Miracle-dz/UniFAR-FTUs huggingface dataset:
The mini astrophysical MeV background observatory (MAMBO) CubeSat mission for gamma-ray astronomy

The origin of the Cosmic Diffuse Gamma-ray (CDG) background in the 0.3 to 30 MeV energy range is a mystery that has persisted for 50 years. The best existing measurements have large systematic uncertainties, and the latest theoretical models based on emission from active galactic nuclei and supernovae differ significantly from these data below 1 MeV. The Mini Astrophysical MeV Background Observatory (MAMBO) is a new CubeSat mission under development at Los Alamos National Laboratory with the goal of making high-quality measurements of the MeV CDG to help solve this puzzle. The concept is motivated by the fact that, since the MeV CDG is relatively bright, only a small detector is required to make high-quality measurements of it. Indeed, the sensitivity of space-based gamma-ray instruments to the MeV CDG is limited not by size, but by the locally generated instrumental background produced by interactions of energetic particles in spacecraft materials. Comparatively tiny CubeSat platforms provide a uniquely quiet environment relative to previous gamma-ray science missions. The MAMBO mission will provide the best measurements ever made of the MeV CDG spectrum and angular distribution, utilizing two key innovations: 1) low instrumental background on a 12U CubeSat platform; and 2) an innovative shielded spectrometer design that simultaneously measures signal and background. Los Alamos is partnering with commercial vendors for the 12U CubeSat bus and ground station network, which we expect will become a new paradigm for low-cost, fast-turnaround space science missions. We present calibration and test results for the payload and simulations of the expected scientific return.
SketchSearch: Fine-tuning Reference Maps to Create Exercises In Support of Video-based Learning for Surgeons

Video-based surgical coaching involves mentors reviewing surgery footage with trainees. Although effective, its use is sporadic due to time constraints. We propose AI-augmented coaching through SketchSearch, allowing experts to create exercises with automated feedback in surgery videos for self-learning. Surgeons often seek specific scenes for teaching, relying on visual cues. SketchSearch simplifies this through a three-step process: key frame extraction, template reference maps creation via image segmentation, and fine-tuning for frame retrieval.
An Algorithmic Approach to Automated Symbolic Transcription of Hindustani Vocals

Although a sizable body of digital music scholarship has focused on automatic transcription, it has almost exclusively been applied to Western music. In this paper, we outline an algorithm to automate the transcription of vocal performances of Hindustāni classical music (HCM) from fundamental frequency (f0) contours. The goal of our algorithm is to output a symbolic representation that reduces the performance to a high-level syntactic construct—akin to a musical score—for use in computational music analysis. In particular, our algorithm not only transcribes notes but also ornamentation, focusing on a subset of the most common ornamentation types in HCM. In order to evaluate the performance of our ornamentation detection and classification, we created a small dataset of Hindustāni ornamentation, labeled by Hindustāni music experts: Ornamentation in Hindustāni Vocals (OHV) dataset. To our knowledge, this is the first such dataset, and the first algorithm to attempt to automatically transcribe both notes and ornamentation from vocals. To evaluate our automatic music transcription algorithm we use the Saraga dataset [39] to evaluate stable notes (swara), and the OHV to evaluate ornamentation. Finally, we transcribe the entire aggregate output (notes and ornamentation) in humdrum format and make it available publicly. Remaining challenges for future research are discussed.
Towards Trauma-Informed Data Donation of Sexual Experience in Online Dating to Improve Sexual Risk Detection AI

Sexual risk detection AI has been touted as a scalable solution for computer-mediated sexual violence. Data donation is a user-centered approach to producing ecologically valid datasets for sexual risk detection AI: voluntarily providing personal data that is representative of risk. However, the act of donating intimate sexual experience data can itself be traumatizing. We propose Ube: a trauma-informed sexual experience data donation app for online daters that is developed jointly with sexual violence experts and care practitioners. Cognitive walkthroughs of Ube with these experts elucidated several design approaches to mitigate retraumatization during data donation, including a conversational agent and mental health checks.
Sounding Out Reconstruction Error-Based Evaluation of Generative Models of Expressive Performance

Generative models of expressive piano performance are usually assessed by comparing their predictions to a reference human performance. A generative algorithm is taken to be better than competing ones if it produces performances that are closer to a human reference performance. However, expert human performers can (and do) interpret music in different ways, making for different possible references, and quantitative closeness is not necessarily aligned with perceptual similarity, raising concerns about the validity of this evaluation approach. In this work, we present a number of experiments that shed light on this problem. Using precisely measured high-quality performances of classical piano music, we carry out a listening test indicating that listeners can sometimes perceive subtle performance difference that go unnoticed under quantitative evaluation. We further present tests that indicate that such evaluation frameworks show a lot of variability in reliability and validity across different reference performances and pieces. We discuss these results and their implications for quantitative evaluation, and hope to foster a critical appreciation of the uncertainties involved in quantitative assessments of such performances within the wider music information retrieval (MIR) community.
Computational Similarity of Portuguese Folk Melodies Using Hierarchical Reduction

