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This Work in Progress (WIP) paper will present an interview protocol development that leverages social media analysis for capturing narratives of neurodivergent (e.g., ADHD, autistic, dyslexic) engineering students. The work presented in this WIP is part of a larger mixed-methods sequential research project which aims to capture neurodivergent engineering student narratives that describe their engineering experiences in terms of strengths and challenges. Through social media analysis, we identified key language used by the neurodivergent community (e.g., neurodivergent, spoon, forget). We developed a few initial themes such as multiple pathways to recognizing one’s identity of being neurodivergent, multiple ways in which neurodivergence symptoms are experienced, and the ways in which an individual internally and outwardly interacts with their own symptoms. To capture neurodivergent narratives, we plan on conducting semi-structured interviews with neurodivergent engineering students three times over the semester (beginning, middle, end). Initial interview protocols for each interview will be developed and adjusted throughout the interview data collection process. An initial compilation of relevant interview questions was compiled from previous research and from the objectives of the research study. This initial pool of questions will then be refined based on our thematic findings and using the nuanced language identified on the social media platforms TikTok, Reddit, and Twitter. Results of this work will be presented in this paper as an interview protocol that will continue to be adapted as part of this larger research study, but can also be used as a starting point for researchers exploring similar topics in capturing the experience of neurodivergent engineering students. 

This Work in Progress (WIP) paper will present an interview protocol development that leverages social media analysis for capturing narratives of neurodivergent (e.g., ADHD, autistic, dyslexic) engineering students. The work presented in this WIP is part of a larger mixed-methods sequential research project which aims to capture neurodivergent engineering student narratives that describe their engineering experiences in terms of strengths and challenges. Through social media analysis, we identified key language used by the neurodivergent community (e.g., neurodivergent, spoon, forget). We developed a few initial themes such as multiple pathways to recognizing one’s identity of being neurodivergent, multiple ways in which neurodivergence symptoms are experienced, and the ways in which an individual internally and outwardly interacts with their own symptoms. To capture neurodivergent narratives, we plan on conducting semi-structured interviews with neurodivergent engineering students three times over the semester (beginning, middle, end). Initial interview protocols for each interview will be developed and adjusted throughout the interview data collection process. An initial compilation of relevant interview questions was compiled from previous research and from the objectives of the research study. This initial pool of questions will then be refined based on our thematic findings and using the nuanced language identified on the social media platforms TikTok, Reddit, and Twitter. Results of this work will be presented in this paper as an interview protocol that will continue to be adapted as part of this larger research study, but can also be used as a starting point for researchers exploring similar topics in capturing the experience of neurodivergent engineering students. 

The GenCyber Teacher Academy (GTA) stands as a pioneering professional development initiative, empowering Connecticut's high school educators in diverse STEM fields to explore and integrate cybersecurity concepts into their teaching. The inaugural 2022 edition facilitated inquiry-based learning and collaborative discourse on GenCyber Cybersecurity Concepts. However, program evaluation uncovered areas for curriculum enhancement. This paper delineates the evaluation process, curriculum revisions, and their implementation outcomes. Findings demonstrate that the revised 2023 GTA fostered improved teacher engagement with modules, enhancing their ability to integrate cybersecurity principles while prioritizing online safety. Notably, the revised GTA fortified the sustainable GenCyber Teacher Academy Teaching and Learning Community, bolstering a network of educators and practitioners destined to collectively mold Connecticut's cybersecurity landscape. 

The field of automated face verification has become saturated in recent years, with state-of-the-art methods outperforming humans on all benchmarks. Many researchers would say that face verification is close to being a solved problem. We argue that evaluation datasets are not challenging enough, and that there is still significant room for improvement in automated face verification techniques. This paper introduces the DoppelVer dataset, a challenging face verification dataset consisting of doppelganger pairs. Doppelgangers are pairs of individuals that are extremely visually similar, oftentimes mistaken for one another. With this dataset, we introduce two challenging protocols: doppelganger and Visual Similarity from Embeddings (ViSE). The doppelganger protocol utilizes doppelganger pairs as negative verification samples. The ViSE protocol selects negative pairs by isolating image samples that are very close together in a particular embedding space. In order to demonstrate the challenge that the DoppelVer dataset poses, we evaluate a state-of-the-art face verification method on the dataset. Our experiments demonstrate that the DoppelVer dataset is significantly more challenging than its predecessors, indicating that there is still room for improvement in face verification technology. 

Circadian rhythms play a vital role in maintaining a person’s well-being but remain difficult to quantify accurately. Numerous approaches exist to measure these rhythms, but they often suffer from performance issues on the individual level. This work implements a Steady-State Kalman Filter as a method for estimating the circadian phase shifts from biometric signals. Our framework can automatically fit the filter’s parameters to biometric data obtained for each individual, and we were able to consistently estimate the phase shift within 1 hour of melatonin estimates on 100% of all subjects in this study. The estimation method opens up the possibility of real-time control and assessment of the circadian system, as well as chronotherapeutic intervention. 

