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New Jersey, like many states, has long struggled with the tension of maintaining a well-funded public education system while not overburdening residents with high property taxes. New Jersey's school funding formula, 2008's School Funding Reform Act (SFRA), includes a determination of how much local funding -- raised through property taxes -- is necessary to support each school districts' budget. At the same time, New Jersey also has a property tax cap that is intended to keep spending down and protect residents from large annual increases in their property tax bills. In many school districts across the state, these two laws are in opposition: one law requires districts to raise taxes to meet their local funding obligation under the SFRA, and the other restricts the amount of local revenue that can be raised through the school tax levy. In this report, the author demonstrates how the property tax cap and funding expectations under the SFRA are in conflict and contribute to disparities in educational opportunities for many New Jersey students.

This is the technical document for the report, "Centering Quality, Centering Equity: Lessons Learned in Increasing Early Childhood Educator Credentials." The report explores Early Childhood Education (ECE) credential requirements in California (CA) and Washington, D.C. (D.C.) for two key reasons: 1) both recently raised these requirements and 2) both are in the process of implementing the new changes. The study does not seek to advocate in favor of or against the adoption of increased credential requirements. Rather, its purpose is to shed light on the need to center racial and economic equity in policy design and implementation--focusing on the impact of increased credential requirements on early childhood educators in states pursuing these changes. The appendices in this technical document are: (1) Make-up of Early Care and Education Workforce; (2) Center-Based Early Educator Characteristics by Role; (3) Center-Based Early Educator Work Experience and Credentials by Role; (4) Center-Based Early Educator Time Worked, Income, and Wages by Role; (5) Lead Teachers' Work Experience and Credentials by Race and Ethnicity; (6) Lead Teachers without a Postsecondary Degree, Characteristics by Race and Ethnicity; (7) Focus Group Interview Protocol for California; (8) Focus Group Interview Protocol for Washington, D.C.; (9) Hourly Wages for Early Childhood Educators; and (10) Comparison of D.C. Teacher Salaries in 2022 and Minimum Salaries Required in Fiscal Year 2024 for Programs Receiving Pay Equity Funds.

Thriving communities depend on a strong early childhood education (ECE) system--one where both young children and members of the workforce are served and supported. In recent years, state government leaders have increasingly focused on changing qualifications for specific ECE roles, as increasing credential requirements has sometimes been associated with increasing quality. However, across the country, early childhood educators face significant barriers to economic security and continuing education--all while supporting children, parents, and their communities with specialized education services. This report examines the barriers that even highly qualified early child educators experience in the face of increased credential requirements. Featuring case studies of California and Washington, D.C., the report offers implications for policies that protect educators and advance racial and economic equity in the profession. Included with the report are an Executive Summary encapsulating the findings and a Technical Document describing the methodology, data collection, and quantitative analysis.

We assess the impact of CaII 3934,3969 and NaI 5891,5897 absorption arising in the interstellar medium (ISM) on the SDSS-IV MaNGA Stellar Library (MaStar) and produce corrected spectroscopy for 80% of the 24,162-star catalog. We model the absorption strength of these transitions as a function of stellar distance, Galactic latitude, and dust reddening based upon high-spectral resolution studies. With this model, we identify 6342 MaStar stars that have negligible ISM absorption ($W^\mathrm{ISM}$(CaII K) $<0.07$ Ang and $W^\mathrm{ISM}$(NaI 5891) $<0.05$ Ang). For 12,110 of the remaining stars, we replace their NaI D profile (and their CaII profile for effective temperatures $T_{\rm eff}>9000$ K) with a coadded spectrum of low-ISM stars with similar $T_{\rm eff}$, surface gravity, and metallicity. For 738 additional stars with $T_{\rm eff}>9000$ K, we replace these spectral regions with a matching ATLAS9-based BOSZ model. This results in a mean reduction in $W$(CaII K) ($W$(NaI D)) of $0.4-0.7$ Ang ($0.6-1.1$ Ang) for hot stars ($T_{\rm eff}>7610$ K), and a mean reduction in $W$(NaI D) of $0.1-0.2$ Ang for cooler stars. We show that interstellar absorption in simple stellar population (SSP) model spectra constructed from the original library artificially enhances $W$(CaII K) by $\gtrsim20\%$ at young ages ($<400$ Myr); dramatically enhances the strength of stellar NaI D in starbursting systems (by ${\gtrsim}50\%$); and enhances stellar NaI D in older stellar populations (${\gtrsim}10$ Gyr) by ${\gtrsim}10\%$. We provide SSP spectra constructed from the cleaned library, and discuss the implications of these effects for stellar population synthesis analyses constraining stellar age, [Na/Fe] abundance, and the initial mass function., Comment: 45 pages, 25 figures, 2 appendices. Accepted to ApJ. Cleaned MaStar stellar library spectra are available at https://doi.org/10.5281/zenodo.14014915 . SSP spectra constructed from the cleaned library are available at https://doi.org/10.5281/zenodo.14807331 . A subset are available for use with the MaNGA DAP at https://github.com/sdss/mangadap/tree/4.2.0/mangadap/data/spectral_templates

