Effectiveness of a Leadership Development Program that Incorporates Social and Emotional Intelligence for Aspiring School Leaders

Focus on social and emotional intelligence competencies to improve effective leadership has become commonplace in the corporate arena and is now considered by many a prerequisite to successful job performance and outcomes (Antonakis, Ashkanasy, & Dasborough, 2009; Grant, Curtayne, & Burton, 2009; Spence & Grant, 2007; Kampa-Kokesch & Anderson, 2001; McGovern, Lindemann, Vergara, Murphy, Barker, & Warrenfeltz, 2001). Only recently has a similar trend become recognized and more accepted in the field of education (Patti, Senge, Madrazo, & Stern, 2015; Patti, Holzer, Brackett, & Stern, 2014). Few studies exist that study the role that educational leaders’ social and emotional competencies in play in their job performance and effectiveness; none exist that explore such development with aspiring school leaders. This quasi-experimental pilot study evaluated the effectiveness of a post-graduate development program for aspiring school leaders that incorporates social and emotional intelligence based on the Goleman-Boyatzis model (Goleman, Boyatsis, & McKee, 2001) and inspired by the original concept of emotional intelligence (Salovey & Mayer, 1990). The interrelated social and emotional competencies explored in this study form four core clusters that include: 1) self-awareness, 2) self-management, 3) relationship management, and 4) social awareness (Brackett, Rivers, & Salovey, 2011; Goleman, 1996; Salovey & Mayer, 1990; Zins & Elias, 2007). This study’s sample consisted of 32 aspiring leaders who participated in a post-graduate educational leadership program at a university in New York. The study evaluated whether or not there were any effects of focused social and emotional intelligence content and skills on aspiring leaders’ emotional intelligence (EI) and other related characteristics such as assertiveness, empathy, mental health, personality, and openness to experience. Post-tests on the various characteristics after one semester found no statistical significance in the tested variables. However, after two years, when the social and emotional intelligence competencies were post-tested (ESCI-U), there were significant findings in the student candidates’ self-reported competencies directly related to leadership. Paired t-test comparisons of the means of Observer raters’ scores did not find statistically significant differences in the competencies assessed. This article discusses these findings as well as the strengths and challenges of implementing social and emotional intelligence development within an aspiring school leaders program; finally, it provides recommendations for further program development and studies

Red Breast Syndrome and Acellular Dermal Matrix

Increasingly popular for use in breast reconstruction, acellular dermal matrix (ADM) can provide support and protection to implants. However, use of ADM may be associated with infection and complications, including red breast syndrome (RBS). RBS is an inflammatory event that typically presents with cutaneous erythema over the domain where the ADM is surgically implanted. As ADM use increases, presumably, more cases of RBS will occur. Thus, techniques and tools to mitigate or manage RBS are needed to improve patient outcomes. Here, we describe a case where RBS was diagnosed and interestingly resolved after exchange for a different brand of dermal matrix. This surgical resolution maintained excellent reconstructive results with no recurrent erythema over a follow-up period of 7 months. Although we cannot rule out RBS due to other variables, RBS due to patient hypersensitivity to certain ADMs has been documented in the literature. In this instance, our results suggest that revision with an alternate ADM brand may serve as a potential solution

Investigating Social Haptic Illusions for Tactile Stroking (SHIFTS)

A common and effective form of social touch is stroking on the forearm. We seek to replicate this stroking sensation using haptic illusions. This work compares two methods that provide sequential discrete stimulation: sequential normal indentation and sequential lateral skin-slip using discrete actuators. Our goals are to understand which form of stimulation more effectively creates a continuous stroking sensation, and how many discrete contact points are needed. We performed a study with 20 participants in which they rated sensations from the haptic devices on continuity and pleasantness. We found that lateral skin-slip created a more continuous sensation, and decreasing the number of contact points decreased the continuity. These results inform the design of future wearable haptic devices and the creation of haptic signals for effective social communication.Comment: To be published in IEEE Haptics Symposium 202

Friction force on slow charges moving over supported graphene

We provide a theoretical model that describes the dielectric coupling of a 2D layer of graphene, represented by a polarization function in the Random Phase Approximation, and a semi-infinite 3D substrate, represented by a surface response function in a non-local formulation. We concentrate on the role of the dynamic response of the substrate for low-frequency excitations of the combined graphene-substrate system, which give rise to the stopping force on slowly moving charges above graphene. A comparison of the dielectric loss function with experimental HREELS data for graphene on a SiC substrate is used to estimate the damping rate in graphene and to reveal the importance of phonon excitations in an insulating substrate. A signature of the hybridization between graphene's pi plasmon and the substrate's phonon is found in the stopping force. A friction coefficient that is calculated for slow charges moving above graphene on a metallic substrate shows an interplay between the low-energy single-particle excitations in both systems.Comment: 13 pages, 5 figures, submitted to Nanotechnology for a special issue related to the NGC 2009 conference (http://asdn.net/ngc2009/index.shtml

