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1. A novel liquid argon purity monitor based on 207 Bi

Author: Baibussinov, B., Bettini, M., Fabris, F., Gan, R., Guglielmi, A., Gurung, G., Marchini, S., Meng, G., Nicoletto, M., Pietropaolo, F., Pons, X., Rampazzo, G., Triozzi, R., Varanini, F., and Voirin, B.
Subjects: Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract: A novel liquid argon purity monitor based on a 207 Bi radioactive source, emitting monochromatic internal-conversion electrons, is presented. This new monitor allows for a very precise and fast measurement of the electronegative impurities concentration in liquid argon. It can be operated continuously in liquid argon TPC experiments without interfering with the main detector operation. Different drift lengths can be assembled for the proposed device, to assess a large range of liquid argon purities while minimizing systematic uncertainties. Two prototypes have been built and successfully operated in dedicated test stands. The results and performance are reported., Comment: 11 pages, 8 figures, 12 references
Published: 2024

2. Enhanced Thermodynamic Stability of Delithiated Nano-LiCoO2 by Lanthanum Doping.

Author: Dahl, Spencer, Costa, Luelc, Bettini, Jefferson, Souza, Flavio, and Castro, Ricardo
Abstract: The dynamic environment within lithium-ion batteries induces significant changes in local thermodynamic functions, hampering the accurate prediction of the stability of the cathodes during cycling. While delithiation primarily affects the surface properties of the cathode structure, there is a lack of fundamental understanding concerning the evolution of interfacial energies with varying stoichiometry. Here, we used microcalorimetry to quantify the thermodynamic changes between the stoichiometric and partially delithiated nano-LiCoO2 states for the first time. A mild delithiation from LiCoO2 to Li0.71CoO2 caused a surface energy reduction, negatively affecting the adhesion between adjacent grains by ∼0.4J/m2. The introduction of lanthanum at 1.0 atom % reduced the surface energy of the stoichiometric LiCoO2 while forcing a constant surface energy state during delithiation down to Li0.57CoO2. This reduced the thermodynamic stress between grains during lithium cycling, mitigating degradation mechanisms. The lanthanum-induced surface stabilization also inhibited the coarsening and dissolution of the cathode particles. We used electron microscopy to propose an atomistic mechanism by which the lanthanum doping pins surface dissolution for improved cathode stability.
Published: 2024

3. Study of charging-up of PCB planes for neutrino experiment readout

Author: Baibussinov, B., Bettini, M., Fabris, F., Guglielmi, A., Marchini, S., Meng, G., Nicoletto, M., Pietropaolo, F., Rampazzo, G., Triozzi, R., and Varanini, F.
Subjects: Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract: The use of double-faced, metallized, perforated PCB planes, segmented into strips for the anodic read-out of ionization signals in liquid argon TPCs, is emerging as a promising technology for charge readout in liquid argon TPCs used in large volume detectors.As a proof of concept, a prototype liquid Argon TPC hosting this new anode configuration based on single side perforated PCB planes has been constructed and exposed to cosmic rays at LNL in Italy. Tests were performed with both the metallized and insulating sides of the anode facing the drift volume, providing the first evidence of the focusing effect on drift electron trajectories through the PCB holes due to charge accumulation on the insulator surface., Comment: 12 pages, 13 figures
Published: 2024

4. Using Large Language Models to Compare Explainable Models for Smart Home Human Activity Recognition

Author: Fiori, Michele, Civitarese, Gabriele, and Bettini, Claudio
Subjects: Computer Science - Human-Computer Interaction, Computer Science - Artificial Intelligence
Abstract: Recognizing daily activities with unobtrusive sensors in smart environments enables various healthcare applications. Monitoring how subjects perform activities at home and their changes over time can reveal early symptoms of health issues, such as cognitive decline. Most approaches in this field use deep learning models, which are often seen as black boxes mapping sensor data to activities. However, non-expert users like clinicians need to trust and understand these models' outputs. Thus, eXplainable AI (XAI) methods for Human Activity Recognition have emerged to provide intuitive natural language explanations from these models. Different XAI methods generate different explanations, and their effectiveness is typically evaluated through user surveys, that are often challenging in terms of costs and fairness. This paper proposes an automatic evaluation method using Large Language Models (LLMs) to identify, in a pool of candidates, the best XAI approach for non-expert users. Our preliminary results suggest that LLM evaluation aligns with user surveys., Comment: Accepted for publication at UbiComp / ISWC 2024's XAIforU workshop
Published: 2024

5. Large Language Models are Zero-Shot Recognizers for Activities of Daily Living

Author: Civitarese, Gabriele, Fiori, Michele, Choudhary, Priyankar, and Bettini, Claudio
Subjects: Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Electrical Engineering and Systems Science - Signal Processing
Abstract: The sensor-based recognition of Activities of Daily Living (ADLs) in smart home environments enables several applications in the areas of energy management, safety, well-being, and healthcare. ADLs recognition is typically based on deep learning methods requiring large datasets to be trained. Recently, several studies proved that Large Language Models (LLMs) effectively capture common-sense knowledge about human activities. However, the effectiveness of LLMs for ADLs recognition in smart home environments still deserves to be investigated. In this work, we propose ADL-LLM, a novel LLM-based ADLs recognition system. ADLLLM transforms raw sensor data into textual representations, that are processed by an LLM to perform zero-shot ADLs recognition. Moreover, in the scenario where a small labeled dataset is available, ADL-LLM can also be empowered with few-shot prompting. We evaluated ADL-LLM on two public datasets, showing its effectiveness in this domain., Comment: Currently under review
Published: 2024

6. No Child Left behind and the Individuals with Disabilities Education Act: Examining Special Educators' Outcomes

Author: Tuan D. Nguyen, Christopher Redding, Allison F. Gilmour, and Elizabeth Bettini
Abstract: Drawing on eight waves of the Schools and Staffing Survey and the National Teacher and Principal Survey, we used a difference-in-differences research design to examine special education teachers' (SETs) responses to No Child Left Behind (NCLB) and the subsequent reauthorization of the Individuals with Disabilities Education Act (IDEA). IDEA was associated with decreases in the proportion of SETs with special education as a field of study and graduate degrees, an increase in co-teaching, and a decrease in the proportion of SETs working in a resource delivery model, with no evidence that NCLB influenced these outcomes. Little consistent evidence was found to indicate these federal policies influenced SETs' job attitudes (e.g., job satisfaction). We identified differences in these associations based on school poverty status and grade level. These findings help to better understand the status and challenges of the current SET workforce and the unintended consequences of federal reform policies.
Published: 2024
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7. Review of Particle Physics*

Author: Navas, S, Amsler, C, Gutsche, T, Hanhart, C, Hernández-Rey, JJ, Lourenço, C, Masoni, A, Mikhasenko, M, Mitchell, RE, Patrignani, C, Schwanda, C, Spanier, S, Venanzoni, G, Yuan, CZ, Agashe, K, Aielli, G, Allanach, BC, Alvarez-Muñiz, J, Antonelli, M, Aschenauer, EC, Asner, DM, Assamagan, K, Baer, H, Banerjee, Sw, Barnett, RM, Baudis, L, Bauer, CW, Beatty, JJ, Beringer, J, Bettini, A, Biebel, O, Black, KM, Blucher, E, Bonventre, R, Briere, RA, Buckley, A, Burkert, VD, Bychkov, MA, Cahn, RN, Cao, Z, Carena, M, Casarosa, G, Ceccucci, A, Cerri, A, Chivukula, RS, Cowan, G, Cranmer, K, Crede, V, Cremonesi, O, D’Ambrosio, G, Damour, T, de Florian, D, de Gouvêa, A, DeGrand, T, Demers, S, Demiragli, Z, Dobrescu, BA, D’Onofrio, M, Doser, M, Dreiner, HK, Eerola, P, Egede, U, Eidelman, S, El-Khadra, AX, Ellis, J, Eno, SC, Erler, J, Ezhela, VV, Fava, A, Fetscher, W, Fields, BD, Freitas, A, Gallagher, H, Gershon, T, Gershtein, Y, Gherghetta, T, Gonzalez-Garcia, MC, Goodman, M, Grab, C, Gritsan, AV, Grojean, C, Groom, DE, Grünewald, M, Gurtu, A, Haber, HE, Hamel, M, Hashimoto, S, Hayato, Y, Hebecker, A, Heinemeyer, S, Hikasa, K, Hisano, J, Höcker, A, Holder, J, Hsu, L, Huston, J, Hyodo, T, Ianni, Al, Kado, M, and Karliner, M
Subjects: Nuclear and Plasma Physics, Particle and High Energy Physics, Physical Sciences
Abstract: The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 2,717 new measurements from 869 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Most of the 120 reviews are updated, including many that are heavily revised. The Review is divided into two volumes. Volume 1 includes the Summary Tables and 97 review articles. Volume 2 consists of the Particle Listings and contains also 23 reviews that address specific aspects of the data presented in the Listings. The complete Review (both volumes) is published online on the website of the Particle Data Group (pdg.lbl.gov) and in a journal. Volume 1 is available in print as the PDG Book. A Particle Physics Booklet with the Summary Tables and essential tables, figures, and equations from selected review articles is available in print, as a web version optimized for use on phones, and as an Android app. The 2024 edition of the Review of Particle Physics should be cited as: S. Navas et al. (Particle Data Group), Phys. Rev. D 110, 030001 (2024)
Published: 2024

8. Searches for new physics below twice the electron mass with GERDA

Author: GERDA Collaboration, Agostini, M., Alexander, A., Araujo, G. R., Bakalyarov, A. M., Balata, M., Barabanov, I., Baudis, L., Bauer, C., Belogurov, S., Bettini, A., Bezrukov, L., Biancacci, V., Bossio, E., Bothe, V., Brugnera, R., Caldwell, A., Calgaro, S., Cattadori, C., Chernogorov, A., Chiu, P. -J., Comellato, T., D'Andrea, V., Demidova, E. V., Di Marco, N., Doroshkevich, E., Fomina, M., Gangapshev, A., Garfagnini, A., Gooch, C., Grabmayr, P., Gurentsov, V., Gusev, K., Hakenmüller, J., Hemmer, S., Hofmann, W., Huang, J., Hult, M., Inzhechik, L. V., Csáthy, J. Janicskó, Jochum, J., Junker, M., Kazalov, V., Kermaïdic, Y., Khushbakht, H., Kihm, T., Kilgus, K., Kirpichnikov, I. V., Klimenko, A., Knöpfle, K. T., Kochetov, O., Kornoukhov, V. N., Krause, P., Kuzminov, V. V., Laubenstein, M., Lindner, M., Lippi, I., Lubashevskiy, A., Lubsandorzhiev, B., Lutter, G., Macolino, C., Majorovits, B., Maneschg, W., Marshall, G., Misiaszek, M., Morella, M., Müller, Y., Nemchenok, I., Neuberger, M., Pandola, L., Pelczar, K., Pertoldi, L., Piseri, P., Pullia, A., Ransom, C., Rauscher, L., Redchuk, M., Riboldi, S., Rumyantseva, N., Sada, C., Sailer, S., Salamida, F., Schönert, S., Schreiner, J., Schütz, A-K., Schulz, O., Schwarz, M., Schwingenheuer, B., Selivanenko, O., Shevchik, E., Shirchenko, M., Shtembari, L., Simgen, H., Smolnikov, A., Stukov, D., Sullivan, S., Vasenko, A. A., Veresnikova, A., Vignoli, C., von Sturm, K., Wester, T., Wiesinger, C., Wojcik, M., Yanovich, E., Zatschler, B., Zhitnikov, I., Zhukov, S. V., Zinatulina, D., Zschocke, A., Zuber, K., and Zuzel, G.
Subjects: Nuclear Experiment, High Energy Physics - Experiment
Abstract: A search for full energy depositions from bosonic keV-scale dark matter candidates of masses between 65 keV and 1021 keV has been performed with data collected during Phase II of the GERmanium Detector Array (GERDA) experiment. Our analysis includes direct dark matter absorption as well as dark Compton scattering. With a total exposure of 105.5 kg yr, no evidence for a signal above the background has been observed. The resulting exclusion limits deduced with either Bayesian or Frequentist statistics are the most stringent direct constraints in the major part of the 140-1021 keV mass range. As an example, at a mass of 150 keV the dimensionless coupling of dark photons and axion-like particles to electrons has been constrained to $\alpha$'/$\alpha$ < 8.7x10$^{-24}$ and g$_{ae}$ < 3.3x10$^{-12}$ at 90% credible interval (CI), respectively. Additionally, a search for peak-like signals from beyond the Standard Model decays of nucleons and electrons is performed. We find for the inclusive decay of a single neutron in $^{76}$Ge a lower lifetime limit of $\tau_n$ > 1.5x10$^{24}$ yr and for a proton $\tau_p$ > 1.3x10$^{24}$ yr at 90% CI. For the electron decay e$^-\rightarrow\nu_e\gamma$ a lower limit of $\tau_e$ > 5.4x10$^{25}$ yr at 90% CI has been determined., Comment: 20 pages, 12 figures, 7 tables
Published: 2024

