Experimental Manipulation Research Articles

When urban exploiters cannot cope with urban stressors anymore: Lessons from an experimental manipulation of developmental corticosterone levels in the house sparrow (Passer domesticus).

When urban exploiters cannot cope with urban stressors anymore: Lessons from an experimental manipulation of developmental corticosterone levels in the house sparrow (Passer domesticus).

Academic motivation-achievement cycle and the behavioural pathways: A short-timeframe experiment with manipulated perceived achievement.

The purported reciprocity between motivation and academic achievement in education has largely been supported by correlational data. Our first aim was to determine experimentally whether motivation and achievement are reciprocally related. The second objective was to investigate a potential behavioural mediation pathway between motivation and achievement by measuring the objective effort expended on learning. Finally, we studied the causality of these relations by analysing the dynamics between motivation and achievement (rather than examining them as individual constructs) when perceived achievement was experimentally manipulated. The study employed a short-timeframe experiment in which 309 Dutch undergraduate students (Mage = 19.89, SD = 2.08) learned new English vocabulary. Their motivation, effort, and achievement were measured at multiple time points within one hour. Midway through the experiment, participants received manipulated feedback indicating an achievement decline, which was expected to influence their subsequent motivation, effort, and actual achievement. A random-intercept cross-lagged panel framework was employed to model how one construct influenced another over time. We found a unilateral effect of achievement on motivation (i.e., no reciprocity), which remained stable across the time points. Our experimental manipulation partially supported a causal interpretation of the unilateral achievement→motivation pathway. Additionally, no mediation effect of effort was identified: motivation was not associated with effort, nor was effort linked to achievement. Our findings underscore the importance of further exploration of behavioural mediation pathways, a broad operationalization of motivation, and the application of appropriate modelling strategies to investigate the motivation-achievement reciprocity.

Protocol for the quantitative assessment of social and nonsocial reward-seeking in mice using an automated two choice operant assay.

Protocol for the quantitative assessment of social and nonsocial reward-seeking in mice using an automated two choice operant assay.

Social mobility beliefs lower preferences for genetically-modified foods.

This multi-study investigation explores the influence of Social Mobility Beliefs (SMB) on consumer preference for genetically-modified (GM) foods. Study 1 (N=500) involved a survey, while Studies 2 (N=261) and 3 (N=300) employed experimental manipulations of SMB. Results demonstrate that higher SMB correlate with less favorable preferences for GM foods due to a heightened importance of adhering to social norms, which include those against GM food consumption. Experimental manipulations of SMB confirmed the causal effect of SMB on lower GM food preferences, while alterations in social norms moderate the effect. These findings underscore the significant role of SMB in shaping preferences toward GM foods. Implications extend to policy-making and communication strategies aimed at fostering sustainable food consumption practices. This research contributes novel insights to the understanding of consumer behavior and its implications for sustainable production.

An experimental test of food limitation and trophic interaction hypotheses on demographic parameters in a cyclic population of red-backed voles

Determining the factors that limit and regulate population density is a key problem in population ecology, but often difficult to test in practice. The northern red-backed vole (Clethrionomys rutilis Pallas, 1779 sec. Kryštufek et al. 2020) occurs throughout the boreal forests of the northern hemisphere and the factors influencing their populations are still being elucidated. A large-scale experiment was conducted in the Yukon from 1986-1996 in which food availability, nutrient availability, predation, and interspecific competition were experimentally manipulated. Paradoxically, there was no evidence that these experimental treatments altered vole population density. Here, we apply a capture-mark-recapture modeling framework to test for experimental treatment effects on recruitment and apparent survival. Experimental manipulations resulted in opposing effects on recruitment and apparent survival. These contrasting demographic effects meant that the population growth rate and density remained unaffected by experimental treatments, upholding the original results. We suggest that as some experimental areas became more saturated with voles, this forced higher levels of vole dispersal or attracted mustelid or avian predators, either of which could result in the contrasting effect on apparent survival. Our results highlight that manipulation of environmental factors can alter demographic parameters without substantially affecting overall abundance.

