486 research outputs found
gaps as derived models and correctness of mice
Assume ZF + AD + V=L(R). Let be a gap with
admissible. We analyze as a natural form of
``derived model'' of a premouse , where is found in a generic extension
of . In particular, we will have , and if ``
exists'', then and in fact have the same universe. This
analysis will be employed in further work, yet to appear, toward a resolution
of a conjecture of Rudominer and Steel on the nature of , for
-small mice . We also establish some preliminary work toward this
conjecture in the present paper.Comment: 128 page
Local Definability of in
We show that in , assuming large cardinals, is locally definable from for all -cardinals . This is a further elaboration of the
statement " is a core model below " made
by John Steel
Discovering structure without labels
The scarcity of labels combined with an abundance of data makes unsupervised learning more attractive than ever. Without annotations, inductive biases must guide the identification of the most salient structure in the data. This thesis contributes to two aspects of unsupervised learning: clustering and dimensionality reduction.
The thesis falls into two parts. In the first part, we introduce Mod Shift, a clustering method for point data that uses a distance-based notion of attraction and repulsion to determine the number of clusters and the assignment of points to clusters. It iteratively moves points towards crisp clusters like Mean Shift but also has close ties to the Multicut problem via its loss function. As a result, it connects signed graph partitioning to clustering in Euclidean space.
The second part treats dimensionality reduction and, in particular, the prominent neighbor embedding methods UMAP and t-SNE. We analyze the details of UMAP's implementation and find its actual loss function. It differs drastically from the one usually stated. This discrepancy allows us to explain some typical artifacts in UMAP plots, such as the dataset size-dependent tendency to produce overly crisp substructures. Contrary to existing belief, we find that UMAP's high-dimensional similarities are not critical to its success.
Based on UMAP's actual loss, we describe its precise connection to the other state-of-the-art visualization method, t-SNE. The key insight is a new, exact relation between the contrastive loss functions negative sampling, employed by UMAP, and noise-contrastive estimation, which has been used to approximate t-SNE. As a result, we explain that UMAP embeddings appear more compact than t-SNE plots due to increased attraction between neighbors. Varying the attraction strength further, we obtain a spectrum of neighbor embedding methods, encompassing both UMAP- and t-SNE-like versions as special cases. Moving from more attraction to more repulsion shifts the focus of the embedding from continuous, global to more discrete and local structure of the data. Finally, we emphasize the link between contrastive neighbor embeddings and self-supervised contrastive learning. We show that different flavors of contrastive losses can work for both of them with few noise samples
Unreachability of Inductive-Like Pointclasses in
Hjorth proved from that there is no sequence of distinct
sets of length . Sargsyan extended Hjorth's technique
to show there is no sequence of distinct sets of length
. Sargsyan conjectured an analogous property is true for any
regular Suslin pointclass in -- i.e. if is a regular Suslin
cardinal in , then there is no sequence of distinct -Suslin sets
of length in . We prove this in the case that the pointclass
is inductive-like
Expectations and expertise in artificial intelligence: specialist views and historical perspectives on conceptualisation, promise, and funding
Artificial intelligence’s (AI) distinctiveness as a technoscientific field that imitates the ability to think went through a resurgence of interest post-2010, attracting a flood of scientific and popular expectations as to its utopian or dystopian transformative consequences. This thesis offers observations about the formation and dynamics of expectations based on documentary material from the previous periods of perceived AI hype (1960-1975 and 1980-1990, including in-between periods of perceived dormancy), and 25 interviews with UK-based AI specialists, directly involved with its development, who commented on the issues during the crucial period of uncertainty (2017-2019) and intense negotiation through which AI gained momentum prior to its regulation and relatively stabilised new rounds of long-term investment (2020-2021). This examination applies and contributes to longitudinal studies in the sociology of expectations (SoE) and studies of experience and expertise (SEE) frameworks, proposing a historical sociology of expertise and expectations framework. The research questions, focusing on the interplay between hype mobilisation and governance, are: (1) What is the relationship between AI practical development and the broader expectational environment, in terms of funding and conceptualisation of AI? (2) To what extent does informal and non-developer assessment of expectations influence formal articulations of foresight? (3) What can historical examinations of AI’s conceptual and promissory settings tell about the current rebranding of AI?