9. Controlling Behavioral Diversity in Multi-Agent Reinforcement Learning

Author: Bettini, Matteo, Kortvelesy, Ryan, and Prorok, Amanda
Subjects: Computer Science - Multiagent Systems, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Computer Science - Robotics
Abstract: The study of behavioral diversity in Multi-Agent Reinforcement Learning (MARL) is a nascent yet promising field. In this context, the present work deals with the question of how to control the diversity of a multi-agent system. With no existing approaches to control diversity to a set value, current solutions focus on blindly promoting it via intrinsic rewards or additional loss functions, effectively changing the learning objective and lacking a principled measure for it. To address this, we introduce Diversity Control (DiCo), a method able to control diversity to an exact value of a given metric by representing policies as the sum of a parameter-shared component and dynamically scaled per-agent components. By applying constraints directly to the policy architecture, DiCo leaves the learning objective unchanged, enabling its applicability to any actor-critic MARL algorithm. We theoretically prove that DiCo achieves the desired diversity, and we provide several experiments, both in cooperative and competitive tasks, that show how DiCo can be employed as a novel paradigm to increase performance and sample efficiency in MARL. Multimedia results are available on the paper's website: https://sites.google.com/view/dico-marl.
Published: 2024

10. The Cambridge RoboMaster: An Agile Multi-Robot Research Platform

Author: Blumenkamp, Jan, Shankar, Ajay, Bettini, Matteo, Bird, Joshua, and Prorok, Amanda
Subjects: Computer Science - Robotics, Computer Science - Multiagent Systems, Electrical Engineering and Systems Science - Systems and Control
Abstract: Compact robotic platforms with powerful compute and actuation capabilities are key enablers for practical, real-world deployments of multi-agent research. This article introduces a tightly integrated hardware, control, and simulation software stack on a fleet of holonomic ground robot platforms designed with this motivation. Our robots, a fleet of customised DJI Robomaster S1 vehicles, offer a balance between small robots that do not possess sufficient compute or actuation capabilities and larger robots that are unsuitable for indoor multi-robot tests. They run a modular ROS2-based optimal estimation and control stack for full onboard autonomy, contain ad-hoc peer-to-peer communication infrastructure, and can zero-shot run multi-agent reinforcement learning (MARL) policies trained in our vectorized multi-agent simulation framework. We present an in-depth review of other platforms currently available, showcase new experimental validation of our system's capabilities, and introduce case studies that highlight the versatility and reliability of our system as a testbed for a wide range of research demonstrations. Our system as well as supplementary material is available online. https://proroklab.github.io/cambridge-robomaster
Published: 2024

11. Reduced Order Modeling for Real-Time Monitoring of Structural Displacements due to Electromagnetic Forces in Large Scale Tokamaks

Author: Lucchini, Francesco, Frescura, Alessandro, Torchio, Riccardo, Alotto, Piergiorgio, and Bettini, Paolo
Subjects: Mathematics - Numerical Analysis
Abstract: The real-time monitoring of the structural displacement of the Vacuum Vessel (VV) of thermonuclear fusion devices caused by electromagnetic (EM) loads is of great interest. In this paper, Model Order Reduction (MOR) is applied to the Integral Equation Methods (IEM) and the Finite Elements Method (FEM) to develop Electromagnetic and Structural Reduced Order Models (ROMs) compatible with real-time execution which allows for the real-time monitoring of strain and displacement in critical positions of Tokamaks machines. Low-rank compression techniques based on hierarchical matrices are applied to reduce the computational cost during the offline stage when the ROMs are constructed. Numerical results show the accuracy of the approach and demonstrate the compatibility with real-time execution in standard hardware.
Published: 2024

12. Comparing Self-Supervised Learning Techniques for Wearable Human Activity Recognition

Author: Ek, Sannara, Presotto, Riccardo, Civitarese, Gabriele, Portet, François, Lalanda, Philippe, and Bettini, Claudio
Subjects: Electrical Engineering and Systems Science - Signal Processing, Computer Science - Human-Computer Interaction, I.2
Abstract: Human Activity Recognition (HAR) based on the sensors of mobile/wearable devices aims to detect the physical activities performed by humans in their daily lives. Although supervised learning methods are the most effective in this task, their effectiveness is constrained to using a large amount of labeled data during training. While collecting raw unlabeled data can be relatively easy, annotating data is challenging due to costs, intrusiveness, and time constraints. To address these challenges, this paper explores alternative approaches for accurate HAR using a limited amount of labeled data. In particular, we have adapted recent Self-Supervised Learning (SSL) algorithms to the HAR domain and compared their effectiveness. We investigate three state-of-the-art SSL techniques of different families: contrastive, generative, and predictive. Additionally, we evaluate the impact of the underlying neural network on the recognition rate by comparing state-of-the-art CNN and transformer architectures. Our results show that a Masked Auto Encoder (MAE) approach significantly outperforms other SSL approaches, including SimCLR, commonly considered one of the best-performing SSL methods in the HAR domain. The code and the pre-trained SSL models are publicly available for further research and development.
Published: 2024

13. ContextGPT: Infusing LLMs Knowledge into Neuro-Symbolic Activity Recognition Models

Author: Arrotta, Luca, Bettini, Claudio, Civitarese, Gabriele, and Fiori, Michele
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Computation and Language
Abstract: Context-aware Human Activity Recognition (HAR) is a hot research area in mobile computing, and the most effective solutions in the literature are based on supervised deep learning models. However, the actual deployment of these systems is limited by the scarcity of labeled data that is required for training. Neuro-Symbolic AI (NeSy) provides an interesting research direction to mitigate this issue, by infusing common-sense knowledge about human activities and the contexts in which they can be performed into HAR deep learning classifiers. Existing NeSy methods for context-aware HAR rely on knowledge encoded in logic-based models (e.g., ontologies) whose design, implementation, and maintenance to capture new activities and contexts require significant human engineering efforts, technical knowledge, and domain expertise. Recent works show that pre-trained Large Language Models (LLMs) effectively encode common-sense knowledge about human activities. In this work, we propose ContextGPT: a novel prompt engineering approach to retrieve from LLMs common-sense knowledge about the relationship between human activities and the context in which they are performed. Unlike ontologies, ContextGPT requires limited human effort and expertise. An extensive evaluation carried out on two public datasets shows how a NeSy model obtained by infusing common-sense knowledge from ContextGPT is effective in data scarcity scenarios, leading to similar (and sometimes better) recognition rates than logic-based approaches with a fraction of the effort.
Published: 2024

14. The Impact of a $10,000 Bonus on Special Education Teacher Shortages in Hawai'i. Working Paper No. 290-0823

Author: National Center for Analysis of Longitudinal Data in Education Research (CALDER) at American Institutes for Research (AIR), Roddy Theobald, Zeyu Xu, Allison Gilmour, Lisa Lachlan-Hache, Liz Bettini, and Nathan Jones
Abstract: We study the impact of a bonus policy implemented by Hawai'i Public Schools starting in fall 2020 that raised the salaries of all special education teachers in the state by $10,000. We estimate that the introduction of this policy reduced the proportion of vacant special education teaching positions by 32%, or 1.2 percentage points, and the proportion of special education positions that were vacant or filled by an unlicensed teacher by 35%, or 4.0 percentage points. The bonus policy did not have significant impacts on special education teacher retention; instead, the impacts of the policy were driven almost entirely by an increase in the number of general education teachers in the state who moved into open special education teaching positions. The effects of the bonus policy were also largest in historically hard-to-staff schools in which all teachers also received "tiered school" bonuses of up to $8,000. Hawai'i therefore represents a unique but instructive case of how strategic financial incentives can help address special education teacher shortages.
Published: 2023

15. Diverse mechanisms of leukemogenesis associated with PAX5 germline mutation

Author: Bettini, Laura Rachele, Fazio, Grazia, Saitta, Claudia, Piazza, Rocco, Palamini, Sonia, Buracchi, Chiara, Rebellato, Stefano, Santoro, Nicola, Simone, Cristiano, Biondi, Andrea, and Cazzaniga, Giovanni
Published: 2024
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16. SICOB Italian clinical practice guidelines for the surgical treatment of obesity and associated diseases using GRADE methodology on bariatric and metabolic surgery

Author: De Luca, Maurizio, Zese, Monica, Bandini, Giulia, Zappa, Marco Antonio, Bardi, Ugo, Carbonelli, Maria Grazia, Carrano, Francesco Maria, Casella, Giovanni, Chianelli, Marco, Chiappetta, Sonja, Iossa, Angelo, Martinino, Alessandro, Micanti, Fausta, Navarra, Giuseppe, Piatto, Giacomo, Raffaelli, Marco, Romano, Eugenia, Rugolotto, Simone, Serra, Roberto, Soricelli, Emanuele, Vitiello, Antonio, Schiavo, Luigi, Zani, Iris Caterina Maria, Ragghianti, Benedetta, Lorenzoni, Valentina, Medea, Gerardo, Antognozzi, Valentina, Bellini, Rosario, Berardi, Giovanna, Campanile, Fabio Cesare, Facchiano, Enrico, Foletto, Mirto, Gentileschi, Paolo, Olmi, Stefano, Petrelli, Massimiliano, Pilone, Vincenzo, Sarro, Giuliano, Ballardini, Donatella, Bettini, Dario, Costanzi, Andrea, Frattini, Francesco, Lezoche, Giovanni, Neri, Barbara, Porri, Debora, Rizzi, Andrea, Rossini, Roberto, Sessa, Luca, D’Alessio, Rossella, Di Mauro, Gianluca, Tolone, Salvatore, Bernante, Paolo, Docimo, Ludovico, Foschi, Diego, Angrisani, Luigi, Basso, Nicola, Busetto, Luca, Di Lorenzo, Nicola, Disoteo, Olga, Forestieri, Pietro, Musella, Mario, Paolini, Barbara, Silecchia, Gianfranco, and Monami, Matteo
Published: 2024
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17. A Descriptive Portrait of the Paraeducator Workforce in Washington State. Working Paper No. 283-0423

Author: National Center for Analysis of Longitudinal Data in Education Research (CALDER) at American Institutes for Research (AIR), Theobald, Roddy, Kaler, Lindsey, Bettini, Elizabeth, and Jones, Nathan
Abstract: We use over 25 years of longitudinal data from Washington state to provide a descriptive portrait of the paraeducator workforce in the state. Paraeducators are more racially and ethnically diverse than special education teachers, particularly in the last decade, and tend to be less experienced. They also have full-time salaries that are about half of the average special education teacher salary. Paraeducator-to-student ratios have decreased over time in the state, but they are higher in schools serving more students of color. Finally, and perhaps most importantly, paraeducator attrition rates from the state's public school workforce have increased dramatically over time; for example, the paraeducator attrition rate after the 2021-22 school year (23%) was over twice as high as the attrition rate after the 2008-09 school year (8%). These findings have implications for how policymakers and school leaders should approach decision-making related to the paraeducator workforce, as well as how researchers might approach further research with this group of educators.
Published: 2023

18. Model Reduction to Spectral Submanifolds in Non-Smooth Dynamical Systems

Author: Bettini, Leonardo, Cenedese, Mattia, and Haller, George
Subjects: Mathematics - Dynamical Systems
Abstract: We develop a model reduction technique for non-smooth dynamical systems using spectral submanifolds. Specifically, we construct low-dimensional, sparse, nonlinear and non-smooth models on unions of slow and attracting spectral submanifolds (SSMs) for each smooth subregion of the phase space and then properly match them. We apply this methodology to both equation-driven and data-driven problems, with and without external forcing., Comment: Submitted to International Journal of Non-Linear Mechanics
Published: 2023

19. BenchMARL: Benchmarking Multi-Agent Reinforcement Learning

Author: Bettini, Matteo, Prorok, Amanda, and Moens, Vincent
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Multiagent Systems
Abstract: The field of Multi-Agent Reinforcement Learning (MARL) is currently facing a reproducibility crisis. While solutions for standardized reporting have been proposed to address the issue, we still lack a benchmarking tool that enables standardization and reproducibility, while leveraging cutting-edge Reinforcement Learning (RL) implementations. In this paper, we introduce BenchMARL, the first MARL training library created to enable standardized benchmarking across different algorithms, models, and environments. BenchMARL uses TorchRL as its backend, granting it high performance and maintained state-of-the-art implementations while addressing the broad community of MARL PyTorch users. Its design enables systematic configuration and reporting, thus allowing users to create and run complex benchmarks from simple one-line inputs. BenchMARL is open-sourced on GitHub: https://github.com/facebookresearch/BenchMARL
Published: 2023

20. Dry powder formulations of hyperimmune serum

Author: Bianchera, Annalisa, Donofrio, Gaetano, Sonvico, Fabio, and Bettini, Ruggero
Published: 2024
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21. Thermal spray to embed optical fibers for the monitoring and protection of metallic structures

Author: Rigamonti, Daniela, Meneses Costa, Hector Reynaldo, Bilotti, Gianmarco, and Bettini, Paolo
Published: 2024
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22. Patterning edge-like defects and tuning defective areas on the basal plane of ultra-large MoS$_{2}$ monolayers toward hydrogen evolution reaction

Author: Florindo, Bianca Rocha, Hasimoto, Leonardo H., de Freitas, Nicolli, Candiotto, Graziâni, Lima, Erika Nascimento, de Lourenço, Cláudia, de Araujo, Ana B. S., Ospina, Carlos, Bettini, Jefferson, Leite, Edson R., Lima, Renato S., Fazzio, Adalberto, Capaz, Rodrigo B., and Santhiago, Murilo
Subjects: Condensed Matter - Materials Science
Abstract: The catalytic sites of MoS$_{2}$ monolayers towards hydrogen evolution are well known to be vacancies and edge-like defects. However, it is still very challenging to control the position, size, and defective areas on the basal plane of Mo$S_{2}$ monolayers by most of defect-engineering routes. In this work, the fabrication of etched arrays on ultra-large supported and free-standing MoS$_{2}$ monolayers using focused ion beam (FIB) is reported for the first time. By tuning the Ga+ ion dose, it is possible to confine defects near the etched edges or spread them over ultra-large areas on the basal plane. The electrocatalytic activity of the arrays toward hydrogen evolution reaction (HER) was measured by fabricating microelectrodes using a new method that preserves the catalytic sites. We demonstrate that the overpotential can be decreased up to 290 mV by assessing electrochemical activity only at the basal plane. High-resolution transmission electron microscopy images obtained on FIB patterned freestanding MoS$_{2}$ monolayers reveal the presence of amorphous regions and X-ray photoelectron spectroscopy indicates sulfur excess in these regions. Density-functional theory calculations provide identification of catalytic defect sites. Our results demonstrate a new rational control of amorphous-crystalline surface boundaries and future insight for defect optimization in MoS$_{2}$ monolayers., Comment: 10 pages, 5 figures
Published: 2023
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23. An improved limit on the neutrinoless double-electron capture of $^{36}$Ar with GERDA

