Search for third generation scalar quarks in events with b-tagged jets with the ATLAS detector

The thesis presents the results of two searches for the direct pair-production of third generation scalar quarks, the stop and the sbottom, in proton-proton collisions at √s = 13 TeV delivered by the Large Hadron Collider (LHC) and recorded by the ATLAS detector. Third generation squarks are studied in the context of natural supersymmetric extensions of the Standard Model, highlighting their role in the solution of the Higgs hierarchy problem and considering both R-parity conserving and violating decay scenarios. The signal models of interest produce final states characterised by the presence of two bottom quarks, and the identification of the hadronic jets generated by their fragmentation plays a crucial role in the analyses. The performance of b-jet identification algorithms is studied in detail, and a novel approach for the estimate of the associated systematic uncertainties is presented. The first analysis in the thesis is a search for a pairproduced sbottom with two-body decays into Standard Model third generation quarks and quasi-degenerate electroweakinos, while the second targets the pair-production of the stop followed by R-parity violating decays into a bottom quark and a lepton. No evidence of SUSY particles is found, and exclusion limits are set on the relevant signal models using dedicated statistical tools

Researching farmer behaviour in climate change adaptation and sustainable agriculture: lessons learned from five case studies

Understanding farmer behaviour is needed for local agricultural systems to produce food sustainably while facing multiple pressures. We synthesize existing literature to identify three fundamental questions that correspond to three distinct areas of knowledge necessary to understand farmer behaviour: 1) decision-making model; 2) cross-scale and cross-level pressures; and 3) temporal dynamics. We use this framework to compare five interdisciplinary case studies of agricultural systems in distinct geographical contexts across the globe. We find that these three areas of knowledge are important to understanding farmer behaviour, and can be used to guide the interdisciplinary design and interpretation of studies in the future. Most importantly, we find that these three areas need to be addressed simultaneously in order to understand farmer behaviour. We also identify three methodological challenges hindering this understanding: the suitability of theoretical frameworks, the trade-offs among methods and the limited timeframe of typical research projects. We propose that a triangulation research strategy that makes use of mixed methods, or collaborations between researchers across mixed disciplines, can be used to successfully address all three areas simultaneously and show how this has been achieved in the case studies. The framework facilitates interdisciplinary research on farmer behaviour by opening up spaces of structured dialogue on assumptions, research questions and methods employed in investigation

Evaluation of Interpretability for Deep Learning algorithms in EEG Emotion Recognition: A case study in Autism

Current models on Explainable Artificial Intelligence (XAI) have shown an evident and quantified lack of reliability for measuring feature-relevance when statistically entangled features are proposed for training deep classifiers. There has been an increase in the application of Deep Learning in clinical trials to predict early diagnosis of neuro-developmental disorders, such as Autism Spectrum Disorder (ASD). However, the inclusion of more reliable saliency-maps to obtain more trustworthy and interpretable metrics using neural activity features is still insufficiently mature for practical applications in diagnostics or clinical trials. Moreover, in ASD research the inclusion of deep classifiers that use neural measures to predict viewed facial emotions is relatively unexplored. Therefore, in this study we propose the evaluation of a Convolutional Neural Network (CNN) for electroencephalography (EEG)-based facial emotion recognition decoding complemented with a novel RemOve-And-Retrain (ROAR) methodology to recover highly relevant features used in the classifier. Specifically, we compare well-known relevance maps such as Layer-Wise Relevance Propagation (LRP), PatternNet, Pattern-Attribution, and Smooth-Grad Squared. This study is the first to consolidate a more transparent feature-relevance calculation for a successful EEG-based facial emotion recognition using a within-subject-trained CNN in typically-developed and ASD individuals

Energy deposition studies for the Upgrade II of LHCb at the CERN Large Hadron Collider

