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This paper presents a review of research on the effectiveness of educational television compared to traditional face-to-face instruction. The studies reviewed are presented under seven rubrics: TV as a catalyst for learning; two-way TV; use of commercial TV shows; simulation of a real situation; TV integrated as part of the classroom lecture; TV courses instead of lecture in the classroom; and TV courses in the home. The author concludes that while TV has proved effective for teaching basic knowledge, it is deficient for teaching cognitive skills requiring more than "level I" knowledge. A bibliography is appended (the latest reference is to a 1975 publication). (BB)

The purpose of this document is to provide the reader with a general understanding regarding the roles and responsibilities of professional student support personnel in West Virginia schools and how, through a collaborative partnership, they can work together to provide a safe and supportive learning environment for WV students. Research confirms that students do better in school when they receive social-emotional and mental health support. They miss fewer classes, concentrate more, are less likely to engage in risky or antisocial behavior, and achieve higher test scores. The most effective way to implement integrated services that support school safety and student learning is through a school-wide multitiered system of support (MTSS). Effective MTSS requires: (1) adequate access to school-employed professional student support personnel and community-based services; (2) integration of services (social-emotional learning, mental health, medical health, behavioral supports, academic supports, school-based services, and community services); (3) adequate staff time for planning and problem-solving; (4) effective collection, evaluation, interpretation, and use of data; (5) patience, commitment, collaborations, and strong leadership; and (6) understanding the various roles of the many student support personnel and how they work together for the benefit of every child. The West Virginia Department of Education (WVDE) recognizes the effectiveness of a multi-tiered system of support and is committed to ensuring equitable education opportunities through the West Virginia Tiered System of Support (WVTSS), a multi-tiered systems framework. WVTSS emphasizes the integration of academics, behavior, and mental health as uniformly critical to student success and focuses on the cohesive system of support rather than interventions alone.

As wavefront quality demands tighten on space systems for applications such as astronomy and laser communication, mounting small optics such that the wavefront is undisturbed, positioning is adjustable and the design is producible, while surviving harsh space environments, is a continuing challenge. We designed multiple candidate flexure mounts to support small optics (up to 50 mm diameter, and over 100 grams) to survive the qualification and acceptance tests of small spacecraft and units as defined in ISO 19683 and a mounting structure which is adjustable in decenter [+/-0.5mm], tip/tilt +/-0.5deg, and piston [+/-0.25mm]. We will present design details along with measurements showing less than approximately lambda/10 wavefront contribution from the optic bonding process, along with thermal and multi-axis vibration test data showing the mounted optics survived the acceptance testing loads and are suitable for operation in a wide range of harsh environments.

This paper presents a comprehensive analysis of RR Lep and BF Vel, two short-period semi-detached oscillating Algols (oEA stars), which are shown to be triple systems. Spectral types of their primaries were determined and radial velocities calculated from spectra observed with the Australian National University's 2.3 m telescope and Wide Field Spectrograph. Spectra of the Na I D doublet confirmed the presence of tertiary components which were apparent in the broadening function analyses and, with H_a spectra during primary eclipses, indicated chromospherical activity in their secondaries. Ground-based telescopes were used for observations in several pass bands for photometric analyses. These data were complemented by data from the TESS mission to enable the modelling of the light curves, followed by a detailed analysis of pulsations. Eclipse-timing variation (ETV) analyses of both systems were used to determine the most likely mechanisms modulating the orbital period. We found mass values M1 = 2.9 M_sun and M2 = 0.75 M_sun for the components of RR Lep, and M1 = 1.93 M_sun and M2 = 0.97 M_sun for those of BF Vel. By integrating information from photometry, spectroscopy and ETV analysis, we found that tertiary components revolve around both systems. The primary star of RR Lep pulsates in 36 frequencies, of which five were identified as independent modes, with the dominant one being 32.28 d^-1. The pulsating component of BF Vel oscillates in 37 frequencies, with the frequency 46.73 d^-1 revealed as the only independent mode. For both systems, many frequencies were found to be related to the orbital frequency. Their physical properties were compared with other oEA stars in Mass-Radius and H-R diagrams, and the pulsational properties of their delta Sct components were compared with currently known systems of this type within the orbital-pulsation period and logg-pulsation period diagrams., Comment: 22 pages, 21 figures, 8 tables, 3 appendices, Accepted for publication in A&A

