Abstract Online tuning of particle accelerators is a complex optimisation problem that continues to require manual intervention by experienced human operators. Autonomous tuning is a rapidly ...expanding field of research, where learning-based methods like Bayesian optimisation (BO) hold great promise in improving plant performance and reducing tuning times. At the same time, reinforcement learning (RL) is a capable method of learning intelligent controllers, and recent work shows that RL can also be used to train domain-specialised optimisers in so-called reinforcement learning-trained optimisation (RLO). In parallel efforts, both algorithms have found successful adoption in particle accelerator tuning. Here we present a comparative case study, assessing the performance of both algorithms while providing a nuanced analysis of the merits and the practical challenges involved in deploying them to real-world facilities. Our results will help practitioners choose a suitable learning-based tuning algorithm for their tuning tasks, accelerating the adoption of autonomous tuning algorithms, ultimately improving the availability of particle accelerators and pushing their operational limits.
Coherent synchrotron radiation (CSR) is generated when the electron bunch length is in the order of the magnitude of the wavelength of the emitted radiation. The self-interaction of short electron ...bunches with their own electromagnetic fields changes the longitudinal beam dynamics significantly. Above a certain current threshold, the micro-bunching instability develops, characterized by the appearance of distinguishable substructures in the longitudinal phase space of the bunch. To stabilize the CSR emission, a real-time feedback control loop based on reinforcement learning (RL) is proposed. Informed by the available THz diagnostics, the feedback is designed to act on the radio frequency (RF) system of the storage ring to mitigate the micro-bunching dynamics. To satisfy low-latency requirements given by the longitudinal beam dynamics, the RL controller has been implemented on hardware (FPGA). In this article, a real-time feedback loop architecture and its performance is presented and compared with a software implementation using Keras-RL on CPU/GPU. The results obtained with the CSR simulation Inovesa demonstrate that the functionality of both platforms is equivalent. The training performance of the hardware implementation is similar to software solution, while it outperforms the Keras-RL implementation by an order of magnitude. The presented RL hardware controller is considered as an essential platform for the development of intelligent CSR control systems.
The predictive coding theory of allostatic-interoceptive load states that brain networks mediating autonomic regulation and interoceptive-exteroceptive balance regulate the internal milieu to ...anticipate future needs and environmental demands. These functions seem to be distinctly compromised in behavioral variant frontotemporal dementia (bvFTD), including alterations of the allostatic-interoceptive network (AIN). Here, we hypothesize that bvFTD is typified by an allostatic-interoceptive overload.
We assessed resting-state heartbeat evoked potential (rsHEP) modulation as well as its behavioral and multimodal neuroimaging correlates in patients with bvFTD relative to healthy control subjects and patients with Alzheimer’s disease (N = 94). We measured 1) resting-state electroencephalography (to assess the rsHEP, prompted by visceral inputs and modulated by internal body sensing), 2) associations between rsHEP and its neural generators (source location), 3) cognitive disturbances (cognitive state, executive functions, facial emotion recognition), 4) brain atrophy, and 5) resting-state functional magnetic resonance imaging functional connectivity (AIN vs. control networks).
Relative to healthy control subjects and patients with Alzheimer’s disease, patients with bvFTD presented more negative rsHEP amplitudes with sources in critical hubs of the AIN (insula, amygdala, somatosensory cortex, hippocampus, anterior cingulate cortex). This exacerbated rsHEP modulation selectively predicted the patients’ cognitive profile (including cognitive decline, executive dysfunction, and emotional impairments). In addition, increased rsHEP modulation in bvFTD was associated with decreased brain volume and connectivity of the AIN. Machine learning results confirmed AIN specificity in predicting the bvFTD group.
Altogether, these results suggest that bvFTD may be characterized by an allostatic-interoceptive overload manifested in ongoing electrophysiological markers, brain atrophy, functional networks, and cognition.
