(M-theory-)Killing spinors on symmetric spaces

We show how the theory of invariant principal bundle connections for reductive homogeneous spaces can be applied to determine the holonomy of generalised Killing spinor covariant derivatives of the form $D= \nabla + \Omega$ in a purely algebraic and algorithmic way, where $\Omega : TM \rightarrow \Lambda^*(TM)$ is a left-invariant homomorphism. Specialising this to the case of symmetric M-theory backgrounds (i.e. $(M,g,F)$ with $(M,g)$ a symmetric space and $F$ an invariant closed 4-form), we derive several criteria for such a background to preserve some supersymmetry and consequently find all supersymmetric symmetric M-theory backgrounds.Comment: Updated abstract for clarity. Added missing geometries to section 6. Main result stand

Parameter estimation in pair hidden Markov models

This paper deals with parameter estimation in pair hidden Markov models (pair-HMMs). We first provide a rigorous formalism for these models and discuss possible definitions of likelihoods. The model being biologically motivated, some restrictions with respect to the full parameter space naturally occur. Existence of two different Information divergence rates is established and divergence property (namely positivity at values different from the true one) is shown under additional assumptions. This yields consistency for the parameter in parametrization schemes for which the divergence property holds. Simulations illustrate different cases which are not covered by our results.Comment: corrected typo

Direct imaging of the induced‐fit effect in molecular self‐assembly

Molecular recognition is a crucial driving force for molecular self‐assembly. In many cases molecules arrange in the lowest energy configuration following a lock‐and‐key principle. When molecular flexibility comes into play, the induced‐fit effect may govern the self‐assembly. Here, the self‐assembly of dicyanovinyl‐hexathiophene (DCV6T) molecules, a prototype specie for highly efficient organic solar cells, on Au(111) by using low‐temperature scanning tunneling microscopy and atomic force microscopy is investigated. DCV6T molecules assemble on the surface forming either islands or chains. In the islands the molecules are straight—the lowest energy configuration in gas phase—and expose the dicyano moieties to form hydrogen bonds with neighbor molecules. In contrast, the structure of DCV6T molecules in the chain assemblies deviates significantly from their gas‐phase analogues. The seemingly energetically unfavorable bent geometry is enforced by hydrogen‐bonding intermolecular interactions. Density functional theory calculations of molecular dimers quantitatively demonstrate that the deformation of individual molecules optimizes the intermolecular bonding structure. The intermolecular bonding energy thus drives the chain structure formation, which is an expression of the induced‐fit effect

Static and dynamic measures of human brain connectivity predict complementary aspects of human cognitive performance

In cognitive network neuroscience, the connectivity and community structure of the brain network is related to cognition. Much of this research has focused on two measures of connectivity - modularity and flexibility - which frequently have been examined in isolation. By using resting state fMRI data from 52 young adults, we investigate the relationship between modularity, flexibility and performance on cognitive tasks. We show that flexibility and modularity are highly negatively correlated. However, we also demonstrate that flexibility and modularity make unique contributions to explain task performance, with modularity predicting performance for simple tasks and flexibility predicting performance on complex tasks that require cognitive control and executive functioning. The theory and results presented here allow for stronger links between measures of brain network connectivity and cognitive processes.Comment: 37 pages; 7 figure

The effect of breakfast protein source on postprandial hunger and glucose response in normal weight and overweight young women

Breakfast consumption has been linked to health benefits such as improved weight regulation and glucose control. Studies have shown higher protein breakfasts lead to a greater reduction in hunger compared to breakfasts higher in carbohydrates. However, few studies have examined the impact of higher protein breakfasts from differing protein sources. The objective of this study was to determine if protein quality (animal (AP) versus plant (PP) protein) influences postprandial appetite, food cravings, food intake and glucose response in participants consuming a high protein breakfast (~30% energy from protein). We hypothesized that AP would be more satiating than PP. Normal weight (NW; n = 12) and overweight women (OW; n = 8) ages 18-36 were recruited to participate. All participants completed two visits in a randomized, cross-over design with one week between visits. Blood glucose and appetite were assessed at 0, 15, 30, 45, 60, and 120 min postprandial. Participants kept a 24-h dietary record for the duration of each test day. Participants preferred the appearance of the AP meal compared to the PP (P \u3c 0.05). No difference was found between NW and OW participants or breakfasts for postprandial appetite responses. The AP had a significantly lower (P \u3c 0.05) glucose response at 30 min compared with PP (-11.6%; 127 + 4 versus 112 + 4 mg/dL) and a slower return to baseline. There was no significant difference in daily energy intake between breakfasts. These data suggest protein source influences postprandial glucose response without significantly impacting appetite response and food intake in regular breakfast consumers

