulators of intracellular processes, exhibiting a stress-limiting effect and restoring oxidation-reduction homeostasis. The most promising in this regard are broadband medium-wave phototherapy and mesodiencephalic modulation.

Establishment of an efficient and wide-spectrum droplet-vitrification cryopreservation for raspberry (Rubus idaeus L.) germplasm and assessments of genetic integrity and vegetative growth in the regenerants

By optimizing size of shoot tips, preculture medium and exposure duration to PVS2, we established an efficient and wide-spectrum droplet-vitrification cryopreservation for shoot tips of raspberry (Rubus idaeus L.). This protocol yielded 80–100% and 67–100% of survival and shoot regrowth levels in cryopreserved shoot tips across 23 raspberry genotypes. Genetic integrity was assessed in cryo-derived regenerants after 3 months of post-cryopreservation using inter simple sequence repeat (ISSR), single nucleotide polymorphism (SNPs), and insertions and deletions (InDels). ISSR did not detect any polymorphic bands in the cryo-derived regenerants. Although the number of SNPs and InDels decreased in the cryo-derived regenerants, variation trends were similar between the cryo-derived regenerants and the control. Plant vegetative growth and root growth were assessed in the cryo-derived plants after 9 weeks of growth in greenhouse. There were no significant differences in plant vegetative growth measured by plant height, number of fully-opened leaved, leaf area, and fresh and dry weight between the cryo-derived plants and the control, although significant differences were observed in root growth measured by root total length, root average diameter and root volume between the two types of plants. The results obtained in the present study indicate that the droplet-vitrification method has great potential for cryopreservation of raspberry germplasm.

RIDGE: Reproducibility, Integrity, Dependability, Generalizability, and Efficiency Assessment of Medical Image Segmentation Models.

Deep learning techniques hold immense promise for advancing medical image analysis, particularly in tasks like image segmentation, where precise annotation of regions or volumes of interest within medical images is crucial but manually laborious and prone to interobserver and intraobserver biases. As such, deep learning approaches could provide automated solutions for such applications. However, the potential of these techniques is often undermined by challenges in reproducibility and generalizability, which are key barriers to their clinical adoption. This paper introduces the RIDGE checklist, a comprehensive framework designed to assess the Reproducibility, Integrity, Dependability, Generalizability, and Efficiency of deep learning-based medical image segmentation models. The RIDGE checklist is not just a tool for evaluation but also a guideline for researchers striving to improve the quality and transparency of their work. By adhering to the principles outlined in the RIDGE checklist, researchers can ensure that their developed segmentation models are robust, scientifically valid, and applicable in a clinical setting.

Assessment of longitudinal load spectrum characteristics and structural fatigue damage of metro vehicle body in service

Aiming at the structural integrity requirements of service vehicles, there is an urgent need to construct a set of analytical methods based on service load characterization to realize the life assessment of the critical weak regions of the vehicle body. This study measured the longitudinal load spectrum of a metro vehicle body under a typical service line using a calibrated coupler and traction bar. Based on the signal characteristics of the longitudinal loads, a dynamic load feature decomposition method is proposed to decompose the longitudinal load features into trend and fluctuation signals to reflect the overall and local laws. The longitudinal load transfer characteristics of the vehicle body under traction, braking, linear, and curved conditions are innovatively analyzed, and a longitudinal load distribution ratio coefficient with generality is proposed as the input of effective service load. The service stress spectrum of the vital points of the vehicle body is constructed, which can more comprehensively and realistically respond to the service stress state of the vehicle body compared with the standard design loads, which further improves the accuracy of the structural integrity assessment.

Integration of overlapping sequences emerges with consolidation through medial prefrontal cortex neural ensembles and hippocampal-cortical connectivity.

Systems consolidation theories propose two mechanisms that enable the behavioral integration of related memories: coordinated reactivation between hippocampus and cortex, and the emergence of cortical traces that reflect overlap across memories. However, there is limited empirical evidence that links these mechanisms to the emergence of behavioral integration over time. In two experiments, participants implicitly encoded sequences of objects with overlapping structure. Assessment of behavioral integration showed that response times during a recognition task reflected behavioral priming between objects that never occurred together in time but belonged to overlapping sequences. This priming was consolidation-dependent and only emerged for sequences learned 24 hr prior to the test. Critically, behavioral integration was related to changes in neural pattern similarity in the medial prefrontal cortex and increases in post-learning rest connectivity between the posterior hippocampus and lateral occipital cortex. These findings suggest that memories with a shared predictive structure become behaviorally integrated through a consolidation-related restructuring of the learned sequences, providing insight into the relationship between different consolidation mechanisms that support behavioral integration.