The Interactive Effects of Experimental Warming and Nitrogen Deposition on Plant Community Structure, Biomass, and Soil Chemistry in an Alpine Grassland Ecosystem

The study of global changes impact on natural ecosystems is one of the current priorities of ecological research due to their recent scale and speed. Alpine grasslands are sensitive ecosystems well-suited for investigating how ecosystem is responding to rapid environmental change. With aim to investigate the impact of increased temperature and nitrogen input on the structure and processes in an alpine ecosystem we established in 2009 a field experiment on Mt. Kráľova hoľa in Central Slovakia (https://deims.org/61c12307-2669-46c1-bf0b-94d40cc6b111). Four treatments were used: increased temperature (T), increased nitrogen input (N), combined increased temperature and nitrogen input (NT), and control (C). Each treatment included six replicates (24 plots total) arranged in a blocked design. Nitrogen addition (10 kg N ha⁻¹ yr⁻¹) was applied as NH₄NO₃ solution in five applications during the growing season, while temperature was raised using open-top chambers (OTCs) designed following ITEX standards. The research plots were established in typical, species-poor, two-layer vegetation of the subalpine zone on silicate bedrock within the Juncion trifidi alliance. Experimental manipulation of temperature and nitrogen input in permanent plots in Mt. Kráľova hoľa showed a differentiated effect of individual treatments on the biomass and structure of the plant community of alpine grasslands. The results show that both nitrogen and temperature increase significantly boosted aboveground biomass. Nitrogen addition (N) has been found to benefit mainly graminoids like Avenella flexuosa and Festuca supina, while dwarf shrubs and mosses experienced moderate biomass increases. The NT treatment resulted in further amplification of graminoid biomass, where Luzula alpinopilosa and Juncus trifidus became dominant, leading to suppression of other functional groups: it may inhibit the growth of dwarf scrub and mosses and results in lichens elimination. In contrast, warming alone (T) yielded the highest overall biomass, driven by the growth of dwarf shrubs, mosses, and lichens, even though graminoids responded modestly. These findings align with global patterns, where dominant species and functional groups play a major role in stabilizing ecosystems under changing conditions. The control treatment shows lower overall biomass than any other treatment, indicating that the experimentally increased temperature and/or nitrogen input improves environmental conditions for plant growth. The Redundancy analysis (RDA) of vegetation records shows that the control treatment (C) is closely correlated with the increased temperature treatment (T). The remaining two treatments, i.e. N- and NT treatments are negatively correlated with two former treatments. Species Avenella flexuosa, Festuca supina, Carex bigelowii and Polytrichum alpinum are positively correlated with added nitrogen treatment (N). The positive correlation with combined NT treatment exhibit Luzula alpinopilosa, Juncus trifidus, and Senecio carpaticus, while other species are negativelly correlated: Homogyne alpina, Hieracium alpinum, Cladonia spp. Species Cetraria islandica, Hypnum sp., Soldanella hungarica, Campanula alpina, Oreogeum montanum, Potentilla aurea, and Nardus stricta, are correlated with C- and T-treatments and these species are most affected by N addition. The ecosystem likely did not utilize all of the added nitrogen, with some leaching into the soil solution, as evidenced by increases in both nitrate and ammonium nitrogen in the lysimeter water. The addition of nitrogen decreased soil pH, with acidic soils becoming even more acidic, and decreased the exchange capacity of ions. There was an increase in the conductivity of lysimeter waters, indicating the leaching of ions from soil particles into the soil solution. We confirmed the leaching of basic cations calcium, magnesium, phosphorus, and potassium into the soil solution, as well as increased concentrations of aluminium, manganese, and zinc. The increase in dissolved organic carbon in the treatments with increased temperature suggests higher decomposition. The study highlights how nitrogen addition can alter community structure, including through shading effects caused by fast-growing graminoids. Understanding these interactions is key for the effective management of alpine grasslands, which face growing risks from climate change and human-driven nitrogen deposition.

