Levels Of Structural Complexity Research Articles

Robustness of highly complex radial carpet beams in turbulent atmospheres

In this study, we report observations of propagating radial carpet beams (RCBs) through a turbulent atmosphere at ground level with a 120 m path length. RCBs are a class of nondiffracting, accelerating, self-healing, and self-amplifying beams, and generated in the diffraction of a plane wave from amplitude/phase radial gratings having different spoke numbers. Observations were made at different times of the day. The intensity profile of an RCB becomes complicated when the number of grating spokes used to generate the beam is large, and includes high intensity spots, called main intensity spots (MISs), which are symmetrically placed at the central area around the beam axis and whose number is equal to (twice) the number of spokes of the amplitude (phase) grating used to generate the beam. With the aid of a telescope and a CCD camera, successive frames of the intensity pattern of the RCBs having different levels of structural complexity are recorded at the end of the path. For the data recorded at different times of the day, we calculate the variance of displacements of MISs along the radial direction. We observe that displacements of the MISs increase with increasing mean temperature of the air; on the other hand, as the complexity of the beam intensity pattern increases, the displacements of the MISs decrease. In order to compare the resilience of different RCBs and a well-known structured beam against atmospheric turbulence, we investigate deformation of the intensity profiles of a Laguerre–Gaussian (LG) beam having a topological charge 20 and different RCBs at the end of the path. It is shown that under the same turbulence condition, highly complex RCBs are more resilient to the destructive effects of the atmospheric turbulence. In particular, for the RCBs generated with gratings having 30 spokes and more, the number of MISs of the received intensity patterns is changed by less than 1% even when the turbulence strength is high. But for the LG beam, its intensity ring is clearly broken in different places, which makes it impossible to follow its maximum intensity in the radial direction

Spectral Response and Wavefront Control of a C-Shaped Fractal Cadmium Telluride/Silicon Carbide Metasurface in the THz Bandgap.

We report theoretical investigations on the spectral behavior of two fractal metasurfaces, performed in the 3–6 THz frequency window (5–10 m equivalent wavelength window), under illumination with both linear and circular polarization state fields. Both metasurfaces stem from the same tree-like structure, based on C-shaped elements, made of cadmium telluride (CdTe), and deposited on silicon carbide (SiC) substrates, the main difference between them being the level of structural complexity. The simulated spectral behavior of both structures indicates the tunability of the reflection spectrum by varying the complexity of the tree-like structure.

Exploring the Structural Fractality of Urban Road Networks by Different Representations

Organisms and other living things grow as fractals, helping to maximize space-filling ability and transmit flow efficiently. In recent years, many studies on fractals have been carried out, mostly at a geometric level, although little work has been done on fractal properties at a structural level. In fact, the capacity of geographical objects, especially road networks, is dependent not only on the geometric distribution described by a geometric fractal dimension but also on the level of structural complexity as described by a structural fractal dimension. Past studies on a structural fractal dimension are limited to a single scale and a single representation. Because different representations could lead to different results in fractal analysis, this study aims to examine the structural fractality of urban road networks by different representations. The road networks of the 100 most populous cities in the United States were examined by three commonly used topological representations. The following results were established: Despite differences in representation, structural fractality always exists; structural fractal dimensions in stroke-based representation are obviously larger than those in segment-based representation; and scale has no obvious effects on structural fractality. These results could deepen our understanding of how urban road networks evolve.

Damage detection in large composite stiffened panels based on a novel SHM building block philosophy

This paper proposes a structural health monitoring (SHM) building block (BB) approach for guided wave based structural health monitoring (GWSHM) of large composite stiffened panel subjected to varying temperature conditions. The proposed approach follows a similar philosophy to industrial substantiation of composite structures through BB by conducting SHM analysis and associated tests at different levels of structural complexity, beginning with small coupon specimens and progressing through structural elements and details (mono-stringer) and finally sub-components (large stiffened composited panel). Each level builds on the knowledge gained at previous, less complex levels. The detection of multiple barely visible impact damage (BVID) in the large panels is achieved by outlier analysis using a reference pristine database gathered from simple coupons and mono-stringer panels under a wide range of temperature variation. This approach enables the data utilisation from lower-level structure in the proposed BB test scheme to higher-level structures and hence reduce the number of tests required for large and complex structures. The detected damage is then localised by a proposed two-step multi-damage localisation method, which first confirms the presence of the damage and narrows down the damaged section then provides an enhanced damage imaging for precise location estimation. Damage detection with a true positive rate of 0.909 and a false positive rate of 0.111 as well as accurate multiple damage localisation are achieved in the flat fuselage panels for a temperature range of 25 °C–50 °C.