We propose a method for computing the similarity of symbolically-encoded Portuguese folk melodies. The main novelty of our method is the use of a preprocessing melodic reduction at multiple hierarchies to filter the surface of folk melodies according to 1) pitch stability, 2) interval salience, 3) beat strength, 4) durational accents, and 5) the linear combination of all former criteria. Based on the salience of each note event per criteria, we create three melodic reductions with three different levels of note retention. We assess the degree to which six folk music similarity measures at multiple reduction hierarchies comply with collected ground truth from experts in Portuguese folk music. The results show that SIAM combined with 75th quantile reduction using the combined or durational accents best models the similarity for a corpus of Portuguese folk melodies by capturing approximately 84-90% of the variance observed in ground truth annotations.
Supporting Independence of Autistic Adults through Mobile and Virtual Reality Technologies

Pervasive symptoms in autistic individuals, such as facing more frequent challenges in social situations, pose significant obstacles in their pursuit of an independent life in adulthood. Although much research has proposed computer-assisted programs (e.g., smartphone apps and VR-based systems), there is a significant lack of systems designed for autistic adults and their independence, and the preferences or characteristics of autistic individuals are not carefully reflected in the design process. Thus, in my dissertation, I focus on two requirements of autistic adults for supporting their independence: (1) an independent and healthy lifestyle and (2) positive social skill practice. These requirements were externalized in two gamified mobile apps (PuzzleWalk and RoutineAid) and two VR-based systems (VISTA and V-DAT). My research aims to design and develop mobile/VR systems and derive design guidelines to support the independence of autistic adults.
Docent: Digital Operation-Centric Elicitation of Novice-friendly Tutorials

Nowadays, novice users often turn to digital tutorials for guidance in software. However, searching and utilizing the tutorial remains a challenge due to the request for proper problem articulation, extensive searches and mind-intensive follow-through. We introduce "Docent", a system designed to bridge this knowledge-seeking gap. Powered by Large Language Models (LLMs), Docent takes vague user input and recent digital operation contexts to reason, seek, and present the most relevant tutorials in-situ. We assume that Docent smooths the user experience and facilitates learning of the software.
Sonic Storyteller: Augmenting Oral Storytelling with Spatial Sound Effects

Traditional oral storytelling has been predominantly limited to a live audience, augmented with voice acting, sound effects, and gestures. With new technologies, the reach of oral storytelling has expanded to allow remote listeners to tune in to radio programs and more recently to listen to podcasts and audio books, asynchronously. Digital tools offer easy-to-use applications that enable anyone the ability to not only narrate a story, but also to augment it in different ways, from adding sound effects in podcasts to narrating audio books with voice effects. In this work, we present a proof-of-concept system that allows oral storytellers to augment their storytelling with spatial sound effects. We present results from a preliminary study (n=12) that found the spatial sound effects to be vivid and immersive, indicating potential for semi-automated ways of augmenting oral storytelling.
The “OpenScore String Quartet” Corpus

The “OpenScore String Quartet” Corpus is a new dataset of historic works for string quartets, encoded by a dedicated team of volunteers, and released freely for all use cases (CC0). In creating this corpus, we built on the experience amassed during the ‘OpenScore Lieder Corpus’ (Gotham and Jonas, MEC 2021), however, the quartets presented some additional challenges including the need for more significant editorial intervention. Here we report on the size and contents of the corpus (more than 100 full quartets by over 40 composers), we discuss the editorial-musicological aspects of producing modern playing scores from ambiguous or incomplete source material, and we suggest some prospective use cases for this dataset in music information retrieval (MIR).
Absolute Phase Estimation from TerraSAR-X Acquisitions using Wideband Interferometry

Estimation of topography for the generation of digital elevation models requires unwrapping of the interferometric phase to obtain the absolute phase. When the topography changes rapidly or the geometry is unfavourable, phase unwrapping cannot always be performed correctly leaving gaps or errors in the digital elevation model. Based on taking the differential phase between two subband interferogramsn, the delta-k technique can artifically increases the height of ambiguity by up to several orders of magnitude. This renders phase unwrapping unnecessary and directly provides the absolute phase. Here we present some preliminary results demonstrating the application of delta-k interferometry to TerraSAR-X data.
Rheuma-VOR study: optimising healthcare of rheumatic diseases by multiprofessional coordinating centres