VPDrought – a novel approach to disentangle atmospheric and soil drought in a natural Scots pine forest

In recent years, an increasing number of studies have reported on forest declines and shifts in species composition in response to changing climatic conditions (Rigling et al. 2012). The intensification of droughts through rising evaporative demand (i.e., vapor pressure deficit or VPD) is a considerable concern because of their disastrous impacts on natural systems (Grossiord et al. 2020; Trotsiuk et al. 2021). For forests, ecosystem services such as wood provisioning and carbon sequestration are severely jeopardized by these changes, leading to significant uncertainties regarding climate regulation. Climate-vegetation models are not only in need of data on atmospheric and soil drought sensing mechanisms but are also critically challenged by insufficient understanding of the processes driving forest vulnerability to climate change. Only by deciphering the single vs. combined VPD and soil moisture effects will we be able to improve global predictions. We apply a scale spanning approach to disentangle the processes affected by atmospheric (i.e., VPD) and soil droughts from the tissue to the tree and the ecosystem level. We set up the first atmospheric humidity and soil moisture manipulative experiment in a mature natural forest. We combine air humidity (and thus VPD) manipulation using a humidification system in the canopy of adult Scots pine trees exposed naturally to high summer VPD and a below canopy through-fall exclusion system (Schaub 2023). The system is installed at the long-term Pfynwald irrigation experiment, which is since 2003 a pivotal WSL long-term experimental monitoring site anticipated to be near its tipping point with respect to climate change (Bose et al. 2022). This experiment helps us understand how the soil moisture responses of trees, shrubs, and microbial communities are altered by atmospheric dryness from the tissue- to the ecosystem-level. This novel manipulative VPD and soil moisture experiment provides an empirical research platform to address the most critical questions in the context of climate impacts in temperate forests. The data will ultimately allow the development of novel predictive methods to assess climate change impacts on forests. Preliminary data will show the effects of altered atmospheric and soil drought on adult Scots pine trees.

Abiotic stress destabilizes the bacterial community of sugar kelp, Saccharina latissima (Phaeophyceae).

As climate change progresses, the intensity and variability of freshwater outflow into the ocean are predicted to increase. The resulting increase in low-salinity events, paired with other abiotic stressors (including increasing temperatures), will be a source of stress for the kelp Saccharina latissima (Saccharina hereafter) and potentially Saccharina-associated bacteria. Bacteria influence host health and can facilitate or hinder host survival and acclimation to stressful abiotic conditions. Therefore, understanding how bacterial communities change under abiotic stress is critical for understanding how abiotic stress will affect kelp physiology. We investigated the effect of abiotic stress on Saccharina and associated bacteria by surveying the bacterial community associated with Saccharina across naturally occurring salinity and temperature gradients, coupled with salinity manipulation experiments. Overall, Saccharina harbored a stable core bacterial community, which decreased in relative abundance under abiotic stress. In the field, both salinity and temperature shaped the bacterial community, with temperature having higher explanatory power most of the time. In the lab, we confirmed that the patterns observed in the field could be replicated by manipulating salinity alone. Decreased relative abundance of core bacteria and increased community dissimilarity in low-salinity in the lab suggest that low-salinity alone can induce a stress response, detectable in the bacterial community of Saccharina.

Lévy Versus Wiener: Assessing the Effects of Model Misspecification on Diffusion Model Parameters

Abstract The Lévy-flight model (LFM; Voss et al., Psychonomic Bulletin & Review, 26, 813–832, 2019) modifies the diffusion decision model (DDM; Ratcliff, Psychological Review, 85(2), 59, 1978) by integrating a heavy-tailed noise distribution into evidence accumulation. Initial studies suggest that the LFM can competitively fit human response time distributions. Consequently, they argued that the LFM may reflect the binary decision process more faithfully. If this is the case, analyzing data with a classical DDM may misrepresent the underlying latent processes. In the present study, we explore the estimation biases that arise when data conforming to an LFM are analyzed with the DDM. We conducted extensive simulations using both basic and full versions of the DDM and the LFM, employing cross-fitting through simulation-based inference with neural networks as implemented in the BayesFlow framework. Given the susceptibility of neural networks to misspecification, we additionally employ a Markov chain Monte Carlo (MCMC) approach as a benchmark for the neural estimates. Our results demonstrate that neural networks and MCMC exhibited nearly identical estimation performance for the basic DDM. Importantly, the basic DDM showed notable overestimation of boundary separation and underestimation of non-decision time when fitted to data generated by the LFM. The full DDM significantly overestimated inter-trial variabilities in starting point and non-decision time, while still overestimating boundary separation. Subsequently, we applied the models to experimental data from a task incorporating speed and accuracy manipulations. Both models reflected the expected effects of the experimental manipulation on boundary separation and non-decision time, additionally, the stability parameter $$\alpha $$ α differed between conditions in the LFM. In conclusion, while our simulations indicate that DDM-based analyses may introduce biases when the true data-generating process aligns more closely with the LFM, applying both models to experimental data led to convergent interpretations.