Comparison of induced neurons reveals slower structural and functional maturation in humans than in apes

We generated induced excitatory neurons (iNeurons, iNs) from chimpanzee, bonobo, and human stem cells by expressing the transcription factor neurogenin-2 (NGN2). Single-cell RNA sequencing showed that genes involved in dendrite and synapse development are expressed earlier during iNs maturation in the chimpanzee and bonobo than the human cells. In accordance, during the first 2 weeks of differentiation, chimpanzee and bonobo iNs showed repetitive action potentials and more spontaneous excitatory activity than human iNs, and extended neurites of higher total length. However, the axons of human iNs were slightly longer at 5 weeks of differentiation. The timing of the establishment of neuronal polarity did not differ between the species. Chimpanzee, bonobo, and human neurites eventually reached the same level of structural complexity. Thus, human iNs develop slower than chimpanzee and bonobo iNs, and this difference in timing likely depends on functions downstream of NGN2.

Environmental complexity during early life shapes average behavior in adulthood

AbstractPersonality has been identified in a range of animal taxa during the last few decades, with important ecological and evolutionary implications. Investigating the effects of environmental factors during early life can provide important insights into the ontogeny of animal personality. We reared newborn mosquitofish, Gambusia affinis, in tanks of different structural complexities, and measured their behavioral traits (i.e., shyness, exploration, and sociability) when they reached sexual maturity. Univariate linear mixed-effects models were fitted to test the effects of environmental complexity and sex on population-average behavior, whereas multivariate models were fitted to quantify behavioral repeatability (i.e., personality) and among-individual correlations (i.e., behavioral syndromes). On average, females were shyer and more social than males, and the fish reared in complex environments were shyer, less explorative, and more social than those reared in open environments. Among-individual differences were consistently large across trials for all behaviors, indicating that personality variation was present in mosquitofish of both sexes reared in different environments. Repeatability did not differ among behaviors, and there were no differences in repeatability in any behavior between sexes or among environments. A negative correlation between shyness and exploration was found in mosquitofish from all treatments at both phenotypic and among-individual levels, with the latter indicating a strong shyness–exploration behavioral syndrome. Our study provides robust evidence that average levels of personality might vary when mosquitofish are raised in different levels of structural complexity during early life.

The application and optimization of super-resolution reconstruction for isotropic out-of-plane MRI to study the musculoskeletal system

ABSTRACT In this paper we optimised and adapted a post-processing super-resolution reconstruction (SRR) algorithm for its use in the semi-automated isotropic reconstruction of non-isotropically acquired musculoskeletal magnetic resonance image (MRI) data. The ability to produce isotropic MRI data facilitated the (1) enhanced out-of-plane image visualisation; (2) semi-automated image registration with CT data of the same anatomical site; and (3) improved image segmentation. The effectiveness of the SRR algorithm was demonstrated on several musculoskeletal scans including ex vivo tibial plateaus, in vivo knees and hands with varying levels of structural complexity and potential for motion artefact.

Combined MD/QTAIM techniques to evaluate ligand-receptor interactions. Scope and limitations.

In medicinal chemistry, it is extremely important to evaluate, as accurately as possible, the molecular interactions involved in the formation of different ligand-receptor (L-R) complexes. Evaluating the different molecular interactions by quantum mechanics calculations is not a simple task, since formation of an L-R complex is a dynamic process. In this case, the use of combined techniques of molecular dynamics (MD) and quantum calculations is one the best possible approaches. In this work we report a comparative study using combined MD and QTAIM (Quantum Theory of Atoms In Molecules) calculations for five biological systems with different levels of structural complexity. We have studied Acetylcholinesterase (AChE), D2 Dopamine Receptor (D2DR), beta Secretase (BACE1), Dihydrofolate Reductase (DHFR) and Sphingosine Kinase 1 (SphK1). In these molecular targets, we have analyzed different ligands with diverse structural characteristics. The inhibitory activities of most of them have been previously measured in our laboratory. Our results indicate that QTAIM calculations can be extremely useful for in silico studies. It is possible to obtain very accurate information about the strength of the molecular interactions that stabilize the formation of the different L-R complexes. Better correlations can be obtained between theoretical and experimental data by using QTAIM calculations, allowing us to discriminate among ligands with similar affinities. QTAIM analysis gives fairly accurate information for weak interactions which are not well described by MD simulations. QTAIM study also allowed us to evaluate and determine which parts of the ligand need to be modified in order to increase its interactions with the molecular target. In this study we have discussed the importance of combined MD/QTAIM calculations for this type of simulations, showing their scopes and limitations.