The primary mechanism of optical memristive devices relies on the phase transitions between amorphous-crystalline states. The slow or energy hungry amorphous-crystalline transitions in optical phase-change materials are detrimental to the devices scalability and performance. Leveraging the integrated photonic platform, we demonstrate a single nanosecond pulse triggered nonvolatile and reversible switching between two layered structures of indium selenide (In2Se3). High resolution pair distribution function reveals the detailed atomistic transition pathways between the layered structures. With inter-layer shear glide and isosymmetric phase transition, the switching between alpha and beta structural states contain low re-configurational entropy, allowing reversible switching between layered structures. Broadband refractive index contrast, optical transparency, and volumetric effect in the crystalline-crystalline phase transition are experimentally characterized in molecular beam epitaxy-grown thin films and compared to ab initials calculations. The nonlinear resonator transmission spectra measure an incremental linear loss rate of 3.3 GHz introduced by 1.5 micrometer long In2Se3 covered lay-er, resulting from the combinations of material absorption and scattering.

Widespread integration of Generative AI tools is transforming white-collar work, reshaping how workers define their roles, manage their tasks, and collaborate with peers. This has created a need to develop an overarching understanding of common worker-driven patterns around these transformations. To fill this gap, we conducted a systematic literature review of 23 studies from the ACM Digital Library that focused on workers' lived-experiences and practitioners with GenAI. Our findings reveal that while many professionals have delegated routine tasks to GenAI to focus on core responsibilities, they have also taken on new forms of AI managerial labor to monitor and refine GenAI outputs. Additionally, practitioners have restructured collaborations, sometimes bypassing traditional peer and subordinate interactions in favor of GenAI assistance. These shifts have fragmented cohesive tasks into piecework creating tensions around role boundaries and professional identity. Our analysis suggests that current frameworks, like job crafting, need to evolve to address the complexities of GenAI-driven transformations.

Nearby blue compact dwarf galaxies (BCDs) share similar properties with objects from the Epoch of Reionization revealed by JWST, in terms of low stellar mass, low metallicity and high specific star-formation rate. Thus, they represent ideal local laboratories for detailed multi-wavelength studies to understand their properties and the mechanisms shaping them. We report the first JWST MIRI/MRS observations of the BCD SBS 0335-052 E, analyzing MIR emission lines tracing different levels of ionization (e.g., [NeII], [SIV], [NeIII], [OIV], [NeV]) of the ionized gas. SBS 0335-052 E MIR emission is characterized by a bright point source, located in one of the youngest and most embedded stellar clusters ($t\sim3$ Myr, $A_V\sim20$), and underlying extended high-ionization emission (i.e., [OIV], [NeV]) from the surroundings of the older and less dusty stellar clusters ($t< 20 $ Myr, $A_V\sim8$). From the comparison with state-of-the-art models, we can exclude shocks, X-ray binaries, and old stellar populations as the main sources of the high ionization. Interestingly, a 4-16% contribution of a $\sim10^5$ M$_\odot$ intermediate massive black hole (IMBH) is needed to justify the strong [NeV]/[NeII] and would be consistent with optical/UV line ratios from previous studies. However, even IMBH models cannot explain the strongest [OIV]/[NeIII]. Also, star-forming models (regardless of including X-ray binaries) struggle to reproduce even the lower ionization line ratios (e.g., [SIV]/[NeII]) typically observed in BCDs. Overall, while current models suggest the need to account for an accreting IMBH in this high-$z$ analog, limitations still exist in predicting high-ionization emission lines (I.P. $>54$ eV) when modeling these low-metallicity environments, thus other sources of ionization cannot be fully ruled out., Comment: Submitted to ApJ

