On continuum beliefs and psychiatric stigma: Similarity to a person with schizophrenia can feel too close for comfort

Continuum belief interventions that blur boundaries between “normal” individuals and individuals with psychiatric problems have shown promise in reducing psychiatric stigma. Interventions to date have afforded participants considerable psychological distance from individuals with mental illness. An intervention that compels psychological closeness to individuals with mental illness may lead to increased anxiety/threat and an attenuated intervention effect on stigma. In a randomized experiment, one hundred thirty-five participants listened to a bogus interview involving an ostensible person with schizophrenia who shared numerous characteristics in common with participants. In the interview, the target person (1) did not verbally broach issues of similarity to “normal” people, (2) endorsed a continuum view, or (3) endorsed a categorical view. Participants then read a bogus research article on schizophrenia that (1) was agnostic with respect to the continuum/categorical distinction, (2) attested to a continuum view, or (3) attested to a categorical view. Correlational analyses demonstrated that greater endorsement of continuum beliefs predicted less stigma. Experimental analyses demonstrated that the continuum intervention had no effect on stigma. The continuum intervention increased participants’ feelings of anxiety/threat, measured via self-report and a lexical decision task. These findings might usefully inform the design of stigma reduction programming centered on continuum beliefs

Regulation and Function of the Dscam1 Extended 3’ UTR mRNA

More than 50% of genes in species from Drosophila to human undergo alternative polyadenylation (APA). It has been shown that neuronal tissues are highly enriched for usage of transcripts with extended alternative 3’ untranslated regions, which are products of APA. Specific function of these longer 3’ UTR transcripts are largely unknown; however, because the 3’ UTR can regulate transcript stability, translational efficiency, and localization, it is plausible that 3’ UTR switching in nervous tissues may serve important biological functions. We chose to study the extended 3’ UTR of Dscam1 as it is one of several axon guidance genes that express an extended 3’ UTR mRNA isoform. We created a Dscam1 extended 3’ UTR mutant using the relatively new CRISPR/CAS9 system. We show that the Dscam1 extended 3’ UTR loss of function mutants have severe deficiencies in locomotor activity and display an increased mortality rate. We have identified that in S2 cells the RNA binding protein ELAV promotes use of the extended 3’ UTR of Dscam1 and also show that ELAV is capable of binding at least two putative binding sites located on the 3’ UTR of Dscam1. Elucidating the important function of these extended 3’ UTRs will benefit not only our knowledge of axon guidance, but may reveal the function of a pervasive neural phenomenon

Emerging Capabilities of Information Technology Governance: Exploring Stakeholder Perspective in Financial Services

Information technology governance is generally defined as the locus of IT decision-making authority. This paper argues that IT governance also includes the capability to integrate IT decision-making between key stakeholders. Exploratory case studies are conducted in Financial Services to develop a richer understanding of what the emerging capabilities are of IT governance. Findings indicate that IT governance capabilities -while necessary, though not sufficient-, go beyond formal-hierarchical modes, and include important lateral and socialisation mechanisms. In particular, the role of competency, credibility and coalition building are essential to IT governance. Directions for future research are discussed

Thermal diffusion near a binary liquid azetrope

Induction of a mass flux by a temperature gradient is known as the thermal diffusion or Soret effect, and is characterized by the thermal diffusion factor. A thermogravitational column’was used to obtain thermal diffusion factors and steady state separations in the ethanol-water mixture at its azeotropic composition. The thermogravitational diffusion column was calibrated using the value of the thermal diffusion factor of the cyclohexane-benzene mixture, which had been previously determined at 25°C. The temperature dependence of the thermal diffusion factor was determined for the ethanol-water system within .5°C of the azeotropic point and in the range of 25° to 77.7°C. Within 1°C of the azeotropic point, the thermal diffusion factor shows an anomalous behavior. It appears to increase rapidly as the azeotrope temperature is approached. In addition to the thermal diffusion factor, the heat of transport and thermal diffusion coefficient were determined for the ethanol-water system as functions of temperature, based on the assumption of Onsager Reciprocity. These parameters also exhibit a divergent character as the boiling point is approached. Further studies are needed to determine the significance of this effect in terms of molecular models. Ethanol enriched fluid from the thermogravitational column operating in the continuous mode was used as feed to a packed distillation column. Further separation occurred via distillation. Thus, thermogravitational columns offer a convenient small scale intermediate to break the azeotropes which often arise in the separation of liquid mixtures by distillation