The physics case for quarkonium-production studies accessible at the US Electron Ion Collider is described., Comment: Latex, 84 pages. Review prepared for Progress in Particle and Nuclear Physics

Regulatory functions are essential in both socioeconomic and biological systems, from corporate managers to regulatory genes in genomes. Regulatory functions come with substantial costs, but are often taken for granted. Here, we empirically examine regulatory costs across diverse systems -- biological organisms (bacteria and eukaryotic genomes), human organizations (companies, federal agencies, universities), and decentralized entities (Wikipedia, cities) -- using scaling analysis. We guide the empirical analysis with a conceptual model, which anticipates the scaling of regulatory costs to shift with the system's internal interaction structure -- well-mixed or modular. We find diverse systems exhibit consistent scaling patterns -- well-mixed systems exhibit superlinear scaling, while modular ones show sublinear or linear scaling. Further, we find that the socioeconomic systems containing more diverse occupational functions tend to have more regulatory costs than expected from their size, confirming the type of interactions also plays a role in regulatory costs. While many socioeconomic systems exhibit efficiencies of scale, regulatory costs in many social systems have grown disproportionally over time. Our finding suggests that the increasing complexity of functions may contribute to this trend. This cross-system comparison offers a framework for understanding regulatory costs and could guide future efforts to identify and mitigate regulatory inefficiencies., Comment: 12 pages, 4 figures

Large language models (LLMs) have enhanced our ability to rapidly analyze and classify unstructured natural language data. However, concerns regarding cost, network limitations, and security constraints have posed challenges for their integration into work processes. In this study, we adopt a systems design approach to employing LLMs as imperfect data annotators for downstream supervised learning tasks, introducing novel system intervention measures aimed at improving classification performance. Our methodology outperforms LLM-generated labels in seven of eight tests, demonstrating an effective strategy for incorporating LLMs into the design and deployment of specialized, supervised learning models present in many industry use cases.

Misinformation - false or misleading information - is considered a significant societal concern due to its associated "misinformation effects," such as political polarization, erosion of trust in institutions, problematic behavior, and public health challenges. However, the prevailing concept is misaligned with what is studied. While misinformation focuses on instances of information about factual matters, the broad spectrum of effects often manifests at a societal level and is shaped by a wide range of interdependent factors such as identity, values, opinions, epistemologies, and disagreements. Unsurprisingly, misinformation effects can occur without the prevalence of misinformation, and misinformation does not necessarily increase the effects studied. Here, we propose using disagreement - conflicting attitudes and beliefs between individuals and communities - as a way to study misinformation effects because it addresses the identified conceptual limitations of misinformation. Furthermore, unlike misinformation, disagreement does not require researchers to determine whether a given information is false or misleading. Thus, it can be studied and, more importantly, measured without the need to make a normative judgment about a given information, even when the specific topic is entirely removed, as we show in a longitudinal disagreement measurement. We demonstrate that disagreement, as a holistic concept, provides better explanations for the occurrence of misinformation effects, enhances precision in developing appropriate interventions, and offers a promising approach for evaluating them through quantification. Finally, we show how disagreement addresses current misinformation research questions and conclude with recommendations for research practice.

We report the discovery of the most eccentric transiting brown dwarf in the brown dwarf desert, TOI02490b. The brown dwarf desert is the lack of brown dwarfs around main sequence stars within $\sim3$~AU and is thought to be caused by differences in formation mechanisms between a star and planet. To date, only $\sim40$ transiting brown dwarfs have been confirmed. \systemt is a $73.6\pm2.4$ \mjupnospace, $1.00\pm0.02$ \rjup brown dwarf orbiting a $1.004_{-0.022}^{+0.031}$ \msunnospace, $1.105_{-0.012}^{+0.012}$ \rsun sun-like star on a 60.33~d orbit with an eccentricity of $0.77989\pm0.00049$. The discovery was detected within \tess sectors 5 (30 minute cadence) and 32 (2 minute and 20 second cadence). It was then confirmed with 31 radial velocity measurements with \feros by the WINE collaboration and photometric observations with the Next Generation Transit Survey. Stellar modelling of the host star estimates an age of $\sim8$~Gyr, which is supported by estimations from kinematics likely placing the object within the thin disc. However, this is not consistent with model brown dwarf isochrones for the system age suggesting an inflated radius. Only one other transiting brown dwarf with an eccentricity higher than 0.6 is currently known in the brown dwarf desert. Demographic studies of brown dwarfs have suggested such high eccentricity is indicative of stellar formation mechanisms., Comment: Accepted for publication in MNRAS, 18 pages, 14 figures

