Specific Processes Research Articles

Can selecting the most qualified candidate be unfair? Learning about socioeconomic advantages and disadvantages reduces the perceived fairness of meritocracy and increases support for socioeconomic diversity initiatives in organizations.

While the majority of Americans today endorse meritocracy as fair, we suggest that these perceptions can be shaped by whether or not people learn about the presence of socioeconomic advantages and disadvantages in others' lives. Across five studies (N = 3,318), we find that people are able to attach socioeconomic inequalities in applicants' backgrounds to their evaluation of the fairness of specific merit-based selection processes and outcomes. Learning that one applicant grew up advantaged-while the other grew up disadvantaged-leads both liberals and conservatives to believe that otherwise identical merit-based procedures and outcomes are significantly less fair. Importantly, learning about starting inequalities leads to greater support for policies that promote socioeconomic diversity in organizations. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Childhood emotion dysregulation mediates the relationship between preschool emotion labeling and adolescent depressive symptoms.

Deficits in emotion processing (e.g., emotion labeling and regulation) are widely implicated in depression risk. While prior literature documents these deficits in concurrence with depression, more research is needed to investigate emotion processing pathways of depression risk across development. The purpose of this study was to investigate if emotion processes (i.e., emotion labeling and emotion regulation/dysregulation) in early and middle childhood predict adolescent depressive symptom severity in a prospective sample. Data were analyzed from a longitudinal study of diverse preschoolers oversampled for depressive symptoms using measures of preschool emotion labeling of faces (i.e., Facial Affect Comprehension Evaluation), middle childhood emotion regulation and dysregulation (i.e., emotion regulation checklist), and adolescent depressive symptoms (i.e., PAPA, CAPA, and KSADS-PL diagnostic interviews). Multilevel models indicated that preschoolers with depression had similar development of emotion labeling in early childhood as peers. Mediation analyses revealed that deficits in preschool-aged anger and surprise labeling ability indirectly predicted higher adolescent depressive symptom severity through increased middle childhood emotion lability/negativity, not decreased emotion regulation. Adolescent depression may be predicted by an emotion processing pathway that spans from early childhood to adolescence, and findings may generalize to high risk for depression youth samples. Specifically, poor emotion labeling in early childhood may lead to increased childhood emotion lability/negativity, which increases the risk for adolescent depressive symptom severity. Findings may help identify specific emotion processing relations in childhood that increase the risk for depression and inform intervention aimed at improving preschoolers' anger and surprise labeling. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Interpreting Observed Interactions between Near-Inertial Waves and Mesoscale Eddies

Abstract The evolution of wind-generated near-inertial waves (NIWs) is known to be influenced by the mesoscale eddy field, yet it remains a challenge to disentangle the effects of this interaction in observations. Here, the model of Young and Ben Jelloul (YBJ), which describes NIW evolution in the presence of slowly evolving mesoscale eddies, is compared to observations from a mooring array in the northeast Atlantic Ocean. The model captures the evolution of both the observed NIW amplitude and phase much more accurately than a slab mixed layer model. The YBJ model allows for the identification of specific physical processes that drive the observed evolution. It reveals that differences in the NIW amplitude across the mooring array are caused by the refractive concentration of NIWs into anticyclones. Advection and wave dispersion also make important contributions to the observed wave evolution. Stimulated generation, a process by which mesoscale kinetic energy acts as a source of NIW potential energy, is estimated to be 20 μW m−2 in the region of the mooring array, which is two orders of magnitude smaller than the global average input to mesoscale kinetic energy and likely not an important contribution to the mesoscale kinetic energy budget in this region. Overall, the results show that the YBJ model is a quantitatively useful tool to interpret observations of NIWs.

Brain-computer interface based generative design framework: an empirical multi-domain application exploration based on human-factors and form-generation interactive mechanisms

