Relative Importance Research Articles

Lobster Diplomacy: Nova Scotia and the Provincial Role in Canada-China Relations

This article concerns the increasingly significant role of subnational entities in international relations, using Nova Scotia's engagement with China as a case study. It highlights the period from 2010 to 2023, during which Nova Scotia leveraged its key export—lobsters—to establish and deepen economic and diplomatic ties with China, thereby carving out an influential role in the broader Canada-China relationship. The article provides an overview of subnational diplomacy's growing importance in international relations. The theoretical framework centres on subnational actors in global diplomacy and examines how Nova Scotia pursued independent diplomatic efforts with China, focusing on economic interests. The case study investigates lobster exports as the cornerstone of Nova Scotia-China relations, driving both economic benefits and diplomatic engagement. Finally, it touches on the economic outcomes for Nova Scotia and the political dynamics between federal and provincial authorities, concluding with broader implications for Canada's foreign policy and subnational actors in international diplomacy.

The Effect of Recording Industry Lawsuits on the Market for Recorded Music

The origination and rapid growth in popularity of file sharing technology at the end of the twentieth century created the potential for a fundamental market shift for any private good that is reduced to information. Through a new exploration of this recent phenomenon within the context of peer-to-peer file sharing technology for music downloads, this article examines the relative importance of various economic factors in determining the national level of file sharing. After employing basic theoretical models and econometric methods, the author finds that file sharing behavior is most responsive to the number of lawsuits brought against consumers, the relative value and amount of leisure time for consumers, household disposable income, and the prevalence of computer virus threats among file-sharing program users. These new findings are discussed in the context of microeconomic expectations that predict a different set of empirical trends in file sharing technology.

The influence of the contextual framing on physio- and occupational therapists’ clinical reasoning in sensory rooms with patients admitted to psychiatry – a qualitative case study

Aim To investigate the influence of contextual framing on physio- and occupational therapists’ clinical reasoning in sensory rooms for patients admitted to psychiatric units. Material and method Physiotherapists and occupational therapists from acute and intensive care units with sensory rooms were invited to participate in the study. The therapists were interviewed following sessions with patients in sensory rooms, using a semi-structured interview guide. These therapists also participated in a focus group interview. All interviews were transcribed and analysed based on the thematic analysis by Braun and Clarke. Results Twenty individual interviews and one focus group interview were conducted with seven physio- and occupational therapists. Three themes with accompanying subthemes emerged: (i) The contextual influence: Therapists’ perceptions of the use of sensory rooms, The dominance of the medical paradigm). (ii) The therapeutic alliance: The therapists’ relational skills, The importance of a good therapeutic patient relation, and Physio- and occupational therapy in a psychiatric setting.: (iii) The therapeutic diagnosis, Therapeutic sensory room interventions, and Holistic approach in a limited timeframe. Conclusion The clinical reasoning of physio- and occupational therapists in sensory-modulating sessions for patients admitted to psychiatric units is influenced by a primarily medically dominated paradigm; legally, economically, and politically. Occupational therapists mainly focus on everyday skills and being in the present, whereas physiotherapists focused on activities with bodily anchoring and awareness.

Common- and rare-variant genetic architecture of heart failure across the allele frequency spectrum.

Heart failure (HF) is a complex trait, influenced by environmental and genetic factors, which affects over 30 million individuals worldwide. Historically, the genetics of HF have been studied in Mendelian forms of disease, where rare genetic variants have been linked to familial cardiomyopathies. More recently, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with risk of HF. However, the relative importance of genetic variants across the allele-frequency spectrum remains incompletely characterized. Here, we report the results of common- and rare-variant association studies of all-cause heart failure, applying recently developed methods to quantify the heritability of HF attributable to different classes of genetic variation. We combine GWAS data across multiple populations including 207,346 individuals with HF and 2,151,210 without, identifying 176 risk loci at genome-wide significance (P-value < 5×10 -8 ). Signals at newly identified common-variant loci include coding variants in Mendelian cardiomyopathy genes ( MYBPC3 , BAG3 ) and in regulators of lipoprotein ( LPL ) and glucose metabolism ( GIPR , GLP1R ). These signals are enriched in myocyte and adipocyte cell types and can be clustered into 5 broad modules based on pleiotropic associations with anthropomorphic traits/obesity, blood pressure/renal function, atherosclerosis/lipids, immune activity, and arrhythmias. Gene burden studies across three biobanks (PMBB, UKB, AOU), including 27,208 individuals with HF and 349,126 without, uncover exome-wide significant (P-value < 1.57×10 -6 ) associations for HF and rare predicted loss-of-function (pLoF) variants in TTN , MYBPC3 , FLNC, and BAG3. Total burden heritability of rare coding variants (2.2%, 95% CI 0.99-3.5%) is highly concentrated in a small set of Mendelian cardiomyopathy genes, while common variant heritability (4.3%, 95% CI 3.9-4.7%) is more diffusely spread throughout the genome. Finally, we show that common-variant background, in the form of a polygenic risk score (PRS), significantly modifies the risk of HF among carriers of pathogenic truncating variants in the Mendelian cardiomyopathy gene TTN. Together, these findings provide a genetic link between dysregulated metabolism and HF, and suggest a significant polygenic component to HF exists that is not captured by current clinical genetic testing.