Persistent increase in understory vegetation following thinning and grazing exclusion in a semiarid pine forest

Abstract Forests function as hotspots for plant functional diversity, hosting numerous nontree plant species in the understory. In tropical, temperate, and Mediterranean forests, density reduction (thinning) treatments have been shown to enhance the abundance of understory plants, including shrubs and herbs. These plant functional types are also known to dominate semiarid steppes and savannas. Yet, it is unknown if thinning in a semiarid forest could have such effects on understory vegetation. Here, we tested the effects of thinning and grazing exclusion on shrub cover and herbaceous biomass in a field manipulation experiment in a semiarid pine forest. Understory development was measured in 21 experimental plots (0.5 ha each) in the dry seasons of the years 2009–22. Fifteen plots were thinned to 300, 200, or 100 trees ha−1 (0%, 33%, and 67% thinning, respectively) and grazing was excluded from half of each plot. Six additional plots were left unthinned at 400–200 trees ha−1, and served as controls. Herbaceous biomass increased significantly with thinning, from ~5 to ~10 kg ha−1 in most years. Shrub cover tended to increase with 67% thinning from ~2% to ~4%, and both shrubs and herbs increased with time. While annual precipitation amount did not directly affect the understory, herbs responded positively to last year precipitation. Ungrazed plots showed higher shrub and herb development than grazed plots, but overall, grazing effect was not significant. Our results show a persistent increase in understory vegetation following thinning in a semiarid pine forest. The gaps formed by thinning created conditions for regrowth of the native nontree vegetation, diversifying the forest structural diversity and its ecosystem services. Yet this change might not sustain under drying conditions.

Supplemental Material for Value-Based Decision-Making in Daily Tobacco Smokers Following Experimental Manipulation of Mood

Supplemental Material for Value-Based Decision-Making in Daily Tobacco Smokers Following Experimental Manipulation of Mood

The Dielectrophoretic Interactions of Curved Particles in a DC Electric Field.

In practical dielectrophoretic cell interaction experiments, cells do not always exhibit circular or rod-like shapes, making the study of dielectrophoretic interactions among irregularly shaped particles of significant importance. We established a mathematical model for curved particles to analyze their mutual dielectrophoretic interactions, incorporating particle deformability by varying their shear modulus, and employed the arbitrary Lagrangian-Eulerian method to describe particle motion and deformation. The results demonstrate that under the influence of a direct current electric field, curved particles undergo rotation, deformation, and mutual attraction due to dielectrophoresis, eventually forming a stable alignment parallel to the applied electric field. Adjusting the electric field strength effectively modulates the interaction intensity and movement velocity between particles. This study elucidates the fundamental principles governing dielectrophoretic interactions among deformable curved particles in DC electric fields, providing theoretical guidance for dielectrophoretic manipulation experiments involving biological cells, metallic particles, and other entities under DC electric fields.

Divergent adaptation of different functional tree seedlings to precipitation changes in a secondary tropical forest

Abstract Seedling adaptation to precipitation change is of great significance for the development and succession of tropical forests under the global climate changes. Here, we conducted a field-based manipulative experiment to assess the performance of different functional seedling (Cassia siamea, N-fixing, and Syzygium hancei, non-N-fixing species) to altered precipitation pattern (control; wetter wet season, WW; delay dry season, DW) in a secondary tropical forest of southern China. The results showed that WW (wetter wet season) and DW (delay dry season) treatments significantly increased leaf mass per area (LMA) of S. hancei, however, precipitation treatment significantly decreased the leaf chlorophyll a concentration of C. siamea, while significantly increased leaf chl b and total chl contents of S. hancei. WW treatment significantly increased the relative grow rate (RGR) of height and total biomass of S. hancei seedling. Additionally, WW and DW treatments significantly increased the leaf soluble sugar concentrations of both seedlings, while DW significantly raised the starch concentration of leaf and coarse root of S. hancei. Moreover, DW treatment significantly enhanced leaf NSC concentrations of both seedlings in this tropical forests. It is surprising that WW treatment unregulated the allocation of soluble sugar, starch, and NSC of leaf and fine root in C. siamea. Thus, the variations of NSC storage and allocation among different tissues in two seedlings may directly reflect the different adapting mechanisms to altered precipitation pattern. Therefore, our results indicated that the S. hancei (non-N-fixing) seedling may adjust the NSC concentrations while the C. siamea (N-fixing) seedling may shift the NSC allocation among different organs adapting to the altered precipitation in the tropical forest.