Human experience in an architectural space is defined as the state of mind that is reflected on their physiological, emotional, and cognitive statuses. Ergonomic data, as an objective manifestation of quantifiable signals generated by the human body during specific spatial perception processes, serves as a vital foundation for spatial evaluation and guidance for optimization. Electroencephalogram (EEG) signals, as quantifiable sensory indicators directly arising from the interaction between individuals and external stimuli, hold substantial potential as a data-driven force and as a means of optimization assessment in the study of generative design. Although existing research has effectively established a unidirectional relationship between EEG and spatial-environment assessment, there is still a notable deficiency in addressing the creation of a two-way, mutually informative feedback mechanism. This study investigates the applicability of EEG signals as a data-driven basis for generative design across universal methods. It delves into various scales and scenarios of digital design, from the microscopic to the macroscopic, encompassing planar and volumetric visual elements, the design of architectural spatial environmental characteristics, and urban space design grounded in human perceptual sightlines. The research examines the viability and appropriateness of an interactive generative design method based on form generation, predicated on human-factor physiological data exemplified by EEG signals. This paper initially conducts a methodological and tool-based examination of current research in ergonomics-driven design and the use of EEG for design assessment, thereby discussing the objective feasibility of employing EEG in interactive generative design. Subsequently, the study establishes an integrated data flow system encompassing multiple hardware and software components to form a comprehensive workflow. Following this setup, empirical studies based on this method are conducted at different scales of application, yielding corresponding form-generative outcomes. Finally, this paper substantiates the rationality and feasibility of this framework in multi environment design domains.

Isolation, screening and optimization of alkaliphilic cellulolytic fungi for production of cellulase

Abstract This study concerns with the production and partial characterization of alkaline cellulase from alkaliphilic cellulolytic (AC) fungi isolated fromsoil in Perlis, Malaysia. The best fungi strain was selected on the basis of producing the highest cellulase at high pH conditions. Cellulase from the selected fungi strain was further characterized under saccharification but varies in operating parameters. Finally, the kinetic model describing the growth of the AC fungi strain was studied by employing the logistic model. Among the tested fungi strains, Basidiomycetes strain (BK1) showed high potentiality for the production of maximum alkaline cellulase production at pH 9 after 72 h of incubation at 30°C containing 6 g·L−1 carboxyl methyl cellulose. The saccharification process showed that the enzyme favour high alkaline condition and proves thermotolerant properties, while 15% (v/v) enzyme loading and 1% substrate concentration recorded the highest glucose production at about 1.2–1.3 mg·mL−1. The novelty of the study is to identify and optimize a unique indigenous fungi that emit alkaliphilic cellulase as alternative usage in biotechnology industries due to its capacity to adapt to the extreme conditions of specific industrial processes. There are revolutionary options for use in biotechnological businesses that involve high pH and therefore have substantial biotechnological promise.

Big data analysis and evaluation for vitality factors of public space of regenerated industrial heritage in Luoyang

Abstract The regeneration of idle industrial heritage buildings needs to take into account many factors such as history, science, art, and social aspects. Current research on industrial heritage regeneration has not developed quantitative research in each factor of assessment, and cannot provide clear guidance and program reference for industrial building regeneration weighting ratios. In this study, we put forward a spatial vitality factor range prediction method based on big data analysis for the regeneration of an industrial heritage public space in Luoyang, aiming to establish a model for the regeneration of industrial heritage abandoned industrial buildings and to provide implementation and regeneration planning. The specific evaluation process and regeneration evaluation design scheme based on Luoyang’s industrial heritage were restored. The weights and percentages of the key domain indicators and branch indicators of the idle industrial building regeneration model were predicted, which provided clear guidance and reference for the planning of regeneration of public spaces of industrial heritage. The prediction accuracy of each key assessment factor was maintained above 90%, and the sequential ranking result of the assessment factors was given. The spatial regeneration prediction scheme provided an effective guide and indicator reference for the case design, highlighting the effectiveness of our approach.

A Guide to Printed Stretchable Conductors.

Printing of stretchable conductors enables the fabrication and rapid prototyping of stretchable electronic devices. For such applications, there are often specific process and material requirements such as print resolution, maximum strain, and electrical/ionic conductivity. This review highlights common printing methods and compatible inks that produce stretchable conductors. The review compares the capabilities, benefits, and limitations of each approach to help guide the selection of a suitable process and ink for an intended application. We also discuss methods to design and fabricate ink composites with the desired material properties (e.g., electrical conductance, viscosity, printability). This guide should help inform ongoing and future efforts to create soft, stretchable electronic devices for wearables, soft robots, e-skins, and sensors.