AdaVis: Adaptive and Explainable Visualization Recommendation for Tabular Data.

Automated visualization recommendation facilitates the rapid creation of effective visualizations, which is especially beneficial for users with limited time and limited knowledge of data visualization. There is an increasing trend in leveraging machine learning (ML) techniques to achieve an end-to-end visualization recommendation. However, existing ML-based approaches implicitly assume that there is only one appropriate visualization for a specific dataset, which is often not true for real applications. Also, they often work like a black box, and are difficult for users to understand the reasons for recommending specific visualizations. To fill the research gap, we propose AdaVis, an adaptive and explainable approach to recommend one or multiple appropriate visualizations for a tabular dataset. It leverages a box embedding-based knowledge graph to well model the possible one-to-many mapping relations among different entities (i.e., data features, dataset columns, datasets, and visualization choices). The embeddings of the entities and relations can be learned from dataset-visualization pairs. Also, AdaVis incorporates the attention mechanism into the inference framework. Attention can indicate the relative importance of data features for a dataset and provide fine-grained explainability. Our extensive evaluations through quantitative metric evaluations, case studies, and user interviews demonstrate the effectiveness of AdaVis.

Do successive performance matter for tone management? Evidence from China

ABSTRACT This paper investigates whether managers deliberately adjust the tone of their non-financial disclosure depending on their firm performance over multiple periods. Using 13,995 firm-year MD&As (Management Discussion and Analysis) in annual reports of companies listed on the Shanghai and Shenzhen Stock Exchanges from 2009 to 2019, we first observe a bias towards good news disclosure by managers in their MD&A section. More importantly, we find that this asymmetric tone management is more pronounced when a firm’s performance declines consecutively. In cross-sectional tests, we provide evidence that the relationship between asymmetric tone management and successive performance is weaker for firms with state ownership and those with a high marketability index. We suggest that in non-U.S. markets, such as China, asymmetric tone management is more likely to reflect the opportunistic behaviour of managers. Overall, our study sheds new light on tone management in emerging markets and highlights the importance of a multi-period relation in understanding managers’ tone management behaviour.

Neutrinos, light, matter, and the unification of gravitational and nuclear forces

Neutrinos, light, matter, and the unification of gravitational and nuclear forces The discovery of neutrinos and the measurement of their masses are significant events in the history of science. The Rotating Lepton Model provides a useful basis for understanding particles and nuclear reactions, highlighting the importance of Special Relativity, Gravity, and Quantum Mechanics in our universe. Professor Constantinos G. Vayenas explains. The discovery of neutrinos by Pauli some 90 years ago and the measurement of their masses by Kajita and McDonald (1) some 20 years ago constitute significant developments in the history of science. The recent (2023) (2) detection of neutrino production during the proton-proton collision experiments at CERN confirms the basic assumption of the Rotating Lepton Model (RLM) (2020), (3) i.e. that protons and neutrons comprise rotating neutrino triads, the former with a central positron. This implies that all matter in our Universe, including electromagnetic radiation, (4) comprises only five elementary particles: The three neutrinos (ν1, ν2, and ν3), the electron, and the positron. It also implies that two forces (gravity and electromagnetism) suffice for describing the interactions between these five particles and the concomitant production of all other composite particles, such as hadrons and bosons.