Tolerant and intolerant macaques show different levels of structural complexity in their vocal communication.

We tested the social complexity hypothesis which posits that animals living in complex social environments should use complex communication systems. We focused on two components of vocal complexity: diversity (number of categories of calls) and flexibility (degree of gradation between categories of calls). We compared the acoustic structure of vocal signals in groups of macaques belonging to four species with varying levels of uncertainty (i.e. complexity) in social tolerance (the higher the degree of tolerance, the higher the degree of uncertainty): two intolerant species, Japanese and rhesus macaques, and two tolerant species, Tonkean and crested macaques. We recorded the vocalizations emitted by adult females in affiliative, agonistic and neutral contexts. We analysed several acoustic variables: call duration, entropy, time and frequency energy quantiles. The results showed that tolerant macaques displayed higher levels of vocal diversity and flexibility than intolerant macaques in situations with a greater number of options and consequences, i.e. in agonistic and affiliative contexts. We found no significant differences between tolerant and intolerant macaques in the neutral context where individuals are not directly involved in social interaction. This shows that species experiencing more uncertain social interactions displayed greater vocal diversity and flexibility, which supports the social complexity hypothesis.

Adaptive rewiring evolves brain-like structure in weighted networks

Activity-dependent plasticity refers to a range of mechanisms for adaptively reshaping neuronal connections. We model their common principle in terms of adaptive rewiring of network connectivity, while representing neural activity by diffusion on the network: Where diffusion is intensive, shortcut connections are established, while underused connections are pruned. In binary networks, this process is known to steer initially random networks robustly to high levels of structural complexity, reflecting the global characteristics of brain anatomy: modular or centralized small world topologies. We investigate whether this result extends to more realistic, weighted networks. Both normally- and lognormally-distributed weighted networks evolve either modular or centralized topologies. Which of these prevails depends on a single control parameter, representing global homeostatic or normalizing regulation mechanisms. Intermediate control parameter values exhibit the greatest levels of network complexity, incorporating both modular and centralized tendencies. The simulation results allow us to propose diffusion based adaptive rewiring as a parsimonious model for activity-dependent reshaping of brain connectivity structure.

Provider Networks in the Neonatal Intensive Care Unit Associate with Length of Stay.

We strive to understand care coordination structures of multidisciplinary teams and to evaluate their effect on post-surgical length of stay (PSLOS) in the Neonatal Intensive Care Unit (NICU). Electronic health record (EHR) data were extracted for 18 neonates, who underwent gastrostomy tube placement surgery at the Vanderbilt University Medical Center NICU. Based on providers' interactions with the EHR (e.g. viewing, documenting, ordering), provider-provider relations were learned and used to build patient-specific provider networks representing the care coordination structure. We quantified the networks using standard network analysis metrics (e.g., in-degree, out-degree, betweenness centrality, and closeness centrality). Coordination structure effectiveness was measured as the association between the network metrics and PSLOS, as modeled by a proportional-odds, logistical regression model. The 18 provider networks exhibited various team compositions and various levels of structural complexity. Providers, whose patients had lower PSLOS, tended to disperse patient-related information to more colleagues within their network than those, who treated higher PSLOS patients (P = 0.0294). In the NICU, improved dissemination of information may be linked to reduced PSLOS. EHR data provides an efficient, accessible, and resource-friendly way to study care coordination using network analysis tools. This novel methodology offers an objective way to identify key performance and safety indicators of care coordination and to study dissemination of patient-related information within care provider networks and its effect on care. Findings should guide improvements in the EHR system design to facilitate effective clinical communications among providers.

Predicting ecosystem components in the Gulf of Mexico and their responses to climate variability with a dynamic Bayesian network model.