Damage failure prediction study of carbon fiber metal laminates in hot stamping process

In addressing the difficulty of forming Fiber Metal Laminates (FMLs), a laminate composed of a 0.1 mm-thick 304 Stainless Steel Foil (SSF) and Carbon Fiber Reinforced Plastics (CFRP) as the base material is prepared using a specific process. Subsequently, forming limit diagrams are obtained through hemispherical bulge forming experiments to investigate the forming performance of FMLs laminates. The damage phenomena of various forming specimens during the thermal stamping process are analyzed. Based on different damage forms, corresponding theoretical models are established to simulate and predict the forming damage modes of FMLs through simulation. The research results indicate that the stamping formability of FMLs is influenced by the damage tolerance of the thin stainless steel foil. During the thermal stamping process, FMLs may experience delamination, fracture/crack of the thin stainless steel foil, and rupture/tearing/wrinkling of the prepreg. To address these issues, cohesive elements, GTN-M-K damage, and Hashin damage models are established, providing a reasonable simulation prediction of the stamping damage phenomena of FMLs.

Investigating the role of spatial thinking in children’s design ideation through an open-ended design-by-analogy challenge

AbstractSpatial thinking is ubiquitous in design. Design education across all age groups encompasses a range of spatially challenging activities, such as forming and modifying mental representations of ideas, and visualizing the scenarios of design prototypes being used. While extensive research has examined the cognitive processes of spatial thinking and their relationships to science, technology, engineering, and mathematics learning, there remains a knowledge gap regarding the specific spatial thinking processes needed for open-ended problems, which may differ from those assessed in close-ended, analytical spatial tasks. To address this gap, we used educational design-based research to develop a nature-inspired, design-by-analogy project and investigate the spatial thinking processes of young, novice designers. 16 children from an international school in the Netherlands participated in this five-week design project. Multimodal evidence from classroom recordings and children’s design works were triangulated to offer insight into the key spatial thinking processes involved in their creation of nature-inspired, analogy-based design prototypes. Our results revealed spatial thinking processes that might not align with those assessed in conventional spatial tests and may be unique to design or open-ended problem-solving. These processes include abstracting spatial features to infer form-function relationships, retrieving a range of relevant visual information from memory, developing multiple possible analogical matches based on spatial features and relationships, elaborating and iterating on the design concepts and representations to make creative and suitable solutions for the design challenge, as well as visualizing design prototypes in practical usage scenarios. By highlighting the nuanced differences between spatial thinking in open-ended, divergent thinking tasks and conventional spatial tasks that demand single correct solutions, our research contributes to a deeper understanding of how children utilize spatial thinking in design and open-ended problem-solving contexts. Furthermore, this case study offers practical implications for scaffolding children's analogical reasoning and nurturing their spatial thinking in design education.

New directions of scientific research and clinical practice in the field of extracorporeal hemocorrection in patients with multiple organ dysfunction: a review

INTRODUCTION: Due to the COVID-19 (infectious disease caused by the SARS-CoV-2 virus) pandemic, we had to take a completely different approach to the nature of critical conditions. The pandemic also made us reconsider many views about it. Moreover, that contributed to the development of new practical approaches for treatment and prevention, including the ones in the field of extracorporeal hemocorrection. OBJECTIVE: Methods for purification of blood and plasma began to be considered as an independent link for the treatment of organ disorders or as a part of extracorporeal support for the life support of the body. MATERIALS AND METHODS: The article consists of three sections: a description of the role of extracorporeal hemocorrection methods in intensive care, their classification and main characteristics; the concept of sequential targeted extracorporeal therapy for a treatable symptom in sepsis; extracorporeal hemocorrection as part of the concept of extracorporeal life support. This article uses literary sources published from January 1, 2022 to July 1, 2023. Materials related to COVID-19 and other specific pathologies (poisoning, acute liver failure, itching, systemic diseases, etc.), requiring separate discussion, are intentionally excluded. RESULTS: Technologies in extracorporeal hemocorrection provide support and/or replacement of organ functions; restoration of body resistance and balance between inflammatory and anti-inflammatory response; restoration of body tolerance (metabolism and regeneration). Nevertheless, despite the convincing pathophysiological rationale for the use of these methods in critical conditions, evidence of its effectiveness is limited. Current trends indicate that future research should be primarily aimed at finding biomarkers that can simultaneously designate specific biological processes; characterize different subgroups of patients; allow targeted choice for the method of therapy. The modulation of biomarkers under the influence of this therapy can show its effectiveness for this particular subgroup of patients at this stage of the disease. CONCLUSIONS: Methods of extracorporeal blood purification should be aimed at prevailing biological processes, at this stage of pathogenesis, and, accordingly, evaluated by the effectiveness of the impact on these processes.

Spatiotemporally Precise Optical Manipulation of Intracellular Molecular Activities.