The Upgrade II of the LHCb experiment is proposed to be installed during the CERN Long Shutdown 4, aiming to operate LHCb at 1.5x$10^{34}cm^{-2}s^{-1}$ that is 75 times its design luminosity and reaching an integrated luminosity of about $400 fb^{-1}$ by the end of the High Luminosity LHC era. This increase of the data sample at LHCb is an unprecedented opportunity for heavy flavour physics measurements. A first upgrade of LHCb, completed in 2022, has already implemented important changes of the LHCb detector and, for the Upgrade II, further detector improvements are being considered. Such a luminosity increase will have an impact not only on the LHCb detector but also on the LHC magnets, cryogenics and electronic equipment placed in the IR8. In fact, the LHCb experiment was conceived to work at a much lower luminosity than ATLAS and CMS, implying minor requirements for protection of the LHC elements from the collision debris and therefore a different layout around the interaction point. The luminosity target proposed for the Upgrade II requires to review the layout of the entire insertion region in order to ensure safe operation of the LHC magnets and to mitigate the risk of failure of the electronic devices. The objective of this paper is to provide an overview of the implications of the Upgrade II of LHCb in the experimental cavern and in the tunnel with a focus on the LHCb detector, electronic devices and accelerator magnets

Higgs mass and vacuum stability in the Standard Model at NNLO

We present the first complete next-to-next-to-leading order analysis of the Standard Model Higgs potential. We computed the two-loop QCD and Yukawa corrections to the relation between the Higgs quartic coupling (lambda) and the Higgs mass (Mh), reducing the theoretical uncertainty in the determination of the critical value of Mh for vacuum stability to 1 GeV. While lambda at the Planck scale is remarkably close to zero, absolute stability of the Higgs potential is excluded at 98% C.L. for Mh < 126 GeV. Possible consequences of the near vanishing of lambda at the Planck scale, including speculations about the role of the Higgs field during inflation, are discussed.Comment: 35 pages, 8 figures. Final published version, misprints fixed, figures update

Design development and implementation of an irradiation station at the neutron time-of-flight facility at CERN

A new parasitic, mixed-field, neutron-dominated irradiation station has been recently commissioned at the European Laboratory for Particle Physics (CERN). The station is installed within the neutron time-of-flight (n_TOF) facility, taking advantage of the secondary radiation produced by the neutron spallation target, with neutrons ranging from 0.025 eV to several hundreds of MeV. The new station allows radiation damage studies to be performed in irradiation conditions that are closer to the ones encountered during the operation of particle accelerators; the irradiation tests carried out in the station will be complementary to the standard tests on materials, usually performed with gamma sources. Samples will be exposed to neutron-dominated doses in the MGy range per year, with minimal impact on the n_TOF facility operation. The station has 24 irradiation positions, each hosting up to 100 cm3 of sample material. In view of its proximity to the n_TOF target, inside protective shielding, the irradiation station and its operating procedures have been carefully developed taking into account the safety of personnel and to avoid any unwanted impact on the operation of the n_TOF facility and experiments. Due to the residual radioactivity of the whole area around the n_TOF target and of the irradiated samples, access to the irradiation station is forbidden to human operators even when the n_TOF facility is not in operation. Robots are used for the remote installation and retrieval of the samples, and other optimizations of the handling procedures were developed in compliance with radiation protection regulations and the aim of minimizing doses to personnel. The sample containers were designed to be radiation tolerant, compatible with remote handling, and subject to detailed risk analysis and testing during their development. The whole life cycle of the irradiated materials, including their post-irradiation examinations and final disposal, was considered and optimized

Stability of flows associated to gradient vector fields and convergence of iterated transport maps

In this paper we address the problem of stability of flows associated to a sequence of vector fields under minimal regularity requirements on the limit vector field, that is supposed to be a gradient. We apply this stability result to show the convergence of iterated compositions of optimal transport maps arising in the implicit time discretization (with respect to the Wasserstein distance) of nonlinear evolution equations of a diffusion type. Finally, we use these convergence results to study the gradient flow of a particular class of polyconvex functionals recently considered by Gangbo, Evans ans Savin. We solve some open problems raised in their paper and obtain existence and uniqueness of solutions under weaker regularity requirements and with no upper bound on the jacobian determinant of the initial datum