Objectives Early diagnosis of inflammatory arthritis is critical to prevent joint damage and functional incapacities. However, the discrepancy between recommendations of early diagnosis and reality is remarkable. The Rheuma-VOR study aimed to improve the time to diagnosis of patients with early arthritis by coordinating cooperation between primary care physicians, specialists and patients in Germany. Methods This prospective non-randomised multicentre study involved 2340 primary care physicians, 72 rheumatologists, 4 university hospitals and 4 rheumatology centres in 4 German Federal States. The two coprimary endpoints (time to diagnosis and screening performance of primary care physicians) were evaluated for early versus late implementation phase. Additionally, time to diagnosis and secondary endpoints (decrease of disease activity, increase in quality of life and overall well-being, improvement of fatigue, depression, functional ability, and work ability, reduction in drug and medical costs and hospitalisation) were compared with a reference cohort of the German Rheumatism Research Centre (DRFZ) reflecting standard care. Results A total of 7049 patients were enrolled in the coordination centres and 1537 patients were diagnosed with a rheumatic disease and consented to further participation. A follow-up consultation after 1 year was realised in 592 patients. The time to diagnosis endpoint and the secondary endpoints were met. In addition, the calculation of cost-effectiveness shows that Rheuma-VOR has a dominant cost–benefit ratio compared with standard care. Discussion Rheuma-VOR has shown an improvement in rheumatological care, patient-reported outcome parameters and cost savings by coordinating the cooperation of primary care physicians, rheumatologists and patients, in a nationwide approach.
Healthy by Nature: Policy Practices Aimed at Maximizing the Human Behavioral Health Benefits of Nature Contact

Research suggests that spending time in nature is associated with numerous human behavioral health benefits, including improved executive functioning abilities, enhanced recovery from stressful situations, better mental health, and better educational outcomes. Greener neighborhoods also tend to have positive population-level health outcomes. Although promising, much of this research has focused primarily on selective populations and fails to account for cultural differences in how “nature” is conceptualized. Therefore, challenges may arise as policymakers aim to implement nature-based policies in their communities, given the immense cultural diversity of the United States alone. Given this ever-present challenge in behavioral sciences, policy recommendations aim both to maximize benefits of nature contact and to employ a flexible equity lens that allow for differences according to community need.
Soil seed bank composition along a forest chronosequence in seasonally moist tropical forest, Panama

We used a forest chronosequence at the Barro Colorado Nature Monument (BCNM) to examine changes in the abundance and species composition of seeds in the soil during forest succession. At each of eight sites varying from 20 yr to 100 yr since abandonment, and at two old-growth (> 500 yr) forest stands, we established two 160-m transects and sampled the surface 0 - 3 cm of soil in cores collected at each 5 m interval. Seed densities were estimated from the number of seedlings germinated from the soil over a six-week period. Contrary to expectation, neither the density of the soil seed bank, nor species richness or diversity were directly related to age since abandonment, but the density of the soil seed bank was correlated with the abundance of seed-bank- forming species in the standing vegetation. In marked contrast to published studies, herbaceous taxa were rare even in the youngest stands, and the common tree species, which ac- counted for most seeds in the soil, were present in all stands. The pioneer tree Miconia argentea (Melastomataceae) was the single most common species in the seed bank, accounting for 62 % of seeds and present in 92 % of soil samples. Rapid recovery of the vegetation of young regrowth stands on BCNM, when compared to sites elsewhere may be partly due to allochthonous seed rain from nearby mature forest stands and the lack of seed inputs of weeds and grasses from agricultural and pasture lands which may inhibit forest succession.
Identification of disulfidptosis-related genes and immune infiltration in lower-grade glioma

Abstract Lower-grade glioma (LGG), a prevalent malignant tumor in the central nervous system, requires accurate prediction and treatment to prevent aggressive progression. We aimed to explore the role of disulfidptosis-related genes (DRGs) in LGG, a recently discovered form of programmed cell death characterized by abnormal disulfide accumulation. Leveraging public databases, we analyzed 532 LGG tumor tissues (The Cancer Genome Atlas), 1,157 normal samples (Genotype-Tissue Expression), and 21 LGG tumor samples with 8 paired normal samples (GSE16011). Our research uncovered intricate relationships between DRGs and crucial aspects of LGG, including gene expression, immune response, mutation, drug sensitivity, and functional enrichment. Notably, we identified significant heterogeneity among disulfidptosis sub-clusters and elucidated specific differential gene expression in LGG, with myeloid cell leukemia-1 (MCL1) as a key candidate. Machine learning techniques validated the relevance of MCL1, considering its expression patterns, prognostic value, diagnostic potential, and impact on immune infiltration. Our study offers opportunities and challenges to unravel potential mechanisms underlying LGG prognosis, paving the way for personalized cancer care and innovative immunotherapeutic strategies. By shedding light on DRGs, particularly MCL1, we enhance understanding and management of LGG.
Monocytes reprogrammed by 4-PBA potently contribute to the resolution of inflammation and atherosclerosis