The following contributions are made: (1) I extend SEE by paying greater attention to the interplay between technoscientific experts and wider collective arenas of discourse amongst non-specialists and showing how AI’s contemporary research cultures are overwhelmingly influenced by the hype environment but also contribute to it. This further highlights the interaction between competing rationales focusing on exploratory, curiosity-driven scientific research against exploitation-oriented strategies at formal and informal levels. (2) I suggest benefits of examining promissory environments in AI and related technoscientific fields longitudinally, treating contemporary expectations as historical products of sociotechnical trajectories through an authoritative historical reading of AI’s shifting conceptualisation and attached expectations as a response to availability of funding and broader national imaginaries. This comes with the benefit of better perceiving technological hype as migrating from social group to social group instead of fading through reductionist cycles of disillusionment; either by rebranding of technical operations, or by the investigation of a given field by non-technical practitioners. It also sensitises to critically examine broader social expectations as factors for shifts in perception about theoretical/basic science research transforming into applied technological fields. Finally, (3) I offer a model for understanding the significance of interplay between conceptualisations, promising, and motivations across groups within competing dynamics of collective and individual expectations and diverse sources of expertise
Evaluation of a novel mRNA-pertussis vaccine against emerging clinical isolates of Bordetella pertussis
Bordetella pertussis is a Gram-negative obligate aerobe that causes a respiratory disease known as pertussis or whooping cough. Pertussis is most severe in younger children, especially infants but the bacteria has been known to colonize adult populations. Before the introduction of the whole-cell pertussis (wP; wP-DTP) vaccine reported numbers of pertussis cases within the US routinely topped 100,000 cases per year. However, with the widespread usage of the wP vaccine case numbers began dropping and reached a low of less than 5,000 cases per year in the late 1970’s and early 80’s. It appeared that B. pertussis was heading towards eradication, but the wP vaccine proved to be highly reactogenic due to remnant endotoxin from the manufacturing process. This reactogenicity caused fear in wP vaccination both abroad and within the US which led to an increase in cases during the late 1980s in the US. Thankfully, work was already being done on the development of an acellular pertussis (aP) vaccine to replace the reactogenic wP. In 1996, the first aP vaccine, combined with diphtheria and tetanus toxoid (DTaP), was licensed for use within the US. These vaccines proved to be less reactogenic as measured by adverse effects but with that came a different immune response to aP vaccination versus wP vaccination. Coinciding with the introduction of DTaP vaccination was a steady increase in pertussis case numbers within the US peaking at over 50,000 in 2012. The theories on this increase include genomic differences in emerging clinical isolates (ECIs) of B. pertussis, rapid waning immunity of DTaP induced immunity, and the humoral Th2 skewed immune response by DTaP vaccination. Each theory has its own merits and we hypothesized that the increase observed in pertussis cases is a combination of all three theories and we propose a potential solution to this increase by using a novel mRNA-DTP vaccine. We first wanted to evaluate if genomic differences between ECIs and historic isolates were causing different levels of pathogenesis and innate immune response in a naïve mouse model. To begin, we cultured 15 different isolates of B. pertussis in a liquid medium and extracted RNA from end log-phase growth of the bacteria. RNAseq was performed and we observed many differences in the transcriptomic profile of ECIs compared to historic isolates in virulence factors including ptxA (pertussis toxin; PT), fhaB (filamentous hemagglutinin; FHA), prn (pertactin; PRN), sphB1 (serine protease homolog of Bordetella 1; SphB1) and brkA (Bordetella resistant to killing genetic locus A; BrkA). However, when the experiment was repeated and end log-phased growth had its proteomic profiles analyzed we observed a major reduction in these differences especially for BrkA, SphB1, and FHA. Next, we intranasally (IN) challenged mice with 15 different isolates of B. pertussis (13 ECIs and 2 historic isolates) to assay markers of disease burden including leukocytosis and bacterial burden. All test isolates had similar levels of bacterial burden, as quantified by CFU, in the lung, trachea, and nasal lavage 3 days post-challenge. We did observe a slight increase in white blood cell and neutrophil counts in the blood of mice challenged with ECIs compared to historic isolates. To complete the study, we chose four representative isolates including one historical (UT25Sm1; UT25) and three ECIs (D420, H762, and I762) to observe differences in host immune response in the lungs of challenged