Intellectual Property, Open Science and Research Biobanks

In biomedical research and translational medicine, the ancient war between exclusivity (private control over information) and access to information is proposing again on a new battlefield: research biobanks. The latter are becoming increasingly important (one of the ten ideas changing the world, according to Time magazine) since they allow to collect, store and distribute in a secure and professional way a critical mass of human biological samples for research purposes. Tissues and related data are fundamental for the development of the biomedical research and the emerging field of translational medicine: they represent the “raw material” for every kind of biomedical study. For this reason, it is crucial to understand the boundaries of Intellectual Property (IP) in this prickly context. In fact, both data sharing and collaborative research have become an imperative in contemporary open science, whose development depends inextricably on: the opportunities to access and use data, the possibility of sharing practices between communities, the cross-checking of information and results and, chiefly, interactions with experts in different fields of knowledge. Data sharing allows both to spread the costs of analytical results that researchers cannot achieve working individually and, if properly managed, to avoid the duplication of research. These advantages are crucial: access to a common pool of pre-competitive data and the possibility to endorse follow-on research projects are fundamental for the progress of biomedicine. This is why the "open movement" is also spreading in the biobank's field. After an overview of the complex interactions among the different stakeholders involved in the process of information and data production, as well as of the main obstacles to the promotion of data sharing (i.e., the appropriability of biological samples and information, the privacy of participants, the lack of interoperability), we will firstly clarify some blurring in language, in particular concerning concepts often mixed up, such as “open source” and “open access”. The aim is to understand whether and to what extent we can apply these concepts to the biomedical field. Afterwards, adopting a comparative perspective, we will analyze the main features of the open models – in particular, the Open Research Data model – which have been proposed in literature for the promotion of data sharing in the field of research biobanks. After such an analysis, we will suggest some recommendations in order to rebalance the clash between exclusivity - the paradigm characterizing the evolution of intellectual property over the last three centuries - and the actual needs for access to knowledge. We argue that the key factor in this balance may come from the right interaction between IP, social norms and contracts. In particular, we need to combine the incentives and the reward mechanisms characterizing scientific communities with data sharing imperative

Identification of autoantibodies to the I protein of the heterogeneous nuclear ribonucleoprotein complex in patients with systemic sclerosis

Objective. To assess the presence of autoantibodies to the I protein (polypyrimidine-tract binding protein) of the heterogeneous nuclear RNPs (hnRNP) in different connective tissue diseases. Antibodies to other hnRNP proteins (A1, A2, and B) have been previously found in patients with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and mixed connective tissue disease (MCTD). Methods. Sera from 101 patients with various connective tissue diseases and 25 normal controls were investigated by enzyme-linked immunosorbent assay and immunoblotting, for their reactivity to highly purified recombinant hnRNP I. Moreover, reactivity to cellular hnRNP I protein was investigated by immunoblotting using a partially purified preparation of hnRNP proteins (including A1, A2, B, and I), and by indirect immunofluorescence. For the analysis of the fluorescence pattern, affinity-purified antibodies to hnRNP I, obtained from a selected patient, were tested on HEp-2 cells. Results. By immunoblotting, antibodies reacting to recombinant hnRNP I were found in 22 of 40 patients with systemic sclerosis (SSc), 3 of 32 with RA, 0 of 23 with SLE, and 0 of 6 with MCTD. Antibodies to recombinant hnRNP I were more frequently found in patients with pre-SSc or limited SSc (15 of 24) than in those with intermediate or diffuse SSc (7 of 16). In indirect immunofluorescence studies, affinity-purified anti-hnRNP I autoantibodies gave a diffuse nucleoplasmic staining. Using an hnRNP preparation from nuclear extracts, anti-hnRNP I reactivity was detectable in SSc sera, while it was not detectable in RA, SLE, and MCTD sera reacting with hnRNP A/B proteins. Conclusion. Human autoimmune sera show distinct patterns of anti-hnRNP reactivity, i.e., anti-A/B in SLE and RA sera, and anti-I in SSc sera. This suggests that A/B proteins and the I protein may be involved in different dynamic hnRNP complexes that elicit different autoimmune responses. From a clinical perspective, anti-hnRNP I antibodies are frequently associated with pre-SSc features, suggesting an early appearance of these antibodies during the course of the disease

Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

A cross-ancestry genome-wide association meta-analysis of amyotrophic lateral sclerosis (ALS) including 29,612 patients with ALS and 122,656 controls identifies 15 risk loci with distinct genetic architectures and neuron-specific biology. Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons