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This paper proposes a hierarchical Bayesian multitask learning model that is applicable to the general multi-task binary classification learning problem where the model assumes a shared sparsity structure across different tasks. We derive a computationally efficient inference algorithm based on variational inference to approximate the posterior distribution. We demonstrate the potential of the new approach on various synthetic datasets and for predicting human health status based on microbiome profile. Our analysis incorporates data pooled from multiple microbiome studies, along with a comprehensive comparison with other benchmark methods. Results in synthetic datasets show that the proposed approach has superior support recovery property when the underlying regression coefficients share a common sparsity structure across different tasks. Our experiments on microbiome classification demonstrate the utility of the method in extracting informative taxa while providing well-calibrated predictions with uncertainty quantification and achieving competitive performance in terms of prediction metrics. Notably, despite the heterogeneity of the pooled datasets (e.g., different experimental objectives, laboratory setups, sequencing equipment, patient demographics), our method delivers robust results.

Programming, which is both economically significant and mentally stimulating, has been found to benefit the aging brain and to enhance cognitive function at various educational levels. Despite its advantages, challenges persist in standardizing and implementing programming education effectively across both the higher and secondary education levels in Brazil. To shed light on these issues, we carried out a systematic review of programming teaching methods in the Brazilian context, examining gaps, common techniques, approaches, and action opportunities in programming education. Our findings provide valuable recommendations for educational policymakers and educators to develop effective and updated national policies to teach programming., Comment: 15 pages

Artificial Intelligence (AI) is pivotal in advancing mobile network systems by facilitating smart capabilities and automation. The transition from 4G to 5G has substantial implications for AI in consolidating a network predominantly geared towards business verticals. In this context, 3GPP has specified and introduced the Network Data Analytics Function (NWDAF) entity at the network's core to provide insights based on AI algorithms to benefit network orchestration. This paper proposes a framework for evolving NWDAF that presents the interfaces necessary to further empower the core network with AI capabilities B5G and 6G. In addition, we identify a set of research directions for realizing a distributed e-NWDAF., Comment: 8 pages

Microorganisms hosted in abiotic structures have led to engineered living materials that can grow, sense and adapt in ways that mimic biological systems. Although porous structures should favor colonization by microorganisms, they have not yet been exploited as abiotic scaffolds for the development of living materials. Here, we report porous ceramics that are colonized by bacteria to form an engineered living material with self-regulated and genetically programmable carbon capture and gas-sensing functionalities. The carbon capture capability is achieved using wild-type photosynthetic cyanobacteria, whereas the gas-sensing function is generated utilizing genetically engineered E. coli. Hierarchical porous clay is used as ceramic scaffold and evaluated in terms of bacterial growth, water uptake and mechanical properties. Using state-of-the-art chemical analysis techniques, we demonstrate the ability of the living porous ceramics to capture CO2 directly from the air and to metabolically turn minute amounts of a toxic gas into a benign scent detectable by humans.

This paper provides a comprehensive review of the TRANSP code, a sophisticated tool for interpretive and predictive analysis of tokamak plasmas, detailing its major capabilities and features. It describes the equations for particle, power, and momentum balance analysis, as well as the poloidal field diffusion equations. The paper outlines the spatial and time grids used in TRANSP and details the equilibrium assumptions and solvers. Various models for heating and current drive, including updates to the NUBEAM model, are discussed. The handling of large-scale events such as sawtooth crashes and pellet injections is examined, along with the predictive capabilities for advancing plasma profiles. The integration of TRANSP with the ITER Integrated Modeling and Analysis Suite (IMAS) is highlighted, demonstrating enhanced data access and analysis capabilities. Additionally, the paper discusses best practices and continuous integration techniques to enhance TRANSP's robustness. The suite of TRANSP tools, designed for efficient data analysis and simulation, further supports the optimization of tokamak operations and coupling with other tokamak codes. Continuous development and support ensure that TRANSP remains a major code for the analysis of experimental data for controlled thermonuclear fusion, maintaining its critical role in supporting the optimization of tokamak operations and advancing fusion research., Comment: Submitted to Computer Physics Communications

