Object preference by walking fruit flies, Drosophila melanogaster, is mediated by vision and graviperception

Walking fruit flies, Drosophila melanogaster, use visual information to orient towards salient objects in their environment, presumably as a search strategy for finding food, shelter or other resources. Less is known, however, about the role of vision or other sensory modalities such as mechanoreception in the evaluation of objects once they have been reached. To study the role of vision and mechanoreception in exploration behavior, we developed a large arena in which we could track individual fruit flies as they walked through either simple or more topologically complex landscapes. When exploring a simple, flat environment lacking three-dimensional objects, flies used visual cues from the distant background to stabilize their walking trajectories. When exploring an arena containing an array of cones, differing in geometry, flies actively oriented towards, climbed onto, and explored the objects, spending most of their time on the tallest, steepest object. A fly’s behavioral response to the geometry of an object depended upon the intrinsic properties of each object and not a relative assessment to other nearby objects. Furthermore, the preference was not due to a greater attraction towards tall, steep objects, but rather a change in locomotor behavior once a fly reached and explored the surface. Specifically, flies are much more likely to stop walking for long periods when they are perched on tall, steep objects. Both the vision system and the antennal chordotonal organs (Johnston’s organs) provide sufficient information about the geometry of an object to elicit the observed change in locomotor behavior. Only when both these sensory systems were impaired did flies not show the behavioral preference for the tall, steep objects

On the Use of Formative Measurement Specifications in Structural Equation Modeling: A Monte Carlo Simulation Study to Compare Covariance-Based and Partial Least Squares Model Estimation Methodologies

The broader goal of this paper is to provide social researchers with some analytical guidelines when investigating structural equation models (SEM) with predominantly a formative specification. This research is the first to investigate the robustness and precision of parameter estimates of a formative SEM specification. Two distinctive scenarios (normal and non-normal data scenarios) are compared with the aid of a Monte Carlo simulation study for various covariance-based structural equation modeling (CBSEM) estimators and various partial least squares path modeling (PLS-PM) weighting schemes. Thus, this research is also one of the first to compare CBSEM and PLS-PM within the same simulation study. We establish that the maximum likelihood (ML) covariance-based discrepancy function provides accurate and robust parameter estimates for the formative SEM model under investigation when the methodological assumptions are met (e.g., adequate sample size, distributional assumptions, etc.). Under these conditions, ML-CBSEM outperforms PLS-PM. We also demonstrate that the accuracy and robustness of CBSEM decreases considerably when methodological requirements are violated, whereas PLS-PM results remain comparatively robust, e.g. irrespective of the data distribution. These findings are important for researchers and practitioners when having to choose between CBSEM and PLS-PM methodologies to estimate formative SEM in their particular research situation.PLS, path modeling, covariance structure analysis, structural equation modeling, formative measurement, simulation study

On the Use of Formative Measurement Specifications in Structural Equation Modeling: A Monte Carlo Simulation Study to Compare Covariance-Based and Partial Least Squares Model Estimation Methodologies

The broader goal of this paper is to provide social researchers with some analytical guidelines when investigating structural equation models (SEM) with predominantly a formative specification. This research is the first to investigate the robustness and precision of parameter estimates of a formative SEM specification. Two distinctive scenarios (normal and non-normal data scenarios) are compared with the aid of a Monte Carlo simulation study for various covariance-based structural equation modeling (CBSEM) estimators and various partial least squares path modeling (PLS-PM) weighting schemes. Thus, this research is also one of the first to compare CBSEM and PLS-PM within the same simulation study. We establish that the maximum likelihood (ML) covariance-based discrepancy function provides accurate and robust parameter estimates for the formative SEM model under investigation when the methodological assumptions are met (e.g., adequate sample size, distributional assumptions, etc.). Under these conditions, ML-CBSEM outperforms PLS-PM. We also demonstrate that the accuracy and robustness of CBSEM decreases considerably when methodological requirements are violated, whereas PLS-PM results remain comparatively robust, e.g. irrespective of the data distribution. These findings are important for researchers and practitioners when having to choose between CBSEM and PLS-PM methodologies to estimate formative SEM in their particular research situation.marketing ;