IA-LSTM: Interaction-Aware LSTM for Pedestrian Trajectory Prediction.

Predicting the trajectory of pedestrians in crowd scenarios is indispensable in self-driving or autonomous mobile robot field because estimating the future locations of pedestrians around is beneficial for policy decision to avoid collision. It is a challenging issue because humans have different walking motions, and the interactions between humans and objects in the current environment, especially between humans themselves, are complex. Previous researchers focused on how to model human-human interactions but neglected the relative importance of interactions. To address this issue, a novel mechanism based on correntropy is introduced. The proposed mechanism not only can measure the relative importance of human-human interactions but also can build personal space for each pedestrian. An interaction module, including this data-driven mechanism, is further proposed. In the proposed module, the data-driven mechanism can effectively extract the feature representations of dynamic human-human interactions in the scene and calculate the corresponding weights to represent the importance of different interactions. To share such social messages among pedestrians, an interaction-aware architecture based on long short-term memory network for trajectory prediction is designed. Experiments are conducted on two public datasets. Experimental results demonstrate that our model can achieve better performance than several latest methods with good performance.

Maternal ethnicity and socioeconomic deprivation: influence on adverse pregnancy outcomes.

To evaluate the relative importance of ethnicity and socioeconomic deprivation in determining the likelihood and prevalence of placentally derived composite of adverse pregnancy outcomes (CAPO) and composite of severe adverse pregnancy outcomes (CAPO-S). This was a single-center retrospective cohort study of data obtained in a tertiary maternity unit. Data regarding ethnicity and socioeconomic deprivation (as measured with indices of multiple deprivation) were collected for 13 165 singleton pregnancies screened routinely in the first trimester for pre-eclampsia using the Fetal Medicine Foundation combined risk-assessment algorithm. CAPO was defined as the presence of one or more interrelated outcomes associated with placental dysfunction, namely, hypertensive disorders of pregnancy, preterm birth, birth weight ≤ 10th centile and stillbirth. CAPO-S was defined as the presence of one or more of the following: hypertensive disorders of pregnancy at < 37 + 0 weeks, preterm birth at < 34 + 0 weeks, birth weight ≤ 5th centile and stillbirth at < 37 + 0 weeks. The prevalence of CAPO was 16.3% in white women, 29.3% in black women and 29.3% in South Asian women. However, half (51.7%) of all CAPO cases occurred in white women. There was a strong interaction between ethnicity and socioeconomic deprivation, with a correlation coefficient of -0.223. Both ethnicity and socioeconomic deprivation influenced the prevalence of CAPO and CAPO-S, with the contribution of ethnicity being the strongest. Black and Asian ethnicity, as well as socioeconomic deprivation, influence the prevalence of placenta-mediated adverse pregnancy outcomes. Despite this, most adverse pregnancy outcomes occur in white women, who represent the majority of the population and are also affected by socioeconomic deprivation. For these reasons, inclusion of socioeconomic deprivation should be considered in early pregnancy risk assessment for placenta-mediated CAPO. © 2024 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Social protection strategies in relations between Ukraine and the European Union

In today’s world, social protection is becoming an increasingly important topic that combines economic, political, and social aspects. Regardless of the level of development of a country, people are constantly looking for ways to ensure their well-being and protect themselves from negative influences. Social protection strategies are of particular importance in relations between Ukraine and the European Union. Ukraine, as a sovereign state, monitors the needs of its population and tries to adapt its social system to European standards. Therefore, the purpose of the study is to analyze the current state and prospects for the development of social protection strategies in Ukraine in the context of cooperation with the European Union to identify possible areas for improving the social sphere and ensuring a high level of social protection for the Ukrainian population. The study uses a variety of methods, including analysis, synthesis, induction, deduction, comparative legal, dialectical, and others. Considering cooperation with the European Union helps to solve socioeconomic problems and ensure a high level of social protection.