Subspecies Composition, Genetic Variation and Structure of Largemouth Bass in Puerto Rico Reservoirs

Subspecies composition and genetic variation are important to the growth and survival of Largemouth Bass and information on these genetic characteristics is required for proper management of the species. In Puerto Rico, a genetic evaluation is needed to develop management plans for Puerto Rico reservoirs and maintain Florida Largemouth Bass at the Maricao Hatchery. Subspecies composition was characterized among reservoirs and the contemporary Maricao Hatchery broodstock in Puerto Rico, and metrics were compared between subspecies and hybrids among reservoir populations. Genetic variation and structure was determined and compared to Largemouth Bass populations in their native range. Florida subspecies were prevalent in all populations and non-introgressed subspecies seemed to be better adapted to the island than introgressed forms. Genetic diversity was lower in Puerto Rico populations and substantial genetic structure among populations was lacking. These results provide genetic information to guide future management and propagation of Largemouth Bass in Puerto Rico

Subspecies Composition, Genetic Variation and Structure of Largemouth Bass in Puerto Rico Reservoirs

Subspecies composition and genetic variation are important to the growth and survival of Largemouth Bass and information on these genetic characteristics is required for proper management of the species. In Puerto Rico, a genetic evaluation is needed to develop management plans for Puerto Rico reservoirs and maintain Florida Largemouth Bass at the Maricao Hatchery. Subspecies composition was characterized among reservoirs and the contemporary Maricao Hatchery broodstock in Puerto Rico, and metrics were compared between subspecies and hybrids among reservoir populations. Genetic variation and structure was determined and compared to Largemouth Bass populations in their native range. Florida subspecies were prevalent in all populations and non-introgressed subspecies seemed to be better adapted to the island than introgressed forms. Genetic diversity was lower in Puerto Rico populations and substantial genetic structure among populations was lacking. These results provide genetic information to guide future management and propagation of Largemouth Bass in Puerto Rico

Cutting-Edge Techniques for Depth Map Super-Resolution

To overcome hardware limitations in commercially available depth sensors which result in low-resolution depth maps, depth map super-resolution (DMSR) is a practical and valuable computer vision task. DMSR requires upscaling a low-resolution (LR) depth map into a high-resolution (HR) space. Joint image filtering for DMSR has been applied using spatially-invariant and spatially-variant convolutional neural network (CNN) approaches. In this project, we propose a novel joint image filtering DMSR algorithm using a Swin transformer architecture. Furthermore, we introduce a Nonlinear Activation Free (NAF) network based on a conventional CNN model used in cutting-edge image restoration applications and compare the performance of the techniques. The proposed algorithms are validated through numerical studies and visual examples demonstrating improvements to state-of-the-art performance while maintaining competitive computation time for noisy depth map super-resolution

Examining Knowledge-Based Information Technology Management Competencies of Business Executives

This paper examines IT management competencies of business executives, and analyzes how IT management competencies of business executives impact IT governance capabilities. A (knowledge-based) model interrelating explicit and tacit IT management competencies of business executives with IT governance capabilities is developed. Following a multi-method research design, preliminary results indicate that IT management competence is a multidimensional construct, in which explicit and tacit knowledge regarding IT and IT management are essential for building IT governance capabilities

Fast, effective, and coherent time series modeling using the sparsity-ranked lasso

The sparsity-ranked lasso (SRL) has been developed for model selection and estimation in the presence of interactions and polynomials. The main tenet of the SRL is that an algorithm should be more skeptical of higher-order polynomials and interactions *a priori* compared to main effects, and hence the inclusion of these more complex terms should require a higher level of evidence. In time series, the same idea of ranked prior skepticism can be applied to the possibly seasonal autoregressive (AR) structure of the series during the model fitting process, becoming especially useful in settings with uncertain or multiple modes of seasonality. The SRL can naturally incorporate exogenous variables, with streamlined options for inference and/or feature selection. The fitting process is quick even for large series with a high-dimensional feature set. In this work, we discuss both the formulation of this procedure and the software we have developed for its implementation via the **srlTS** R package. We explore the performance of our SRL-based approach in a novel application involving the autoregressive modeling of hourly emergency room arrivals at the University of Iowa Hospitals and Clinics. We find that the SRL is considerably faster than its competitors, while producing more accurate predictions