Methanol (CH$_3$OH) and formaldehyde (H$_2$CO) are chemically coupled organic molecules proposed to act as an intermediate step between simple molecules and more complex prebiotic compounds. Their abundance distributions across disks regulate the prebiotic potential of material at different disk radii. We present observations of multiple methanol and formaldehyde transitions toward the Herbig Ae disk HD 100546 obtained with ALMA, building upon the previous serendipitous detection of methanol in this source. We find that methanol has a higher rotational temperature ($T_\mathrm{rot}$) than formaldehyde towards both the centrally concentrated emission component in the inner disk ($0-110$ au) and a radially separate dust ring farther out in the disk ($180-260$ au). $T_\mathrm{rot}$ decreases for methanol and formaldehyde from the inner ($152^{+35}_{-27}$ K and $76^{+9}_{-8}$ K) to the outer disk ($52^{+8}_{-6}$ K and $31^{+2}_{-2}$ K), suggesting that we are tracing two different chemical environments. $T_\mathrm{rot}$ for both species in the inner disk is consistent with thermal desorption as the origin, while the outer disk reservoir is driven by non-thermal desorption. The CH$_3$OH/H$_2$CO column density ratio decreases from 14.6$^{+5.2}_{-4.6}$ in the inner disk to $1.3^{+0.3}_{-0.2}$ in the outer disk, consistent with modelling predictions. The CH$_3$OH/H$_2$CO column density ratio for the inner disk is consistent with the median value in the range of column density ratios compiled from Solar System comets which would have formed at a similar distance. This supports the notion that interstellar ice is inherited and preserved by protoplanetary disks around solar-mass and intermediate-mass stars as we are seeing 'fresh' ice sublimation, as well as providing more evidence for the presence of prebiotic precursor molecules in planet-forming regions., Comment: 35 pages, 16 figures

While extensively studied in normal metals, semimetals and semiconductors, the superconducting (SC) proximity effect remains elusive in the emerging field of flat-band systems. In this study we probe proximity-induced superconductivity in Josephson junctions (JJs) formed between superconducting NbTiN electrodes and twisted bilayer graphene (TBG) weak links. Here the TBG acts as a highly tunable topological flat-band system, which due to its twist-angle dependent bandwidth, allows to probe the SC proximity effect at the crossover from the dispersive to the flat-band limit. Contrary to our original expectations, we find that the SC remains strong even in the flat-band limit, and gives rise to broad, dome shaped SC regions, in the filling dependent phase diagram. In addition, we find that unlike in conventional JJs, the critical current Ic strongly deviates from a scaling with the normal state conductance GN. We attribute these findings to the onset of strong electron interactions, which can give rise to an excess critical current, and also work out the potential importance of quantum geometric terms as well as multiband pairing mechanisms. Our results present the first detailed study of the SC proximity effect in the flat-band limit and shed new light on the mechanisms that drive the formation of SC domes in flat-band systems.