MAIA and Humphrey Perimetry Differ in Their Estimation of Homonymous Visual Field Defects.

To assess whether the Humphrey Visual Field Analyzer (HFA) and the Macular Integrity Assessment instrument (MAIA) provide equivalent estimates of visual deficit size, severity, and progression in cortically blinded participants. Reliable, monocular 10-2 HFA and MAIA fields were collected at baseline, and after a blind-field training intervention (n = 54) or no intervention (n = 6) in adult participants with occipital strokes. Binocular HFA and MAIA mean sensitivities (MS) were first computed, before creating binocular maps of visual sensitivity for each perimetry system to calculate deficit areas, using a unitary, published, less than 10 dB criterion to define blindness. We contrasted HFA/MAIA MS and deficit area at individual study visits, together with change in these measures between visits. At individual visits, MS and deficit areas were well-correlated, but there were systematic differences between machines, greater for the intact than impaired hemifields, with the MAIA overestimating areas of visual deficit relative to the HFA. Between visits, the two perimeters' assessment of change in MS was correlated, but change in the deficit area was not, despite good test reliability. Reliable HFA and MAIA tests produce well-correlated but systematically offset estimates of visual sensitivity and deficit area in patients with homonymous field defects, which can impact assessment of progression. Cortically blinded patients exhibited comparable changes in sensitivity (spontaneous and training induced) when assessed using Humphrey and fundus-controlled MAIA perimetry. However, the photopic vs. mesopic nature of these tests impacted participant performance and suggests that custom, machine-specific criteria are needed to comparably define blindness on both systems.

Information and Analytical System Monitoring and Assessment of the Water Bodies State in the Mineral Resources Complex

Currently, one of the most pressing global issues is ensuring that human activities have access to water resources that meet essential quality standards. This challenge is addressed by implementing a series of organizational and technical measures aimed at preserving the ecology of water basins and reducing the level of harmful industrial emissions and other pollutants in the aquatic environment. To guarantee the necessary quality of water resources, monitoring is conducted based on selected parameters using various methods and means of technical quality control. From these results, suitable measures are formulated and applied to maintain water quality. Various scientific works extensively discuss different approaches to water quality management and compliance with specified requirements. Modern strategies for developing water monitoring systems leverage the capabilities of information systems that collect, process, store, and transmit information, enabling the resolution of issues in geographically distributed water bodies in real time. This paper proposes an approach that employs mathematical methods to identify the most significant factors determining water quality and to assess their interrelations using methods of a priori ranking, multivariate correlation regression analysis, and integral quantitative assessment. A hardware and software solution for the development of a unified integrated information and analytical system is proposed. This system enables continuous monitoring and assessment of water bodies based on a set of key parameters, addressing a range of critical tasks. This paper provides a detailed description of the software product, presents a demonstration using real-world data, and discusses the anticipated benefits of implementing such an information and analytical system.