AI assistants are being increasingly used by students enrolled in higher education institutions. While these tools provide opportunities for improved teaching and education, they also pose significant challenges for assessment and learning outcomes. We conceptualize these challenges through the lens of vulnerability, the potential for university assessments and learning outcomes to be impacted by student use of generative AI. We investigate the potential scale of this vulnerability by measuring the degree to which AI assistants can complete assessment questions in standard university-level STEM courses. Specifically, we compile a novel dataset of textual assessment questions from 50 courses at EPFL and evaluate whether two AI assistants, GPT-3.5 and GPT-4 can adequately answer these questions. We use eight prompting strategies to produce responses and find that GPT-4 answers an average of 65.8% of questions correctly, and can even produce the correct answer across at least one prompting strategy for 85.1% of questions. When grouping courses in our dataset by degree program, these systems already pass non-project assessments of large numbers of core courses in various degree programs, posing risks to higher education accreditation that will be amplified as these models improve. Our results call for revising program-level assessment design in higher education in light of advances in generative AI., Comment: 20 pages, 8 figures

Despite the remarkable performance of Large Language Models (LLMs), they still struggle with generating logically sound arguments, resulting in potential risks such as spreading misinformation. An important factor contributing to LLMs' suboptimal performance in generating coherent arguments is their oversight of logical fallacies. To address this issue, we introduce FIPO, a fallacy-informed framework that leverages preference optimization methods to steer LLMs toward logically sound arguments. FIPO includes a classification loss, to capture the fine-grained information on fallacy categories. Our results on argumentation datasets show that our method reduces the fallacy errors by up to 17.5%. Furthermore, our human evaluation results indicate that the quality of the generated arguments by our method significantly outperforms the fine-tuned baselines, as well as prior preference optimization methods, such as DPO. These findings highlight the importance of ensuring models are aware of logical fallacies for effective argument generation.

The potential future democratization of spaceflight reveals a need for design of experiences that extend beyond our current conceptualization of spaceflight. Research on career astronauts indicates that transformative experiences occur during spaceflight despite the physiological and psychological stressors involved. This phenomenon allows us to envision a future where such profound experiences are accessible to diverse spaceflight participants. In this position paper, we advocate for acknowledging how design decisions made at the genesis of commercial spaceflight might impact space travelers of this speculative future. In proposing salutogenesis as an orienting topic, a potential design framework, and as a metric for spaceflight participant experience, we offer a call to action for the broader experience design community to engage with the design of profound experiences for spaceflight participants., Comment: SpaceCHI 2023

We present initial results from the Polarisation Sky Survey of the Universe's Magnetism (POSSUM), analysing 22,817 Faraday Rotation Measures (RMs) with median uncertainties of 1.2 rad m^-2 across 1,520 square degrees to study magnetised gas associated with 55 nearby galaxy groups (z less than 0.025) with halo masses between 10^12.5 and 10^14.0 M_sun. We identify two distinct gas phases: the Intragroup Medium (IGrM) within 0-2 splashback radii and the Warm-Hot Intergalactic Medium (WHIM) extending from 2 to 7 splashback radii. These phases enhance the standard deviation of residual (i.e., Galactic foreground RM-subtracted) RMs by 6.9 +/- 1.8 rad m^-2 and 4.2 +/- 1.2 rad m^-2, respectively. Estimated magnetic field strengths are several microGauss within the IGrM and 0.1-1 microGauss in the WHIM. We estimate the plasma beta in both phases and show that magnetic pressure might be more dynamically important than in the ICM of more massive clusters or sparse cosmic web filaments. Our findings indicate that "missing baryons" in the WHIM likely extend beyond the gravitational radii of group-mass halos to Mpc scales, consistent with large-scale, outflow-driven "magnetised bubbles" seen in cosmological simulations. We demonstrate that RM grids are an effective method for detecting magnetised thermal gas at galaxy group interfaces and within the cosmic web. This approach complements X-ray and Sunyaev-Zel'dovich effect methods, and when combined with Fast Radio Burst Dispersion Measures, data from the full POSSUM survey, comprising approximately a million RMs, will allow direct magnetic field measurements to further our understanding of baryon circulation in these environments and the magnetised universe., Comment: 15 pages, 7 figures, 3 tables. Accepted for publication in MNRAS