The Gulf of Mexico is an ecologically and economically important marine ecosystem that is affected by a variety of natural and anthropogenic pressures. These complex and interacting pressures, together with the dynamic environment of the Gulf, present challenges for the effective management of its resources. The recent adoption of Bayesian networks to ecology allows for the discovery and quantification of complex interactions from data after making only a few assumptions about observations of the system. In this study, we apply Bayesian network models, with different levels of structural complexity and a varying number of hidden variables to account for uncertainty when modeling ecosystem dynamics. From these models, we predict focal ecosystem components within the Gulf of Mexico. The predictive ability of the models varied with their structure. The model that performed best was parameterized through data-driven learning techniques and accounted for multiple ecosystem components’ associations and their interactions with human and natural pressures over time. Then, we altered sea surface temperature in the best performing model to explore the response of different ecosystem components to increased temperature. The magnitude and even direction of predicted responses varied by ecosystem components due to heterogeneity in driving factors and their spatial overlap. Our findings suggest that due to varying components’ sensitivity to drivers, changes in temperature will potentially lead to trade-offs in terms of population productivity. We were able to discover meaningful interactions between ecosystem components and their environment and show how sensitive these relationships are to climate perturbations, which increases our understanding of the potential future response of the system to increasing temperature. Our findings demonstrate that accounting for additional sources of variation, by incorporating multiple interactions and pressures in the model layout, has the potential for gaining deeper insights into the structure and dynamics of ecosystems.

Ca12 [Mn19 N23 ] and Ca133 [Mn216 N260 ]: Structural Complexity by 2D Intergrowth.

Two new calcium nitridomanganates, Ca12 [Mn19 N23 ] (P3, a=11.81341(3) Å, c=5.58975(2) Å, Z=1) and Ca133 [Mn216 N260 ] (P3‾ , a=39.477(1) Å, c=5.5974(2) Å, Z=1), were obtained by a gas-solid reaction of Ca3 N2 and Mn with N2 at 1273 K and 1223 K, respectively. The crystal structure of Ca12 [Mn19 N23 ] was determined from high-resolution X-ray synchrotron powder diffraction data, whereas single-crystal X-ray diffraction was employed to establish the crystal structure of the Ca133 [Mn216 N260 ] phase, which classifies as a complex metallic alloy (CMA). Both crystal structures have 2D nitridomanganate layers containing similar building blocks but of different levels of structural complexity. Bonding analysis as well as magnetic susceptibility and electron spin resonance measurements revealed that only a fraction of the Mn atoms in both structures carries a localized magnetic moment, while for most Mn species the magnetism is quenched as a result of metal-metal bond formation.

Ca12[Mn19N23] and Ca133[Mn216N260]: Structural Complexity by 2D Intergrowth

AbstractTwo new calcium nitridomanganates, Ca12[Mn19N23] (P3, a=11.81341(3) Å, c=5.58975(2) Å, Z=1) and Ca133[Mn216N260] ( , a=39.477(1) Å, c=5.5974(2) Å, Z=1), were obtained by a gas–solid reaction of Ca3N2 and Mn with N2 at 1273 K and 1223 K, respectively. The crystal structure of Ca12[Mn19N23] was determined from high‐resolution X‐ray synchrotron powder diffraction data, whereas single‐crystal X‐ray diffraction was employed to establish the crystal structure of the Ca133[Mn216N260] phase, which classifies as a complex metallic alloy (CMA). Both crystal structures have 2D nitridomanganate layers containing similar building blocks but of different levels of structural complexity. Bonding analysis as well as magnetic susceptibility and electron spin resonance measurements revealed that only a fraction of the Mn atoms in both structures carries a localized magnetic moment, while for most Mn species the magnetism is quenched as a result of metal–metal bond formation.

A structural rank reduction operator for removing artifacts in least-squares reverse time migration

Least-square reverse time migration (LSRTM) has been widely accepted because of its exceptional performance in mitigating migration artifacts and preserving the reflection amplitude. Due to the ill-posedness of the inverse problem, regularization methods or constraints must be applied to the reflectivity model. In this paper, we propose a novel iterative LSRTM framework that is regularized by a lowrank constraint. The lowrank constraint is applied along the geological structure of the subsurface reflectivity image and thus can also be called structural lowrank constraint. The lowrank constraint is applied by iteratively applying a rank reduction operator that is based on the lowrank approximation theory. The rank reduction operator applied along the structure direction can effectively remove those artifacts caused from sparse shot/receiver sampling or other circumstances. Compared with the traditionally used smoothness based constraint, the lowrank constraint is more capable of removing noise while preserving edge details. Since the constraint is applied in post-stack seismic image, the extra computational cost caused by the singular value decomposition (SVD) of the rank reduction operator is negligible compared with the computational cost of the migration operator. Numerical examples with different levels of structural complexity are used to demonstrate the effectiveness and validity of the proposed algorithm.