In this paper, we introduce an alternative approach to enhancing Multi-Agent Reinforcement Learning (MARL) through the integration of domain knowledge and attention-based policy mechanisms. Our methodology focuses on the incorporation of domain-specific expertise into the learning process, which simplifies the development of collaborative behaviors. This approach aims to reduce the complexity and learning overhead typically associated with MARL by enabling agents to concentrate on essential aspects of complex tasks, thus optimizing the learning curve. The utilization of attention mechanisms plays a key role in our model. It allows for the effective processing of dynamic context data and nuanced agent interactions, leading to more refined decision-making. Applied in standard MARL scenarios, such as the Stanford Intelligent Systems Laboratory (SISL) Pursuit and Multi-Particle Environments (MPE) Simple Spread, our method has been shown to improve both learning efficiency and the effectiveness of collaborative behaviors. The results indicate that our attention-based approach can be a viable approach for improving the efficiency of MARL training process, integrating domain-specific knowledge at the action level., Comment: This paper was published at Proceedings of FLAIRS-37, May 19-21, Sandestin Beach, FL. The proceedings version is available at https://journals.flvc.org/FLAIRS/issue/view/6284

Nuclear magnetic resonance (NMR) is particularly relevant for studies of internuclear spin coupling at zero and ultra-low fields (ZULF), where spin-spin interactions dominate over Zeeman ones. Here we report on ZULF NMR in CdTe. In this semiconductor all magnetic isotopes have spin $I = 1/2$, so that internuclear interactions are never overshadowed by quadrupole effects. Our experiments rely on warm-up spectroscopy, a technique that combines optical pumping, additional cooling via adiabatic demagnetisation, and detection of the oscillating magnetic field-induced warm-up of the nuclear spin system via Hanle effect. We show that NMR spectra exhibit a rich fine structure, consistent with the low abundance of magnetic isotopes in CdTe, their zero quadrupole moments, as well as direct and indirect interactions between them. A model assuming that the electromagnetic radiation is absorbed by nuclear spin clusters composed of up to 5 magnetic isotopes allows us to reproduce the shape of a major part of the measured spectra., Comment: 9 pages, 7 figures, 2 tables

Microorganisms can create engineered materials with exquisite structures and living functionalities. Although synthetic biology tools to genetically manipulate microorganisms continue to expand, the bottom-up rational design of engineered living materials still relies on prior knowledge of genotype-phenotype links for the function of interest. Here, we utilize a high-throughput directed evolution platform to enhance the fitness of whole microorganisms under selection pressure and identify novel genetic pathways to program the functionalities of engineered living materials. Using Komagataeibacter sucrofermentans as a model cellulose-producing microorganism, we show that our droplet-based microfluidic platform enables the directed evolution of these bacteria towards a small number of cellulose overproducers from an initial pool of 40'000 random mutants. Sequencing of the evolved strains reveals an unexpected link between the cellulose-forming ability of the bacteria and a gene encoding a protease complex responsible for protein turnover in the cell. The ability to enhance the fitness of microorganisms towards specific phenotypes and to discover new genotype-phenotype links makes this high-throughput directed evolution platform a promising tool for the development of the next generation of engineered living materials.

Self-healing silicones that are able to restore the functionalities and extend the lifetime of soft devices hold great potential in many applications. However, currently available silicones need to be triggered to self-heal or suffer from creep-induced irreversible deformation during use. Here, we design and print silicone objects that are programmed at the molecular and architecture levels to achieve self-healing at room temperature while simultaneously resisting creep. At the molecular scale, dioxaborolanes moieties are incorporated into silicones to synthesize self-healing vitrimers, whereas conventional covalent bonds are exploited to make creep-resistant elastomers. When combined into architectured printed parts at a coarser length scale, layered materials exhibit fast healing at room temperature without compromising the elastic recovery obtained from covalent polymer networks. A patient-specific vascular phantom is printed to demonstrate the potential of architectured silicones in creating damage-resilient functional devices using molecularly designed elastomer materials.