Coinciding spring and autumn frosts have a limited impact on carbon fluxes in a grassland ecosystem

Frosts, increasingly prevalent due to climate warming, can offset the carbon storage benefits of an extended growing season, potentially exacerbating climate warming. However, existing research primarily focus on species, with limited evidence on carbon fluxes at the ecosystem scale. Using a manipulative experiment simulating 7-day frosts in a temperate grassland, we find that ongoing frosts, whether in spring or autumn, have limited effects on gross ecosystem productivity, ecosystem respiration, and net ecosystem productivity during the frost measurement periods. However, frosts profoundly impact net ecosystem productivity over the entire growing season outside the frost measurement periods. Specifically, spring frosts significantly increase net ecosystem productivity, autumn frosts marginal decrease it, and the combined effect of both frosts neutralize net ecosystem productivity. The early-year (2018–2020) impacts of frosts on net ecosystem productivity may be driven by plant eco-physiological changes, whereas the late-year impacts (2021–2023) were attributed to shifts in plant community structure. Our findings suggest that frequent frosts in both seasons may not stimulate ecosystem carbon release in temperate grasslands. Understanding these patterns is crucial for predicting carbon balance and developing effective climate-change mitigation strategies in response to the future warmer climate.

Fungal community and taxa specialization to host and environment interactions in two temperate forests.

The structure and function of plant-associated fungal communities (i.e. mycobiome) is shaped by biotic and abiotic factors, and can impact plant community dynamics. We evaluated the effects of different environmental factors in structuring the communities of seedling-associated fungi in temperate tree species, considering both the Janzen-Connell hypothesis as well as the impacts of climate warming. We tested the hypothesis that fungal host-specialization is observed at both the individual fungus and fungal community levels and is modulated by environmental conditions. The seedling fungal communities were characterized from tree species grown in two forests, under experimental manipulation of light, warming, and distance to and density of conspecifics. Fungal communities were analyzed using generalized joint attribute models. While warming, light, and forest site played a role in structuring seedling fungal communities, host, distance to, and density of conspecifics were stronger contributors. Furthermore, we could identify which fungal taxa responded to which predictors. This work supports the concept of fungal host-specialization at the community level, and points to particular fungal taxa which may play roles in density- and distance-dependent regulation of plant species diversity in the studied forests.

Assessing the Work-Life-Balance among Nurses in Sulu Sanitarium and General Hospital

This research aimed to evaluate the extent of work–life balance experienced by nurses at Sulu Sanitarium and General Hospital. Utilizing a quantitative approach, the study relied on structured data collection and statistical analysis to objectively assess key variables. The methodology incorporated both descriptive and correlational designs descriptive to detail the characteristics of the nursing population without experimental manipulation, and correlational to explore associations between different factors. Data were gathered from nurses working at the hospital located in Barangay San Raymundo, within the Municipality of Jolo, the administrative center of Sulu Province in the Philippines. A total of 100 participants were surveyed, though this number may not fully capture the diversity of the hospital’s entire nursing staff. Results indicated that most respondents were relatively young, primarily female, and in contractual positions with limited tenure. Overall, nurses reported manageable workloads and supportive work environments that facilitated effective time use and work–life integration. Additionally, demographic variables such as age, sex, civil status, employment classification, and years of service showed no significant impact on how work–life balance was perceived. The study further emphasized a strong link between workload perception, time management, and overall balance between professional and personal life.

Macroecological patterns in experimental microbial communities.