Dementia is becoming increasingly prevalent in Latin America, contrasting with stable or declining rates in North America and Europe. This scenario places unprecedented clinical, social, and economic ...burden upon patients, families, and health systems. The challenges prove particularly pressing for conditions with highly specific diagnostic and management demands, such as frontotemporal dementia. Here we introduce a research and networking initiative designed to tackle these ensuing hurdles, the Multi-partner consortium to expand dementia research in Latin America (ReDLat). First, we present ReDLat's regional research framework, aimed at identifying the unique genetic, social, and economic factors driving the presentation of frontotemporal dementia and Alzheimer's disease in Latin America relative to the US. We describe ongoing ReDLat studies in various fields and ongoing research extensions. Then, we introduce actions coordinated by ReDLat and the Latin America and Caribbean Consortium on Dementia (LAC-CD) to develop culturally appropriate diagnostic tools, regional visibility and capacity building, diplomatic coordination in local priority areas, and a knowledge-to-action framework toward a regional action plan. Together, these research and networking initiatives will help to establish strong cross-national bonds, support the implementation of regional dementia plans, enhance health systems' infrastructure, and increase translational research collaborations across the continent.
We have evaluated the data-efficient Bayesian optimization method for the specific task of injection tuning in a circular accelerator. In this paper, we describe the implementation of this method at ...the Karlsruhe Research Accelerator with up to nine tuning parameters, including the determination of the associated hyperparameters. We show that the Bayesian optimization method outperforms manual tuning and the commonly used Nelder-Mead optimization algorithm in both simulation and experiment. The algorithm was also successfully used to ease the commissioning phase after the installation of new injection magnets and is regularly used during accelerator operations. We demonstrate that the introduction of context variables that include intrabunch scattering effects, such as the Touschek effect, further improves the control and robustness of the injection process.
Behavioral variant frontotemporal dementia (bvFTD) has been related to different genetic factors. Identifying multimodal phenotypic heterogeneity triggered by various genetic influences is critical ...for improving diagnosis, prognosis, and treatments. However, the specific impact of different genetic levels (mutations vs. risk variants vs. sporadic presentations) on clinical and neurocognitive phenotypes is not entirely understood, specially in patites from underrepresented regions such as Colombia.
Here, in a multiple single cases study, we provide systematic comparisons regarding cognitive, neuropsychiatric, brain atrophy, and gene expression-atrophy overlap in a novel cohort of FTD patients (n = 42) from Colombia with different genetic levels, including patients with known genetic influences (G-FTD) such as those with genetic mutations (GR1) in particular genes (MAPT, TARDBP, and TREM2); patients with risk variants (GR2) in genes associated with FTD (tau Haplotypes H1 and H2 and APOE variants including ε2, ε3, ε4); and sporadic FTD patients (S-FTD (GR3)).
We found that patients from GR1 and GR2 exhibited earlier disease onset, pervasive cognitive impairments (cognitive screening, executive functioning, ToM), and increased brain atrophy (prefrontal areas, cingulated cortices, basal ganglia, and inferior temporal gyrus) than S-FTD patients (GR3). No differences in disease duration were observed across groups. Additionally, significant neuropsychiatric symptoms were observed in the GR1. The GR1 also presented more clinical and neurocognitive compromise than GR2 patients; these groups, however, did not display differences in disease onset or duration. APOE and tau patients showed more neuropsychiatric symptoms and primary atrophy in parietal and temporal cortices than GR1 patients. The gene-atrophy overlap analysis revealed atrophy in regions with specific genetic overexpression in all G-FTD patients. A differential family presentation did not explain the results.
Our results support the existence of genetic levels affecting the clinical, neurocognitive, and, to a lesser extent, neuropsychiatric presentation of bvFTD in the present underrepresented sample. These results support tailored assessments characterization based on the parallels of genetic levels and neurocognitive profiles in bvFTD.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Although social cognition is compromised in patients with neurodegenerative disorders such as behavioral variant frontotemporal dementia (bvFTD) and Alzheimer's disease (AD), research on moral ...emotions and their neural correlates in these populations is scarce. No previous study has explored the utility of moral emotions, compared to and in combination with classical general cognitive state tools, to discriminate bvFTD from AD patients.