The Near Infrared Imager and Slitless Spectrograph instrument (NIRISS) is the Canadian Space Agency (CSA) contribution to the suite of four science instruments of JWST. As one of the three NIRISS observing modes, the Single Object Slitless Spectroscopy (SOSS) mode is tailor-made to undertake time-series observations of exoplanets to perform transit spectroscopy. The SOSS permits observing point sources between 0.6 and 2.8 um at a resolving power of 650 at 1.25 um using a slit-less cross-dispersing grism while its defocussing cylindrical lens enables observing targets as bright as J=6.7 by spreading light across 23 pixels along the cross-dispersion axis. This paper officially presents the design of the SOSS mode, its operation, characterization, and its performance, from ground-based testing and flight-based Commissioning. On-sky measurements demonstrate a peak photon conversion efficiency of 55% at 1.2 um. The first time-series on the A-type star BD+60o1753 achieves a flux stability close to the photon-noise limit, so far tested to a level of 20 parts per million on 40-minute time-scales after simply subtracting a long-term trend. Uncorrected 1/f noise residuals underneath the spectral traces add an extra source of noise equivalent to doubling the readout noise. Preliminary analysis of a HAT-P-14b transit time-series indicates that it is difficult to remove all the noise in pixels with partially saturated ramps. Overall, the SOSS delivers performance at the level required to tackle key exoplanet science programs such as detecting secondary atmospheres on terrestrial planets and measuring abundances of several chemical species in gas giants., Comment: 41 pages, 28 figures, accepted for publication in PASP

The Near-Infrared Imager and Slitless Spectrograph (NIRISS) is the science module of the Canadian-built Fine Guidance Sensor (FGS) onboard the James Webb Space Telescope (JWST). NIRISS has four observing modes: 1) broadband imaging featuring seven of the eight NIRCam broadband filters, 2) wide-field slitless spectroscopy (WFSS) at a resolving power of $\sim$150 between 0.8 and 2.2 $\mu$m, 3) single-object cross-dispersed slitless spectroscopy (SOSS) enabling simultaneous wavelength coverage between 0.6 and 2.8 $\mu$m at R$\sim$700, a mode optimized for exoplanet spectroscopy of relatively bright ($J<6.3$) stars and 4) aperture masking interferometry (AMI) between 2.8 and 4.8 $\mu$m enabling high-contrast ($\sim10^{-3}-10^{-4}$) imaging at angular separations between 70 and 400 milliarcsec for relatively bright ($M<8$) sources. This paper presents an overview of the NIRISS instrument, its design, its scientific capabilities, and a summary of in-flight performance. NIRISS shows significantly better response shortward of $\sim2.5\,\mu$m resulting in 10-40% sensitivity improvement for broadband and low-resolution spectroscopy compared to pre-flight predictions. Two time-series observations performed during instrument commissioning in the SOSS mode yield very stable spectro-photometry performance within $\sim$10% of the expected noise. The first space-based companion detection of the tight binary star AB Dor AC through AMI was demonstrated.

Exciton energy structure and population dynamics in a wide CdTe/CdZnTe quantum well are studied by spectrally-resolved pump-probe spectroscopy. Multiple excitonic resonances in reflectance spectra are observed and identified by solving numerically three-dimensional Schr\"odinger equation. The pump-probe reflectivity signal is shown to be dominated by the photoinduced nonradiative broadening of the excitonic resonances, while pump-induced exciton energy shift and reduction of the oscillator strength appear to be negligible. This broadening is induced by the reservoir of dark excitons with large in-plane wave vector, which are coupled to the the bright excitons states. The dynamics of the pump-induced nonradiative broadening observed experimentally is characterised by three components: signal build up on the scale of tens of picoseconds (i) and bi-exponential decay on the scale of one nanosecond (ii) and ten nanosecons (iii). Possible mechanisms of the reservoir population and depletion responsible for this behaviour are discussed., Comment: 8 pages, 3 figures