mice. Briefly, mice were IN challenged as before and lungs were harvested 3 days post-challenge. RNA was extracted from the lungs and RNAseq was performed which revealed no major differences in host gene activation and repression in challenged mice. Even though there were large differences in the transcriptomic profiles of ECIs, there was no difference in the host genomic response or bacterial burden upon challenge in mice between ECIs and historic isolates. There was a slight increase in leukocytosis in ECI challenged mice. These data suggest that genomic differences in ECIs are not a major contributor to increased pathogenesis leading to an increase in reported pertussis cases. We then continued the previous study by introducing a vaccination component to evaluate if ECIs were better at evading vaccine-mediated immunity. Mice were primed and boosted with 1/80th human dose of either DTaP or wP vaccine and IN challenged with one of the four representative isolates used previously. We observed that B. pertussis specific IgG antibodies induced by both DTaP and wP vaccinations bound to all tested isolates similarly. Vaccinated mice were then IN challenged with either UT25Sm1 (historic) or an ECI (D420, H762, or I762) and we observed that both vaccines controlled the induction of proinflammatory cytokines regardless of which challenge isolate was used. We next investigated if PT produced by ECIs was able to evade neutralizing antibodies and induce leukocytosis. Again, DTaP was able to reduce leukocytosis regardless of the challenge isolate. ECIs did not induce more white blood cells or neutrophils on days 3 and 7 post-challenge compared to the historic isolate. Lastly, we investigated if ECIs challenge would lead to increased bacterial burden post-challenge. Bacterial clearance of ECIs was comparable to the historic isolate control in the lung, trachea, and nasal lavage 3 days post-challenge. Interestingly, while the burden was not increased more than the historic isolate, it appeared that ECIs were able to persist longer in the lungs in mice. All these data taken together suggest ECIs are not able to evade aP vaccine-mediated immunity in mice. After evaluating the role ECIs may have in the rise in pertussis cases, we wanted to develop a standardized aerosol challenge protocol due to the inconsistencies in this challenge method in the field. The protocol was developed using commercially available nebulizers, dosing chamber, and dose controller to remove any difference in laboratory designed challenge systems. We observed that this aerosol protocol was reproducible and deposited near identical numbers of bacteria from challenge to challenge. Along the same line, we developed a streptomycin resistant ECI (D420Sm1) from the baboon challenge model challenge isolate (D420). This lab adapted isolate has a single nucleotide polymorphism which confers streptomycin resistance. D420Sm1 has near identical growth characteristics and pathogenesis to the parent D420 isolate. Lastly, we aimed to evaluate a potential solution to the rise in pertussis cases with a novel mRNA-DTP vaccine. To begin, we sought to optimize the PtxA-mRNA antigen for future inclusion in the mRNA-DTP vaccine. Mice were vaccinated with either a control vaccine (DTaP, wP, gPT), an experimental recombinant PT protein (Protein) vaccine, or one of two mRNA vaccines (mRNA-C210 or mRNA-C180). Post-boost, no vaccine induced IgG antibody titers specific to any B oligomer of PT. Both the mRNA-C210 and mRNA-C180 induced IgG antibodies to PT and PtxA. Mice were then challenged with purified PT and leukocytosis was evaluated 3 days later. Again, both mRNA vaccines reduced leukocytosis and neutrophilia compared to the mock vaccinated group and similar to DTaP. The mRNA-C180 antigen was selected due to the higher IgG antibody titers specific to PT holotoxin and this antigen was included in the study formulation of mRNA-DTP. Also, we utilized the coughing rat model of pertussis to add a coughing parameter to the study. Briefly, Sprague-Dawley rats were vaccinated with 1/10th human dose of DTaP or wP, or 10 μg of mRNA-DTP. Serological analysis via ELISA revealed that mRNA-DTP was immunogenic in rats and induced comparable titers of PRN-specific, FHA-specific, and B. pertussis-specific IgG antibodies to DTaP and wP vaccination. mRNA-DTP did induce PT-specific IgG antibodies however they were lower than DTaP vaccinated rats. Interestingly, in previous experiments in mice the mRNA-DTP vaccine was able to skew towards Th1 subclass of IgG antibodies however in rats the subclass was skewed towards Th2 IgG1 subclass. Even so, bacterial burden in respiratory tissues were reduced for all vaccine groups and an even further reduction was observed in mRNA-DTP compared to DTaP vaccination. Moreover, mRNA-DTP vaccination reduced bacterial burden to the lower limit of detection in the nasal lavage by day 9 post-challenge. Next, we aimed to evaluate if mRNA-DTP vaccination would reduce coughing in rats comparable to the DTaP group because DTaP vaccination is known to reduce disease manifestations. We observed that coughing began on day 4 post-challenge and for MVC remained for the duration of the experiment. All vaccine groups were able to limit