Controlling chemical processes in live cells is a challenging task. The spatial heterogeneity of biochemical reactions in cells is often overlooked by conventional means of incubating cells with desired chemicals. A comprehensive understanding of spatially diverse biochemical processes requires precise control over molecular activities at the subcellular level. Herein, a closed-loop optoelectronic control system is developed that allows the manipulation of biomolecular activities in live cells at high spatiotemporal precision. Chemical-selective fluorescence signals are utilized to command lasers that trigger specific chemical processes or control the activation of photoswitchable inhibitors at desired targets. This technology is fully compatible with laser scanning confocal fluorescence microscopes. The authors demonstrate selective interactions of a 405nm laser with targeted organelles and simultaneous monitoring of cell responses by fluorescent protein signals. Notably, blue laser interaction with the endoplasmic reticulum leads to a more pronounced reduction in cytosolic green fluorescent protein signals in comparison to that with nuclei and lipid droplets. Moreover, when combined with a photoswitchable inhibitor, microtubule polymerization is selectively inhibited within the subcellular compartments. This technology enables subcellular spatiotemporal optical manipulation over chemical processes and drug activities, exclusively at desired targets, while minimizing undesired effects on non-targeted locations.

Contribution of the medial entorhinal cortex to performance on the Traveling Salesperson Problem in rats

In order to successfully navigate through space, animals must rely on multiple cognitive processes, including orientation in space, memory of object locations, and navigational decisions based on that information. Although highly-controlled behavioral tasks are valuable for isolating and targeting specific processes, they risk producing a narrow understanding of complex behavior in natural contexts. The Traveling Salesperson Problem (TSP) is an optimization problem that can be used to study naturalistic foraging behaviors, in which subjects select routes between multiple baited targets. Foraging is a spontaneous, yet complex, behavior, involving decision-making, attention, course planning, and memory. Previous research found that hippocampal lesions in rats impaired TSP task performance, particularly on measures of spatial memory. Although traditional laboratory tests have shown the medial entorhinal cortex (MEC) to play an important role in spatial memory, if and how the MEC is involved in finding efficient solutions to the TSP remains unknown. In the current study, rats were trained on the TSP, learning to retrieve bait from targets in a variety of spatial configurations. After recovering from either an MEC lesion or control sham surgery, the rats were tested on eight new configurations. Our results showed that, similar to rats with hippocampal lesions, MEC-lesioned rats were impaired on measures of spatial memory, but not spatial decision-making, with greatest impairments on configurations requiring a global navigational strategy for selecting the optimal route. These findings suggest that the MEC is important for effective spatial navigation, especially when global cue processing is required.

Hydrothermal synthesis of LiMn0.79Fe0.2Mg0.01PO4/C composite cathode materials using different Li3PO4 precursors

Doping and particle size controlling are two important approaches to improve the electrochemical performance of LiMnxFe1−xPO4 cathode materials. By employing a straightforward hydrothermal method and utilizing cost-effective lithium phosphate (Li3PO4) as the precursor, we successfully synthesized high Mn-content LiMn0.79Fe0.2Mg0.01PO4/C composites. The results reveal that the minute amount of Mg substantially enhances the electrochemical performance. In the subsequent mechanism study using Li3PO4 precursors with different particle size, we found that the nucleation process, dependent on specific surface area and diffusion rate, is likely to play a critical role for the size and morphology of formed LiMn0.79Fe0.2Mg0.01PO4. LiMn0.79Fe0.2Mg0.01PO4/C (LMFP-1), synthesized from initially smaller-sized and less agglomerated Li3PO4 (LPO-1), exhibited the most diminutive average particle size coupled with the highest specific surface area, which further facilitated electrolyte interfacial interaction and promoted Li+ diffusion kinetics. At 1C, LMFP-1 displayed a specific capacity of 110.7 mAh g−1, with 97.07% capacity retention after 200 cycles. This study provides pivotal insights for the synthesis of high-performance LiMnxFe1−xPO4 materials.