Author: GERDA Collaboration, Agostini, M., Alexander, A., Araujo, G. R., Bakalyarov, A. M., Balata, M., Barabanov, I., Baudis, L., Bauer, C., Belogurov, S., Bettini, A., Bezrukov, L., Biancacci, V., Bossio, E., Bothe, V., Brudanin, V., Brugnera, R., Caldwell, A., Cattadori, C., Chernogorov, A., Comellato, T., D'Andrea, V., Demidova, E. V., Di Marco, N., Doroshkevich, E., Fischer, F., Fomina, M., Gangapshev, A., Garfagnini, A., Gooch, C., Grabmayr, P., Gurentsov, V., Gusev, K., Hakenmüller, J., Hemmer, S., Hofmann, W., Huang, J., Hult, M., Inzhechik, L. V., Csáthy, J. Janicskó, Jochum, J., Junker, M., Kazalov, V., Kermaïdic, Y., Khushbakht, H., Kihm, T., Kilgus, K., Kirpichnikov, I. V., Klimenko, A., Kneißl, R., Knöpfle, K. T., Kochetov, O., Kornoukhov, V. N., Korošec, M., Krause, P., Kuzminov, V. V., Laubenstein, M., Lindner, M., Lippi, I., Lubashevskiy, A., Lubsandorzhiev, B., Lutter, G., Macolino, C., Majorovits, B., Maneschg, W., Manzanillas, L., Marshall, G., Misiaszek, M., Morella, M., Müller, Y., Nemchenok, I., Pandola, L., Pelczar, K., Pertoldi, L., Piseri, P., Pullia, A., Ransom, C., Rauscher, L., Redchuk, M., Riboldi, S., Rumyantseva, N., Sada, C., Salamida, F., Schönert, S., Schreiner, J., Schütt, M., Schütz, A-K., Schulz, O., Schwarz, M., Schwingenheuer, B., Selivanenko, O., Shevchik, E., Shirchenko, M., Shtembari, L., Simgen, H., Smolnikov, A., Stukov, D., Vasenko, A. A., Veresnikova, A., Vignoli, C., von Sturm, K., Wester, T., Wiesinger, C., Wojcik, M., Yanovich, E., Zatschler, B., Zhitnikov, I., Zhukov, S. V., Zinatulina, D., Zschocke, A., Zsigmond, A. J., Zuber, K., and Zuzel, G.
Subjects: Nuclear Experiment
Abstract: The GERmanium Detector Array (GERDA) experiment operated enriched high-purity germanium detectors in a liquid argon cryostat, which contains 0.33% of $^{36}$Ar, a candidate isotope for the two-neutrino double-electron capture (2$\nu$ECEC) and therefore for the neutrinoless double-electron capture (0$\nu$ECEC). If detected, this process would give evidence of lepton number violation and the Majorana nature of neutrinos. In the radiative 0$\nu$ECEC of $^{36}$Ar, a monochromatic photon is emitted with an energy of 429.88 keV, which may be detected by the GERDA germanium detectors. We searched for the $^{36}$Ar 0$\nu$ECEC with GERDA data, with a total live time of 4.34 yr (3.08 yr accumulated during GERDA Phase II and 1.26 yr during GERDA Phase I). No signal was found and a 90% C.L. lower limit on the half-life of this process was established T$_{1/2}$ > 1.5x10$^{22}$ yr, Comment: 10 pages, 5 figures, 1 table
Published: 2023

24. Searches for new physics below twice the electron mass with GERDA

Author: Agostini, M., Alexander, A., Araujo, G., Bakalyarov, A. M., Balata, M., Barabanov, I., Baudis, L., Bauer, C., Belogurov, S., Bettini, A., Bezrukov, L., Biancacci, V., Bossio, E., Bothe, V., Brugnera, R., Caldwell, A., Calgaro, S., Cattadori, C., Chernogorov, A., Chiu, P.-J., Comellato, T., D’Andrea, V., Demidova, E. V., Marco, N. Di, Doroshkevich, E., Fomina, M., Gangapshev, A., Garfagnini, A., Gooch, C., Grabmayr, P., Gurentsov, V., Gusev, K., Hakenmüller, J., Hemmer, S., Hofmann, W., Huang, J., Hult, M., Inzhechik, L. V., Csáthy, J. Janicskó, Jochum, J., Junker, M., Kazalov, V., Kermaïdic, Y., Khushbakht, H., Kihm, T., Kilgus, K., Kirpichnikov, I. V., Klimenko, A., Knöpfle, K. T., Kochetov, O., Kornoukhov, V. N., Krause, P., Kuzminov, V. V., Laubenstein, M., Lindner, M., Lippi, I., Lubashevskiy, A., Lubsandorzhiev, B., Lutter, G., Macolino, C., Majorovits, B., Maneschg, W., Marshall, G., Misiaszek, M., Morella, M., Müller, Y., Nemchenok, I., Neuberger, M., Pandola, L., Pelczar, K., Pertoldi, L., Piseri, P., Pullia, A., Ransom, C., Rauscher, L., Redchuk, M., Riboldi, S., Rumyantseva, N., Sada, C., Sailer, S., Salamida, F., Schönert, S., Schreiner, J., Schütz, A-K., Schulz, O., Schwarz, M., Schwingenheuer, B., Selivanenko, O., Shevchik, E., Shirchenko, M., Shtembari, L., Simgen, H., Smolnikov, A., Stukov, D., Sullivan, S., Vasenko, A. A., Veresnikova, A., Vignoli, C., Sturm, K. von, Wester, T., Wiesinger, C., Wojcik, M., Yanovich, E., Zatschler, B., Zhitnikov, I., Zhukov, S. V., Zinatulina, D., Zschocke, A., Zuber, K., and Zuzel, G.
Published: 2024
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25. European Association for the Study of Obesity (EASO) Position Statement on Medical Nutrition Therapy for the Management of Individuals with Overweight or Obesity and Cancer

Author: Giovanna Muscogiuri, Luigi Barrea, Silvia Bettini, Marwan El Ghoch, Niki Katsiki, Liisa Tolvanen, Ludovica Verde, Annamaria Colao, Luca Busetto, Volkan Demirhan Yumuk, and Maria Hassapidou
Subjects: obesity, cancer, diet, nutrition, mediterranean diet, ketogenic diet, intermittent fasting, Nutrition. Foods and food supply, TX341-641, Nutritional diseases. Deficiency diseases, RC620-627
Abstract: Obesity, a prevalent and multifactorial disease, is linked to a range of metabolic abnormalities, including insulin resistance, dyslipidemia, and chronic inflammation. These imbalances not only contribute to cardiometabolic diseases but also play a significant role in cancer pathogenesis. The rising prevalence of obesity underscores the need to investigate dietary strategies for effective weight management for individuals with overweight or obesity and cancer. This European Society for the Study of Obesity (EASO) position statement aimed to summarize current evidence on the role of obesity in cancer and to provide insights on the major nutritional interventions, including the Mediterranean diet (MedDiet), the ketogenic diet (KD), and the intermittent fasting (IF), that should be adopted to manage individuals with overweight or obesity and cancer. The MedDiet, characterized by high consumption of plant-based foods and moderate intake of olive oil, fish, and nuts, has been associated with a reduced cancer risk. The KD and the IF are emerging dietary interventions with potential benefits for weight loss and metabolic health. KD, by inducing ketosis, and IF, through periodic fasting cycles, may offer anticancer effects by modifying tumor metabolism and improving insulin sensitivity. Despite the promising results, current evidence on these dietary approaches in cancer management in individuals with overweight or obesity is limited and inconsistent, with challenges including variability in adherence and the need for personalized dietary plans.
Published: 2024
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26. Validation of a radiosynthesis method and a novel quality control system for [68 Ga]Ga-MAA: is TLC enough to assess radiopharmaceutical quality?

Author: Silvia Migliari, Stefano Bruno, Annalisa Bianchera, Ilaria De Nardis, Antonio Scarano, Monica Lusardi, Anna Gaiani, Alessandra Guercio, Maura Scarlattei, Giorgio Baldari, Ruggero Bettini, and Livia Ruffini
Subjects: [68 Ga]Ga-macroaggregated human serum albumin, Radiopharmaceuticals, High pressure liquid chromatography, SDS-PAGE, Morphological structure and size distribution, Lung perfusion imaging, Medical physics. Medical radiology. Nuclear medicine, R895-920, Therapeutics. Pharmacology, RM1-950
Abstract: Abstract Background Technetium-99 m-labelled macroaggregated human serum albumin ([99mTc]Tc-MAA) is commonly used for lung perfusion scintigraphy. The European Pharmacopoeia (Eu.Ph.) specifies thin-layer chromatography (TLC) as the only method to assess its radiochemical purity (RCP). Similarly, TLC is the sole method reported in the literature to evaluate the RCP of Gallium-68-labelled MAA [68 Ga]Ga-MAA, recently introduced for lung perfusion PET/CT imaging. Since [68 Ga]Ga-MAA is prepared from commercial kits originally designed for the preparation of [99mTc]Tc-MAA, it is essential to optimize and validate the preparation methods for [68 Ga]Ga-MAA. Results We tested a novel, simplified method for the preparation of [68 Ga]Ga-MAA that does not require organic solvents, prewash or final purification steps to remove radioactive impurities. We assessed the final product using radio-TLC, radio-UV-HPLC, and radio SDS-PAGE. Overall, our quality control (QC) method successfully detected [68 Ga]Ga-MAA along with all potential impurities, including free Ga-68, [68 Ga]Ga-HSA, unlabeled HSA, which may occur during labelling process and HEPES residual, a non-toxic but non-human-approved contaminant, used as buffer solution. We then applied our QC system to [68 Ga]Ga-MAA prepared under different conditions (25°–40°–75°–95 °C), thus defining the optimal temperature for labelling. Scanning Electron Microscopy (SEM) analysis of the products obtained through our novel method confirmed that most [68 Ga]Ga-MAA particles preserved the morphological structure and size distribution of unlabeled MAA, with a particle diameter range of 25–50 μm, assuring diagnostic efficacy. Conclusions We optimized a novel method to prepare [68 Ga]Ga-MAA through a QC system capable of monitoring all impurities of the final products.
Published: 2024
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27. Extreme climatic events, biotic interactions and species-specific responses drive tree crown defoliation and mortality in Italian forests

Author: Bussotti F, Papitto G, Di Martino D, Cocciufa C, Cindolo C, Cenni E, Bettini D, Iacopetti G, Ghelardini L, Moricca S, Panzavolta T, Bracalini M, and Pollastrini M
Subjects: Climate Change, Crown Defoliation, Emerging Forest Diseases, Forest Health Monitoring, Heatwaves and Droughts, ICP Forests, Forestry, SD1-669.5
Abstract: The frequency of forest disturbances has increased in recent years, provoking widespread defoliation, crown dieback and tree mortality. The ICP Forests monitoring network offers a unique platform for observing the impacts on forests of heatwaves, droughts and other extreme climatic events, as well as the trends of defoliation and mortality. The Italian ICP Forests Level I network consists of 261 permanent plots where tree crown defoliation and damage symptoms are assessed visually each year by well-trained crews of the Corpo Forestale dello Stato (2001-2016) and the Carabinieri Forestale from 2017 onward. This paper aims to assess the main tree species’ responses, in terms of defoliation and mortality, to severe climatic events. The results are discussed in relation to species-specific physiological behaviour and bioclimatic regions. A significant trend toward increasing defoliation and mortality has been observed since 2010 in both conifers and broadleaves. Conifers (especially Picea abies), which are largely diffuse in the Alpine regions, have suffered from bark beetle outbreaks due to severe windstorms (such as Vaia in 2018) and recurrent dry years. In the temperate regions, characterised by deciduous broadleaved trees, the most relevant defoliation events coincided with the driest and hottest years, with low relative humidity (2012, 2017 and 2021-2022), only partially recovering in the subsequent years. Among them, Fagus sylvatica and Quercus cerris, along with increased defoliation, showed symptoms caused by fungi of the genus Biscogniauxia, causal agents of “charcoal canker”, in less favourable site conditions. Quercus pubescens was the most resilient species, able to restore its crown after defoliation. The Mediterranean forests, with evergreen broadleaved species, showed no significant trends but were impacted at the most drought-prone coastal sites. The findings evidenced that the current ICP Forests network in Italy represents a fundamental infrastructure for monitoring impacts and trends connected to climate change and species-specific responses. A local intensification of the grid would help to capture under-represented species or ecological conditions.
Published: 2024
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28. Examining Relationships between Field Placements and Preservice Teachers' Self-Efficacy and Career Plans