The relation of clinical governance climate on quality of care mediated by patient safety culture

The hospital organization determines quality of care (QOC) from health services; however, there are many challenges due to the different backgrounds of healthcare workers. Essentially, governance is needed to guarantee a process oriented toward clinical outcomes. Unfortunately, research on clinical management with dimensional measurements conducted in private hospitals is still scanty. This study aimed to investigate the relationship between clinical governance climate (CGC) on QOC mediated by a patient safety culture (PSC) and the control variable adaptation to workload in relation to QOC. Participants were healthcare workers in two private hospitals that have been fully accredited; 416 participants met the requirements. Data were collected by distributing questionnaires in March 2023. Data were analyzed through partial least square – structural equation model (PLS-SEM). The study result indicated a significant positive relationship between CGC and PSC (β=0.851, p-value&amp;lt;0.05). Further, a positive relationship between PSC to QOC (β=0.654, p-value&amp;lt;0.05) was established. However, insufficient evidence indicates a direct relation between CGC on QOC (p-value&amp;gt;0.05). The role of PSC as a full mediating was confirmed (β=0.557, p-value&amp;lt;0.05, CI 95% 0.441-0.677). The finding of this study is the importance of CGC relation to QOC mediated by PSC in private hospitals.

Ethnopharmacological Survey of Medicinal Plants Used by Local Herbalists and Traditional Healers for the Treatment of Cancer in Jordan

Background: As many Jordanians include herbs in their treatment, an ethnopharmacological survey was conducted to identify the most prescribed plants for the treatment of cancer by local herbalists and traditional healers in Jordan, aiming to encourage the prescription that is based on scientific evidence, to tackle some important practices in traditional healing, and to provide candidates for the isolation of new anticancer agents. Methods: Thirty-two Jordanian herbalists and traditional healers were interviewed. Both the use value and frequency of citation were implemented as quantitative methods to demonstrate the relative importance of a chosen species for the treatment of cancer. Furthermore, literature was screened for evidences that supported or opposed the use of the plants of interest Results: It was revealed that 31 plants are currently used in Jordan for the treatment of cancer, with Curcuma longa and Ephedra foeminea being the most used ones. Conclusions: It was noticed that the use of many prescribed plants could be rationalised by in vitro and/or in vivo studies. However, more attention should be paid by practitioners to some important aspects, such as the method of use and preparation of plants, their interaction with chemotherapeutic agents and the differences in their efficacy against different cancer types.

HelloTalk Application as an Alternative for Building Students’ Reading Ability on Narative Texts

English was regarded as a foreign language in Indonesia and holds significant importance in various domains, including education, economy, international relations, and technology. Consequently, the Indonesian government has designated English as the primary foreign language, mandatory for learning in both schools and universities. Thus, English has incorporated into the curriculum from elementary level up to university. This research aimed to determine if there is a significant difference in the reading abilities of students taught using the Hellotalk application compared to those taught through conventional methods.in this school most of students still low to read the English text so the Reseacher interesting to give new method for them. The method used Quantitative research, with an experimental method and quasi-experimental design. The target population consisted of seventh-grade students. Purposive sampling was utilized to select a sample of 25 students for the experimental group and 25 students for the control group. Data collection involved the use of a multiple-choice test, which was subsequently analyzed using the independent t-test in SPSS 25. The research findings revealed a significant distinction between the experimental group and the control group. This meant that Hellotalk Application was suitable to use in teaching reading on narrative texts at the seventh grade.

MHGCN+: Multiplex Heterogeneous Graph Convolutional Network

Heterogeneous graph convolutional networks have gained great popularity in tackling various network analytical tasks on heterogeneous graph data, ranging from link prediction to node classification. However, most existing works ignore the relation heterogeneity with multiplex networks between multi-typed nodes and the different importance of relations in meta-paths for node embedding, which can hardly capture the heterogeneous structure signals across different relations. To tackle this challenge, this work proposes a M ultiplex H eterogeneous G raph C onvolutional N etwork (MHGCN+) for multiplex heterogeneous network embedding. Our MHGCN+ can automatically learn the useful heterogeneous meta-path interactions of different lengths with different importance in multiplex heterogeneous networks through multi-layer convolution aggregation. Additionally, we effectively integrate both multi-relation structural signals and attribute semantics into the learned node embeddings with both unsupervised and semi-supervised learning paradigms. Extensive experiments on seven real-world datasets with various network analytical tasks demonstrate the significant superiority of MHGCN+ against state-of-the-art embedding baselines in terms of all evaluation metrics. The source code of our method is available at: https://github.com/FuChF/MHGCN-plus .