Modern language models (LMs) pose a new challenge in capability assessment. Static benchmarks inevitably saturate without providing confidence in the deployment tolerances of LM-based systems, but developers nonetheless claim that their models have generalized traits such as reasoning or open-domain language understanding based on these flawed metrics. The science and practice of LMs requires a new approach to benchmarking which measures specific capabilities with dynamic assessments. To be confident in our metrics, we need a new discipline of model metrology -- one which focuses on how to generate benchmarks that predict performance under deployment. Motivated by our evaluation criteria, we outline how building a community of model metrology practitioners -- one focused on building tools and studying how to measure system capabilities -- is the best way to meet these needs to and add clarity to the AI discussion., Comment: Conference paper at COLM 2024

Understanding the noise characteristics of high quantum efficiency silicon-based ultraviolet detectors, developed by the Microdevices Lab at the Jet Propulsion Laboratory, is critical for current and proposed UV missions using these devices. In this paper, we provide an overview of our detector noise characterization test bench that uses delta-doped, photon counting, Electron-multiplying CCDs (EMCCDs) to understand the fundamental noise properties relevant to all silicon CCDs and CMOS arrays. This work attempts to identify the source of the dark current plateau that has been previously measured with photon-counting EMCCDs and is known to be prevalent in other silicon-based arrays. It is suspected that the plateau could be due to a combination of detectable photons in the tail of blackbody radiation of the ambient instrument, low-level light leaks, and a non-temperature-dependent component that varies with substrate voltage. Our innovative test setup delineates the effect of the ambient environment during dark measurements by independently controlling the temperature of the detector and surrounding environment. We present the design of the test setup and preliminary results., Comment: Submitted for Proceedings of SPIE Astronomical Telescopes+Instrumentation 2024, Paper number: 13093-26

The emergence of spatial coherence in a confined two-dimensional Bose gas of exciton-polaritons with tuneable interactions offers a unique opportunity to explore the role of interactions in a phase transition in a driven-dissipative quantum system, where both the phase transition and thermalisation are mediated by interactions. We investigate, experimentally and numerically, the phase correlations and steady-state properties of the gas over a wide range of interaction strengths by varying the photonic/excitonic fraction of the polaritons and their density. We find that the first order spatial coherence function exhibits algebraic decay consistent with the Berezinskii-Kosterlitz-Thouless (BKT) phase transition. Surprisingly, the exponent of the algebraic decay is inversely proportional to the coherent density of polaritons, in analogy to equilibrium superfluids above the BKT transition, but with a different proportionality constant. Our work paves the way for future investigations of the phenomenon of phase transitions and superfluidity in a driven-dissipative setting, Comment: 11 pages, 6 figures

Defect physics is at the heart of microelectronics. By keeping track of the reference energy in total energy calculations, we explicitly show that the "potential alignment" correction vanishes, and the classic Markov-Payne correction yields accurate results. From linear response theory, we further formulate an accurate expression for the quadrupole correction. Application to numerous defects including anisotropic material yields accurate formation energies in small supercells and the historically slow convergence of the 2+ diamond vacancy is shown to be a result of slow varying gap levels of the defect leading to a size dependent dielectric constant.

A rapidly growing number of applications rely on a small set of closed-source language models (LMs). This dependency might introduce novel security risks if LMs develop self-recognition capabilities. Inspired by human identity verification methods, we propose a novel approach for assessing self-recognition in LMs using model-generated "security questions". Our test can be externally administered to keep track of frontier models as it does not require access to internal model parameters or output probabilities. We use our test to examine self-recognition in ten of the most capable open- and closed-source LMs currently publicly available. Our extensive experiments found no empirical evidence of general or consistent self-recognition in any examined LM. Instead, our results suggest that given a set of alternatives, LMs seek to pick the "best" answer, regardless of its origin. Moreover, we find indications that preferences about which models produce the best answers are consistent across LMs. We additionally uncover novel insights on position bias considerations for LMs in multiple-choice settings., Comment: Code to reproduce experiments and replicate findings is made available at https://github.com/trdavidson/self-recognition