Author: Tashnuva Shaheen, Hannah Mathews, Elizabeth Bettini, and Nathan Jones
Abstract: Field placements are arguably the most crucial component of traditional preservice special education teacher preparation. In field placements, cooperating teachers and university supervisors foster preservice special educators' sense of efficacy to teach, supporting their investment in continuing in the profession. Although ample research indicates the importance of cooperating teachers for preservice teachers' outcomes, little of this research has been conducted with preservice special educators. Moreover, prior research has almost never focused on university supervisors, despite their critical role bridging the relationship between content learned in coursework and the applied practice of special education within placement schools. In this investigation, we examined how preservice special educators' experiences of support from cooperating teachers and university supervisors relate to their teacher self-efficacy and their plans to teach. Analyzing a survey of 154 preservice special educators from six traditional preparation programs, we found that perceptions of university supervisors' support significantly predicted both self-efficacy and plans to teach, whereas perceptions of support from cooperating teachers were unrelated to either outcome. Our findings indicate that university supervisors' roles are crucial for preservice special educators' outcomes, and thus that they could be an important leverage point for improving special education teacher preparation. We call for much more extensive research on university supervisors' roles.
Published: 2024
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29. Self-Efficacy, Burnout, and Intent to Leave for Teachers of Students with Emotional and Behavioral Disorders

Author: Nelson C. Brunsting, Kristabel Stark, Elizabeth Bettini, Kathleen Lynne Lane, David James Royer, Eric Alan Common, and Marcia L. Rock
Abstract: Due to ongoing and severe teacher shortages, preparing and sustaining a skilled special education teacher (SET) workforce is a top policy priority. Understanding predictors of SETs' intent to leave is crucial for policy makers and school leaders alike, as they seek to develop interventions to support retention efforts. In this study, we examined attrition intentions among SETs serving students with emotional and behavioral disorders (EBDs), using longitudinal survey data from a U.S. nationally representative sample of teachers in the 2019-2020 school year (fall-winter-spring). We measured teachers' self-efficacy and burnout in fall, winter, and spring as well as teachers' intent to leave in spring. We found all three dimensions of fall burnout (emotional exhaustion, depersonalization, and reduced personal accomplishment) had an indirect effect on spring intent to leave. All three dimensions of burnout in the spring predicted intent to leave, as did winter scores on depersonalization. Cross-time relationships between of dimensions of self-efficacy and burnout were revealed; however, at no timepoint was self-efficacy a significant predictor of intent to leave in spring, whether directly or indirectly. We discuss implications for both practitioners and researchers.
Published: 2024
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30. Principals' Conceptions of Their Roles Supporting Self-Contained Programs for Students with Emotional/Behavioral Disorders

Author: Elizabeth Bettini, Michelle M. Cumming, Alexandra A. Lauterbach, and Hannah Morris Mathews
Abstract: Special educators serving students with emotional/behavioral disorders (EBD) depend on their principals' support, yet prior research has not explored principals' roles in supporting these programs. Using constructivist grounded theory methods, we analyzed interviews with five elementary school principals about their roles in supporting self-contained programs for students with EBD. Principals held widely varying "conceptions of students with EBD, visions" for their program, and understandings of their own "roles and responsibilities" for their programs; collectively, interactions among these gave rise to principals' "senses of agency," both for the program's capacity to be a causal agent in promoting student growth and their own capacity, as leaders, to improve the program. Our findings indicate the centrality of principals' conceptions of EBD for how they support self-contained programs for students with EBD, which has important implications for future research and practice regarding principal leadership for special education. [This is the online first version of an article published in "Remedial and Special Education."]
Published: 2024
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31. Final Results of GERDA on the Two-Neutrino Double-$\beta$ Decay Half-Life of $^{76}$Ge

Author: GERDA collaboration, Agostini, M., Alexander, A., Araujo, G. R., Bakalyarov, A. M., Balata, M., Barabanov, I., Baudis, L., Bauer, C., Belogurov, S., Bettini, A., Bezrukov, L., Biancacci, V., Bossio, E., Bothe, V., Brugnera, R., Caldwell, A., Calgaro, S., Cattadori, C., Chernogorov, A., Chiu, P. -J., Comellato, T., D'Andrea, V., Demidova, E. V., Di Giacinto, A., Di Marco, N., Doroshkevich, E., Fischer, F., Fomina, M., Gangapshev, A., Garfagnini, A., Gooch, C., Grabmayr, P., Gurentsov, V., Gusev, K., Hackenmüller, S., Hemmer, S., Hofmann, W., Huang, J., Hult, M., Inzhechik, L. V., Csáthy, J. Janicskó, Jochum, J., Junker, M., Kazalov, V., Kermaïdic, Y., Khushbakht, H., Kihm, T., Kilgus, K., Kirpichnikov, I. V., Klimenko, A., Knöpfle, K. T., Kochetov, O., Kornoukhov, V. N., Krause, P., Kuzminov, V. V., Laubenstein, M., Lehnert, B., Lindner, M., Lippi, I., Lubashevskiy, A., Lubsandorzhiev, B., Lutter, G., Macolino, C., Majorovits, B., Maneschg, W., Manzanillas, L., Marshall, G., Miloradovic, M., Mingazheva, R., Misiaszek, M., Morella, M., Müller, Y., Nemchenok, I., Neuberger, M., Pandola, L., Pelczar, K., Pertoldi, L., Piseri, P., Pullia, A., Ransom, C., Rauscher, L., Redchuk, M., Riboldi, S., Rumyantseva, N., Sada, C., Sailer, S., Salamida, F., Schönert, S., Schreiner, J., Schütt, M., Schütz, A. -K., Schulz, O., Schwarz, M., Schwingenheuer, B., Selivanenko, O., Shevchik, E., Shirchenko, M., Shtembari, L., Simgen, H., Smolnikov, A., Stukov, D., Sullivan, S., Vasenko, A. A., Veresnikova, A., Vignoli, C., von Sturm, K., Wester, T., Wiesinger, C., Wojcik, M., Yanovich, E., Zatschler, B., Zhitnikov, I., Zhukov, S. V., Zinatulina, D., Zschocke, A., Zsigmond, A. J., Zuber, K., and Zuzel, G.
Subjects: Nuclear Experiment
Abstract: We present the measurement of the two-neutrino double-$\beta$ decay rate of $^{76}$Ge performed with the GERDA Phase II experiment. With a subset of the entire GERDA exposure, 11.8 kg$\cdot$yr, the half-life of the process has been determined: $T^{2\nu}_{1/2} = (2.022 \pm 0.018_{stat} \pm 0.038_{sys})\times10^{21}$ yr. This is the most precise determination of the $^{76}$Ge two-neutrino double-$\beta$ decay half-life and one of the most precise measurements of a double-$\beta$ decay process. The relevant nuclear matrix element can be extracted: $M^{2\nu}_{\text{eff}} = (0.101\pm0.001).$, Comment: 7 pages, 4 figures, 2 tables
Published: 2023
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32. Search for tri-nucleon decays of $^{76}$Ge in GERDA

Author: GERDA collaboration, Agostini, M., Alexander, A., Araujo, G., Bakalyarov, A. M., Balata, M., Barabanov, I., Baudis, L., Bauer, C., Belogurov, S., Bettini, A., Bezrukov, L., Biancacci, V., Bossio, E., Bothe, V., Brugnera, R., Caldwell, A., Calgaro, S., Cattadori, C., Chernogorov, A., Chiu, P. -J., Comellato, T., D'Andrea, V., Demidova, E. V., Di Giacinto, A., Di Marco, N., Doroshkevich, E., Fischer, F., Fomina, M., Gangapshev, A., Garfagnini, A., Gooch, C., Grabmayr, P., Gurentsov, V., Gusev, K., Hakenmüller, J., Hemmer, S., Hofmann, W., Hult, M., Inzhechik, L. V., Csáthy, J. Janicskó, Jochum, J., Junker, M., Kazalov, V., Kermaïdic, Y., Khushbakht, H., Kihm, T., Kilgus, K., Kirpichnikov, I. V., Klimenko, A., Knöpfle, K. T., Kochetov, O., Kornoukhov, V. N., Krause, P., Kuzminov, V. V., Laubenstein, M., Lindner, M., Lippi, I., Lubashevskiy, A., Lubsandorzhiev, B., Lutter, G., Macolino, C., Majorovits, B., Maneschg, W., Manzanillas, L., Marshall, G., Misiaszek, M., Morella, M., Müller, Y., Nemchenok, I., Neuberger, M., Pandola, L., Pelczar, K., Pertoldi, L., Piseri, P., Pullia, A., Rauscher, L., Redchuk, M., Riboldi, S., Rumyantseva, N., Sada, C., Sailer, S., Salamida, F., Schönert, S., Schreiner, J., Schütt, M., Schütz, A-K., Schulz, O., Schwarz, M., Schwingenheuer, B., Selivanenko, O., Shevchik, E., Shirchenko, M., Shtembari, L., Simgen, H., Smolnikov, A., Stukov, D., Sullivan, S., Vasenko, A. A., Veresnikova, A., Vignoli, C., von Sturm, K., Wester, T., Wiesinger, C., Wojcik, M., Yanovich, E., Zatschler, B., Zhitnikov, I., Zhukov, S. V., Zinatulina, D., Zschocke, A., Zsigmond, A. J., Zuber, K., and Zuzel, G.
Subjects: Nuclear Experiment
Abstract: We search for tri-nucleon decays of $^{76}$Ge in the dataset from the GERmanium Detector Array (GERDA) experiment. Decays that populate excited levels of the daughter nucleus above the threshold for particle emission lead to disintegration and are not considered. The ppp-, ppn-, and pnn-decays lead to $^{73}$Cu, $^{73}$Zn, and $^{73}$Ga nuclei, respectively. These nuclei are unstable and eventually proceed by the beta decay of $^{73}$Ga to $^{73}$Ge (stable). We search for the $^{73}$Ga decay exploiting the fact that it dominantly populates the 66.7 keV $^{73m}$Ga state with half-life of 0.5 s. The nnn-decays of $^{76}$Ge that proceed via $^{73m}$Ge are also included in our analysis. We find no signal candidate and place a limit on the sum of the decay widths of the inclusive tri-nucleon decays that corresponds to a lower lifetime limit of 1.2x10$^{26}$ yr (90% credible interval). This result improves previous limits for tri-nucleon decays by one to three orders of magnitude., Comment: 8 pages, 9 figures, 3 tables
Published: 2023
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33. Visible-Light Assisted Covalent Surface Functionalization of Reduced Graphene Oxide Nanosheets with Arylazo Sulfones

Author: Lombardi, Lorenzo, Kovtun, Alessandro, Mantovani, Sebastiano, Bertuzzi, Giulio, Favaretto, Laura, Bettini, Cristian, Palermo, Vincenzo, Melucci, Manuela, and Bandini, Marco
Subjects: Condensed Matter - Mesoscale and Nanoscale Physics
Abstract: We present an environmentally benign methodology for the covalent functionalization (arylation) of reduced graphene oxide (rGO) nanosheets with arylazo sulfones. A variety of tagged aryl units were conveniently accommodated at the rGO surface via visible light irradiation of suspensions of carbon nanostructured materials in aqueous media. Mild reaction conditions, absence of photosensitizers, functional group tolerance and high atomic fractions (XPS analysis) represent some of the salient features characterizing the present methodology. Control experiments for the mechanistic elucidation (Raman analysis) and chemical nanomanipulation of the tagged rGO surfaces are also reported.
Published: 2023
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34. Combining Public Human Activity Recognition Datasets to Mitigate Labeled Data Scarcity

Author: Presotto, Riccardo, Ek, Sannara, Civitarese, Gabriele, Portet, François, Lalanda, Philippe, and Bettini, Claudio
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract: The use of supervised learning for Human Activity Recognition (HAR) on mobile devices leads to strong classification performances. Such an approach, however, requires large amounts of labeled data, both for the initial training of the models and for their customization on specific clients (whose data often differ greatly from the training data). This is actually impractical to obtain due to the costs, intrusiveness, and time-consuming nature of data annotation. Moreover, even with the help of a significant amount of labeled data, model deployment on heterogeneous clients faces difficulties in generalizing well on unseen data. Other domains, like Computer Vision or Natural Language Processing, have proposed the notion of pre-trained models, leveraging large corpora, to reduce the need for annotated data and better manage heterogeneity. This promising approach has not been implemented in the HAR domain so far because of the lack of public datasets of sufficient size. In this paper, we propose a novel strategy to combine publicly available datasets with the goal of learning a generalized HAR model that can be fine-tuned using a limited amount of labeled data on an unseen target domain. Our experimental evaluation, which includes experimenting with different state-of-the-art neural network architectures, shows that combining public datasets can significantly reduce the number of labeled samples required to achieve satisfactory performance on an unseen target domain., Comment: IEEE SMARTCOMP 2023
Published: 2023

35. Neuro-Symbolic Approaches for Context-Aware Human Activity Recognition

Author: Arrotta, Luca, Civitarese, Gabriele, and Bettini, Claudio
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Electrical Engineering and Systems Science - Signal Processing
Abstract: Deep Learning models are a standard solution for sensor-based Human Activity Recognition (HAR), but their deployment is often limited by labeled data scarcity and models' opacity. Neuro-Symbolic AI (NeSy) provides an interesting research direction to mitigate these issues by infusing knowledge about context information into HAR deep learning classifiers. However, existing NeSy methods for context-aware HAR require computationally expensive symbolic reasoners during classification, making them less suitable for deployment on resource-constrained devices (e.g., mobile devices). Additionally, NeSy approaches for context-aware HAR have never been evaluated on in-the-wild datasets, and their generalization capabilities in real-world scenarios are questionable. In this work, we propose a novel approach based on a semantic loss function that infuses knowledge constraints in the HAR model during the training phase, avoiding symbolic reasoning during classification. Our results on scripted and in-the-wild datasets show the impact of different semantic loss functions in outperforming a purely data-driven model. We also compare our solution with existing NeSy methods and analyze each approach's strengths and weaknesses. Our semantic loss remains the only NeSy solution that can be deployed as a single DNN without the need for symbolic reasoning modules, reaching recognition rates close (and better in some cases) to existing approaches.
Published: 2023

36. TorchRL: A data-driven decision-making library for PyTorch

Author: Bou, Albert, Bettini, Matteo, Dittert, Sebastian, Kumar, Vikash, Sodhani, Shagun, Yang, Xiaomeng, De Fabritiis, Gianni, and Moens, Vincent
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract: Striking a balance between integration and modularity is crucial for a machine learning library to be versatile and user-friendly, especially in handling decision and control tasks that involve large development teams and complex, real-world data, and environments. To address this issue, we propose TorchRL, a generalistic control library for PyTorch that provides well-integrated, yet standalone components. With a versatile and robust primitive design, TorchRL facilitates streamlined algorithm development across the many branches of Reinforcement Learning (RL) and control. We introduce a new PyTorch primitive, TensorDict, as a flexible data carrier that empowers the integration of the library's components while preserving their modularity. Hence replay buffers, datasets, distributed data collectors, environments, transforms and objectives can be effortlessly used in isolation or combined. We provide a detailed description of the building blocks, supporting code examples and an extensive overview of the library across domains and tasks. Finally, we show comparative benchmarks to demonstrate its computational efficiency. TorchRL fosters long-term support and is publicly available on GitHub for greater reproducibility and collaboration within the research community. The code is opensourced on https://github.com/pytorch/rl.
Published: 2023

37. Validation of a radiosynthesis method and a novel quality control system for [68 Ga]Ga-MAA: is TLC enough to assess radiopharmaceutical quality?