Aircraft-based mass balance estimate of methane emissions from offshore gas facilities in the southern North Sea

Abstract. Atmospheric methane (CH4) concentrations have more than doubled since the beginning of the industrial age, making CH4 the second most important anthropogenic greenhouse gas after carbon dioxide (CO2). The oil and gas sector represents one of the major anthropogenic CH4 emitters as it is estimated to account for 22 % of global anthropogenic CH4 emissions. An airborne field campaign was conducted in April–May 2019 to study CH4 emissions from offshore gas facilities in the southern North Sea with the aim of deriving emission estimates using a top-down (measurement-led) approach. We present CH4 fluxes for six UK and five Dutch offshore platforms or platform complexes using the well-established mass balance flux method. We identify specific gas production emissions and emission processes (venting and fugitive or flaring and combustion) using observations of co-emitted ethane (C2H6) and CO2. We compare our top-down estimated fluxes with a ship-based top-down study in the Dutch sector and with bottom-up estimates from a globally gridded annual inventory, UK national annual point-source inventories, and operator-based reporting for individual Dutch facilities. In this study, we find that all the inventories, except for the operator-based facility-level reporting, underestimate measured emissions, with the largest discrepancy observed with the globally gridded inventory. Individual facility reporting, as available for Dutch sites for the specific survey date, shows better agreement with our measurement-based estimates. For all the sampled Dutch installations together, we find that our estimated flux of (122.9 ± 36.8) kg h−1 deviates by a factor of 0.64 (0.33–12) from reported values (192.8 kg h−1). Comparisons with aircraft observations in two other offshore regions (the Norwegian Sea and the Gulf of Mexico) show that measured, absolute facility-level emission rates agree with the general distribution found in other offshore basins despite different production types (oil, gas) and gas production rates, which vary by 2 orders of magnitude. Therefore, mitigation is warranted equally across geographies.

Competition between dual alkali metal ions fuels high-performance sodium-ion batteries

Dual alkali metal ion battery is expected to apply in future high-efficiency energy storage applications as it can skillfully combine the advantages of Li+ and Na+. However, the specific insertion and extraction processes of the two ions are not well explained. Herein, a layered sodium transition metal oxide electrode with ordered mixing of Na/Li ions is prepared by ion exchange method. The ion behavior is explained in terms of activation energy of chemical reaction and Gibbs free energy. Based on thermodynamic analysis and material characterizations, the priorities of Na+ and Li+ deblock reactions are determined. The competition mechanism of alkali metal ions and the double gain effect of Li are revealed by electrochemical experiments. This work is expected to provide a positive impact on the future design of multifunctional cathodes for advanced rechargeable batteries.

Amygdala-hippocampus somatostatin interneuron beta-synchrony underlies a cross-species biomarker of emotional state

Emotional responses arise from limbic circuits including the hippocampus and amygdala. In the human brain, beta-frequency communication between these structures correlates with self-reported mood and anxiety. However, both the mechanism and significance of this biomarker as a readout vs. driver of emotional state remain unknown. Here, we show that beta-frequency communication between ventral hippocampus and basolateral amygdala also predicts anxiety-related behavior in mice, both on long timescales (∼30min) and immediately preceding behavioral choices. Genetically encoded voltage indicators reveal that this biomarker reflects synchronization between somatostatin interneurons across both structures. Indeed, synchrony between these neurons dynamically predicts approach-avoidance decisions, and optogenetically shifting the phase of synchronization by just 25ms is sufficient to bidirectionally modulate anxiety-related behaviors. Thus, back-translation establishes a human biomarker as a causal determinant (not just predictor) of emotional state, revealing a novel mechanism whereby interregional synchronization that is frequency, phase, and cell type specific controls emotional processing.

Integrated fatigue assessment method considering average stress effects of large-scale lattice wind turbine support structures

Modular assembly techniques for ultra-high lattice wind turbine support structures are gaining popularity as a viable solution for wind energy development in low wind speed areas. However, efficient fatigue assessment of the overall structure is crucial for the widespread promotion and application of these structures. Existing engineering methods for fatigue assessment suffer from limitations in calculation efficiency and often fail to account for the effects of average stress. To address these issues, a novel integrated fatigue assessment method is proposed, which is both fast and efficient while considering the impact of average stress. The method enables the computation of cumulative fatigue damage and fatigue life for each component, as well as the identification of the location of the greatest cumulative fatigue damage in the structure. An onshore ultra-high lattice wind turbine support structure, modularly assembled to a height of 180 m, is utilized as an application example to illustrate the specific implementation process of the proposed method. The effect of different fatigue load conditions and transfer functions on cumulative fatigue damage is analyzed, and the relationship between transfer function and fatigue accumulation damage is examined. The findings indicate that average stress plays a crucial role in the cumulative fatigue damage of ultra-high lattice wind turbine support structures, and the proposed integrated fatigue assessment method simplifies the calculation process for fatigue-resistant designs substantially.