Ecology has historically benefited from the characterization of statistical patterns of biodiversity within and across communities, an approach known as macroecology. Within microbial ecology, macroecological approaches have identified universal patterns of diversity and abundance that can be captured by effective models. Experimentation has simultaneously played a crucial role, as the advent of high-replication community time-series has allowed researchers to investigate underlying ecological forces. However, there remains a gap between experiments performed in the laboratory and macroecological patterns documented in natural systems, as we do not know whether these patterns can be recapitulated in the lab and whether experimental manipulations produce macroecological effects. This work aims at bridging the gap between experimental ecology and macroecology. Using high-replication time-series, we demonstrate that microbial macroecological patterns observed in nature exist in a laboratory setting, despite controlled conditions, and can be unified under the Stochastic Logistic Model of growth (SLM). We found that demographic manipulations (e.g., migration) impact observed macroecological patterns. By modifying the SLM to incorporate said manipulations alongside experimental details (e.g., sampling), we obtain predictions that are consistent with macroecological outcomes. By combining high-replication experiments with ecological models, microbial macroecology can be viewed as a predictive discipline.

The Role of Causality in Explainable Artificial Intelligence

ABSTRACTCausality and eXplainable Artificial Intelligence (XAI) have developed as separate fields in computer science, even though the underlying concepts of causation and explanation share common ancient roots. This is further enforced by the lack of review works jointly covering these two fields. In this paper, we investigate the literature to try to understand how and to what extent causality and XAI are intertwined. More precisely, we seek to uncover what kinds of relationships exist between the two concepts and how one can benefit from them, for instance, in building trust in AI systems. As a result, three main perspectives are identified. In the first one, the lack of causality is seen as one of the major limitations of current AI and XAI approaches, and the “optimal” form of explanations is investigated. The second is a pragmatic perspective and considers XAI as a tool to foster scientific exploration for causal inquiry, via the identification of pursue‐worthy experimental manipulations. Finally, the third perspective supports the idea that causality is propaedeutic to XAI in three possible manners: exploiting concepts borrowed from causality to support or improve XAI, utilizing counterfactuals for explainability, and considering accessing a causal model as explaining itself. To complement our analysis, we also provide relevant software solutions used to automate causal tasks. We believe our work provides a unified view of the two fields of causality and XAI by highlighting potential domain bridges and uncovering possible limitations.

Brand posts with memes on social media: perceived humor and consumer engagement

Purpose As memes become an increasingly more common form of communication on social media, brands are beginning to leverage their humorous appeal as a strategy to capture consumer attention. This study aims to examine how brand social media posts that feature memes influence consumers’ perceived humor and impact consumer engagement behavior. Furthermore, this study investigates the potential pitfalls of using memes in more serious, cause-related campaigns. Design/methodology/approach The authors gathered data through a series of six studies, comprised of five experiments and one study using real-world social media data from X (formerly Twitter). The authors tested the hypotheses using both real data and experimental manipulations of memes, measuring perceived humor and engagement metrics. Findings Consumers perceived posts with memes to be more humorous than non-meme posts leading to increased consumer engagement, reflected by the number of likes and shares. However, using memes in cause-related campaigns resulted in a decrease in consumer engagement. Research limitations/implications This study contributes to the authors’ understanding of the role of perceived humor conveyed through memes in consumer online engagement and the limitations of humor in cause-related campaigns. For marketers, meme usage should align with the message tone to maximize the positive impact on consumer engagement. Originality/value This research highlights the dual role of memes in branded social media content, examining both the advantages and potential risks of perceived humor in memes. This study provides valuable insight into how memes influence consumer engagement and identifies conditions where meme use may detract from a brand’s marketing strategy.

Redefining residential mobility: The impact pathways of residential mobility experiences and expectations on subjective well‐being

AbstractResidential mobility is a critical socio‐ecological factor involving substantial changes in both physical and social environments. However, existing research has inconsistently defined and measured residential mobility, creating ambiguity about whether past experiences or future expectations primarily drive its psychological impact. This study addresses this gap by examining both the distinctions and connections between residential mobility experiences and expectations, with the goal of identifying the primary mechanism influencing subjective well‐being. Guided by pragmatic prospection theory and sensitised‐specialisation theory, we conducted two studies. In Study 1, a manipulation experiment revealed that residential mobility expectations had a stronger impact on subjective well‐being than residential mobility experiences. In Study 2, a large‐scale survey demonstrated that residential mobility expectations mediate the relationship between residential mobility experiences and subjective well‐being. Together, these findings highlight the distinct yet interconnected roles of residential mobility experiences and expectations. While residential mobility experiences provide a foundational context, it is the expectations of future mobility that predominantly shape the psychological impact on well‐being. These results underscore residential mobility expectations as the primary mechanism by which residential mobility influences individual outcomes, offering valuable theoretical and practical insights.