Author: Migliari, Silvia, Bruno, Stefano, Bianchera, Annalisa, De Nardis, Ilaria, Scarano, Antonio, Lusardi, Monica, Gaiani, Anna, Guercio, Alessandra, Scarlattei, Maura, Baldari, Giorgio, Bettini, Ruggero, and Ruffini, Livia
Published: 2024
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38. Pure niobium manufactured by Laser-Based Powder Bed Fusion: influence of process parameters and supports on as-built surface quality

Author: Candela, Silvia, Rebesan, Pietro, De Bortoli, Diego, Carmignato, Simone, Zanini, Filippo, Candela, Valentina, Dima, Razvan, Pepato, Adriano, Weinmann, Markus, and Bettini, Paolo
Published: 2024
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39. System Neural Diversity: Measuring Behavioral Heterogeneity in Multi-Agent Learning

Author: Bettini, Matteo, Shankar, Ajay, and Prorok, Amanda
Subjects: Computer Science - Multiagent Systems, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Computer Science - Robotics
Abstract: Evolutionary science provides evidence that diversity confers resilience in natural systems. Yet, traditional multi-agent reinforcement learning techniques commonly enforce homogeneity to increase training sample efficiency. When a system of learning agents is not constrained to homogeneous policies, individuals may develop diverse behaviors, resulting in emergent complementarity that benefits the system. Despite this, there is a surprising lack of tools that quantify behavioral diversity. Such techniques would pave the way towards understanding the impact of diversity in collective artificial intelligence and enabling its control. In this paper, we introduce System Neural Diversity (SND): a measure of behavioral heterogeneity in multi-agent systems. We discuss and prove its theoretical properties, and compare it with alternate, state-of-the-art behavioral diversity metrics used in the robotics domain. Through simulations of a variety of cooperative multi-robot tasks, we show how our metric constitutes an important tool that enables measurement and control of behavioral heterogeneity. In dynamic tasks, where the problem is affected by repeated disturbances during training, we show that SND allows us to measure latent resilience skills acquired by the agents, while other proxies, such as task performance (reward), fail to. Finally, we show how the metric can be employed to control diversity, allowing us to enforce a desired heterogeneity set-point or range. We demonstrate how this paradigm can be used to bootstrap the exploration phase, finding optimal policies faster, thus enabling novel and more efficient MARL paradigms.
Published: 2023

40. SelfAct: Personalized Activity Recognition based on Self-Supervised and Active Learning

Author: Arrotta, Luca, Civitarese, Gabriele, Valente, Samuele, and Bettini, Claudio
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Human-Computer Interaction, Electrical Engineering and Systems Science - Signal Processing
Abstract: Supervised Deep Learning (DL) models are currently the leading approach for sensor-based Human Activity Recognition (HAR) on wearable and mobile devices. However, training them requires large amounts of labeled data whose collection is often time-consuming, expensive, and error-prone. At the same time, due to the intra- and inter-variability of activity execution, activity models should be personalized for each user. In this work, we propose SelfAct: a novel framework for HAR combining self-supervised and active learning to mitigate these problems. SelfAct leverages a large pool of unlabeled data collected from many users to pre-train through self-supervision a DL model, with the goal of learning a meaningful and efficient latent representation of sensor data. The resulting pre-trained model can be locally used by new users, which will fine-tune it thanks to a novel unsupervised active learning strategy. Our experiments on two publicly available HAR datasets demonstrate that SelfAct achieves results that are close to or even better than the ones of fully supervised approaches with a small number of active learning queries.
Published: 2023

41. POPGym: Benchmarking Partially Observable Reinforcement Learning

Author: Morad, Steven, Kortvelesy, Ryan, Bettini, Matteo, Liwicki, Stephan, and Prorok, Amanda
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Robotics
Abstract: Real world applications of Reinforcement Learning (RL) are often partially observable, thus requiring memory. Despite this, partial observability is still largely ignored by contemporary RL benchmarks and libraries. We introduce Partially Observable Process Gym (POPGym), a two-part library containing (1) a diverse collection of 15 partially observable environments, each with multiple difficulties and (2) implementations of 13 memory model baselines -- the most in a single RL library. Existing partially observable benchmarks tend to fixate on 3D visual navigation, which is computationally expensive and only one type of POMDP. In contrast, POPGym environments are diverse, produce smaller observations, use less memory, and often converge within two hours of training on a consumer-grade GPU. We implement our high-level memory API and memory baselines on top of the popular RLlib framework, providing plug-and-play compatibility with various training algorithms, exploration strategies, and distributed training paradigms. Using POPGym, we execute the largest comparison across RL memory models to date. POPGym is available at https://github.com/proroklab/popgym.
Published: 2023

42. Special Educators' Experiences of Interpersonal Interactions While Serving Students with Emotional/Behavioral Disorders

Author: Bettini, Elizabeth, Lillis, Jennifer, Stark, Kristabel, Brunsting, Nelson C., and Mathews, Hannah Morris
Abstract: Students with emotional/behavioral disorders are increasingly included in general education settings, requiring their special educators to coordinate with other educators. Yet, research provides limited insights into their interactions with other educators. Thus, we qualitatively examined how special educators experienced and navigated interactions with other educators when serving students with emotional/behavioral disabilities in self-contained classes that were actively moving students into more inclusive placements. Participants emphasized that their work was interdependent with others; they relied on others for work essential to meeting students' needs. They shared that interactions were shaped by conceptions of students' needs, the division of responsibilities, and resources. They experienced interactions on a continuum from alignment to misalignment; when experiencing alignment, they felt supported to meet student needs, whereas they felt misalignment challenged those efforts. Participants described using varied strategies to promote alignment. Results have implications for coordinating teachers' efforts to serve students with emotional/behavioral disabilities. [For the corresponding grantee submission, see ED614959.]
Published: 2022
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43. Momentary Affective Experiences of Teachers Serving Students with Emotional and Behavioral Disabilities in Self-Contained Settings

Author: Stark, Kristabel, Bettini, Elizabeth, and Chi, Olivia
Abstract: Emotions play an important role in the work of teachers serving students with emotional and behavioral disabilities (EBD), yet little is known about teachers' momentary affective experiences. In this study, we collected 710 surveys regarding momentary affect from 14 teachers of students with EBD. We used descriptive analysis and variance decomposition to examine the frequency, intensity, and variability of these experiences. We then tested a series of models to explore how specific professional activities relate to teachers' momentary affect. We found that teachers experienced positive affect more frequently and intensely than negative affect and that large proportions of the variation in positive and negative affect can be attributed to variation within individual teachers across time points. For these teachers, engaging in discipline was significantly associated with a higher negative affect, whereas engaging in instructional activities was associated with a higher positive affect. We discuss implications for researchers and practitioners. [For the corresponding grantee submission, see ED627065.]
Published: 2023
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44. Heterogeneous Multi-Robot Reinforcement Learning

Author: Bettini, Matteo, Shankar, Ajay, and Prorok, Amanda
Subjects: Computer Science - Robotics, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Computer Science - Multiagent Systems
Abstract: Cooperative multi-robot tasks can benefit from heterogeneity in the robots' physical and behavioral traits. In spite of this, traditional Multi-Agent Reinforcement Learning (MARL) frameworks lack the ability to explicitly accommodate policy heterogeneity, and typically constrain agents to share neural network parameters. This enforced homogeneity limits application in cases where the tasks benefit from heterogeneous behaviors. In this paper, we crystallize the role of heterogeneity in MARL policies. Towards this end, we introduce Heterogeneous Graph Neural Network Proximal Policy Optimization (HetGPPO), a paradigm for training heterogeneous MARL policies that leverages a Graph Neural Network for differentiable inter-agent communication. HetGPPO allows communicating agents to learn heterogeneous behaviors while enabling fully decentralized training in partially observable environments. We complement this with a taxonomical overview that exposes more heterogeneity classes than previously identified. To motivate the need for our model, we present a characterization of techniques that homogeneous models can leverage to emulate heterogeneous behavior, and show how this "apparent heterogeneity" is brittle in real-world conditions. Through simulations and real-world experiments, we show that: (i) when homogeneous methods fail due to strong heterogeneous requirements, HetGPPO succeeds, and, (ii) when homogeneous methods are able to learn apparently heterogeneous behaviors, HetGPPO achieves higher resilience to both training and deployment noise.
Published: 2023

45. Liquid argon light collection and veto modeling in GERDA Phase II

Author: GERDA collaboration, Agostini, M., Alexander, A., Araujo, G. R., Bakalyarov, A. M., Balata, M., Barabanov, I., Baudis, L., Bauer, C., Belogurov, S., Bettini, A., Bezrukov, L., Biancacci, V., Bossio, E., Bothe, V., Brugnera, R., Caldwell, A., Calgaro, S., Cattadori, C., Chernogorov, A., Chiu, P-J., Comellato, T., D'Andrea, V., Demidova, E. V., Di Giacinto, A., Di Marco, N., Doroshkevich, E., Fischer, F., Fomina, M., Gangapshev, A., Garfagnini, A., Gooch, C., Grabmayr, P., Gurentsov, V., Gusev, K., Hakenmüller, J., Hemmer, S., Hofmann, W., Hult, M., Inzhechik, L. V., Csáthy, J. Janicskó, Jochum, J., Junker, M., Kazalov, V., Kermaïdic, Y., Khushbakht, H., Kihm, T., Kilgus, K., Kirpichnikov, I. V., Klimenko, A., Knöpfle, K. T., Kochetov, O., Kornoukhov, V. N., Krause, P., Kuzminov, V. V., Laubenstein, M., Lehnert, B., Lindner, M., Lippi, I., Lubashevskiy, A., Lubsandorzhiev, B., Lutter, G., Macolino, C., Majorovits, B., Maneschg, W., Manzanillas, L., Marshall, G., Miloradovic, M., Mingazheva, R., Misiaszek, M., Morella, M., Müller, Y., Nemchenok, I., Neuberger, M., Pandola, L., Pelczar, K., Pertoldi, L., Piseri, P., Pullia, A., Rauscher, L., Redchuk, M., Riboldi, S., Rumyantseva, N., Sada, C., Sailer, S., Salamida, F., Schönert, S., Schreiner, J., Schütt, M., Schütz, A-K., Schulz, O., Schwarz, M., Schwingenheuer, B., Selivanenko, O., Shevchik, E., Shirchenko, M., Shtembari, L., Simgen, H., Smolnikov, A., Stukov, D., Sullivan, S., Vasenko, A. A., Veresnikova, A., Vignoli, C., von Sturm, K., Wegmann, A., Wester, T., Wiesinger, C., Wojcik, M., Yanovich, E., Zatschler, B., Zhitnikov, I., Zhukov, S. V., Zinatulina, D., Zschocke, A., Zsigmond, A. J., Zuber, K., and Zuzel, G.
Subjects: Physics - Instrumentation and Detectors, High Energy Physics - Experiment, Nuclear Experiment
Abstract: The ability to detect liquid argon scintillation light from within a densely packed high-purity germanium detector array allowed the GERDA experiment to reach an exceptionally low background rate in the search for neutrinoless double beta decay of $^{76}$Ge. Proper modeling of the light propagation throughout the experimental setup, from any origin in the liquid argon volume to its eventual detection by the novel light read-out system, provides insight into the rejection capability and is a necessary ingredient to obtain robust background predictions. In this paper, we present a model of the GERDA liquid argon veto, as obtained by Monte Carlo simulations and constrained by calibration data, and highlight its application for background decomposition.
Published: 2022
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46. Dynamic Olfactometry Measurements of Geothermal Endogenous Gas Emissions