Tracing Englacial Layers in Radargram via Semi-supervised Method: A Preliminary Result

The melting of ice sheets significantly contributes to sea level rise, highlighting the crucial need to comprehend the structure of ice for climate benefits. The stratigraphy of ice sheets revealed through ice layer radargrams gives us a window into historical depth-age correlations and accumulation rates. Harnessing this knowledge is not only crucial for interpreting both past and present ice dynamics, especially concerning the Greenland ice sheet, but also for making informed decisions to mitigate the impacts of climate change. Ice layer tracing is prevalently conducted using manual or semi-automatic approaches, requiring significant time and expertise. This study aims to address the need for efficient and precise tracing methods in a two-step process. This is achieved by utilizing an unsupervised annotation method (i.e., ARESELP) to train deep learning models, thereby reducing the need for extensive and time-consuming manual annotations. Four prominent deep learning-based segmentation techniques, namely U-Net, U-Net+VGG19, U-Net+Inception, and Attention U-Net, are benchmarked. Additionally, various thresholding methods such as binary, Otsu, and CLAHE have been explored to achieve optimal enhancement for the true label annotation images. Our preliminary experiments indicate that the combination of attention U-Net with specific processing techniques yields the best performance in terms of the binary IoU metric.

Unveiling the principles of stochastic resonance and complex potential functions for bearing fault diagnosis

This paper introduces a novel and complex Unsaturated Piecewise Linear Quad-Stable Stochastic Resonance System (UPLQSR) to address the issue of output saturation in the Classical Quad-Stable Stochastic Resonance (CQSR) system. By linearizing the structure of the potential function, the constraints imposed by high-order terms are effectively eliminated, allowing Brownian particles to move more freely. Numerical simulations demonstrate that UPLQSR achieves significantly higher output signal amplitudes compared to CQSR, highlighting its remarkable signal amplification capability. By analyzing the structure of the potential function, the relationship between the height of the potential barrier and the aggressiveness of the particles jumping is determined. Utilizing adiabatic approximation theory, the paper derives the Steady-state Probability Density (SPD), Mean First Passage Time (MFPT), and Spectral Amplification (SA), revealing the specific process of the particle jumping, as well as the influence of the parameters on the performance of the UPLQSR. After optimizing parameters using the Adaptive Genetic Algorithm (GA), UPLQSR is applied to the early fault diagnosis of various bearing models under Gaussian white noise, demonstrating superior fault detection capabilities. In summary, this study pioneered the theory of non-saturation of quad-stable systems, optimized the weak signal detection technique, and provided a more accurate means of signal identification and analysis, highlighting its great value of application in engineering.

Computational dissection of genetic variation modulating the response of multiple photosynthetic phenotypes to the light environment

BackgroundThe expression of biological traits is modulated by genetics as well as the environment, and the level of influence exerted by the latter may vary across characteristics. Photosynthetic traits in plants are complex quantitative traits that are regulated by both endogenous genetic factors and external environmental factors such as light intensity and CO2 concentration. The specific processes impacted occur dynamically and continuously as the growth of plants changes. Although studies have been conducted to explore the genetic regulatory mechanisms of individual photosynthetic traits or to evaluate the effects of certain environmental variables on photosynthetic traits, the systematic impact of environmental variables on the dynamic process of integrated plant growth and development has not been fully elucidated.ResultsIn this paper, we proposed a research framework to investigate the genetic mechanism of high-dimensional complex photosynthetic traits in response to the light environment at the genome level. We established a set of high-dimensional equations incorporating environmental regulators to integrate functional mapping and dynamic screening of gene‒environment complex systems to elucidate the process and pattern of intrinsic genetic regulatory mechanisms of three types of photosynthetic phenotypes of Populus simonii that varied with light intensity. Furthermore, a network structure was established to elucidate the crosstalk among significant QTLs that regulate photosynthetic phenotypic systems. Additionally, the detection of key QTLs governing the response of multiple phenotypes to the light environment, coupled with the intrinsic differences in genotype expression, provides valuable insights into the regulatory mechanisms that drive the transition of photosynthetic activity and photoprotection in the face of varying light intensity gradients.ConclusionsThis paper offers a comprehensive approach to unraveling the genetic architecture of multidimensional variations in photosynthetic phenotypes, considering the combined impact of integrated environmental factors from multiple perspectives.