Closed classes of functions, generalized constraints and clusters

Classes of functions of several variables on arbitrary non-empty domains that are closed under permutation of variables and addition of dummy variables are characterized in terms of generalized constraints, and hereby Hellerstein's Galois theory of functions and generalized constraints is extended to infinite domains. Furthermore, classes of operations on arbitrary non-empty domains that are closed under permutation of variables, addition of dummy variables and composition are characterized in terms of clusters, and a Galois connection is established between operations and clusters.Comment: 21 page

Scanning Tunneling Spectroscopic Studies of the Effects of Dielectrics and Metallic Substrates on the Local Electronic Characteristics of Graphene

Atomically resolved imaging and spectroscopic characteristics of graphene grown by chemical vapor deposition (CVD) on copper foils are investigated and compared with those of mechanical exfoliated graphene on SiO_2. For exfoliated graphene, the local spectral deviations from ideal behavior may be attributed to strain induced by the SiO_2 substrate. For CVD grown graphene, the lattice structure appears strongly distorted by the underlying copper, with regions in direct contact with copper showing nearly square lattices whereas suspended regions from thermal relaxation exhibiting nearly honeycomb or hexagonal lattice structures. The electronic density of states (DOS) correlates closely with the atomic arrangements of carbon, showing excess zero-bias tunneling conductance and nearly energy-independent DOS for strongly distorted graphene, in contrast to the linearly dispersive DOS for suspended graphene. These results suggest that graphene can interact strongly with both metallic and dielectric materials in close proximity, leading to non-negligible modifications to the electronic properties

Evidence for Strain-Induced Local Conductance Modulations in Single-Layer Graphene on SiO_2

Graphene has emerged as an electronic material that is promising for device applications and for studying two-dimensional electron gases with relativistic dispersion near two Dirac points. Nonetheless, deviations from Dirac-like spectroscopy have been widely reported with varying interpretations. Here we show evidence for strain-induced spatial modulations in the local conductance of single-layer graphene on SiO_2 substrates from scanning tunneling microscopic (STM) studies. We find that strained graphene exhibits parabolic, U-shaped conductance vs bias voltage spectra rather than the V-shaped spectra expected for Dirac fermions, whereas V-shaped spectra are recovered in regions of relaxed graphene. Strain maps derived from the STM studies further reveal direct correlation with the local tunneling conductance. These results are attributed to a strain-induced frequency increase in the out-of-plane phonon mode that mediates the low-energy inelastic charge tunneling into graphene

Regularized covariance estimation for weighted maximum likelihood policy search methods

Many episode-based (or direct) policy search algorithms, maintain a multivariate Gaussian distribution as search distribution over the parameter space of some objective function. One class of algorithms, such as episodic REPS, PoWER or PI2 uses, a weighted maximum likelihood estimate (WMLE) to update the mean and covariance matrix of this distribution in each iteration. However, due to high dimensionality of covariance matrices and limited number of samples, the WMLE is an unreliable estimator. The use of WMLE leads to over-fitted covariance estimates, and, hence the variance/entropy of the search distribution decreases too quickly, which may cause premature convergence. In order to alleviate this problem, the estimated covariance matrix can be regularized in different ways, for example by using a convex combination of the diagonal covariance estimate and the sample covariance estimate. In this paper, we propose a new covariance matrix regularization technique for policy search methods that uses the convex combination of the sample covariance matrix and the old covariance matrix used in last iteration. The combination weighting is determined by specifying the desired entropy of the new search distribution. With this mechanism, the entropy of the search distribution can be gradually decreased without damage from the maximum likelihood estimate

Ultralow threshold graded-index separate-confinement heterostructure single quantum well (Al,Ga)As lasers

Broad area graded‐index separate‐confinement heterostructure single quantum well lasers grown by molecular‐beam epitaxy (MBE) with threshold current density as low as 93 A/cm^2 (520 μm long) have been fabricated. Buried lasers formed from similarly structured MBE material with liquid phase epitaxy regrowth had threshold currents at submilliampere levels when high reflectivity coatings were applied to the end facets. A cw threshold current of 0.55 mA was obtained for a laser with facet reflectivities of ∼80%, a cavity length of 120 μm, and an active region stripe width of 1 μm. These devices driven directly with logic level signals have switch‐on delays <50 ps without any current prebias. Such lasers permit fully on–off switching while at the same time obviating the need for bias monitoring and feedback control

College Student Dating Partner Drinking Profiles: Differences in Relationship Functioning and Relationship-Specific Alcohol Expectancies