Author: Marzio Invernizzi, Giacomo Scolieri, Francesca Tagliaferri, Alessandro Bettini, Marcello Cinci, Alessandro Lenzi, and Selena Sironi
Subjects: Chemical engineering, TP155-156, Computer engineering. Computer hardware, TK7885-7895
Abstract: Gaseous emissions which may be of odour impact and interest are not solely derived from industrial processes or agricultural fields, but also from natural sources. Natural odorous gaseous emissions are often present in geothermal areas. In these cases, the inventory and the measurement of the emitted gas flows are not trivial. This work presents the experience of an olfactometric survey conducted in a geothermal-interest area, specifically around Mt. Amiata, Tuscany, Italy. Dynamic olfactometry analyses showed odour concentrations in the order of millions of ouE/m3. While the main constituent of these natural gas emissions was CO2, the very high odour concentration data primarily resulted from the high portion of H2S in these emissions, with detected concentrations ranging from 1,000 to 10,000 ppmv. This not only indicates the presence of odour impact potential but also the high risk for people in the nearby area due to the high concentration of this gas. In parallel with the measurement of representative concentration data of these spot vents, a flexible and innovative approach was established for the measurement of emitted gas flow. The main breakthrough was obtained via the revamping of a balometer, a tool used for the measurement of indoor airflows, in the measurement of the gas flow of large spot vents (i.e. mine gates). Thanks to this stretchy approach, it was possible to estimate the OER of these emissions: the overall OER of all the inventory of the investigated spot vents in the area was impressive, and reached almost 10 million of ouE/s.
Published: 2024