One-loop $S^{d+1}$ path integrals were shown to factorize into two parts: a bulk thermal ideal gas partition function in a $dS_{d+1}$ static patch and an edge partition function associated with degrees of freedom living on $S^{d-1}$. Here, we analyze the $\mathfrak{so}(d)$ structure of the edge partition functions for massive and massless totally symmetric tensors of arbitrary rank in any $d\geq 3$. For linearized Einstein gravity on $S^{d+1}$, we find that the edge partition function receives contributions from shift-symmetric vector and scalar fields on $S^{d-1}$ that nonlinearly realize the isometry group $SO(d+2)$ of $S^{d+1}$, suggesting a possible interpretation in terms of an embedded $S^{d-1}$ brane., Comment: 52 pages+appendices, 2 figures

Quantum state tomography (QST) allows for the reconstruction of quantum states through measurements and some inference technique under the assumption of repeated state preparations. Bayesian inference provides a promising platform to achieve both efficient QST and accurate uncertainty quantification, yet is generally plagued by the computational limitations associated with long Markov chains. In this work, we present a novel Bayesian QST approach that leverages modern distributed parallel computer architectures to efficiently sample a $D$-dimensional Hilbert space. Using a parallelized preconditioned Crank--Nicholson Metropolis-Hastings algorithm, we demonstrate our approach on simulated data and experimental results from IBM Quantum systems up to four qubits, showing significant speedups through parallelization. Although highly unorthodox in pooling independent Markov chains, our method proves remarkably practical, with validation ex post facto via diagnostics like the intrachain autocorrelation time. We conclude by discussing scalability to higher-dimensional systems, offering a path toward efficient and accurate Bayesian characterization of large quantum systems., Comment: 8 pages, 5 figures

Kagome superconductors AV$_3$Sb$_5$ (A=K, Rb, Cs) have sparked considerable interest due to the presence of several intertwined symmetry-breaking phases within a single material. Recently, hysteresis and reentrant superconductivity were observed experimentally through magnetoresistance measurements in RbV$_{3}$Sb$_{5}$, providing strong evidence of a spontaneous time-reversal symmetry breaking superconducting state. The unconventional magnetic responses, combined with crystalline symmetry, impose strong constraints on the possible pairing symmetries of the superconducting state. In this work, we propose that RbV$_3$Sb$_5$ is an odd-parity superconductor characterized by spin-polarized Cooper pairs. The hysteresis in magnetoresistance and the reentrant superconductivity can both be explained by the formation and evolution of superconducting domains composed of non-unitary pairing. Considering the nodal properties of the kagome superconductor RbV$_{3}$Sb$_{5}$, it is topological and characterized by Majorana zero modes at its boundary, which can be detected through tunneling experiments.

Unconventional magnetic orders usually interplay with superconductivity in intriguing ways. In this work, we propose that a conventional superconductor in proximity to a compensated $p$-wave magnet exhibits behaviors analogous to those of Ising superconductivity found in transition-metal dichalcogenides, which we refer to as pseudo-Ising superconductivity. The pseudo-Ising superconductivity is characterized by several distinctive features: (i) it stays much more robust under strong $p$-wave magnetism than usual ferromagnetism or $d$-wave altermagnetism, thanks to the apparent time-reversal symmetry in $p$-wave spin splitting; (ii) in the low-temperature regime, a second-order superconducting phase transition occurs at a significantly enhanced in-plane upper critical magnetic field $B_{c2}$; (iii) the supercurrent-carrying state establishes non-vanishing out-of-plane spin magnetization, which is forbidden by symmetry in Rahsba and Ising superconductors. We further propose a spin-orbit-free scheme to realize Majorana zero modes by placing superconducting quantum wires on a $p$-wave magnet. Our work establishes a new form of unconventional superconductivity generated by $p$-wave magnetism., Comment: 6 pages, 4 figures

Alternating twisted multilayer graphene presents a compelling multiband system for exploring superconductivity. Here we investigate robust superconductivity in alternating twisted quadralayer graphene, elucidating carrier contributions from both flat and dispersive bands. The superconductivity is robust, with a strong electrical field tunability, a maximum BKT transition temperature of 1.6 K, and high critical magnetic fields beyond the Pauli limit. We disentangle the carrier density of Dirac bands and flat bands from the Landau fan diagram. Moreover, we could estimate the flatband Fermi velocity from the obtained high critical current near half filling when superconductivity is killed at finite magnetic fields, and further quantify the superfluid stiffness from the low critical current in the superconducting regime. Our results exhibit the electric field tunable coupling strength within the superconducting phase, revealing unconventional properties with vanishing Fermi velocity and large superfluid stiffness. These phenomena, attributed to substantial quantum metric contributions, offer new insights into the mechanisms underlying unconventional superconductivity in moire systems.