Background: Although the majority of research on partner drinking styles has examined married couples, dating partners may influence one another\u27s problem behaviors including alcohol use. Objectives: This study identified patterns of at-risk alcohol use in college women and their dating partners using a person-centered statistical approach (i.e., latent profile analysis). Methods: Participants were 286 college student women in dating relationships. They completed questionnaires regarding their own and their partners\u27 drinking, alcohol use severity, intimate partner violence (IPV), relationship satisfaction, and relationship-specific alcohol expectancies. Data were collected in 2012 through 2013. Results: Results revealed three distinct, latent classes based on both partners\u27 alcohol outcomes. The Low-Risk group (58%) consisted of non-heavy drinking partners. In the High-Risk - Higher Men class (27%), men drank more than women; however, both men and women were high-risk drinkers. The High-Risk - Higher Women group (15%) consisted of high-risk drinking partners but women consumed more alcohol than men. Both high-risk couple groups were more dissatisfied in their relationships and experienced more IPV, but held stronger beliefs about how alcohol influenced their relationship. Conclusions/Importance: Findings indicate that there are several distinct classes of dating couples that differ in relationship problems and beliefs about alcohol\u27s impact on their relationship. Riskier couples differ in behaviors and alcohol-related beliefs from low-risk couples. These findings may inform the development of more efficacious alcohol interventions tailored toward high-risk drinking dating couples

Effective Theories for Circuits and Automata

Abstracting an effective theory from a complicated process is central to the study of complexity. Even when the underlying mechanisms are understood, or at least measurable, the presence of dissipation and irreversibility in biological, computational and social systems makes the problem harder. Here we demonstrate the construction of effective theories in the presence of both irreversibility and noise, in a dynamical model with underlying feedback. We use the Krohn-Rhodes theorem to show how the composition of underlying mechanisms can lead to innovations in the emergent effective theory. We show how dissipation and irreversibility fundamentally limit the lifetimes of these emergent structures, even though, on short timescales, the group properties may be enriched compared to their noiseless counterparts.Comment: 11 pages, 9 figure

Testing a Model of Caffeinated Alcohol-Specific Expectancies

Introduction- The present study sought to further understand the association between caffeinated alcoholic beverage (CAB) use and alcohol-related risks. In particular, we focused on the role of two identified expectancies specific to CAB use: intoxication enhancement and avoidance of negative consequences. Although outcome expectancies are consistent predictors of substance use, limited research has examined expectancies related to CAB use and their association with alcohol-related behaviors, such as protecting themselves from alcohol-related harms. Consequently, the present study examined CAB-specific expectancies and protective behavioral strategies (PBS) as mediators of CAB use and negative consequences. Methods- Participants were 322 (219 women) college drinkers who completed self-report measures of typical CAB and alcohol use, CAB-specific expectancies, PBS use, and alcohol-related harms. Results- Structural equation modeling revealed, after controlling for typical non-CAB heavy alcohol use, a significant indirect effect of CAB use to alcohol-related problems through avoidance of negative consequences CAB expectancies and PBS use. However, intoxication enhancement expectancies did not mediate this association. Conclusions- Our findings indicate that heavier CAB use was associated with stronger expectations that drinking CABs can help avoid negative consequences. These beliefs were related to using fewer PBS when drinking and a greater likelihood of experiencing problems. Given that these expectancies may be underlying mechanisms of CAB use, their inclusion in existing alcohol interventions may be beneficial

A Latent Profile Analysis of Drinking Patterns Among Nonstudent Emerging Adults

Research indicates that nonstudent emerging adults, as compared to their college-attending peers, are at higher risk for experiencing alcohol-related problems, including alcohol use disorders. The present study sought to extend the limited research on nonstudent drinking by (1) identifying sub-groups of nonstudent drinkers based on their drinking patterns and (2) determining the extent to which social-cognitive between-person factors related to drinking (i.e., social expectancies, perceived drinking norms, social drinking motivations) distinguish these sub-groups. Participants were 195 (65.1% men) nonstudent emerging adult heavy episodic drinkers recruited from the community. Mean age was 21.88 (SD = 2.08) years and 45.4% were unemployed. Latent profile analysis identified two classes based on drinking across 30 days. The moderate drinkers group (n = 143; 73.3%) reported consuming 10-11 drinks weekly and drinking two to three times per week, on average. The heavy drinkers class (n = 52; 26.7%) reported consuming 42-43 drinks weekly and drinking six to seven days per week. Both groups exhibited a cyclic pattern of drinking whereby weekday drinking was lower, with increases on the weekend; the heavy drinkers class had stronger weekend increases starting earlier. Heavy drinkers reported greater volume, frequency, and problematic drinking behaviors, as compared to the moderate drinkers. The heavy drinkers class also endorsed stronger social motives and perceived their peers to drink more. The present study offered unique insights into nonstudent emerging adult drinking patterns by identifying sub-populations of drinkers based on their past 30-day use. Knowledge gained from this study could aide in tailoring existing alcohol interventions to nonstudents to reduce alcohol-related harms