Defining properties of neural crest-derived progenitor cells from the apex of human developing tooth

The connective tissue of the human tooth arises from cells that are derived from the cranial neural crest and, thus, are termed as "ectomesenchymal cells." Here, cells being located in a pad-like tissue adjacent to the apex of the developing tooth, which we designated the third molar pad, were separated by the microexplant technique. When outgrowing from the explant, dental neural crest-derived progenitor cells (dNC-PCs) adhered to plastic, proliferated steadily, and displayed a fibroblast-like morphology. At the mRNA level, dNC-PCs expressed neural crest marker genes like Sox9, Snail1, Snail2, Twist1, Msx2, and Dlx6. Cytofluorometric analysis indicated that cells were positive for CD49d (alpha4 integrin), CD56 (NCAM), and PDGFRalpha, while negative for CD31, CD34, CD45, and STRO-1. dNC-PCs could be differentiated into neurogenic, chondrogenic, and osteogenic lineages and were shown to produce bone matrix in athymic mice. These results demonstrate that human third molar pad possesses neural crest-derived cells that represent multipotent stem/progenitor cells. As a rather large amount of dNC-PCs could be obtained from each single third molar, cells may be used to regenerate a wide range of tissues within the craniofacial region of humans

Developmental Dynamics of General and School-Subject-Specific Components of Academic Self-Concept, Academic Interest, and Academic Anxiety

The present study investigated the developmental dynamics of general and subject-specific (i.e., mathematics, French, and German) components of students' academic self-concept, anxiety, and interest. To this end, the authors integrated three lines of research: (a) hierarchical and multidimensional approaches to the conceptualization of each construct, (b) longitudinal analyses of bottom-up and top-down developmental processes across hierarchical levels, and (c) developmental processes across subjects. The data stemmed from two longitudinal large-scale samples (N = 3498 and N = 3863) of students attending Grades 7 and 9 in Luxembourgish schools. Nested-factor models were applied to represent each construct at each grade level. The analyses demonstrated that several characteristics were shared across constructs. All constructs were multidimensional in nature with respect to the different subjects, showed a hierarchical organization with a general component at the apex of the hierarchy, and had a strong separation between the subject-specific components at both grade levels. Further, all constructs showed moderate differential stabilities at both the general (0.42 < r < 0.55) and subject-specific levels (0.45 < r < 0.73). Further, little evidence was found for top-down or bottom-up developmental processes. Rather, general and subject-specific components in Grade 9 proved to be primarily a function of the corresponding components in Grade 7. Finally, change in several subject- specific components could be explained by negative effects across subjects

Solar wind interaction with a comet: evolution, variability, and implication

Once a cometary plasma cloud has been created through ionisation of the cometary neutrals, it presents an obstacle to the solar wind and the magnetic field within it. The acceleration and incorporation of the cometary plasma by the solar wind is a complex process that shapes the cometary plasma environment and is responsible for the creation of boundaries such as a bow shock and diamagnetic cavity boundary. It also gives rise to waves and electric fields which in turn contribute to the acceleration of the plasma. This chapter aims to provide an overview of how the solar wind is modified by the presence of the cometary plasma, and how the cometary plasma is incorporated into the solar wind. We will also discuss models and techniques widely used in the investigation of the plasma environment in the context of recent findings by Rosetta. In particular, this chapter highlights the richness of the processes and regions within this environment and how processes on small scales can shape boundaries on large scales. It has been fifteen years since the last book on Comets was published and since then we have made great advances in the field of cometary research. But many open questions remain which are listed and discussed with particular emphasis on how to advance the field of cometary plasma science through future space missions.Comment: Chapter 17 as part of book: Comets II

Parameter estimation from occupation times—a white noise approach

We derive an equation to compute directly the expected occupation time of the centered Ornstein–Uhlenbeck process. This allows us toidentify the parameters of the Ornstein–Uhlenbeck process for available occupation times via a standard least squares minimization. To test the method,we generate occupation times via Monte–Carlo simulations and recover theparameters with the above mentioned procedure