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit., Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figures

Radio spectroscopy provides a unique inspection perspective for solar and space weather research, which can reveal the plasma and energetic electron information in the solar corona and inner heliosphere. However, Radio-Frequency Interference (RFI) from human activities affects sensitive radio telescopes, and significantly affects the quality of observation. Thus, RFI detection and mitigation for the observations is necessary to obtain high quality, science-ready data. The flagging of RFI is particularly challenging for the solar and space weather observations at low frequency, because the solar radio bursts can be brighter than the RFI, and may show similar temporal behavior. In this work, we investigate RFI flagging methods for solar and space weather observations, including a strategy for AOFlagger, and a novel method that makes use of a morphology convolution. These algorithms can effectively flag RFI while preserving solar radio bursts.

The skin of humanoid robots often lacks human tactility and the inherent self-repair capability of biological tissues. Recently, researchers have grown a living, self-healing skin on a robot finger by subsequent culturing of human dermal and epidermal cells. Here, we highlight the significance of this study alongside challenges toward developing biohybrid robots equipped with sensate and adaptive living robotic skins.

Identifying and calibrating quantitative dynamical models for physical quantum systems is important for a variety of applications. Here we present a closed-loop Bayesian learning algorithm for estimating multiple unknown parameters in a dynamical model, using optimised experimental "probe" controls and measurement. The estimation algorithm is based on a Bayesian particle filter, and is designed to autonomously choose informationally-optimised probe experiments with which to compare to model predictions. We demonstrate the performance of the algorithm in both simulated calibration tasks and in an experimental single-qubit ion-trap system. Experimentally, we find that with 60x fewer samples, we exceed the precision of conventional calibration methods, delivering an approximately 93x improvement in efficiency (as quantified by the reduction of measurements required to achieve a target residual uncertainty and multiplied by the increase in accuracy). In simulated and experimental demonstrations, we see that successively longer pulses are selected as the posterior uncertainty iteratively decreases, leading to an exponential improvement in the accuracy of model parameters with the number of experimental queries., Comment: 18 pages, 8 figures

The James Webb Space Telescope's Near Infrared Imager and Slitless Spectrograph (JWST-NIRISS) flies a 7-hole non-redundant mask (NRM), the first such interferometer in space, operating at 3-5 \micron~wavelengths, and a bright limit of $\simeq 4$ magnitudes in W2. We describe the NIRISS Aperture Masking Interferometry (AMI) mode to help potential observers understand its underlying principles, present some sample science cases, explain its operational observing strategies, indicate how AMI proposals can be developed with data simulations, and how AMI data can be analyzed. We also present key results from commissioning AMI. Since the allied Kernel Phase Imaging (KPI) technique benefits from AMI operational strategies, we also cover NIRISS KPI methods and analysis techniques, including a new user-friendly KPI pipeline. The NIRISS KPI bright limit is $\simeq 8$ W2 magnitudes. AMI (and KPI) achieve an inner working angle of $\sim 70$ mas that is well inside the $\sim 400$ mas NIRCam inner working angle for its circular occulter coronagraphs at comparable wavelengths., Comment: 30 pages, 10 figures

