Structural Equation Modelling

"Structural Equation Modelling (SEM) is a relatively recently developed statistical technique based upon factor analysis and multiple regression. This review will cover four of the most widely used (in psychology departments) packages, looking in particular at their suitability for use in a teaching environment, rather than an in depth look at their technical capabilities: LISREL 8.20, EQS 5.6, AMOS 3.6, SEPath. The four programs reviewed were all tested running Windows 95, on a 166 MHz Pentium, with 32 MB RAM." (author's abstract)"'Structural Equation Modelling' (SEM) ist eine vor relativ kurzer Zeit entwickelte statistische Technik, die auf Faktoranalyse und multipler Regression basiert. Dieser Überblick wird die vier (in psychologischen Fachbereichen) am häufigsten benutzen Pakete abdecken und sie besonders hinsichtlich ihrer Eignung für den Gebrauch in einer Lehrumgebung überprüfen, anstatt sich die technischen Fähigkeiten in aller Tiefe anzusehen: LISREL 8.20, EQS 5.6, AMOS 3.6, SEPath. Die vier geprüften Programme wurden alle mit Windows 95 auf einem 166 MHz Pentium mit 32 MB RAM getestet." (Autorenreferat

A Mathematical Model of Sentimental Dynamics Accounting for Marital Dissolution

BACKGROUND: Marital dissolution is ubiquitous in western societies. It poses major scientific and sociological problems both in theoretical and therapeutic terms. Scholars and therapists agree on the existence of a sort of second law of thermodynamics for sentimental relationships. Effort is required to sustain them. Love is not enough. METHODOLOGY/PRINCIPAL FINDINGS: Building on a simple version of the second law we use optimal control theory as a novel approach to model sentimental dynamics. Our analysis is consistent with sociological data. We show that, when both partners have similar emotional attributes, there is an optimal effort policy yielding a durable happy union. This policy is prey to structural destabilization resulting from a combination of two factors: there is an effort gap because the optimal policy always entails discomfort and there is a tendency to lower effort to non-sustaining levels due to the instability of the dynamics. CONCLUSIONS/SIGNIFICANCE: These mathematical facts implied by the model unveil an underlying mechanism that may explain couple disruption in real scenarios. Within this framework the apparent paradox that a union consistently planned to last forever will probably break up is explained as a mechanistic consequence of the second law

Nasal respiration is necessary for ketamine-dependent high frequency network oscillations and behavioral hyperactivity in rats

Changes in oscillatory activity are widely reported after subanesthetic ketamine, however their mechanisms of generation are unclear. Here, we tested the hypothesis that nasal respiration underlies the emergence of high-frequency oscillations (130–180 Hz, HFO) and behavioral activation after ketamine in freely moving rats. We found ketamine 20 mg/kg provoked “fast” theta sniffing in rodents which correlated with increased locomotor activity and HFO power in the OB. Bursts of ketamine-dependent HFO were coupled to “fast” theta frequency sniffing. Theta coupling of HFO bursts were also found in the prefrontal cortex and ventral striatum which, although of smaller amplitude, were coherent with OB activity. Haloperidol 1 mg/kg pretreatment prevented ketamine-dependent increases in fast sniffing and instead HFO coupling to slower basal respiration. Consistent with ketamine-dependent HFO being driven by nasal respiration, unilateral naris blockade led to an ipsilateral reduction in ketamine-dependent HFO power compared to the control side. Bilateral nares blockade reduced ketamine-induced hyperactivity and HFO power and frequency. These findings suggest that nasal airflow entrains ketamine-dependent HFO in diverse brain regions, and that the OB plays an important role in the broadcast of this rhythm

Breed differences in placental development during late gestation between Chinese Meishan and White crossbred gilts in response to intrauterine crowding