Exploring Human Response Times to Combinations of Audio, Haptic, and Visual Stimuli from a Mobile Device

Auditory, haptic, and visual stimuli provide alerts, notifications, and information for a wide variety of applications ranging from virtual reality to wearable and hand-held devices. Response times to these stimuli have been used to assess motor control and design human-computer interaction systems. In this study, we investigate human response times to 26 combinations of auditory, haptic, and visual stimuli at three levels (high, low, and off). We developed an iOS app that presents these stimuli in random intervals and records response times on an iPhone 11. We conducted a user study with 20 participants and found that response time decreased with more types and higher levels of stimuli. The low visual condition had the slowest mean response time (mean +/- standard deviation, 528 +/- 105 ms) and the condition with high levels of audio, haptic, and visual stimuli had the fastest mean response time (320 +/- 43 ms). This work quantifies response times to multi-modal stimuli, identifies interactions between different stimuli types and levels, and introduces an app-based method that can be widely distributed to measure response time. Understanding preferences and response times for stimuli can provide insight into designing devices for human-machine interaction.Comment: Accepted to World Haptics Conference 202

The Atacama Cosmology Telescope: Two-Season ACTPol Spectra and Parameters

We present the temperature and polarization angular power spectra measured by the Atacama Cosmology Telescope Polarimeter (ACTPol). We analyze night-time data collected during 2013-14 using two detector arrays at 149 GHz, from 548 deg$^2$ of sky on the celestial equator. We use these spectra, and the spectra measured with the MBAC camera on ACT from 2008-10, in combination with Planck and WMAP data to estimate cosmological parameters from the temperature, polarization, and temperature-polarization cross-correlations. We find the new ACTPol data to be consistent with the LCDM model. The ACTPol temperature-polarization cross-spectrum now provides stronger constraints on multiple parameters than the ACTPol temperature spectrum, including the baryon density, the acoustic peak angular scale, and the derived Hubble constant. Adding the new data to planck temperature data tightens the limits on damping tail parameters, for example reducing the joint uncertainty on the number of neutrino species and the primordial helium fraction by 20%.Comment: 23 pages, 25 figure

Biological Contribution to Social Influences on Alcohol Drinking: Evidence from Animal Models

Social factors have a tremendous influence on instances of heavy drinking and in turn impact public health. However, it is extremely difficult to assess whether this influence is only a cultural phenomenon or has biological underpinnings. Research in non-human primates demonstrates that the way individuals are brought up during early development affects their future predisposition for heavy drinking, and research in rats demonstrates that social isolation, crowding or low social ranking can lead to increased alcohol intake, while social defeat can decrease drinking. Neurotransmitter mechanisms contributing to these effects (i.e., serotonin, GABA, dopamine) have begun to be elucidated. However, these studies do not exclude the possibility that social effects on drinking occur through generalized stress responses to negative social environments. Alcohol intake can also be elevated in positive social situations, for example, in rats following an interaction with an intoxicated peer. Recent studies have also begun to adapt a new rodent species, the prairie vole, to study the role of social environment in alcohol drinking. Prairie voles demonstrate a high degree of social affiliation between individuals, and many of the neurochemical mechanisms involved in regulation of these social behaviors (for example, dopamine, central vasopressin and the corticotropin releasing factor system) are also known to be involved in regulation of alcohol intake. Naltrexone, an opioid receptor antagonist approved as a pharmacotherapy for alcoholic patients, has recently been shown to decrease both partner preference and alcohol preference in voles. These findings strongly suggest that mechanisms by which social factors influence drinking have biological roots, and can be studied using rapidly developing new animal models

Autoimmune Disease Classification by Inverse Association with SNP Alleles

With multiple genome-wide association studies (GWAS) performed across autoimmune diseases, there is a great opportunity to study the homogeneity of genetic architectures across autoimmune disease. Previous approaches have been limited in the scope of their analysis and have failed to properly incorporate the direction of allele-specific disease associations for SNPs. In this work, we refine the notion of a genetic variation profile for a given disease to capture strength of association with multiple SNPs in an allele-specific fashion. We apply this method to compare genetic variation profiles of six autoimmune diseases: multiple sclerosis (MS), ankylosing spondylitis (AS), autoimmune thyroid disease (ATD), rheumatoid arthritis (RA), Crohn's disease (CD), and type 1 diabetes (T1D), as well as five non-autoimmune diseases. We quantify pair-wise relationships between these diseases and find two broad clusters of autoimmune disease where SNPs that make an individual susceptible to one class of autoimmune disease also protect from diseases in the other autoimmune class. We find that RA and AS form one such class, and MS and ATD another. We identify specific SNPs and genes with opposite risk profiles for these two classes. We furthermore explore individual SNPs that play an important role in defining similarities and differences between disease pairs. We present a novel, systematic, cross-platform approach to identify allele-specific relationships between disease pairs based on genetic variation as well as the individual SNPs which drive the relationships. While recognizing similarities between diseases might lead to identifying novel treatment options, detecting differences between diseases previously thought to be similar may point to key novel disease-specific genes and pathways