An improved habitat suitability index for the great crested newt Triturus cristatus

An improved habitat suitability index for the great crested newt Triturus cristatus

A Study of Impact of Parental Encouragement on Achievement Motivation at Secondary Level Student

Parents are the chief architects in shaping the personality of the child. Parent's attitudes a pre-dominant role in fostering or hindering the child's development. Although, parental encouragement is essential for the child at all stages. But it becomes increasingly significant at secondary level. Due to more pressures and strains of studies, peer groups, competitions etc. achievement motivation at secondary level is found to be the foremost variable which has a great impact on the personality and future prospects of the child. Taking into consideration the importance of relation of these variables with parental encouragement. The present study is an attempt to appraise the effect of parental encouragement on achievement motivation at secondary level. Ex-post facto research method is best suited for the under taken study. Population of the present study comprises all secondary schools situated in Greater Noida, Gautam Budh Nagar. One UP Board school and one CBSE Board school were taken from list of all school. Researcher has selected a sample of 150 students. Of these 150 students 75 students are from one CBSE Board school and another 75 students are from one UP Board school. The major data gathering tools and techniques such as psychological tests, enquiry forms, observation, Interview, Socio-metric techniques Data gathering devices are termed as tools. Statistical mean, SD, T Test, Independent one sample t-test, Independent two sample t-test, paired samples employed. The study found that secondary school students had average parental encouragement, with both boys and girls equally motivated by their parents. Additionally, both boys and girls had an average achievement motivation level, indicating a diminishing awareness of gender differences among parents. The study explores Parental Encouragement among students in Greater Noida schools, suggesting a longitudinal, longitudinal study for different age groups and a developmental study. The study focuses on Achievement Motivation as a key factor for parental encouragement, specifically among secondary school students in Greater Noida. The scope includes sampling procedures, data collection and analysis techniques, and the development of measuring tools.

Analysis of Factors Affecting the Implementation of Sustainable Building Projects

Abstract: Sustainability concept can be defined as “meeting the needs of the present without compromising the needs of the future” [7]. Conventional buildings approximately consumes more than 30% of energy while utilising around 40% of resources while also simultaneously generating 40% of wastes and 35% of harmful green-house gases [8]. The sustainable building construction approach has the potential to make a significant contribution to sustainable development, especially considering the building industry’s considerable influence. Based on our literature assessment, we discovered that multiple research reveal a general lack of consistency across outcomes in different geographical locations regarding factors impacting the implementation of sustainable building projects. Therefore this study is based on the analysis of factors that impact the implementation of sustainable building projects and the effects of sustainable building projects on various critical factors. For the result of the research analysis, the Reliability analysis which was conducted based on Cronbach's Alpha Coefficient for the factors affecting the implementation of sustainable building projects were found to be 0.76658442 which can conclude that the reliability level of the questionnaires responses was good while based on Relative Importance Index (RII) analysis factors affecting the implementation of sustainable building projects were ranked, with material related factors being the most significant (RII 0.705) among other factors. Additionally, the impact of implementing sustainable building projects on different critical factors was determined, with RII analysis indicating that the most significant impact will occur in terms of economic benefits (RII 0.767). Overall, the study tried fulfilling all the objectives which were stated.

Information and analytical support for economic evaluation and digital indication of innovative development of a developer enterprise in construction

In the conditions of functioning of construction enterprises, the importance of relations between the development of a construction and investment project and its stakeholders (stakeholders), which influence various aspects of project activities in order to make a profit, is growing. Reducing the effectiveness of interaction between construction developers and their partners, such as customers, contractors, design organizations, competitors and public organizations, requires the development of theoretical and methodological foundations for the implementation of a stakeholder-oriented strategy for managing construction enterprises. This strategy includes the organization of financing and implementation of a real estate development project, ta king into account the constraints and with the aim of obtaining commercial benefits. In today's world, construction development is a n area that is constantly being influenced by innovative technologies and strategies. The economic development of a country is determined by the efficiency of construction enterprises, which are an important indicator of the status and trends of the internal and external economic environment. The article explores innovative directions aimed at updating business processes and organizational structures of enterprises in the field of construction development. By analyzing and systematizing modern approaches to management and the use of advanced technologies, the article considers such innovative areas as the introduction of the Building Information Modeling (BIM) system, the use of intelligent management systems, the development of digital platforms, and others. Coverage of these areas will allow to provide an economic assessment and determine the criteria for qualimetric and factor analysis of indicators of innovative development of enterprises in the construction industry and their impact on the efficiency of business processes and competitiveness of enterprises. The economic assessment of innovative development in the development system is an important tool for enterprises seeking to achieve sustainable growth and success. Innovations have become a key success factor in the modern economy, especially in the field of construction and real estate development. Ukraine, as a country with active construction activity, has a great potential for innovative changes in this sector. However, for the effective implementation of innovations in the activities of construction enterprises, a deep economic assessment and economic and managerial analysis are required. This article serves as a source for studying and understanding innovative trends in construction development and considers the possibilities of their implementation to improve the efficiency of management and economic diagnostics and digital administration of directive indicators for assessing the innovative development of a construction developer enterprise.

