How should discrepancy be assessed in perfectionism research? A psychometric analysis and proposed refinement of the Almost Perfect Scale–Revised

Research on perfectionism with the Almost Perfect Scale-Revised (APS-R) distinguishes adaptive perfectionists versus maladaptive perfectionists based primarily on their responses to the 12-item unidimensional APS-R discrepancy subscale, which assesses the sense of falling short of standards. People described as adaptive perfectionists have high standards but low levels of discrepancy (i.e., relatively close to attaining these standards). Maladaptive perfectionists have perfectionistic high standards and high levels of discrepancy. In the current work, we re-examine the psychometric properties of the APS-R discrepancy subscale and illustrate that this supposedly unidimensional discrepancy measure may actually consists of more than one factor. Psychometric analyses of data from student and community samples distinguished a pure fiveitem discrepancy factor and a second four-item factor measuring dissatisfaction. The five-item factor is recommended as a brief measure of discrepancy from perfection and the four-item factor is recommended as a measure of dissatisfaction with being imperfect. Overall, our results confirm past suggestions that most people with maladaptive perfectionism are characterized jointly by chronic dissatisfaction as well as a sense of being discrepant due to having fallen short of expectations. These findings are discussed in terms of their implications for the assessment of perfectionism, as well as the implications for research and practice

R&D results on a CsI-TTGEM based photodetector

The very high momentum particle identification detector proposed for the ALICE upgrade is a focusing RICH using a C4F10 gaseous radiator. For the detection of Cherenkov photons, one of the options currently under investigation is to use a CsI coated Triple-Thick-GEM (CsI-TTGEM) with metallic or resistive electrodes. We will present results from the laboratory studies as well as preliminary results of beam tests of a RICH detector prototype consisting of a CaF2 radiator coupled to a 10x10 cm2 CsI-TTGEM equipped with a pad readout and GASSIPLEX-based front-end electronics. With such a prototype the detection of Cherenkov photons simultaneously with minimum ionizing particles has been achieved for the first time in a stable operation mode

The effect of geometry on charge confinement in three dimensions

We show that, in contrast to the flat case, the Maxwell theory is not confining in the background of the three dimensional BTZ black-hole (covering space). We also study the effect of the curvature on screening behavior of Maxwell-Chern-Simons model in this space-time.Comment: 8 pages. To be published in Europhysics Letter

Assessing the resilience of a river management regime: Informal learning in a shadow network in the Tisza River Basin

Global sources of change offer unprecedented challenges to conventional river management strategies, which no longer appear capable of credibly addressing a trap: the failure of conventional river defense engineering to manage rising trends of disordering extreme events, including frequency and intensity of floods, droughts, and water stagnation in the Hungarian reaches of the Tisza River Basin. Extreme events punctuate trends of stagnation or decline in the ecosystems, economies, and societies of this river basin that extend back decades, and perhaps, centuries. These trends may be the long-term results of defensive strategies of the historical river management regime that reflect a paradigm dating back to the Industrial Revolution: "Protect the Landscape from the River." Since then all policies have defaulted to the imperatives of this paradigm such that it became the convention underlying the current river management regime. As an exponent of this convention the current river management regimes' methods, concepts, infrastructure, and paradigms that reinforce one another in setting the basin's development trajectory, have proven resilient to change from wars, political, and social upheaval for centuries. Failure to address the trap makes the current river management regimes resilience appear detrimental to the regions future development prospects and prompts demand for transformation to a more adaptive river management regime. Starting before transition to democracy, a shadow network has generated multiple dialogues in Hungary, informally exploring the roots of this trap as part of a search for ideas and methods to revitalize the region. We report on how international scientists joined one dialogue, applying system dynamics modeling tools to explore barriers and bridges to transformation of the current river management regime and develop the capacity for participatory science to expand the range of perspectives that inform, monitor, and revise learning, policy, and the practice of river management

A machine learning resource allocation solution to improve video quality in remote education

The current global pandemic crisis has unquestionably disrupted the higher education sector, forcing educational institutions to rapidly embrace technology-enhanced learning. However, the COVID-19 containment measures that forced people to work or stay at home, have determined a significant increase in the Internet traffic that puts tremendous pressure on the underlying network infrastructure. This affects negatively content delivery and consequently user perceived quality, especially for video-based services. Focusing on this problem, this paper proposes a machine learning-based resource allocation solution that improves the quality of video services for increased number of viewers. The solution is deployed and tested in an educational context, demonstrating its benefit in terms of major quality of service parameters for various video content, in comparison with existing state of the art. Moreover, a discussion on how the technology is helping to mitigate the effects of massively increasing internet traffic on the video quality in an educational context is also presented