Brain Modularity Mediates the Relation between Task Complexity and Performance

Recent work in cognitive neuroscience has focused on analyzing the brain as a network, rather than as a collection of independent regions. Prior studies taking this approach have found that individual differences in the degree of modularity of the brain network relate to performance on cognitive tasks. However, inconsistent results concerning the direction of this relationship have been obtained, with some tasks showing better performance as modularity increases and other tasks showing worse performance. A recent theoretical model (Chen & Deem, 2015) suggests that these inconsistencies may be explained on the grounds that high-modularity networks favor performance on simple tasks whereas low-modularity networks favor performance on more complex tasks. The current study tests these predictions by relating modularity from resting-state fMRI to performance on a set of simple and complex behavioral tasks. Complex and simple tasks were defined on the basis of whether they did or did not draw on executive attention. Consistent with predictions, we found a negative correlation between individuals' modularity and their performance on a composite measure combining scores from the complex tasks but a positive correlation with performance on a composite measure combining scores from the simple tasks. These results and theory presented here provide a framework for linking measures of whole brain organization from network neuroscience to cognitive processing.Comment: 47 pages; 4 figure

The Effect of Whey Protein Supplementation at Breakfast on Tryptophan Levels, Food Intake, and Mood in Postmenopausal Women in a 16-Week Randomized Controlled Trial

Whey protein isolate supplementation has been recognized as having potential for regulating appetite, thereby potentially improving mood and food intake. The objectives of this project were to 1) analyze the effects of high-quality whey protein intake on overall diet and 2) identify and examine a correlation between tryptophan levels and mood regulation. This research was conducted using a randomized experimental design. A total of 13 postmenopausal women (12+ months after last reported menstrual cycle) were recruited and allocated to one of two dietary intervention (DI) groups: 1) control (maintain current lifestyle; CON; n = 6), and 2) whey protein isolate (WPI; 25 g; n = 7). Protein was consumed prior to 10:00 AM daily. Both interventions were followed daily for 16 weeks. All laboratory visits required participants to arrive fasted with complete 3-day dietary logs. Participants completed the Pittsburgh Sleep Quality Index (PSQI) and Profile of Moods Questionnaire. Height, weight, and waist-to-hip ratio were measured. A blood draw was administered to assess sleep and metabolic blood markers. A one-way repeated measures analysis of variance (ANOVA) was used to assess the differences in body mass index (BMI) and Profile of Mood States (POMS). One-way ANOVA was used to calculate the POMS Total Mood Disturbance scores. Clinical biomarker differences were determined through repeated-measures ANOVA (statistically significant: P \u3c 0.05). Prism GraphPad Software v. 9.0 (La Jolla, California) was used for all analyses. Results were inconclusive. We found no correlation between daily whey protein isolate supplementation and tryptophan levels, overall diet, or mood regulation

The Distance to the Coma Cluster from Surface Brightness Fluctuations

We report on the first determination of the distance to the Coma Cluster based on surface brightness fluctuation (SBF) measurements obtained from Hubble Space Telescope WFPC2 observations of the bright E0 galaxy NGC 4881 in the Coma Cluster and ground-based observations of the standard E1 galaxy NGC 3379 in the Leo-I group. Relative distances based on the I-band fluctuation magnitude, I(SBF), are strongly dependent on metallicity and age of the stellar population. However, the radial changes in the stellar populations of the two giant ellipticals, NGC 3379 and NGC 4881, are well described by published Mg_2 gradients, and the ground-based measurements of I(SBF) at several radial points in NGC 3379 are used to calibrate I(SBF) in terms of the Mg_2 index. The distance to NGC 3379, assumed to be identical to the average SBF distance of the Leo-I group, is combined with the new SBF measurements of NGC 4881 to obtain a Coma Cluster distance of 102+-14 Mpc. Combining this distance with the cosmic recession velocity of Coma (7186+-428 km/s), we find the Hubble constant to be H_0 = 71+-11 km/s/Mpc.Comment: 12 pages, LaTex, includes aaspp4.sty and 3 eps figures. To appear in ApJ Letter

The multiple quantum NMR dynamics in systems of equivalent spins with the dipolar ordered initial state

The multiple quantum (MQ) NMR dynamics in the system of equivalent spins with the dipolar ordered initial state is considered. The high symmetry of the MQ Hamiltonian is used in order to develop the analytical and numerical methods for an investigation of the MQ NMR dynamics in the systems consisting of hundreds of spins from "the first principles". We obtain the dependence of the intensities of the MQ NMR coherences on their orders (profiles of the MQ NMR coherences) for the systems of $200 - 600$ spins. It is shown that these profiles may be well approximated by the exponential distribution functions. We also compare the MQ NMR dynamics in the systems of equivalent spins having two different initial states, namely the dipolar ordered state and the thermal equilibrium state in the strong external magnetic field.Comment: 11 pages 4 figure