We present a pair-wise force law in a system of N particles that produces analytic solutions for arbitrary number of particles, masses, and initial conditions. Each pair of particles interacts via a force that is proportional to the product of their masses and their separation distance, with the force directed radially. We show that, despite the N-body interaction, each particle behaves as if it interacts only with the center of mass of the system. This effective two-body interaction behaves as Hooke's Law with a common frequency for all particles, with the familiar analytic solutions for the trajectories. With these analytic solutions, it is possible to efficiently simulate a collection of these particles and incorporate other external forces. As an example, we simulate the particles within an adiabatically expanding container and calculate pressure and temperature in both the attractive and repulsive cases., Comment: 12 pages, 3 figures

RLHF-aligned LMs have shown unprecedented ability on both benchmarks and long-form text generation, yet they struggle with one foundational task: next-token prediction. As RLHF models become agent models aimed at interacting with humans, they seem to lose their world modeling -- the ability to predict what comes next in arbitrary documents, which is the foundational training objective of the Base LMs that RLHF adapts. Besides empirically demonstrating this trade-off, we propose a potential explanation: to perform coherent long-form generation, RLHF models restrict randomness via implicit blueprints. In particular, RLHF models concentrate probability on sets of anchor spans that co-occur across multiple generations for the same prompt, serving as textual scaffolding but also limiting a model's ability to generate documents that do not include these spans. We study this trade-off on the most effective current agent models, those aligned with RLHF, while exploring why this may remain a fundamental trade-off between models that act and those that predict, even as alignment techniques improve.

Despite some progress over the ensuing seven years and high aspirations for college and career success held by Black students and families, Black students continue to experience among the highest rates of chronic absenteeism, are the least likely to be supported to reach grade-level standards in math and reading, and graduate from high school and enroll in college at lower rates than their peers. Much more work remains to be done by state and local leaders to eradicate disparities in opportunities and to clear the path for all Black students to thrive. The Eastside Union School District (EUSD), located in southern California, provides an example of how system leaders can intentionally undertake this critical work. This case study highlights EUSD's implementation of strategies focused on improving educational experiences and supports for Black students and families, uplifting both promising practices and emerging challenges during the early stages of the process. The authors hope this case study will inspire districts across the state to adopt proven equity-centered practices and to adapt strategies to fit their unique local contexts.

For far too long in California, remedial courses in California Community Colleges meant costly barriers to student success. Fortunately, recent legislation -- Assembly Bill 705 signed into law in 2017 -- requires these colleges to eliminate remedial courses and instead use research-backed strategies like corequisite support to help students complete transfer-level courses. Ed Trust-West's latest "bright spot" looks at Ventura College (VC) and its implementation of Assembly Bill 705 (AB 705), outlining the successful strategies the college is leveraging to place students into coursework that gives them the best chance of completing transferable, college-level math within a year of their first attempt. The report describes VC's strategies for increasing access to transfer-level math courses and supporting students to complete those courses.

In recent years, quantum information science has made significant progress, leading to a multitude of quantum protocols for the most diverse applications. States carrying resources such as quantum coherence are a key component for these protocols. In this study, we optimize the quantum coherence of a nonresonantly excited exciton-polariton condensate of long living polaritons by minimizing the condensate's interaction with the surrounding reservoir of excitons and free carriers. By combining experimental phase space data with a displaced thermal state model, we observe how quantum coherence builds up as the system is driven above the condensation threshold. Our findings demonstrate that a spatial separation between the condensate and the reservoir enhances the state's maximum quantum coherence directly beyond the threshold. These insights pave the way for integrating polariton systems into hybrid quantum devices and advancing applications in quantum technologies., Comment: 17 pages, 5 figures

Generating rationales that justify scoring decisions has been a promising way to facilitate explainability in automated scoring systems. However, existing methods do not match the accuracy of classifier-based methods. Plus, the generated rationales often contain hallucinated information. To address these issues, we propose a novel framework capable of generating more faithful rationales and, more importantly, matching performance with classifier-based black-box scoring systems. We first mimic the human assessment process by querying Large Language Models (LLMs) to generate a thought tree. We then summarise intermediate assessment decisions from each thought tree path for creating synthetic rationale data and rationale preference data. Finally, we utilise the generated synthetic data to calibrate LLMs through a two-step training process: supervised fine-tuning and preference optimization. Extensive experimental results demonstrate that our framework achieves a 38% assessment performance improvement in the QWK score compared to prior work while producing higher-quality rationales, as recognised by human evaluators and LLMs. Our work sheds light on the effectiveness of performing preference optimization using synthetic preference data obtained from thought tree paths.