The objective of this study was to evaluate placental development during late gestation (day 100) between Chinese Meishan (CM; n = 7) and White crossbred (WC; n = 5) gilts following intrauterine crowding induced by unilaterally hysterectomy-ovariectomy. Gross placental morphology and areolae density as well as histological morphology (i.e., folded bilayer and placental stroma) were analyzed using computer-assisted morphometry for placentas of the smallest and largest fetuses within each litter. There was a breed by fetal size interaction (P \u3c 0.01) for areolae density in which placentas for large CM fetuses had greater areolae density compared to small CM fetuses, but the density of areolae was greater for CM fetuses compared to WC fetuses, irrespective of fetal size. The width of the folded bilayer was greater (P \u3c 0.01) in placentas for WC gilts compared to CM gilts, irrespective of fetal size. Placentas for small fetuses had greater (P \u3c 0.01) folded bilayer width compared to large fetuses, irrespective of breed. The placental stromal width was greater (P \u3c 0.01) in placentas for large fetuses compared to small, irrespective of breed. The difference between stromal width in placentas between divergent-sized littermates, however, was greater (P = 0.05) in WC gilts compared to CM gilts, indicating there was a limited response to intrauterine crowding in CM gilts. These results indicate there is an altered placental development during late gestation in CM compared to WC gilts, thus, there are likely different mechanisms for responding to intrauterine crowding between breeds

Spectroscopic probes of reactive potential energy surfaces

Free radicals play an important role in many important atmospheric and combustion reactions. Their study however, is often hampered due to their high reactivity, and thus short lifetimes, limiting the number densities which can be generated in the laboratory. While a great deal of progess has been made by studying radicals isolated in the gas-phase, much less is known about the interactions between radicals, or the interaction between a radical and another closed shell species. Clearly of interest is what happens at the transition state of a chemical reaction, the point at which bonds are broken and reformed. The areas of the potential energy surface that lead up to the transition state are the entrance and exit channel valleys, which represent weakly bound clusters between two (or more) reagent or product molecules in a chemical reaction. Due to the fact that at long-range the interaction potential is almost always attractive, minima develop near the base of the transition state which may support bound or quasi-bound states. Given that the barriers to a chemical reaction are typically several orders of magnitude larger than the dispersion forces holding these entrance channel complexes together, their importance to reaction dynamics has largely been neglected. However, there is now compelling evidence that these weak forces may actually control the dynamics in some instances due to the corresponding orientational effects. The work detailed in this thesis is focused on applying super_uid helium droplets to the study of these entrance and exit channel complexes. The extremely cold and gentle nature of the helium matrix allows us to stabilize highly reactive complexes and using high-resolution infrared spectroscopy we are able to probe the structure and dynamics of these systems

Charting Galactic Accelerations with Stellar Streams and Machine Learning

We present a data-driven method for reconstructing the galactic acceleration field from phase-space measurements of stellar streams. Our approach is based on a flexible and differentiable fit to the stream in phase-space, enabling a direct estimate of the acceleration vector along the stream. Reconstruction of the local acceleration field can be applied independently to each of several streams, allowing us to sample the acceleration field due to the underlying galactic potential across a range of scales. Our approach is methodologically different from previous works, since a model for the gravitational potential does not need to be adopted beforehand. Instead, our flexible neural-network-based model treats the stream as a collection of orbits with a locally similar mixture of energies, rather than assuming that the stream delineates a single stellar orbit. Accordingly, our approach allows for distinct regions of the stream to have different mean energies, as is the case for real stellar streams. Once the acceleration vector is sampled along the stream, standard analytic models for the galactic potential can then be rapidly constrained. We find our method recovers the correct parameters for a ground-truth triaxial logarithmic halo potential when applied to simulated stellar streams. Alternatively, we demonstrate that a flexible potential can be constrained with a neural network, though standard multipole expansions can also be constrained. Our approach is applicable to simple and complicated gravitational potentials alike, and enables potential reconstruction from a fully data-driven standpoint using measurements of slowly phase-mixing tidal debris.Comment: 32 pages, 10 figures, Submitted for publication. Comments welcome. Code will be made available upon publicatio

Quantum cascade laser-based mid-infrared spectrochemical imaging of tissue and biofluids

Mid-infrared spectroscopic imaging is a rapidly emerging technique in biomedical research and clinical diagnostics that takes advantage of the unique molecular fingerprint of cells, tissue and biofluids to provide a rich biochemical image without the need for staining. Spectroscopic analysis allows for the objective classification of biological material at a molecular level.1 This “label free” molecular imaging technique has been applied to histology, cytology, surgical pathology, microbiology and stem cell research, and can be used to detect subtle changes to the genome, proteome and metabolome.2,3,4 The new wealth of biochemical information made available by this technique has the distinct potential to improve cancer patient outcome through the identification of earlier stages of disease, drug resistance, new disease states and high-risk populations.4 However, despite the maturity of this science, instrumentation that provide increased sample throughput, improved image quality, a small footprint, low maintenance and require minimal spectral expertise are essential for clinical translation