Excitement about the promise of quantum computers is tempered by the reality that the hardware remains exceptionally fragile and error-prone, forming a bottleneck in the development of novel applications. In this manuscript, we describe and experimentally test a fully autonomous workflow designed to deterministically suppress errors in quantum algorithms from the gate level through to circuit execution and measurement. We introduce the key elements of this workflow, delivered as a software package called Fire Opal, and survey the underlying physical concepts: error-aware compilation, automated system-wide gate optimization, automated dynamical decoupling embedding for circuit-level error cancellation, and calibration-efficient measurement-error mitigation. We then present a comprehensive suite of performance benchmarks executed on IBM hardware, demonstrating up to > 1000X improvement over the best alternative expert-configured techniques available in the open literature. Benchmarking includes experiments using up to 16 qubit systems executing: Bernstein Vazirani, Quantum Fourier Transform, Grover's Search, QAOA, VQE, Syndrome extraction on a five-qubit Quantum Error Correction code, and Quantum Volume. Experiments reveal a strong contribution of Non-Markovian errors to baseline algorithmic performance; in all cases the deterministic error-suppression workflow delivers the highest performance and approaches incoherent error bounds without the need for any additional sampling or randomization overhead, while maintaining compatibility with all additional probabilistic error suppression techniques., Comment: 20 pages, 16 figures

We introduce the scientific motivations for the development of the Cassegrain U-Band Efficient Spectrograph (CUBES) that is now in construction for the Very Large Telescope. The assembled cases span a broad range of contemporary topics across Solar System, Galactic and extragalactic astronomy, where observations are limited by the performance of current ground-based spectrographs shortwards of 400nm. A brief background to each case is presented and specific technical requirements on the instrument design that flow-down from each case are identified. These were used as inputs to the CUBES design, that will provide a factor of ten gain in efficiency for astronomical spectroscopy over 300-405nm, at resolving powers of R~24,000 and ~7,000. We include performance estimates that demonstrate the ability of CUBES to observe sources that are up to three magnitudes fainter than currently possible at ground-ultraviolet wavelengths, and we place its predicted performance in the context of existing facillities., Comment: Accepted for publication in Experimental Astronomy

Photoluminescence and polarized reflection spectra of quantum well structures with symmetric Cd$_{0.9}$Zn$_{0.1}$Te/CdTe/Cd$_{0.9}$Zn$_{0.1}$Te and asymmetric Cd$_{0.9}$Zn$_{0.1}$Te/CdTe/Cd$_{0.4}$Mg$_{0.6}$Te barriers were studied. The Stokes parameters of the reflected light from these structures were measured. In the structures with symmetric barriers, exciton resonances were found in the reflection spectra and were not present in the photoluminescence spectra. In structures with asymmetric barriers, in the region of exciton resonances, the phenomenon of light birefringence was detected, caused by a lower symmetry of the interfaces compared to the symmetry of bulk crystals. A discussion of both phenomena was given.

The Aerospace Simulation Environment (Ambiente de Simula\c{c}\~ao Aeroespacial -- ASA in Portuguese) is a custom-made object-oriented simulation framework developed mainly in C++ that enables the modeling and simulation of military operational scenarios to support the development of tactics and procedures in the aerospace context for the Brazilian Air Force. This work describes the ASA framework, bringing its distributed architecture for managing multiple simulation machines, a data analysis platform for post-processing simulation data, the capability of loading models at simulation runtime, and a batch mode execution platform to perform multiple independent executions simultaneously. In addition, we present a list of recent works using the ASA framework as a simulation tool in the air combat context.

We explore the near-term intersection of quantum computing with the transport sector. To support near-term integration, we introduce a framework for assessing the suitability of transport optimization problems for obtaining potential performance enhancement using quantum algorithms. Given a suitable problem, we then present a workflow for obtaining valuable transport solutions using quantum computers, articulate the limitations on contemporary systems, and describe newly available performance-enhancing tools applicable to current commercial quantum computing systems. We make this integration process concrete by following the assessment framework and integration workflow for an exemplary vehicle routing optimization problem: the Capacitated Vehicle Routing Problem. We present novel advances to exponentially reduce the required computational resources, and experimentally demonstrate a prototype implementation exhibiting over 20X circuit performance enhancement on a real quantum device., Comment: Accepted as a scientific paper for the 28th ITS World Congress 2022 Los Angeles