The effects of habitat complexity on periphyton biomass accumulation and taxonomic structure during colonization

Habitat complexity plays a significant role in biological communities, but its effect on periphyton is still poorly understood. For example, the response of periphyton to changes in habitat relative to colonization time remains to be elucidated. Our hypothesis was that habitat complexity positively affects periphyton biomass, algal diversity, and change in species composition, while the response of periphyton to habitat complexity depends on colonization time. To test this hypothesis, we evaluated periphyton on artificial substrate distinct levels of habitat complexity at the intermediate (15 days) and advanced phases of colonization (30 days). Biomass, species richness, and diversity increased with level of structural complexity, but these attributes present significant difference only at the 15th day of colonization. In contrast, species composition changed with the increase of fractal dimension at both colonization times. Algal community response to distinct levels of structural habitat complexity was most significant at the 15th day of colonization. Our results showed that biomass, adaptive strategies groups, and taxonomic structure in periphyton were affected by habitat complexity, but that response was dependent on colonization time. Therefore, we concluded that colonization time is a factor that should be considered in assessing the effects of habitat complexity on periphyton.

Structural complexity and fish body size interactively affect habitat optimality.

Predator-prey interactions are strongly influenced by habitat structure, particularly in coastal marine habitats such as seagrasses in which structural complexity (SC) may vary over small spatial scales. For seagrass mesopredators such as juvenile fishes, optimality models predict that fitness will be maximized at levels of SC that enhance foraging but minimize predation risk, both of which are functions of body size. We tested the hypothesis that in eelgrass (Zostera marina) habitat, optimal SC for juvenile giant kelpfish (Heterostichus rostratus), an abundant eelgrass mesopredator in southern California, changes through ontogeny. To do this, we quantified eelgrass SC effects on habitat associations, relative predation risk, and foraging efficiency for three size classes of juvenile giant kelpfish. We found that habitat selection differed with fish size: small fish selected dense eelgrass, whereas larger fish selected sparse eelgrass. Small kelpfish experienced the lowest relative predation risk in dense eelgrass but also had higher foraging efficiency in dense eelgrass, suggesting that dense eelgrass is selected by these fish because it minimizes risk and maximizes potential for growth. Surprisingly, larger kelpfish did not experience lower predation risk than small kelpfish. However, larger kelpfish experienced higher foraging efficiency in sparse eelgrass vs. dense eelgrass, suggesting that they select sparse eelgrass to maximize foraging efficiency. Our study highlights that trade-offs between predation risk and foraging can occur within a single habitat type, that studies should consider how habitat value changes through ontogeny, and that seagrass habitat value may be maximal when within-patch variability in SC is high.