coughing compared to MVC however mRNA-DTP was able to completely abrogate the coughing phenotype and only a single cough was recorded during the study. This was comparable to the non-challenged group which had only three recorded coughs unrelated to B. pertussis challenge. These data suggest that mRNA-DTP was able to protect rats from bacterial burden and pertussis manifestations comparable to currently licensed DTaP and wP vaccines. The work presented in this thesis suggests that genomic differences in ECIs compared to historic isolates is not a major factor in the recent increase in pertussis cases. Further, it provides a standardized protocol for aerosol challenge and the adaptation of an ECI to be used in laboratory studies. The main finding in this thesis is that a novel mRNA-DTP vaccine was shown to be a potential solution to the increase in pertussis cases
Learning Curricula in Open-Ended Worlds
Deep reinforcement learning (RL) provides powerful methods for training optimal sequential decision-making agents. As collecting real-world interactions can entail additional costs and safety risks, the common paradigm of sim2real conducts training in a simulator, followed by real-world deployment. Unfortunately, RL agents easily overfit to the choice of simulated training environments, and worse still, learning ends when the agent masters the specific set of simulated environments. In contrast, the real-world is highly open-ended—featuring endlessly evolving environments and challenges, making such RL approaches unsuitable. Simply randomizing across a large space of simulated environments is insufficient, as it requires making arbitrary distributional assumptions, and as the design space grows, it can become combinatorially less likely to sample specific environment instances that are useful for learning. An ideal learning process should automatically adapt the training environment to maximize the learning potential of the agent over an open-ended task space that matches or surpasses the complexity of the real world. This thesis develops a class of methods called Unsupervised Environment Design (UED), which seeks to enable such an open-ended process via a principled approach for gradually improving the robustness and generality of the learning agent. Given a potentially open-ended environment design space, UED automatically generates an infinite sequence or curriculum of training environments at the frontier of the learning agent’s capabilities. Through both extensive empirical studies and theoretical arguments founded on minimax-regret decision theory and game theory, the findings in this thesis show that UED autocurricula can produce RL agents exhibiting significantly improved robustness and generalization to previously unseen environment instances. Such autocurricula are promising paths toward open-ended learning systems that approach general intelligence—a long sought-after ambition of artificial intelligence research—by continually generating and mastering additional challenges of their own design
Applications
Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications
PhD students´day FMST 2023
The authors gave oral presentations of their work online as part of a Doctoral Students’ Day held on 15 June 2023, and they reflect the challenging work done by the students and their supervisors in the fields of metallurgy, materials engineering and management. There are 82 contributions in total, covering a range of areas – metallurgical technology, thermal engineering and fuels in industry, chemical metallurgy, nanotechnology, materials science and engineering, and industrial systems management. This represents a cross-section of the diverse topics investigated by doctoral students at the faculty, and it will provide a guide for Master’s graduates in these or similar disciplines who are interested in pursuing their scientific careers further, whether they are from the faculty here in Ostrava or engineering faculties elsewhere in the Czech Republic. The quality of the contributions varies: some are of average quality, but many reach a standard comparable with research articles published in established journals focusing on disciplines of materials technology. The diversity of topics, and in some cases the excellence of the contributions, with logical structure and clearly formulated conclusions, reflect the high standard of the doctoral programme at the faculty.Ostrav
Observing Conflict Escalation in World Society: Ukraine's Maidan and Mali's Breakup
How do conflicts escalate? This is one of the major questions in conflict research. To offer further answers, Richard Bösch follows a tripartite agenda: First, he develops a constructivist methodology for the study of conflict escalation embedded in a Luhmannian systems theoretical world society perspective. Bösch argues that conflicts can be observed as social systems and he looks at the process of conflict escalation by analysing communication. Second, this analysis offers two case studies: the Maidan protests in Ukraine 2013-2014 and Mali's crisis 2010-2012. Third, it gives insights on how systems theoretical research can be beneficial for Peace and Conflict Studies
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