Understanding optical absorption in silicon nitride is crucial for cutting-edge technologies like photonic integrated circuits, nanomechanical photothermal infrared sensing and spectroscopy, and cavity optomechanics. Yet, the origin of its strong dependence on film deposition and fabrication process is not fully understood. This Letter leverages nanomechanical photothermal sensing to investigate optical extinction $\kappa_{\mathrm{ext}}$ at 632.8 nm wavelength in LPCVD SiN strings across a wide range of deposition-related tensile stresses ($200-850$ MPa). Measurements reveal a reduction in $\kappa_{\mathrm{ext}}$ from 10$^3$ to 10$^1$ ppm with increasing stress, correlated to variations in Si/N content ratio. Within the band-fluctuations framework, this trend indicates an increase of the energy bandgap with the stress, ultimately reducing absorption. Overall, this study showcases the power and simplicity of nanomechanical photothermal sensing for low absorption measurements, offering a sensitive, scattering-free platform for material analysis in nanophotonics and nanomechanics., Comment: Main text: 7 pages, 3 figures, 1 table Supporting Information: 4 pages, 4 figures, 1 table

We report the canonical properties of Bose-Einstein condensation of polaritons, seen previously in many low-temperature experiments, at room temperature in a GaAs/AlGaAs structure. These effects include a nonlinear energy shift of the polaritons, showing that they are not non-interacting photons, and dramatic line narrowing due to coherence, giving coherent emission with spectral width of 0.24 meV at room temperature with no external stabilization. This opens up the possibility of room temperature nonlinear optical devices based on polariton condensation.

In 2021, the high-mass X-ray binary EXO 2030+375 underwent a giant X-ray outburst, the first since 2006, that reached a peak flux of ${\sim}600\,\mathrm{mCrab}$ (3-50\,keV). The goal of this work is to study the spectral evolution over the course of the outburst, search for possible cyclotron resonance scattering features (CRSFs), and to associate spectral components with the emission pattern of the accretion column. We used broadband spectra taken with the Nuclear Spectroscopic Telescope Array (NuSTAR), the Neutron Star Interior Composition Explorer (NICER), and Chandra near the peak and during the decline phase of the outburst. We describe the data with established empirical continuum models and perform pulse-phase-resolved spectroscopy. We compare the spectral evolution with pulse phase using a proposed geometrical emission model. We find a significant spectral hardening toward lower luminosity, a behavior that is expected for super-critical sources. The continuum shape and evolution cannot be described by a simple power-law model with exponential cutoff; it requires additional absorption or emission components. We can confirm the presence of a narrow absorption feature at ${\sim}10\,\mathrm{keV}$ in both NuSTAR observations. The absence of harmonics puts into question the interpretation of this feature as a CRSF. The empirical spectral components cannot be directly associated with identified emission components from the accretion column., Comment: 12 pages, 8 figures, accepted in A&A

We present a careful calibration of the exciton fraction of polaritons in high-$Q$ ($\sim 300,000$), long-lifetime ($\sim 300$ ps), GaAs/AlGaAs microcavities.This is a crucial parameter for many-body theories which include the polariton-polariton interactions.It is much harder to establish this number in high-$Q$ structures compared to low-$Q$ structures, because the upper polariton is nearly invisible in high-$Q$ cavities.We present a combination of photoluminescence, photoluminescence excitation, and reflectivity measurements to highly constrain the fit model, and compare the results of this model to the results from low-$Q$ structures.We present a fitted curve of exciton fraction as a function of the lower polariton energy for multiple samples which have been used in prior experiments., Comment: 16 pages, 11 figures

PLATO (PLAnetary Transits and Oscillations of stars) is ESA's M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2 R_(Earth)) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5 %, 10 %, 10 % for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO's target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile at the beginning of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases.

