Negative partisanship is real, measurable, and affects political behaviour

Many people explain their political involvement with reference to the kinds of outcomes they’d like to avoid, with Republicans and Democrats alike often framing their campaigns around ‘keeping out’ the opposite side. But what do we actually know about what Nicholas J. Caruana calls ‘negative partisanship’? He presents evidence from Canada that shows it explains a great deal about political involvement, and that there are lessons for political engagement more widely

Should Voters Decide? Exploring Successes, Failures and Effects of Electoral Reform

Are Citizens’ Assemblies useful tools for reforming democratic institutions and addressing the democratic deficit? Evaluating the utility of using mini-publics to deliberate issues like electoral reform based only on their record of success does not recommend this approach. But this sort of assessment is weakened by a lacuna in the study of Citizens’ Assemblies: we do not know whether such deliberative bodies, thanks to their inherent high levels of democratic participation, might have added democracy-enhancing value over and above traditional elite-centric reforms. This dissertation establishes a theoretical model for evaluating whether a particular path to electoral reform has independent effects on the quality of democracy and on the democratic deficit, regardless of whether the proposed change is implemented. Elite-centric and more deliberative processes are evaluated based on their input and output legitimacy (Scharpf 1997, 1999) to determine whether high-input-legitimacy processes, such as Citizens’ Assemblies or similar efforts, have a positive effect on the quality of democracy, even in the absence of changed electoral laws. Twelve case studies at the national and subnational levels within the last thirty years are evaluated using a detailed and deeply historical treatment to determine whether the enhanced input legitimacy of a deliberative process has independent effects that make the Citizens’ Assembly template worth using to tackle the democratic deficit. The overall conclusion of the study is that Citizens’ Assemblies can fail to have an independent effect on the quality of democracy if the process is abandoned or subverted by elites, and proposed reforms require elite support through to the end in order to have a positive effect. Therefore, Citizens’ Assemblies can be worthwhile as tools to reform democracy if they receive proper elite support from start to finish

Pseudo-Saliency for Human Gaze Simulation

Understanding and modeling human vision is an endeavor which can be; and has been, approached from multiple disciplines. Saliency prediction is a subdomain of computer vision which tries to predict human eye movements made during either guided or free viewing of static images. In the context of simulation and animation, vision is often also modeled for the purposes of realistic and reactive autonomous agents. These often focus more on plausible gaze movements of the eyes and head, and are less concerned with scene understanding through visual stimuli. In order to bring techniques and knowledge over from computer vision fields into simulated virtual humans requires a methodology to generate saliency maps. Traditional saliency models are ill suited for this due to large computational costs as well as a lack of control due to the nature of most deep network based models. The primary contribution of this thesis is a proposed model for generating pseudo-saliency maps for virtual characters, Parametric Saliency Maps (PSM). This parametric model calculates saliency as a weighted combination of 7 factors selected from saliency and attention literature. Experiments conducted show that the model is expressive enough to mimic results from state-of-the-art saliency models to a high degree of similarity, as well as being extraordinarily cheap to compute by virtue of being done using the graphics processing pipeline of a simulation. The secondary contribution, two models are proposed for saliency driven gaze control. These models are expressive and present novel approaches for controlling the gaze of a virtual character using only visual saliency maps as input

Pseudo-Saliency for Human Gaze Simulation

Understanding and modeling human vision is an endeavor which can be; and has been, approached from multiple disciplines. Saliency prediction is a subdomain of computer vision which tries to predict human eye movements made during either guided or free viewing of static images. In the context of simulation and animation, vision is often also modeled for the purposes of realistic and reactive autonomous agents. These often focus more on plausible gaze movements of the eyes and head, and are less concerned with scene understanding through visual stimuli. In order to bring techniques and knowledge over from computer vision fields into simulated virtual humans requires a methodology to generate saliency maps. Traditional saliency models are ill suited for this due to large computational costs as well as a lack of control due to the nature of most deep network based models. The primary contribution of this thesis is a proposed model for generating pseudo-saliency maps for virtual characters, Parametric Saliency Maps (PSM). This parametric model calculates saliency as a weighted combination of 7 factors selected from saliency and attention literature. Experiments conducted show that the model is expressive enough to mimic results from state-of-the-art saliency models to a high degree of similarity, as well as being extraordinarily cheap to compute by virtue of being done using the graphics processing pipeline of a simulation. The secondary contribution, two models are proposed for saliency driven gaze control. These models are expressive and present novel approaches for controlling the gaze of a virtual character using only visual saliency maps as input

Bwiet u ta’ ġo fihom

Ġabra ta’ poeżiji u proża li tinkludi: Leħen l-għanja tas-skiet ta’ Ġużi Abela – Dawl u dija ta’ Pawlu Aquilina – Rwiefen ta’ V. M. Pellegrini – Rakkont Eġizzjan ta’ Fredu Nicholas – Marija Reġina ta’ Ġużè Chetcuti – Il-bwiet u ta’ ġo fihom ta’ Vincent Caruana.N/

A review of sensorless control in induction machines using HF injection and test vectors

This paper describes various methods aimed at tracking the flux and rotor position for cage induction machines without a shaft sensor using specially designed saliencies or natural saliencies. The estimation methods employ a High Frequency (HF) signal or test vectors to detect the machine saliency. As is common knowledge, multiple saliences can cause problems to track only one particular saliency. Ways to overcome this problem for rotor position and rotor flux tracking are discussed. The performance of these methods is investigated at all loads at low and zero speed and also at zero fundamental frequency.peer-reviewe

Assessing ChatGPT’s theoretical knowledge and prescriptive accuracy in bacterial infections: a comparative study with infectious diseases residents and specialists

Objectives: Advancements in Artificial Intelligence(AI) have made platforms like ChatGPT increasingly relevant in medicine. This study assesses ChatGPT's utility in addressing bacterial infection-related questions and antibiogram-based clinical cases. Methods: This study involved a collaborative effort involving infectious disease (ID) specialists and residents. A group of experts formulated six true/false, six open-ended questions, and six clinical cases with antibiograms for four types of infections (endocarditis, pneumonia, intra-abdominal infections, and bloodstream infection) for a total of 96 questions. The questions were submitted to four senior residents and four specialists in ID and inputted into ChatGPT-4 and a trained version of ChatGPT-4. A total of 720 responses were obtained and reviewed by a blinded panel of experts in antibiotic treatments. They evaluated the responses for accuracy and completeness, the ability to identify correct resistance mechanisms from antibiograms, and the appropriateness of antibiotics prescriptions. Results: No significant difference was noted among the four groups for true/false questions, with approximately 70% correct answers. The trained ChatGPT-4 and ChatGPT-4 offered more accurate and complete answers to the open-ended questions than both the residents and specialists. Regarding the clinical case, we observed a lower accuracy from ChatGPT-4 to recognize the correct resistance mechanism. ChatGPT-4 tended not to prescribe newer antibiotics like cefiderocol or imipenem/cilastatin/relebactam, favoring less recommended options like colistin. Both trained- ChatGPT-4 and ChatGPT-4 recommended longer than necessary treatment periods (p-value = 0.022). Conclusions: This study highlights ChatGPT's capabilities and limitations in medical decision-making, specifically regarding bacterial infections and antibiogram analysis. While ChatGPT demonstrated proficiency in answering theoretical questions, it did not consistently align with expert decisions in clinical case management. Despite these limitations, the potential of ChatGPT as a supportive tool in ID education and preliminary analysis is evident. However, it should not replace expert consultation, especially in complex clinical decision-making