Background Chronic inflammation initiated by inflammatory monocytes underlies the pathogenesis of atherosclerosis. However, approaches that can effectively resolve chronic low-grade inflammation targeting monocytes are not readily available. The small chemical compound 4-phenylbutyric acid (4-PBA) exhibits broad anti-inflammatory effects in reducing atherosclerosis. Selective delivery of 4-PBA reprogrammed monocytes may hold novel potential in providing targeted and precision therapeutics for the treatment of atherosclerosis. Methods Systems analyses integrating single-cell RNA-sequencing and complementary immunological approaches characterized key resolving characteristics as well as defining markers of reprogrammed monocytes trained by 4-PBA. Molecular mechanisms responsible for monocyte reprogramming was assessed by integrated biochemical and genetic approaches. The inter-cellular propagation of homeostasis resolution was evaluated by co-culture assays with donor monocytes trained by 4-PBA and recipient naïve monocytes. The in vivo effects of monocyte resolution and atherosclerosis prevention by 4-PBA were assessed with the high fat diet-fed ApoE-/- mouse model with i.p. 4-PBA administration. Furthermore, the selective efficacy of 4-PBA trained monocytes were examined by i.v. transfusion of ex vivo trained monocytes by 4-PBA into recipient high fat diet-fed ApoE-/- mice. Results In this study, we found that monocytes can be potently reprogrammed by 4-PBA into an immune-resolving state characterized by reduced adhesion and enhanced expression of anti-inflammatory mediator CD24. Mechanistically, 4-PBA reduced the expression of ICAM-1 via reducing peroxisome stress and attenuating SYK-mTOR signaling. Concurrently, 4-PBA enhanced the expression of resolving mediator CD24 through promoting PPARγ neddylation mediated by TOLLIP. 4-PBA trained monocytes can effectively propagate anti-inflammation activity to neighboring monocytes through CD24. Our data further demonstrated that 4-PBA trained monocytes effectively reduce atherosclerosis pathogenesis when administered in vivo. Conclusion Our study describes a robust and effective approach to generate resolving monocytes, characterizes novel mechanisms for targeted monocyte reprogramming, and offers a precision-therapeutics for atherosclerosis based on delivering reprogrammed resolving monocytes.
P116 from Mycoplasma is a self-sufficient lipid uptake and delivery machinery

Lipid acquisition and transport are fundamental processes in all organisms, but many of the key players remain unidentified. Here, we elucidate the lipid-cycling mechanism of the Mycoplasma pneumoniae membrane protein P116. We show that P116 not only extracts lipids from its environment but also self-sufficiently deposits them into both bacterial and eukaryotic cell membranes as well as liposomes. Our structures and molecular dynamics simulation show that the N-terminal region of P116, which resembles an SMP domain, is responsible for perturbing the membrane, while a hydrophobic pocket exploits the chemical gradient to collect the lipids and the protein’s dorsal side acts as a mediator of membrane directionality. Furthermore, ligand binding and growth curve assays suggest the potential for designing small molecule inhibitors targeting this essential and immunodominant protein. We show that P116 is a versatile lipid acquisition and delivery machinery that shortcuts the multi-protein pathways used by more complex organisms. Thus, our work advances the understanding of common lipid transport strategies, which may aid research into the mechanisms of more complex lipid-handling machineries.
A novel class of ultra-stable endospore appendages decorated with collagen-like tip fibrillae

Bacterial endospores are remarkable examples of biological resilience, representing a dormant and heavily fortified differentiation form capable of withstanding physical and chemical stressors detrimental to vegetative cells. In pathogenic firmicutes, spores also form an infectious particle and can take up a central role in the environmental persistence and dissemination of disease. A poorly understood aspect of spore-mediated infection is the fibrous structures or ‘endospore appendages’ (ENAs) that have been seen to decorate the spores of pathogenic Bacilli and Clostridia. New methodological approaches are opening an unprecedented window on these long enigmatic structures. Using cryoID, Alphafold modelling and genetic approaches we identify a novel class of ultra-robust ENAs formed by Bacillus paranthracis. We demonstrate that L-ENA are encoded by a three-gene cluster (ena3) that contains all components for the self-assembly of ladder-like protein nanofibers of stacked heptameric rings, their anchoring to the exosporium, and their termination in a trimeric ‘ruffle’ made of a collagen-like BclA paralogue. Phylogenomic analyses shows the ena3 gene cluster as a mobile element with a polyphyletic distribution across pathogenic Bacilli.