Improved quality of online education using prioritized multi-agent reinforcement learning for video traffic scheduling

The recent global pandemic has transformed the way education is delivered, increasing the importance of videobased online learning. However, this puts a significant pressure on the underlying communication networks and the limited available bandwidth needs to be intelligently allocated to support a much higher transmission load, including video-based services. In this context, this paper proposes a Machine Learning (ML)-based solution that dynamically prioritizes content viewers with heterogeneous video services to increase their Quality of Service (QoS) and perceived Quality of Experience (QoE). The proposed approach makes use of the novel Prioritized Multi- Agent Reinforcement Learning solution (PriMARL) to decide the prioritization order of the video-based services based on networking conditions. However, the performance in terms of QoS and QoE provisioning to learners with different profiles and networking conditions depends on the type of scheduler employed in the frequency domain to conduct the scheduling and the radio resource allocation. To decide the best approach to be followed, we employ the proposed PriMARL solution with different types of scheduling rules and compare them with other state-of-theart solutions in terms of throughput, delay, packet loss, Peak Signal-to-Noise Ratio (PSNR), and Mean Opinion Score (MOS) for different traffic loads and characteristics. We show that the proposed solution achieves the best user QoE results

Galaxy Cluster Scaling Relations between Bolocam Sunyaev-Zel'dovich Effect and Chandra X-ray Measurements

We present scaling relations between the integrated Sunyaev-Zel'dovich Effect (SZE) signal, $Y_{\rm SZ}$, its X-ray analogue, $Y_{\rm X}\equiv M_{\rm gas}T_{\rm X}$, and total mass, $M_{\rm tot}$, for the 45 galaxy clusters in the Bolocam X-ray-SZ (BOXSZ) sample. All parameters are integrated within $r_{2500}$. $Y_{2500}$ values are measured using SZE data collected with Bolocam, operating at 140 GHz at the Caltech Submillimeter Observatory (CSO). The temperature, $T_{\rm X}$, and mass, $M_{\rm gas,2500}$, of the intracluster medium are determined using X-ray data collected with Chandra, and $M_{\rm tot}$ is derived from $M_{\rm gas}$ assuming a constant gas mass fraction. Our analysis accounts for several potential sources of bias, including: selection effects, contamination from radio point sources, and the loss of SZE signal due to noise filtering and beam-smoothing effects. We measure the $Y_{2500}$--$Y_{\rm X}$ scaling to have a power-law index of $0.84\pm0.07$, and a fractional intrinsic scatter in $Y_{2500}$ of $(21\pm7)\%$ at fixed $Y_{\rm X}$, both of which are consistent with previous analyses. We also measure the scaling between $Y_{2500}$ and $M_{2500}$, finding a power-law index of $1.06\pm0.12$ and a fractional intrinsic scatter in $Y_{2500}$ at fixed mass of $(25\pm9)\%$. While recent SZE scaling relations using X-ray mass proxies have found power-law indices consistent with the self-similar prediction of 5/3, our measurement stands apart by differing from the self-similar prediction by approximately 5$\sigma$. Given the good agreement between the measured $Y_{2500}$--$Y_{\rm X}$ scalings, much of this discrepancy appears to be caused by differences in the calibration of the X-ray mass proxies adopted for each particular analysis.Comment: 31 pages, 15 figures, accepted by ApJ 04/11/2015. This version is appreciably different from the original submission: it includes an entirely new appendix, extended discussion, and much of the material has been reorganize

Plant roots steer resilience to perturbation of river floodplains

Freshwater ecosystems along river floodplains host among the greatest biodiversity on Earth and are known to respond to anthropic pressure. For water impounded systems, resilience to changes in the natural flow regime is believed to be bi-directional. Whether such resilience prevents the system from returning to pristine conditions after the flow regime changes reverse is as yet unclear, though widely documented. In this work we show that temporal irreversibility of river floodplains to recover their status may be explained by the dynamics of riparian water-tolerant plant roots. Our model is a quantitative tool that will benefit scientists and practitioners in predicting the impact of changing flow regimes on long-term river floodplain dynamics

Perturbations of anti-de Sitter black holes

I review perturbations of black holes in asymptotically anti-de Sitter space. I show how the quasi-normal modes governing these perturbations can be calculated analytically and discuss the implications on the hydrodynamics of gauge theory fluids per the AdS/CFT correspondence. I also discuss phase transitions of hairy black holes with hyperbolic horizons and the dual superconductors emphasizing the analytical calculation of their properties.Comment: 25 pages, 4 figures, prepared for the proceedings of the 5th Aegean Summer School "From Gravity to Thermal Gauge Theories: the AdS/CFT Correspondence," Milos, Greece, September 2009