A Review of Three Major Sociological Theories and an Islamic Perspective

Social theory to a great extent is older than sociology itself. It can be found in the Old Testament, Hindu's Vedas and Chinese literature. Even social theories of modern social science orientation can be traced back 2400 years to ancient Athens. They were used as a means of visualising the social universe in order to obtain practical knowledge about it. (Caplow 1971: 156). However, modern sociology, as a science of society, emerged only after the extension of scientific method into the social world. This happened in early nineteenth century when systematic efforts were made to evolve a science of society as a distinct perspective from philosophy, history, politics, economy and other social sciences. (Cotgrove 1967:32). However, efforts at establishing a separate identity for the science of society involved formulation of various theories about the nature of social system and the methods of their study. Sociologists in pursue of this, formulated different theories from which three are the most popular. Therefore, this paper deals with the three major sociological theories namely, Structure Functionalism, Symbolic Interactionism and Conflict Theory.Structural FunctionalismCharon (1992) views Structural Functionalism as a sociological theory that depicts society as a social system consisting of various structures, organizations and institutions, influencing each other and affecting the whole system. It focuses on the function of the institutions and their contribution to the continuity of the social system.Although some historians trace functionalism to Montestquieu (Cohen 1968:34 ) its roots can be traced to works of Herbert Spencer (1820-1903) an English sociologist, Wilfredo Pareto, (1848-1923) an Italian sociologist and Emile Durkheim (1855-1917) French sociologist (Joel 1991). Furthermore, some insights to functionalism can be drawn from August Comte's (1798-1857) concept of social static, a study of the coexistence of social phenomenon, based on the assumption of the interrelatedness of institutions, belief and morals of the society. He proposed this as one part of sociological inquiry in which the existence of each item in the whole is explained by the law that prescribe its manner of coexistence with other (Cohen 1968).Herbert Spencer suggested a structural analysis of society by drawing functional analogy between society and an organism. According to him, society like organism displays different levels of structural complexity, which can be measured in terms of different component elements of its structures. Thus, a structure composed of identical elements would more or less be self-sufficient. But composition of the structure from unlike elements needs a greater degree of interdependence. Therefore, the degree of the integration of the whole depends on the extent of the difference that exists between the individual structural elements. In other words, the existence of more difference between the structural elements brings about greater integration in the whole and enables it to survive by reducing its internal disharmony. Thus, Spencer contributed something new to functionalism by analysing the different levels of complexity of society in terms of structural component and their contribution to functioning of the whole.Structural Functionalism, as Percy observed, is more indebted to Emile Durkheim than Spencer. Even though, like Spencer, he was influenced by biological thinking in his early stage of writings, yet he was able to identify some of the loopholes in its explanation (Cohen 1968: 35-36). By doing so he made the theory more attractive and useful to social anthropologists as well as sociologists in general.Durkheim analysed division of labour, in terms of its cause and function hence, holding integration or reintegration of society as its function and moral density as its cause. He attributed the breakdown of the constraints built into simple society to pressure caused by growth of population and the broad scope of interaction. …

Effect of tagatose on growth dynamics of Salmonella Typhimurium and Listeria monocytogenes in media with different levels of structural complexity and in UHT skimmed milk

Tagatose is a novel low-calorie sweetener which addition changes food product properties, e.g., aw, and formula, that may influence food-microbial growth dynamics in both liquid and solid products. The aim of this work was to study growth dynamics of Salmonella Typhimurium and Listeria monocytogenes in liquid and solid media enriched with tagatose (1.5, 4.5 and 7.5% (w/v)), at 4, 8 and 20 °C. More specifically, liquid media were chemically defined minimal medium, general medium and UHT skimmed milk; gelatine and a gelatine-dextran mixture were the gelling agents used, leading respectively a homogeneous and heterogeneous solid system. At regular intervals, cell concentration was determined and the Baranyi and Roberts (1994) model was fitted for growth parameter estimation. Results show a reduced and even no growth of S. Typhimurium with increasing tagatose concentrations, especially at low temperatures and when increasing media complexity. The behaviour of L. monocytogenes is not affected by tagatose, except in liquid at 4 °C, where tagatose facilitates the growth in general culture media. Varying responses of the studied bacteria to changes in media formulation should be considered for future product design.

Mesopredator foraging success in eelgrass (Zostera marina L.): Relative effects of epiphytes, shoot density, and prey abundance

In seagrass habitats, structural complexity influences predator foraging success and prey survival by moderating encounter rates and behaviors of predators and prey. Studies of the effects of structural complexity on predator–prey interactions typically vary seagrass shoot density, biomass, or architecture. Filamentous epiphytic algae commonly grow on seagrass blades and add structure to seagrasses, but the effect of epiphytes on the outcome of predator–prey interactions has rarely been explored. This study determined the relative effects of simulated seagrass epiphytes, eelgrass (Zostera marina) shoot density, and prey density on the foraging behaviors of a common predator, the juvenile giant kelpfish Heterostichus rostratus (Girard, 1854) and on escape responses of their prey, grass shrimp Hippolyte californiensis (Holmes, 1895). Juvenile giant kelpfish hunted for grass shrimp in a laboratory experiment in which two levels of grass shrimp density were crossed with three levels of structural complexity (low density artificial eelgrass, low density artificial eelgrass with artificial epiphytes, and high density artificial eelgrass). Increased structural complexity had variable effects on juvenile kelpfish activity levels, but enhanced their success at catching prey after detection, resulting in no net effect of structural complexity on the total number of prey captured. Grass shrimp made fewer escape attempts in high vs. low structural complexity, which may have enhanced kelpfish foraging success because kelpfish rarely pursued fleeing prey. Prey density did not influence kelpfish behaviors or the total amount of prey they consumed. These results suggest that it is important to consider how different forms of habitat complexity affect the mechanisms by which predators hunt for prey in structured marine habitats.