47. Stratified analyses refine association between TLR7 rare variants and severe COVID-19

Author: Jannik Boos, Caspar I. van der Made, Gayatri Ramakrishnan, Eamon Coughlan, Rosanna Asselta, Britt-Sabina Löscher, Luca V.C. Valenti, Rafael de Cid, Luis Bujanda, Antonio Julià, Erola Pairo-Castineira, J. Kenneth Baillie, Sandra May, Berina Zametica, Julia Heggemann, Agustín Albillos, Jesus M. Banales, Jordi Barretina, Natalia Blay, Paolo Bonfanti, Maria Buti, Javier Fernandez, Sara Marsal, Daniele Prati, Luisa Ronzoni, Nicoletta Sacchi, Joachim L. Schultze, Olaf Riess, Andre Franke, Konrad Rawlik, David Ellinghaus, Alexander Hoischen, Axel Schmidt, Kerstin U. Ludwig, Valeria Rimoldi, Elvezia M. Paraboschi, Alessandra Bandera, Flora Peyvandi, Giacomo Grasselli, Francesco Blasi, Francesco Malvestiti, Serena Pelusi, Cristiana Bianco, Lorenzo Miano, Angela Lombardi, Pietro Invernizzi, Alessio Gerussi, Giuseppe Citerio, Andrea Biondi, Maria Grazia Valsecchi, Marina Elena Cazzaniga, Giuseppe Foti, Ilaria Beretta, Mariella D'Angiò, Laura Rachele Bettini, Xavier Farré, Susana Iraola-Guzmán, Manolis Kogevinas, Gemma Castaño-Vinyals, Koldo Garcia-Etxebarria, Beatriz Nafria, Mauro D'Amato, Adriana Palom, Colin Begg, Sara Clohisey, Charles Hinds, Peter Horby, Julian Knight, Lowell Ling, David Maslove, Danny McAuley, Johnny Millar, Hugh Montgomery, Alistair Nichol, Peter J.M. Openshaw, Alexandre C. Pereira, Chris P. Ponting, Kathy Rowan, Malcolm G. Semple, Manu Shankar-Hari, Charlotte Summers, Timothy Walsh, Latha Aravindan, Ruth Armstrong, Heather Biggs, Ceilia Boz, Adam Brown, Richard Clark, Audrey Coutts, Judy Coyle, Louise Cullum, Sukamal Das, Nicky Day, Lorna Donnelly, Esther Duncan, Angie Fawkes, Paul Fineran, Max Head Fourman, Anita Furlong, James Furniss, Bernadette Gallagher, Tammy Gilchrist, Ailsa Golightly, Fiona Griffiths, Katarzyna Hafezi, Debbie Hamilton, Ross Hendry, Andy Law, Dawn Law, Rachel Law, Sarah Law, Rebecca Lidstone-Scott, Louise Macgillivray, Alan Maclean, Hanning Mal, Sarah McCafferty, Ellie Mcmaster, Jen Meikle, Shona C. Moore, Kirstie Morrice, Lee Murphy, Sheena Murphy, Mybaya Hellen, Wilna Oosthuyzen, Chenqing Zheng, Jiantao Chen, Nick Parkinson, Trevor Paterson, Katherine Schon, Andrew Stenhouse, Mihaela Das, Maaike Swets, Helen Szoor-McElhinney, Filip Taneski, Lance Turtle, Tony Wackett, Mairi Ward, Jane Weaver, Nicola Wrobel, Marie Zechner, Gill Arbane, Aneta Bociek, Sara Campos, Neus Grau, Tim Owen Jones, Rosario Lim, Martina Marotti, Marlies Ostermann, Christopher Whitton, Zoe Alldis, Raine Astin-Chamberlain, Fatima Bibi, Jack Biddle, Sarah Blow, Matthew Bolton, Catherine Borra, Ruth Bowles, Maudrian Burton, Yasmin Choudhury, David Collier, Amber Cox, Amy Easthope, Patrizia Ebano, Stavros Fotiadis, Jana Gurasashvili, Rosslyn Halls, Pippa Hartridge, Delordson Kallon, Jamila Kassam, Ivone Lancoma-Malcolm, Maninderpal Matharu, Peter May, Oliver Mitchelmore, Tabitha Newman, Mital Patel, Jane Pheby, Irene Pinzuti, Zoe Prime, Oleksandra Prysyazhna, Julian Shiel, Melanie Taylor, Carey Tierney, Suzanne Wood, Anne Zak, Olivier Zongo, Stephen Bonner, Keith Hugill, Jessica Jones, Steven Liggett, Evie Headlam, Nageswar Bandla, Minnie Gellamucho, Michelle Davies, Christopher Thompson, Marwa Abdelrazik, Dhanalakshmi Bakthavatsalam, Munzir Elhassan, Arunkumar Ganesan, Anne Haldeos, Jeronimo Moreno-Cuesta, Dharam Purohit, Rachel Vincent, Kugan Xavier, Kumar Rohit, Frater Alasdair, Malik Saleem, Carter David, Jenkins Samuel, Zoe Lamond, Wall Alanna, Jaime Fernandez-Roman, David O. Hamilton, Emily Johnson, Brian Johnston, Maria Lopez Martinez, Suleman Mulla, David Shaw, Alicia A.C. Waite, Victoria Waugh, Ingeborg D. Welters, Karen Williams, Anna Cavazza, Maeve Cockrell, Eleanor Corcoran, Maria Depante, Clare Finney, Ellen Jerome, Mark McPhail, Monalisa Nayak, Harriet Noble, Kevin O'Reilly, Evita Pappa, Rohit Saha, Sian Saha, John Smith, Abigail Knighton, David Antcliffe, Dorota Banach, Stephen Brett, Phoebe Coghlan, Ziortza Fernandez, Anthony Gordon, Roceld Rojo, Sonia Sousa Arias, Maie Templeton, Megan Meredith, Lucy Morris, Lucy Ryan, Amy Clark, Julia Sampson, Cecilia Peters, Martin Dent, Margaret Langley, Saima Ashraf, Shuying Wei, Angela Andrew, Archana Bashyal, Neil Davidson, Paula Hutton, Stuart McKechnie, Jean Wilson, David Baptista, Rebecca Crowe, Rita Fernandes, Rosaleen Herdman-Grant, Anna Joseph, Denise O'Connor, Meryem Allen, Adam Loveridge, India McKenley, Eriko Morino, Andres Naranjo, Richard Simms, Kathryn Sollesta, Andrew Swain, Harish Venkatesh, Jacyntha Khera, Jonathan Fox, Gillian Andrew, Lucy Barclay, Marie Callaghan, Rachael Campbell, Sarah Clark, Dave Hope, Lucy Marshall, Corrienne McCulloch, Kate Briton, Jo Singleton, Sohphie Birch, Lutece Brimfield, Zoe Daly, David Pogson, Steve Rose, Ceri Battle, Elaine Brinkworth, Rachel Harford, Carl Murphy, Luke Newey, Tabitha Rees, Marie Williams, Sophie Arnold, Petra Polgarova, Katerina Stroud, Eoghan Meaney, Megan Jones, Anthony Ng, Shruti Agrawal, Nazima Pathan, Deborah White, Esther Daubney, Kay Elston, Lina Grauslyte, Musarat Hussain, Mandeep Phull, Tatiana Pogreban, Lace Rosaroso, Erika Salciute, George Franke, Joanna Wong, Aparna George, Laura Ortiz-Ruiz de Gordoa, Emily Peasgood, Claire Phillips, Michelle Bates, Jo Dasgin, Jaspret Gill, Annette Nilsson, James Scriven, Carlos Castro Delgado, Deborah Dawson, Lijun Ding, Georgia Durrant, Obiageri Ezeobu, Sarah Farnell-Ward, Abiola Harrison, Rebecca Kanu, Susannah Leaver, Elena Maccacari, Soumendu Manna, Romina Pepermans Saluzzio, Joana Queiroz, Tinashe Samakomva, Christine Sicat, Joana Texeira, Edna Fernandes Da Gloria, Ana Lisboa, John Rawlins, Jisha Mathew, Ashley Kinch, William James Hurt, Nirav Shah, Victoria Clark, Maria Thanasi, Nikki Yun, Kamal Patel, Sara Bennett, Emma Goodwin, Matthew Jackson, Alissa Kent, Clare Tibke, Wiesia Woodyatt, Ahmed Zaki, Azmerelda Abraheem, Peter Bamford, Kathryn Cawley, Charlie Dunmore, Maria Faulkner, Rumanah Girach, Helen Jeffrey, Rhianna Jones, Emily London, Imrun Nagra, Farah Nasir, Hannah Sainsbury, Clare Smedley, Tahera Patel, Matthew Smith, Srikanth Chukkambotla, Aayesha Kazi, Janice Hartley, Joseph Dykes, Muhammad Hijazi, Sarah Keith, Meherunnisa Khan, Janet Ryan-Smith, Philippa Springle, Jacqueline Thomas, Nick Truman, Samuel Saad, Dabheoc Coleman, Christopher Fine, Roseanna Matt, Bethan Gay, Jack Dalziel, Syamlan Ali, Drew Goodchild, Rhiannan Harling, Ravi Bhatterjee, Wendy Goddard, Chloe Davison, Stephen Duberly, Jeanette Hargreaves, Rachel Bolton, Miriam Davey, David Golden, Rebecca Seaman, Shiney Cherian, Sean Cutler, Anne Emma Heron, Anna Roynon-Reed, Tamas Szakmany, Gemma Williams, Owen Richards, Yusuf Cheema, Hollie Brooke, Sarah Buckley, Jose Cebrian Suarez, Ruth Charlesworth, Karen Hansson, John Norris, Alice Poole, Alastair Rose, Rajdeep Sandhu, Brendan Sloan, Elizabeth Smithson, Muthu Thirumaran, Veronica Wagstaff, Alexandra Metcalfe, Mark Brunton, Jess Caterson, Holly Coles, Matthew Frise, Sabi Gurung Rai, Nicola Jacques, Liza Keating, Emma Tilney, Shauna Bartley, Parminder Bhuie, Sian Gibson, Amanda Lyle, Fiona McNeela, Jayachandran Radhakrishnan, Alistair Hughes, Bryan Yates, Jessica Reynolds, Helen Campbell, Maria Thompsom, Steve Dodds, Stacey Duffy, Sandra Greer, Karen Shuker, Ascanio Tridente, Reena Khade, Ashok Sundar, George Tsinaslanidis, Isobel Birkinshaw, Joseph Carter, Kate Howard, Joanne Ingham, Rosie Joy, Harriet Pearson, Samantha Roche, Zoe Scott, Hollie Bancroft, Mary Bellamy, Margaret Carmody, Jacqueline Daglish, Faye Moore, Joanne Rhodes, Mirriam Sangombe, Salma Kadiri, Maria Croft, Ian White, Victoria Frost, Maia Aquino, Rajeev Jha, Vinodh Krishnamurthy, Lai Lim, Li Lim, Edward Combes, Teishel Joefield, Sonja Monnery, Valerie Beech, Sallyanne Trotman, Christine Almaden-Boyle, Pauline Austin, Louise Cabrelli, Stephen Cole, Matt Casey, Susan Chapman, Clare Whyte, Yolanda Baird, Aaron Butler, Indra Chadbourn, Linda Folkes, Heather Fox, Amy Gardner, Raquel Gomez, Gillian Hobden, Luke Hodgson, Kirsten King, Michael Margarson, Tim Martindale, Emma Meadows, Dana Raynard, Yvette Thirlwall, David Helm, Jordi Margalef, Kristine Criste, Rebecca Cusack, Kim Golder, Hannah Golding, Oliver Jones, Samantha Leggett, Michelle Male, Martyna Marani, Kirsty Prager, Toran Williams, Belinda Roberts, Karen Salmon, Peter Anderson, Katie Archer, Karen Austin, Caroline Davis, Alison Durie, Olivia Kelsall, Jessica Thrush, Charlie Vigurs, Laura Wild, Hannah-Louise Wood, Helen Tranter, Alison Harrison, Nicholas Cowley, Michael McAlindon, Andrew Burtenshaw, Stephen Digby, Emma Low, Aled Morgan, Naiara Cother, Tobias Rankin, Sarah Clayton, Alex McCurdy, Cecilia Ahmed, Balvinder Baines, Sarah Clamp, Julie Colley, Risna Haq, Anne Hayes, Jonathan Hulme, Samia Hussain, Sibet Joseph, Rita Kumar, Zahira Maqsood, Manjit Purewal, Leonie Benham, Zena Bradshaw, Joanna Brown, Melanie Caswell, Jason Cupitt, Sarah Melling, Stephen Preston, Nicola Slawson, Emma Stoddard, Scott Warden, Bethan Deacon, Ceri Lynch, Carla Pothecary, Lisa Roche, Gwenllian Sera Howe, Jayaprakash Singh, Keri Turner, Hannah Ellis, Natalie Stroud, Jodie Hunt, Joy Dearden, Emma Dobson, Andy Drummond, Michelle Mulcahy, Sheila Munt, Grainne O'Connor, Jennifer Philbin, Chloe Rishton, Redmond Tully, Sarah Winnard, Susanne Cathcart, Katharine Duffy, Alex Puxty, Kathryn Puxty, Lynne Turner, Jane Ireland, Gary Semple, Kate Long, Simon Whiteley, Elizabeth Wilby, Bethan Ogg, Amanda Cowton, Andrea Kay, Melanie Kent, Kathryn Potts, Ami Wilkinson, Suzanne Campbell, Ellen Brown, Julie Melville, Jay Naisbitt, Rosane Joseph, Maria Lazo, Olivia Walton, Alan Neal, Peter Alexander, Schvearn Allen, Joanne Bradley-Potts, Craig Brantwood, Jasmine Egan, Timothy Felton, Grace Padden, Luke Ward, Stuart Moss, Susannah Glasgow, Lynn Abel, Michael Brett, Brian Digby, Lisa Gemmell, James Hornsby, Patrick MacGoey, Pauline O'Neil, Richard Price, Natalie Rodden, Kevin Rooney, Radha Sundaram, Nicola Thomson, Bridget Hopkins, Laura Thrasyvoulou, Heather Willis, Martyn Clark, Martina Coulding, Edward Jude, Jacqueline McCormick, Oliver Mercer, Darsh Potla, Hafiz Rehman, Heather Savill, Victoria Turner, Charlotte Downes, Kathleen Holding, Katie Riches, Mary Hilton, Mel Hayman, Deepak Subramanian, Priya Daniel, Oluronke Adanini, Nikhil Bhatia, Maines Msiska, Rebecca Collins, Ian Clement, Bijal Patel, A. Gulati, Carole Hays, K. Webster, Anne Hudson, Andrea Webster, Elaine Stephenson, Louise McCormack, Victoria Slater, Rachel Nixon, Helen Hanson, Maggie Fearby, Sinead Kelly, Victoria Bridgett, Philip Robinson, Julie Camsooksai, Charlotte Humphrey, Sarah Jenkins, Henrik Reschreiter, Beverley Wadams, Yasmin Death, Victoria Bastion, Daphene Clarke, Beena David, Harriet Kent, Rachel Lorusso, Gamu Lubimbi, Sophie Murdoch, Melchizedek Penacerrada, Alastair Thomas, Jennifer Valentine, Ana Vochin, Retno Wulandari, Brice Djeugam, Gillian Bell, Katy English, Amro Katary, Louise Wilcox, Michelle Bruce, Karen Connolly, Tracy Duncan, Helen T-Michael, Gabriella Lindergard, Samuel Hey, Claire Fox, Jordan Alfonso, Laura Jayne Durrans, Jacinta Guerin, Bethan Blackledge, Jade Harris, Martin Hruska, Ayaa Eltayeb, Thomas Lamb, Tracey Hodgkiss, Lisa Cooper, Joanne Rothwell, Angela Allan, Felicity Anderson, Callum Kaye, Jade Liew, Jasmine Medhora, Teresa Scott, Erin Trumper, Adriana Botello, Liana Lankester, Nikitas Nikitas, Colin Wells, Bethan Stowe, Kayleigh Spencer, Craig Brandwood, Lara Smith, Katie Birchall, Laurel Kolakaluri, Deborah Baines, Anila Sukumaran, Elena Apetri, Cathrine Basikolo, Laura Catlow, Bethan Charles, Paul Dark, Reece Doonan, Alice Harvey, Daniel Horner, Karen Knowles, Stephanie Lee, Diane Lomas, Chloe Lyons, Tracy Marsden, Danielle McLaughlan, Liam McMorrow, Jessica Pendlebury, Jane Perez, Maria Poulaka, Nicola Proudfoot, Melanie Slaughter, Kathryn Slevin, Vicky Thomas, Danielle Walker, Angiy Michael, Matthew Collis, Tracey Cosier, Gemma Millen, Neil Richardson, Natasha Schumacher, Heather Weston, James Rand, Nicola Baxter, Steven Henderson, Sophie Kennedy-Hay, Christopher McParland, Laura Rooney, Malcolm Sim, Gordan McCreath, Louise Akeroyd, Shereen Bano, Matt Bromley, Lucy Gurr, Tom Lawton, James Morgan, Kirsten Sellick, Deborah Warren, Brian Wilkinson, Janet McGowan, Camilla Ledgard, Amelia Stacey, Kate Pye, Ruth Bellwood, Michael Bentley, Jeremy Bewley, Zoe Garland, Lisa Grimmer, Bethany Gumbrill, Rebekah Johnson, Katie Sweet, Denise Webster, Georgia Efford, Karen Convery, Deirdre Fottrell-Gould, Lisa Hudig, Jocelyn Keshet-Price, Georgina Randell, Katie Stammers, Maria Bokhari, Vanessa Linnett, Rachael Lucas, Wendy McCormick, Jenny Ritzema, Amanda Sanderson, Helen Wild, Anthony Rostron, Alistair Roy, Lindsey Woods, Sarah Cornell, Fiona Wakinshaw, Kimberley Rogerson, Jordan Jarmain, Robert Parker, Amie Reddy, Ian Turner-Bone, Laura Wilding, Peter Harding, Caroline Abernathy, Louise Foster, Andrew Gratrix, Vicky Martinson, Priyai Parkinson, Elizabeth Stones, Llucia Carbral-Ortega, Georgia Bercades, David Brealey, Ingrid Hass, Niall MacCallum, Gladys Martir, Eamon Raith, Anna Reyes, Deborah Smyth, Letizia Zitter, Sarah Benyon, Suzie Marriott, Linda Park, Samantha Keenan, Elizabeth Gordon, Helen Quinn, Kizzy Baines, Lenka Cagova, Adama Fofano, Lucie Garner, Helen Holcombe, Sue Mepham, Alice Michael Mitchell, Lucy Mwaura, Krithivasan Praman, Alain Vuylsteke, Julie Zamikula, Bally Purewal, Vanessa Rivers, Stephanie Bell, Hayley Blakemore, Borislava Borislavova, Beverley Faulkner, Emma Gendall, Elizabeth Goff, Kati Hayes, Matt Thomas, Ruth Worner, Kerry Smith, Deanna Stephens, Louise Mew, Esther Mwaura, Richard Stewart, Felicity Williams, Lynn Wren, Sara-Beth Sutherland, Emily Bevan, Jane Martin, Dawn Trodd, Geoff Watson, Caroline Wrey Brown, Amy Collins, Waqas Khaliq, Estefania Treus Gude, Olugbenga Akinkugbe, Alasdair Bamford, Emily Beech, Holly Belfield, Michael Bell, Charlene Davies, Gareth A.L. Jones, Tara McHugh, Hamza Meghari, Lauran O'Neill, Mark J. Peters, Samiran Ray, Ana Luisa Tomas, Iona Burn, Geraldine Hambrook, Katarina Manso, Ruth Penn, Pradeep Shanmugasundaram, Julie Tebbutt, Danielle Thornton, Jade Cole, Rhys Davies, Donna Duffin, Helen Hill, Ben Player, Emma Thomas, Angharad Williams, Denise Griffin, Nycola Muchenje, Mcdonald Mupudzi, Richard Partridge, Jo-Anna Conyngham, Rachel Thomas, Mary Wright, Maria Alvarez Corral, Reni Jacob, Cathy Jones, Craig Denmade, Sarah Beavis, Katie Dale, Rachel Gascoyne, Joanne Hawes, Kelly Pritchard, Lesley Stevenson, Amanda Whileman, Patricia Doble, Joanne Hutter, Corinne Pawley, Charmaine Shovelton, Marius Vaida, Deborah Butcher, Susie O'Sullivan, Nicola Butterworth-Cowin, Norfaizan Ahmad, Joann Barker, Kris Bauchmuller, Sarah Bird, Kay Cawthron, Kate Harrington, Yvonne Jackson, Faith Kibutu, Becky Lenagh, Shamiso Masuko, Gary H. Mills, Ajay Raithatha, Matthew Wiles, Jayne Willson, Helen Newell, Alison Lye, Lorenza Nwafor, Claire Jarman, Sarah Rowland-Jones, David Foote, Joby Cole, Roger Thompson, James Watson, Lisa Hesseldon, Irene Macharia, Luke Chetam, Jacqui Smith, Amber Ford, Samantha Anderson, Kathryn Birchall, Kay Housley, Sara Walker, Leanne Milner, Helena Hanratty, Helen Trower, Patrick Phillips, Simon Oxspring, Ben Donne, Catherine Jardine, Dewi Williams, Alasdair Hay, Rebecca Flanagan, Gareth Hughes, Scott Latham, Emma McKenna, Jennifer Anderson, Robert Hull, Kat Rhead, Carina Cruz, Natalie Pattison, Rob Charnock, Denise McFarland, Denise Cosgrove, Ashar Ahmed, Anna Morris, Srinivas Jakkula, Asifa Ali, Megan Brady, Sam Dale, Annalisa Dance, Lisa Gledhill, Jill Greig, Kathryn Hanson, Kelly Holdroyd, Marie Home, Diane Kelly, Ross Kitson, Lear Matapure, Deborah Melia, Samantha Mellor, Tonicha Nortcliffe, Jez Pinnell, Matthew Robinson, Lisa Shaw, Ryan Shaw, Lesley Thomis, Alison Wilson, Tracy Wood, Lee-Ann Bayo, Ekta Merwaha, Tahira Ishaq, Sarah Hanley, Meg Hibbert, Dariusz Tetla, Chrsitopher Woodford, Latha Durga, Gareth Kennard-Holden, Debbie Branney, Jordan Frankham, Sally Pitts, Nigel White, Shondipon Laha, Mark Verlander, Alexandra Williams, Abdelhakim Altabaibeh, Ana Alvaro, Kayleigh Gilbert, Louise Ma, Loreta Mostoles, Chetan Parmar, Kathryn Simpson, Champa Jetha, Lauren Booker, Anezka Pratley, Colene Adams, Anita Agasou, Tracie Arden, Amy Bowes, Pauline Boyle, Mandy Beekes, Heather Button, Nigel Capps, Mandy Carnahan, Anne Carter, Danielle Childs, Denise Donaldson, Kelly Hard, Fran Hurford, Yasmin Hussain, Ayesha Javaid, James Jones, Sanal Jose, Michael Leigh, Terry Martin, Helen Millward, Nichola Motherwell, Rachel Rikunenko, Jo Stickley, Julie Summers, Louise Ting, Helen Tivenan, Louise Tonks, Rebecca Wilcox, Maureen Holland, Natalie Keenan, Marc Lyons, Helen Wassall, Chris Marsh, Mervin Mahenthran, Emma Carter, Thomas Kong, Helen Blackman, Ben Creagh-Brown, Sinead Donlon, Natalia Michalak-Glinska, Sheila Mtuwa, Veronika Pristopan, Armorel Salberg, Eleanor Smith, Sarah Stone, Charles Piercy, Jerik Verula, Dorota Burda, Rugia Montaser, Lesley Harden, Irving Mayangao, Cheryl Marriott, Paul Bradley, Celia Harris, Susan Anderson, Eleanor Andrews, Janine Birch, Emma Collins, Kate Hammerton, Ryan O'Leary, Michele Clark, Sarah Purvis, Russell Barber, Claire Hewitt, Annette Hilldrith, Karen Jackson-Lawrence, Sarah Shepardson, Maryanne Wills, Susan Butler, Silvia Tavares, Amy Cunningham, Julia Hindale, Sarwat Arif, Sarah Bean, Karen Burt, Michael Spivey, Carrie Demetriou, Charlotte Eckbad, Sarah Hierons, Lucy Howie, Sarah Mitchard, Lidia Ramos, Alfredo Serrano-Ruiz, Katie White, Fiona Kelly, Daniele Cristiano, Natalie Dormand, Zohreh Farzad, Mahitha Gummadi, Kamal Liyanage, Brijesh Patel, Sara Salmi, Geraldine Sloane, Vicky Thwaites, Mathew Varghese, Anelise C. Zborowski, John Allan, Tim Geary, Gordon Houston, Alistair Meikle, Peter O'Brien, Miranda Forsey, Agilan Kaliappan, Anne Nicholson, Joanne Riches, Mark Vertue, Elizabeth Allan, Kate Darlington, Ffyon Davies, Jack Easton, Sumit Kumar, Richard Lean, Daniel Menzies, Richard Pugh, Xinyi Qiu, Llinos Davies, Hannah Williams, Jeremy Scanlon, Gwyneth Davies, Callum Mackay, Joannne Lewis, Stephanie Rees, Metod Oblak, Monica Popescu, Mini Thankachen, Andrew Higham, Kerry Simpson, Jayne Craig, Rosie Baruah, Sheila Morris, Susie Ferguson, Amy Shepherd, Luke Stephen Prockter Moore, Marcela Paola Vizcaychipi, Laura Gomes de Almeida Martins, Jaime Carungcong, Inthakab Ali Mohamed Ali, Karen Beaumont, Mark Blunt, Zoe Coton, Hollie Curgenven, Mohamed Elsaadany, Kay Fernandes, Sameena Mohamed Ally, Harini Rangarajan, Varun Sarathy, Sivarupan Selvanayagam, Dave Vedage, Matthew White, Mandy Gill, Paul Paul, Valli Ratnam, Sarah Shelton, Inez Wynter, Siobhain Carmody, Valerie Joan Page, Claire Marie Beith, Karen Black, Suzanne Clements, Alan Morrison, Dominic Strachan, Margaret Taylor, Michelle Clarkson, Stuart D'Sylva, Kathryn Norman, Fiona Auld, Joanne Donnachie, Ian Edmond, Lynn Prentice, Nikole Runciman, Dario Salutous, Lesley Symon, Anne Todd, Patricia Turner, Abigail Short, Laura Sweeney, Euan Murdoch, Dhaneesha Senaratne, Michaela Hill, Thogulava Kannan, Wild Laura, Rikki Crawley, Abigail Crew, Mishell Cunningham, Allison Daniels, Laura Harrison, Susan Hope, Ken Inweregbu, Sian Jones, Nicola Lancaster, Jamie Matthews, Alice Nicholson, Gemma Wray, Helen Langton, Rachel Prout, Malcolm Watters, Catherine Novis, Anthony Barron, Ciara Collins, Sundeep Kaul, Heather Passmore, Claire Prendergast, Anna Reed, Paula Rogers, Rajvinder Shokkar, Meriel Woodruff, Hayley Middleton, Oliver Polgar, Claire Nolan, Kanta Mahay, Dawn Collier, Anil Hormis, Victoria Maynard, Cheryl Graham, Rachel Walker, Ellen Knights, Alicia Price, Alice Thomas, Chris Thorpe, Teresa Behan, Caroline Burnett, Jonathan Hatton, Elaine Heeney, Atideb Mitra, Maria Newton, Rachel Pollard, Rachael Stead, Vishal Amin, Elena Anastasescu, Vikram Anumakonda, Komala Karthik, Rizwana Kausar, Karen Reid, Jacqueline Smith, Janet Imeson-Wood, Denise Skinner, Jane Gaylard, Dee Mullan, Julie Newman, Alison Brown, Vikki Crickmore, Gabor Debreceni, Joy Wilkins, Liz Nicol, Rosie Reece-Anthony, Mark Birt, Alison Ghosh, Emma Williams, Louise Allen, Eva Beranova, Nikki Crisp, Joanne Deery, Tracy Hazelton, Alicia Knight, Carly Price, Sorrell Tilbey, Salah Turki, Sharon Turney, Joshua Cooper, Cheryl Finch, Sarah Liderth, Alison Quinn, Natalia Waddington, Tina Coventry, Susan Fowler, Michael MacMahon, Amanda McGregor, Anne Cowley, Judith Highgate, Jane Gregory, Susan O'Connell, Tim Smith, Luigi Barberis, Shameer Gopal, Nichola Harris, Victoria Lake, Stella Metherell, Elizabeth Radford, Amelia Daniel, Joanne Finn, Rajnish Saha, Nikki White, Phil Donnison, Fiona Trim, Beena Eapen, Jenny Birch, Laura Bough, Josie Goodsell, Rebecca Tutton, Patricia Williams, Sarah Williams, Barbara Winter-Goodwin, Ailstair Nichol, Kathy Brickell, Michelle Smyth, Lorna Murphy, Samantha Coetzee, Alistair Gales, Igor Otahal, Meena Raj, Craig Sell, Paula Hilltout, Jayne Evitts, Amanda Tyler, Joanne Waldron, Kate Beesley, Sarah Board, Agnieszka Kubisz-Pudelko, Alison Lewis, Jess Perry, Lucy Pippard, Di Wood, Clare Buckley, Peter Barry, Neil Flint, Patel Rekha, Dawn Hales, Lara Bunni, Claire Jennings, Monica Latif, Rebecca Marshall, Gayathri Subramanian, Peter J. McGuigan, Christopher Wasson, Stephanie Finn, Jackie Green, Erin Collins, Bernadette King, Andy Campbell, Sara Smuts, Joseph Duffield, Oliver Smith, Lewis Mallon, Watkins Claire, Liam Botfield, Joanna Butler, Catherine Dexter, Jo Fletcher, Atul Garg, Aditya Kuravi, Poonam Ranga, Emma Virgilio, Zakaula Belagodu, Bridget Fuller, Anca Gherman, Olumide Olufuwa, Remi Paramsothy, Carmel Stuart, Naomi Oakley, Charlotte Kamundi, David Tyl, Katy Collins, Pedro Silva, June Taylor, Laura King, Charlotte Coates, Maria Crowley, Phillipa Wakefield, Jane Beadle, Laura Johnson, Janet Sargeant, Madeleine Anderson, Ailbhe Brady, Rebekah Chan, Jeff Little, Shane McIvor, Helena Prady, Helen Whittle, Bijoy Mathew, Ben Attwood, Penny Parsons, Geraldine Ward, Pamela Bremmer, West Joe, Baird Tracy, Ruddy Jim, Ellie Davies, Sonia Sathe, Catherine Dennis, Alastair McGregor, Victoria Parris, Sinduya Srikaran, Anisha Sukha, Noreen Clarke, Jonathan Whiteside, Mairi Mascarenhas, Avril Donaldson, Joanna Matheson, Fiona Barrett, Marianne O'Hara, Laura Okeefe, Clare Bradley, Christine Eastgate-Jackson, Helder Filipe, Daniel Martin, Amitaa Maharajh, Sara Mingo Garcia, Glykeria Pakou, Mark De Neef, Kathy Dent, Elizabeth Horsley, Muhmmad Nauman Akhtar, Sandra Pearson, Dorota Potoczna, Sue Spencer, Melanie Clapham, Rosemary Harper, Una Poultney, Polly Rice, Rachel Mutch, Lisa Armstrong, Hayley Bates, Emma Dooks, Fiona Farquhar, Brigid Hairsine, Chantal McParland, Sophie Packham, Rehana Bi, Barney Scholefield, Lydia Ashton, Linsha George, Sophie Twiss, David Wright, Manish Chablani, Amy Kirkby, Kimberley Netherton, Kim Davies, Linda O'Brien, Zohra Omar, Emma Perkins, Tracy Lewis, Isobel Sutherland, Karen Burns, Dr Ben Chandler, Kerry Elliott, Janine Mallinson, Alison Turnbull, Prisca Gondo, Bernard Hadebe, Abdul Kayani, Bridgett Masunda, Taya Anderson, Dan Hawcutt, Laura O'Malley, Laura Rad, Naomi Rogers, Paula Saunderson, Kathryn Sian Allison, Deborah Afolabi, Jennifer Whitbread, Dawn Jones, Rachael Dore, Matthew Halkes, Pauline Mercer, Lorraine Thornton, Joy Dawson, Sweyn Garrioch, Melanie Tolson, Jonathan Aldridge, Ritoo Kapoor, David Loader, Karen Castle, Sally Humphreys, Ruth Tampsett, Katherine Mackintosh, Amanda Ayers, Wendy Harrison, Julie North, Suzanne Allibone, Roman Genetu, Vidya Kasipandian, Amit Patel, Ainhi Mac, Anthony Murphy, Parisa Mahjoob, Roonak Nazari, Lucy Worsley, Andrew Fagan, Thomas Bemand, Ethel Black, Arnold Dela Rosa, Ryan Howle, Shaman Jhanji, Ravishankar Rao Baikady, Kate Colette Tatham, Benjamin Thomas, Dina Bell, Rosalind Boyle, Katie Douglas, Lynn Glass, Emma Lee, Liz Lennon, Austin Rattray, Abigail Taylor, Rachel Anne Hughes, Helen Thomas, Alun Rees, Michaela Duskova, Janet Phipps, Suzanne Brooks, Michelle Edwards, Sheena Quaid, Ekaterina Watson, Adam Brayne, Emma Fisher, Jane Hunt, Peter Jackson, Duncan Kaye, Nicholas Love, Juliet Parkin, Victoria Tuckey, Lynne Van Koutrik, Sasha Carter, Benedict Andrew, Louise Findlay, Katie Adams, Jen Service, Alison Williams, Claire Cheyne, Anne Saunderson, Sam Moultrie, Miranda Odam, Kathryn Hall, Isheunesu Mapfunde, Charlotte Willis, Alex Lyon, Chunda Sri-Chandana, Joslan Scherewode, Lorraine Stephenson, Sarah Marsh, John Hardy, Henry Houlden, Eleanor Moncur, Ambreen Tariq, Arianna Tucci, Maria Hobrok, Ronda Loosley, Heather McGuinness, Helen Tench, Rebecca Wolf-Roberts, Val Irvine, Benjamin Shelley, Claire Gorman, Abhinav Gupta, Elizabeth Timlick, Rebecca Brady, Barry Milligan, Arianna Bellini, Jade Bryant, Anton Mayer, Amy Pickard, Nicholas Roe, Jason Sowter, Alex Howlett, Katy Fidler, Emma Tagliavini, and Kevin Donnelly
Subjects: SARS-CoV-2, host genetics, toll-like receptor 7, targeted sequencing, rare variants, variant collapsing analysis, Genetics, QH426-470
Abstract: Summary: Despite extensive global research into genetic predisposition for severe COVID-19, knowledge on the role of rare host genetic variants and their relation to other risk factors remains limited. Here, 52 genes with prior etiological evidence were sequenced in 1,772 severe COVID-19 cases and 5,347 population-based controls from Spain/Italy. Rare deleterious TLR7 variants were present in 2.4% of young (
Published: 2024
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48. Insights Into Child Abuse and Neglect in the Washington DC, Maryland, and Virginia (DMV) Area: Evidence and Opportunities