Sustainable Consumption Behaviour and Common Goods: Education, Culture, Rule of Law, Work, and Solidarity

It is increasingly imperative to foster consumption behaviours that are more environmentally responsible. In order to design impact and sustainable actions that promote a transition to a more sustainable society, it is crucial to understand the underlying motivators that drive this change. Within this framework, this study sought to demonstrate how the comprehensive experience of common goods (solidarity, work, rule of law, culture, and education) is linked to such consumption behaviours. In order to test this hypothesis, a hypothetical-deductive quantitative approach was utilised, employing the second-generation statistical technique of partial least squares structural equation modeling (PLS-SEM) for data analysis. The results revealed that only the common good of Solidarity exhibits a significant relationship with Sustainable Consumption Behaviour. Additionally, Work and Education as common goods demonstrate a relationship of relative importance with this behaviour. Additionally, relationships were found between the common good, showcasing the interconnectedness rooted in cultural norms that strengthen individuals' experiences and, thus, cultivate a sense of community - an essential component for promoting consciousness and modifying behaviours. The novelty of this work is that it was not only focused on governing the commons, but also on how they are distributed and maintained for the long term. The theoretical basis was that natural resources are finite goods to which everyone should have access; however, not everyone enjoys them. That is why a limitation in agency impedes the experience of common goods and, therefore, in sustainable consumption. This study demonstrated that prioritising the welfare of others in addition to oneself, known as altruism, enhances the satisfaction derived from selfless consumption. The implications of this research include the development of instructional interventions incorporating motivational aspects to encourage sustainable consumption practices, ultimately supporting the shift necessary for the well-being of future generations.

Explainable machine learning for predicting stomatal conductance across multiple plant functional types

Stomatal conductance (gs) is a key leaf-level function controlling water, carbon, and energy exchange between vegetation and the surrounding environment. Conventionally, semi-empirical models have been used to model gs, but these models require re-parameterization as ecosystems undergo phenological changes over the growing season. In contrast, machine learning (ML) models offer a potential path to overcome this problem but are less interpretable than process-based models. This study explores ML as an approach to develop flexible and robust models of gs for a range of plant functional types (PFTs), including C3 crops, C3 grasses, shrubs, and tree species across different continents. An explainable machine-learning approach (eXML) was used here to provide novel interpretations and insights into the ML model formulations and relative predictor importance. We contrast the performance of three ML architectures: extreme gradient boosting, random forests, and neural networks. Models were developed and examined using many combinations of environmental and physiological predictors. The results demonstrated that ML models significantly outperform conventional semi-empirical models in predicting gs responses to the environment, while not requiring re-parameterization as is required in the semi-empirical paradigm. Particular focus is placed on models formulated around predictor sets that are: (a) relevant to gs estimation in modern terrestrial biophysical simulation models, and (b) composed of variables describing environmental and physiological drivers that can be remotely sensed non-invasively. “Generalized” models developed using data from all four PFTs demonstrated strong predictive performance using only three predictor variables, capturing 63–80 % of the variability in stomatal conductance across all ML architectures. Four predictor variables resulted in models capturing 79–83 % of gs variability, and models developed using all five predictor variables examined here were able to capture as much as 87 % of gs variability across all PFTs. Uncertainty in gs predictions was quantified using quantile regression. Shapley additive explanations was applied to unravel instance-based positive and negative contributions of environmental and physiological predictors to gs modeling, while illustrating that the models are consistent with the underlying ecophysiology. This work demonstrates the power of ML to introduce a new paradigm in the simulation of highly dynamic ecophysiological processes critical to environmental prediction.