The macroeconomy is a sophisticated dynamic system involving significant uncertainties that complicate modelling. In response, decision makers consider multiple models that provide different predictions and policy recommendations which are then synthesized into a policy decision. In this setting, we introduce and develop Bayesian predictive decision synthesis (BPDS) to formalize monetary policy decision processes. BPDS draws on recent developments in model combination and statistical decision theory that yield new opportunities in combining multiple models, emphasizing the integration of decision goals, expectations and outcomes into the model synthesis process. Our case study concerns central bank policy decisions about target interest rates with a focus on implications for multi-step macroeconomic forecasting.

Nanomechanical photothermal sensing has significantly advanced single-molecule/particle microscopy and spectroscopy, and infrared detection through the use of nanomechanical resonators that detect shifts in resonant frequency due to photothermal heating. However, the relationship between resonator design, photothermal sensitivity, and response time remains unclear. This paper compares three resonator types - strings, drumheads, and trampolines - to explore this relationship. Through theoretical modeling, experimental validation, and finite element method simulations, we find that strings offer the highest sensitivity (with a noise equivalent power of 280 fW/Hz$^{1/2}$ for strings made of silicon nitride), while drumheads exhibit the fastest thermal response. The study reveals that photothermal sensitivity correlates with the average temperature rise and not the peak temperature. Finally, the impact of photothermal back-action is discussed, which can be a major source of frequency instability. This work clarifies the performance differences and limits among resonator designs and guides the development of advanced nanomechanical photothermal sensors, benefiting a wide range of applications., Comment: Main text 28 pages, 7 figures. Supplementary Information: 11 pages, 10 figures

Theoretical developments in sequential Bayesian analysis of multivariate dynamic models underlie new methodology for causal prediction. This extends the utility of existing models with computationally efficient methodology, enabling routine exploration of Bayesian counterfactual analyses with multiple selected time series as synthetic controls. Methodological contributions also define the concept of outcome adaptive modelling to monitor and inferentially respond to changes in experimental time series following interventions designed to explore causal effects. The benefits of sequential analyses with time-varying parameter models for causal investigations are inherited in this broader setting. A case study in commercial causal analysis-- involving retail revenue outcomes related to marketing interventions-- highlights the methodological advances., Comment: 23 pages, 6 figures

The field of AI alignment aims to steer AI systems toward human goals, preferences, and ethical principles. Its contributions have been instrumental for improving the output quality, safety, and trustworthiness of today's AI models. This perspective article draws attention to a fundamental challenge inherent in all AI alignment endeavors, which we term the "AI alignment paradox": The better we align AI models with our values, the easier we make it for adversaries to misalign the models. We illustrate the paradox by sketching three concrete example incarnations for the case of language models, each corresponding to a distinct way in which adversaries can exploit the paradox. With AI's increasing real-world impact, it is imperative that a broad community of researchers be aware of the AI alignment paradox and work to find ways to break out of it, in order to ensure the beneficial use of AI for the good of humanity.

The Be X-ray binary EXO 2030+375 went through its third recorded giant outburst from June 2021 to early 2022. We present the results of both spectral and timing analysis based on NICER monitoring, covering the 2-10 keV flux range from 20 to 310 mCrab. Dense monitoring with observations carried out about every second day and a total exposure time of 160 ks allowed us to closely track the source evolution over the outburst. Changes in spectral shape and pulse profiles showed a stable luminosity dependence during the rise and decline. The same type of dependence has been seen in past outbursts. The pulse profile is characterized by several distinct peaks and dips. The profiles show a clear dependence on luminosity with a stark transition at a luminosity of 2x10^36 erg/s, indicating a change in the emission pattern. Using relativistic ray-tracing, we demonstrate how anisotropic beaming of emission from an accretion channel with constant geometrical configuration can give rise to the observed pulse profiles over a range of luminosities., Comment: 15 pages, 16 figures, accepted by A&A

In this article, we construct codes with hierarchical locality using natural geometric structures in Artin-Schreier surfaces of the form $y^p-y=f(x,z)$. Our main theorem describes the codes, their hierarchical structure and recovery algorithms, and gives parameters. We also develop a family of examples using codes defined over $\mathbb{F}_{p^2}$ on the surface $y^p-y=x^{p+1}z^2+x^2z^{p+1}$. We count the $\mathbb{F}_{p^2}$-rational points on the surface, a topic of more general number theoretic interest, and provide more explicit parameters a better bound on minimum distance for these codes. An additional example and some generalizations are also considered.