Author: Intima Alrimawi PhD, RN, Elizabeth Bettini PhD, APRN, PCNS-BC, Clishia Taylor DMIN, MBA, RN, CDI, ICTTP, Ahmad Rajeh Saifan PhD, RN, and Nabeel Al-Yateem PhD, RN
Subjects: Pediatrics, RJ1-570
Abstract: Child abuse and neglect (CAN) significantly impact health, the economy, and society. This narrative review examines CAN in the Washington DC, Maryland, and Virginia (DMV) region, comparing it with national and international levels. The review highlights high CAN rates in the DMV, driven by factors such as socioeconomic status, parental substance abuse, and child vulnerabilities. Screening and reporting challenges, exacerbated by the COVID-19 pandemic, impede accurate data collection. This review emphasizes the need for standardized reporting mechanisms, economic investment in public health, and intersectoral collaboration. It recommends targeted support for at-risk families, specialized care for vulnerable children, and the development of predictive screening tools. Continuous research on regional and cultural factors and the pandemic’s impact is crucial for future resilience. Addressing CAN requires a comprehensive approach involving prevention, early detection, intervention, and policy reform to safeguard the well-being of children.
Published: 2024
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49. Speck: a traditional culinary specialty from the Italian Alps. A microbiological, molecular and chemical evaluation

Author: Stefano Colorio, Francesca Precazzini, Martina Stella, Michela Rabini, Gloria Paolazzi, Evelin Elke Oberkalmsteiner, Mara Borghi, Astrid Bettini, and Alexander Tavella
Subjects: Speck, food safety criteria, process hygiene criteria, Food processing and manufacture, TP368-456
Abstract: South Tyrol is the northernmost Italian province; its history, geography, and closeness to other European countries, such as Austria and Switzerland, have influenced both culture and food production. Among the South Tyrolean culinary specialties, a type of dry-cured ham called Südtiroler Speck/Speck Alto Adige (Speck) plays a relevant role and has gained increasing significance both on a national and international level over the last 2 decades. Despite it being a common culinary product in Italian and international markets, there is not much published data regarding the microbiological and chemical features of Speck. This study describes the analytical results obtained during a period of 7 years, during which the main pathogens and contaminants were considered.
Published: 2024
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50. Tradução e validação do instrumento Childhood Hearing Loss Question Prompt List for Parents para a língua portuguesa brasileira

Author: Adriéli Bettini de Moraes, Elaine Cristina Moreto Paccola, Amanda Salimon, Adriane Lima Mortari Moret, Natália Barreto Frederigue-Lopes, and Regina Tangerino de Souza Jacob
Subjects: Perda auditiva, Criança, Família, Aconselhamento, Tradução, Validação, Otorhinolaryngology, RF1-547
Abstract: RESUMO Objetivo traduzir e validar para o português brasileiro o instrumento Childhood Hearing Loss Question Prompt List for Parents, visando apoiar a comunicação entre profissionais de saúde e famílias de crianças com perda auditiva no Brasil. Métodos abordagem metodológica compreendendo a tradução e adaptação transcultural do instrumento, seguida de validação por meio de um processo iterativo que envolveu especialistas e o público-alvo. A tradução foi realizada por tradutores bilíngues, com subsequente retrotradução e revisão por um comitê de especialistas, para assegurar a equivalência conceitual e cultural. A validação envolveu a coleta e análise de feedback de pais de crianças com perda auditiva e profissionais fonoaudiólogos, utilizando o Índice de Validade de Conteúdo para avaliar a adequação do instrumento. Resultados a análise indicou aceitação positiva do instrumento traduzido, com a maioria dos itens atingindo Índice de Validade de Conteúdo acima do limiar de 0,78, refletindo a relevância e compreensibilidade do instrumento no contexto brasileiro. Um item específico não atingiu o índice desejado, destacando a necessidade de revisão adicional para otimizar a clareza e pertinência. Conclusão o Childhood Hearing Loss Question Prompt List for Parents traduzido e validado demonstrou ser uma ferramenta eficaz para o contexto brasileiro, facilitando a comunicação centrada na família e o envolvimento em cuidados auditivos pediátricos. Este estudo reforça a importância de adaptar e validar instrumentos de avaliação para refletir as especificidades culturais e linguísticas, assegurando a aplicabilidade e eficácia no atendimento às famílias de crianças com perda auditiva.
Published: 2024
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