To examine self-conscious (guilt and embarrassment) and other-oriented (pity and indignation) moral emotions, their subjective experience, and their structural brain underpinnings in bvFTD (n = 31) and AD (n = 30) patients, compared to healthy controls (n = 37). We also explored the potential utility of moral emotions measures to discriminate bvFTD from AD.
We used a modified version of the Moral Sentiment Task measuring the participants' accuracy scores and their emotional subjective experiences.
bvFTD patients exhibited greater impairments in self-conscious and other-oriented moral emotions as compared with AD patients and healthy controls. Moral emotions combined with general cognitive state tools emerged as useful measures to discriminate bvFTD from AD patients. In bvFTD patients, lower moral emotions scores were associated with lower gray matter volumes in caudate nucleus and inferior and middle temporal gyri. In AD, these scores were associated with lower gray matter volumes in superior and middle frontal gyri, middle temporal gyrus, inferior parietal lobule and supramarginal gyrus.
These findings contribute to a better understanding of moral emotion deficits across neurodegenerative disorders, highlighting the potential benefits of integrating this domain into the clinical assessment.
Machine learning has emerged as a powerful solution to the modern challenges in accelerator physics. However, the limited availability of beam time, the computational cost of simulations, and the ...high dimensionality of optimization problems pose significant challenges in generating the required data for training state-of-the-art machine learning models. In this work, we introduce heetah, a yorch-based high-speed differentiable linear beam dynamics code. heetah enables the fast collection of large datasets by reducing computation times by multiple orders of magnitude and facilitates efficient gradient-based optimization for accelerator tuning and system identification. This positions heetah as a user-friendly, readily extensible tool that integrates seamlessly with widely adopted machine learning tools. We showcase the utility of heetah through five examples, including reinforcement learning training, gradient-based beamline tuning, gradient-based system identification, physics-informed Bayesian optimization priors, and modular neural network surrogate modeling of space charge effects. The use of such a high-speed differentiable simulation code will simplify the development of machine learning-based methods for particle accelerators and fast-track their integration into everyday operations of accelerator facilities. Published by the American Physical Society 2024
In parallel with the development and design of different technological advances, competencies in nursing have advanced. With the development of robotics, it is expected that nursing robotic ...competencies will also increase. The aim of this study is to review the competencies in nursing robotics. A review was conducted between January 2017 and December 2023. The search strategy was carried out in the MEDLINE database (through PubMed). This review explores the developmental competencies in nursing robotics and informatics. The data extraction in this review included an intentional search for competencies and learning outcomes in engineering and robotic programs. A total of 340 competencies and program outcomes were reviewed. The synthesis of the data established a total of 17 developmental competencies in nursing robotics based on this knowledge extraction, which we organized into five categories: assessment, diagnosis, planning, intervention (implementation) and evaluation. This review suggests that nursing robotic competencies for the development of care robotics are still scarce, and there is an opportunity for the development of competencies and the definition of new roles in the area of nursing informatics in order to adapt to the new health care demands of society.
Persons that lived through periods of confinement suffered an impact on their physical and mental health. The adaptation of the lifestyle in relation to activity, sleep and social relationships is ...key to facing these periods of confinement. The aim is to validate a series of care recommendations aimed at being able to maintain an active and healthy confinement, which serves to prepare the population for future health crises. This study is part of a general strategy based on a care recommendation guide for COVID-19. The validation was carried out by a group of experts using the Delphi technique through a questionnaire that uses the Content Validity Index (CVI) and considers high validation those with a score >0.80. A total of 75 care recommendations are proposed: 30 on activity-exercise (CVI = 0.82), 14 on sleep-rest (CVI = 0.83) and 31 on roles-relationships (CVI = 0.83). Additionally, 49 recommendations achieve high validation. The care recommendations integrate a person-centred model, which addresses individual characteristics (age, health status, professional role). An active and healthy confinement requires respecting social distance measures, maintaining a balance between physical activity and sleep, and using technologies to promote social contact, which promote well-being and avoid depression and anxiety.
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