Context.Blazars are beamed active galactic nuclei (AGNs) known for their strong multi-wavelength variability on timescales ranging from years down to minutes. Many different models have been proposed to explain this variability. Aims.We aim to investigate the suitability of the twisting jet model presented in previous works to explain the multi-wavelength behaviour of BL Lacertae, the prototype of one of the blazar classes. According to this model, the jet is inhomogeneous, curved, and twisting, and the long-term variability is due to changes in the Doppler factor due to variations in the orientation of the jet-emitting regions. Methods.We analysed optical data of the source obtained during monitoring campaigns organised by the Whole Earth Blazar Telescope (WEBT) in 2019–2022, together with radio data from the WEBT and other teams, andγ-ray data from theFermisatellite. In this period, BL Lacertae underwent an extraordinary activity phase, reaching its historical optical andγ-ray brightness maxima. Results.The application of the twisting jet model to the source light curves allows us to infer the wiggling motion of the optical, radio, andγ-ray jet-emitting regions. The optical-radio correlation shows that the changes in the radio viewing angle follow those in the optical viewing angle by about 120 days, and it suggests that the jet is composed of plasma filaments, which is in agreement with some radio high-resolution observations of other sources. Theγ-ray emitting region is found to be co-spatial with the optical one, and the analysis of theγ-optical correlation is consistent with both the geometric interpretation and a synchrotron self-Compton (SSC) origin of the high-energy photons. Conclusions.We propose a geometric scenario where the jet is made up of a pair of emitting plasma filaments in a sort of double-helix curved rotating structure, whose wiggling motion produces changes in the Doppler beaming and can thus explain the observed multi-wavelength long-term variability. 

Abstract Dysregulated arousal often accompanies neurodevelopmental disorders such as attention deficit hyperactivity disorder and autism spectrum disorder. Recently, we have found that adolescent homozygous Brattleboro (Hom) rats, which contain a mutation in the arginine vasopressin (AVP) gene, exhibit lower behavioral arousal than their heterozygous (Het) littermates in the open field test. This hypoaroused phenotype could be due to loss of AVP in magnocellular cells that supply AVP to the peripheral circulation and project to limbic structures or parvocellular cells that regulate the stress axis and other central targets. Alternatively, hypoarousal could be a side effect of diabetes insipidus – polydipsia and polyuria seen in Hom rats due to loss of AVP facilitation of water reabsorption in the kidney. We developed a viral-rescue approach to “cure” magnocellular AVP cells of their Brattleboro mutation. Infusion of a recombinant adeno-associated virus (rAAV) containing a functionalAvpgene and promoter (rAAV-AVP) rescued AVP within magnocellular cells and fiber projections of the paraventricular nucleus of the hypothalamus (PVN) of male and female adolescent Hom rats. Furthermore, water intake was markedly reduced, ameliorating the symptoms of diabetes insipidus. In contrast, open field activity was unaffected. These findings indicate that the hyporaoused phenotype of adolescent Hom rats is not due to the loss of AVP function in magnocellular cells or a side effect of diabetes insipidus, but favors the hypothesis that central, parvocellular AVP mechanisms underlie the regulation of arousal during adolescence. 

This paper presents a search for massive, charged, long-lived particles with the ATLAS detector at the Large Hadron Collider using an integrated luminosity of $$140~fb^{−1}$$ of proton-proton collisions at $$\sqrt{s}=13$$~TeV. These particles are expected to move significantly slower than the speed of light. In this paper, two signal regions provide complementary sensitivity. In one region, events are selected with at least one charged-particle track with high transverse momentum, large specific ionisation measured in the pixel detector, and time of flight to the hadronic calorimeter inconsistent with the speed of light. In the other region, events are selected with at least two tracks of opposite charge which both have a high transverse momentum and an anomalously large specific ionisation. The search is sensitive to particles with lifetimes greater than about 3 ns with masses ranging from 200 GeV to 3 TeV. The results are interpreted to set constraints on the supersymmetric pair production of long-lived R-hadrons, charginos and staus, with mass limits extending beyond those from previous searches in broad ranges of lifetime 

This report presents a comprehensive collection of searches for new physics performed by the ATLAS Collaboration during the Run~2 period of data taking at the Large Hadron Collider, from 2015 to 2018, corresponding to about 140~$$^{-1}$$ of $$\sqrt{s}=13$$~TeV proton--proton collision data. These searches cover a variety of beyond-the-standard model topics such as dark matter candidates, new vector bosons, hidden-sector particles, leptoquarks, or vector-like quarks, among others. Searches for supersymmetric particles or extended Higgs sectors are explicitly excluded as these are the subject of separate reports by the Collaboration. For each topic, the most relevant searches are described, focusing on their importance and sensitivity and, when appropriate, highlighting the experimental techniques employed. In addition to the description of each analysis, complementary searches are compared, and the overall sensitivity of the ATLAS experiment to each type of new physics is discussed. Summary plots and statistical combinations of multiple searches are included whenever possible. 

Top-quark pair production is observed in lead–lead ( $\mathrm{Pb}+\mathrm{Pb}$) collisions at $\sqrt{s_{\mathrm{NN}}}=5.02\mathrm{TeV}$at the Large Hadron Collider with the ATLAS detector. The data sample was recorded in 2015 and 2018, amounting to an integrated luminosity of $1.9{\mathrm{nb}}^{-1}$. Events with exactly one electron and one muon and at least two jets are selected. Top-quark pair production is measured with an observed (expected) significance of 5.0 (4.1) standard deviations. The measured top-quark pair production cross section is ${\sigma }_{t\overline{t}}=3.6{}_{-0.9}^{+1.0}\left(\mathrm{stat}\right){}_{-0.5}^{+0.8}\left(\mathrm{syst}\right)\mathrm{\mu }\mathrm{b}$, with a total relative uncertainty of 31%, and is consistent with theoretical predictions using a range of different nuclear parton distribution functions. The observation of this process consolidates the evidence of the existence of all quark flavors in the preequilibrium stage of the quark-gluon plasma at very high energy densities, similar to the conditions present in the early Universe. © 2025 CERN, for the ATLAS Collaboration2025CERN