Bridging Cultures, Advancing AI

In an era where generative AI (AI) is reshaping education at breakneck speed, how can institutions keep pace while also ensuring authentic learning? Our international Community of Practice (CoP) offers a compelling answer. Spanning Australia and Vietnam, this unique collaboration has not only navigated cultural differences but leveraged them to create a rich tapestry of AI integration strategies in HE. From unexpected synergies to challenging assumptions, our journey offers crucial insights for educators worldwide grappling with AI's transformative power. Established in April 2023, our CoP has grown to approximately 500 members drawn from multiple campuses across Australia and Vietnam. This cross-cultural collaboration aligns with Wenger's (1999) Communities of Practice theory and demonstrates a novel approach to harnessing global collective intelligence in HE. Our CoP has critically examined the impact of AI on HE, exploring its transformative potential and challenges in teaching methodologies, learning experiences, and assessment practices. Our discussions have extended to the ethical and environmental considerations of increased AI adoption in education, aligning with the growing need for sustainable technological integration in academia. Key outcomes of the CoP include: Development of AI-integrated curriculum frameworks and co-creation of staff training materials, enhancing institutional readiness for AI integration; Design and implementation of innovative learning tools, such as AI-generated interactive personas, enhancing student engagement and outcomes; Facilitation of research collaborations, resulting in both publications and multiple conference presentations; Exploration of AI-enabled learning analytics for personalised learning, with initial implementation across different cultural contexts; and Amplification of public awareness about AI in Southeast Asian education, as evidenced by extensive media coverage in Vietnam. Our CoP's activities, including monthly expert-led meetings and weekly newsletters, have catalysed significant advancements in Technology Enhanced Learning (TEL) research and practice. The initiative's success aligns with the TPACK framework (Mishra & Koehler, 2006) and social learning theory (Bandura, 1977), supporting contextualised AI integration in pedagogy and andragogy across diverse educational settings. Our CoP has overcome significant challenges, including sustaining engagement across time zones and sourcing diverse expert speakers, through dedicated leadership and strong institutional support. The CoP's impact led to its official recognition and the formation of a cross-school steering committee, further amplifying its influence and demonstrating its strategic importance to the institution. This presentation will share key insights from our journey, including strategies for fostering engagement in a remote, cross-cultural CoP focused on rapidly evolving technology. We will discuss successful AI-enabled pedagogies implemented by CoP members, how challenges were addressed, and the impact of diverse cultural perspectives on AI adoption. A key lesson learned is the importance of balancing AI integration with maintaining academic integrity and authentic assessment in the rapidly evolving landscape of educational technology. By sharing our experiences, we aim to provide a model for other institutions seeking to harness collective intelligence in shaping the future of AI in HE, while addressing critical issues such as appropriate AI use, systemic approaches to programmatic assessment, and the process of learning and teaching in an AI-enhanced environment.

Structural Integrity Evaluation Of 3D Printed Graphene-Reinforced Pla Notched Plates Using Failure Assessment Diagrams

Abstract Failure Assessment Diagrams (FADs) constitute a well-known structural integrity evaluation tool that allows structural components containing crack-like defects to be assessed through a simultaneous analysis of fracture and plastic-collapse processes. FADs are included in the most recognized structural integrity assessment procedures/standards, such as BS7910 and API 579/ASME FFS-1, and their use is generally limited to metallic components containing crack-like defects. On the other hand, structural responsibilities are being assumed by 3D printed composites, and particularly by those obtained through FFF (Fused Filament Fabrication), beyond their most extended use as prototyping materials. The resulting structural components may contain notch-type defects (e.g., grooves, corners, holes, etc.) that determine their corresponding structural integrity. Thus, it is necessary to define structural integrity assessment criteria for this kind of materials when containing any kind of stress risers, beyond crack-like defects. This work justifies the use of BS7910 Level 1 FAD, coupled with a notch correction derived from the Theory of Critical Distances (TCD), to analyze graphene-reinforced PLA plates subjected to pure tensile loading conditions and containing U- and V-notches. The results reveal that, for U- and V-notches, the assessment points representing the plates at failure are located within the FAD area corresponding to unsafe conditions, providing conservative evaluations with moderate safety margins. For plates containing circular holes, the proposed approach provides unsafe predictions.

Crosstalk Delay and Reliability Analysis of Carbon Nanotube On-Chip Interconnects: Modelling and Optimization using Metaheuristic Algorithm

In the field of VLSI technology, the miniaturization of ICs poses significant challenges to overall interconnect performance, particularly due to the rising concerns of crosstalk-induced reliability and durability issues. This work explores graphene-based randomly mixed carbon nanotube bundle (RMCB) interconnects as a viable solution for advanced reliable VLSI applications. Employing metaheuristic algorithms (Maximum Hole Degree, Particle Swarm Optimization, Stoyan and Yaskov Algorithm), this study seeks to optimize RMCB structures, maximizing carbon nanotube density within a fixed area. Notably, this study explores the effectiveness of algorithms’ performance in optimizing RMCB structures at a nano-technology node. Extensive signal integrity and reliability assessments, considering both rugged and pristine substrates, reveal that Stoyan and Yaskov (SY)-based optimization excels over PSO and MHD-based counterparts in terms of on-chip interconnect performance and reliability. The SY structure significantly dominates MHD-based (and PSO) counterparts by reducing crosstalk delay by 50% (30%), enhancing the average failure rate by 40% (37%), and improving electromigration reliability by 170% (63%).

Associations Between Vestibular Perception and Cognitive Performance in Healthy Adults.

A growing body of evidence has linked vestibular function to the higher-order cognitive ability in aging individuals. Past evidence has suggested unique links between vestibular function and cognition on the basis of end-organ involvement (i.e., otoliths versus canals). However, past studies have only assessed vestibular reflexes despite the diversity of vestibular pathways. Thus, this exploratory study aimed to assess associations between vestibular perception and cognition in aging adults to determine potential relationships. Fifty adults (21 to 84 years; mean = 52.9, SD = 19.8) were included in this cross-sectional study. All participants completed a vestibular perceptual threshold test battery designed to target perception predominantly mediated by each end-organ pair and intra-vestibular integration: 1 Hz y-translation (utricle), 1 Hz z-translation (saccule), 2 Hz yaw rotation (horizontal canals), 2 Hz right anterior, left posterior (RALP), and left anterior, right posterior (LARP) tilts (vertical canals), and 0.5 Hz roll tilt (canal-otolith integration). Participants also completed standard assessments of cognition and path integration: Digit Symbol Substitution Test (DSST), Trail Making Test (TMT), and the Gait Disorientation Test (GDT). Associations were assessed using Spearman rank correlation, and multivariable regression analyses. For correlation analyses, DSST correlated to RALP/LARP tilt, roll tilt, and z-translation. TMT-A only correlated to z-translation, and TMT-B correlated to roll tilt and z-translation after correcting for multiple comparisons. GDT correlated to RALP/LARP tilt and y-translation. In age-adjusted regression analyses, DSST and TMT-B were associated with z-translation thresholds and GDT was associated with y-translation thresholds. In this cross-sectional study, we identified associations between vestibular perceptual thresholds with otolith contributions and standard measures of cognition. These results are in line with past results suggesting unique associations between otolith function and cognitive performance.

Analysis of students’ conceptual change in learning Newton’s third law with an integrated framework of model analysis and knowledge integration

The purpose of this study is to examine how students may hold coexisting and competing conceptual ideas and how students’ uses of such ideas may evolve during the process of conceptual change by combining two complementary methods including model analysis and the conceptual framework model of knowledge integration. Conceptual change is fundamental to science learning, highlighting the processes of students’ transitions from predominantly relying on alternative views to using scientific ones. Recent studies suggest a growing consensus that alternative views and scientific conceptions coexist and compete in students’ learning. However, explicit research on how the states of coexistence and competition evolve during the process of conceptual change is underdeveloped. Building on existing research, the model analysis provides a quantitative framework to represent the different consistent and coexisting/competing states through probabilities of consistent and/or mixed (coexisting) use of incorrect and scientific ideas. Meanwhile, the conceptual framework model of knowledge integration provides content-specific, cognitive explanations for the developmental levels and processes of conceptual change from novice to expert. By combining these two methods, researchers can gain insights into how the coexistence and competition among different conceptual ideas may evolve as conceptual change progresses. To target the research goal, a model-based knowledge integration assessment of Newton’s third law is developed to measure students’ levels of knowledge integration and model states in a single test. Quantitative data were collected from Chinese high school students, supplemented by interviews with a subgroup from the same population. The model analysis results show the heterogeneity of conceptual development and the evolving competition across novice, intermediate, and expert students, as well as across different concept dimensions. The interviews provide cognitive explanations for the observed model states, framed from the lens of knowledge integration. These insights can inform the development of effective assessments and instructional strategies to facilitate favorable conceptual change in student learning. Published by the American Physical Society 2024

Food and land system transformations under different societal perspectives on sustainable development

Abstract The future of food and land systems is crucial for achieving multiple UN Sustainable Development Goals, given their essential role in providing adequate nutrition and their significant impact on Earth system processes. Despite widespread consensus on the need for transformation, discussed strategies vary widely, from technology-driven to sufficiency-focused approaches, emphasizing different agents of change and policy mixes. This study assesses the implications of a new generation of target-seeking scenarios incorporating such diverse sustainability perspectives. We apply two integrated assessment models to explore food and land futures under three whole-economy Sustainable Development Pathways (SDPs): Economy-driven Innovation, Resilient Communities, and Managing the Global Commons. Our assessment shows that all SDPs align sufficient food supply with progress towards planetary integrity, halting biodiversity loss, mitigating adverse impacts from irrigation, and significantly reducing nitrogen pollution. While all pathways comply with the Paris climate target, they diverge in the timing of climate mitigation efforts and focus on different greenhouse gases and emission sources. The Economy-driven Innovation pathway rapidly achieves net-negative CO2 emissions from the land system, whereas Resilient Communities and Managing the Global Commons significantly decrease agricultural non-CO2 emissions. Moreover, sustainability interventions attenuate trade-offs associated with narrowly focused mitigation pathways and reduce reliance on carbon dioxide removal strategies like re/afforestation and bioenergy with carbon capture and storage.