We construct and classify all polynomial growth solutions to certain drift-harmonic equations on complete manifolds with paraboloidal asymptotics. These encompass the natural drift-harmonic equations on certain steady gradient Ricci solitons. Specifically, we show that all drift-harmonic functions with polynomial growth asymptotically separate variables, and compute the dimensions of spaces of drift-harmonic functions with a given polynomial growth rate. The proof uses an inductive argument that alternates between constructing and asymptotically controlling drift-harmonic functions., Comment: 50 pages. v2: tidied up some parts, changed exposition. Main result and proof are the same

Explainable AI (XAI) provides methods to understand non-interpretable machine learning models. However, we have little knowledge about what legal experts expect from these explanations, including their legal compliance with, and value against European Union legislation. To close this gap, we present the Explanation Dialogues, an expert focus study to uncover the expectations, reasoning, and understanding of legal experts and practitioners towards XAI, with a specific focus on the European General Data Protection Regulation. The study consists of an online questionnaire and follow-up interviews, and is centered around a use-case in the credit domain. We extract both a set of hierarchical and interconnected codes using grounded theory, and present the standpoints of the participating experts towards XAI. We find that the presented explanations are hard to understand and lack information, and discuss issues that can arise from the different interests of the data controller and subject. Finally, we present a set of recommendations for developers of XAI methods, and indications of legal areas of discussion. Among others, recommendations address the presentation, choice, and content of an explanation, technical risks as well as the end-user, while we provide legal pointers to the contestability of explanations, transparency thresholds, intellectual property rights as well as the relationship between involved parties., Comment: Artificial Intelligence and Law (Springer Nature)

White dwarfs (WDs) are the most abundant compact objects, and recent surveys have suggested that over a third of WDs in accreting binaries host a strong (B $\gtrsim$ 1 MG) magnetic field. However, the origin and evolution of WD magnetism remain under debate. Two WD pulsars, AR Sco and J191213.72-441045.1 (J1912), have been found, which are non-accreting binaries hosting rapidly spinning (1.97-min and 5.30-min, respectively) magnetic WDs. The WD in AR Sco is slowing down on a $P/\dot{P}\approx 5.6\times 10^6$ yr timescale. It is believed they will eventually become polars, accreting systems in which a magnetic WD (B $\approx 10-240$ MG) accretes from a Roche lobe-filling donor spinning in sync with the orbit ($\gtrsim 78$ min). Here, we present multiwavelength data and analysis of Gaia22ayj, which outbursted in March 2022. We find that Gaia22ayj is a magnetic accreting WD that is rapidly spinning down ($P/\dot{P} = 6.1^{+0.3}_{-0.2}\times 10^6$ yr) like WD pulsars, but shows clear evidence of accretion, like polars. Strong linear polarization (40%) is detected in Gaia22ayj; such high levels have only been seen in the WD pulsar AR Sco and demonstrate the WD is magnetic. High speed photometry reveals a 9.36-min period accompanying a high amplitude ($\sim 2$ mag) modulation. We associate this with a WD spin or spin-orbit beat period, not an orbital period as was previously suggested. Fast (60-s) optical spectroscopy reveals a broad ``hump'', reminiscent of cyclotron emission in polars, between 4000-8000 Angstrom. We find an X-ray luminosity of $L_X = 2.7_{-0.8}^{+6.2}\times10^{32} \textrm{ erg s}^{-1}$ in the 0.3-8 keV energy range, while two VLA radio campaigns resulted in a non-detection with a $F_r < 15.8\mu\textrm{Jy}$ 3$ \sigma$ upper limit. The shared properties of both WD pulsars and polars suggest that Gaia22ayj is a missing link between the two classes of magnetic WD binaries., Comment: Submitted to PASP; comments welcome

We explore the empirical power-law relationship between X-ray luminosity (Lx) and total surface magnetic flux (Phi), established across solar magnetic elements, time- and disk-averaged emission from the Sun, older active stars, and pre-main-sequence (PMS) stars. Previous models of large PMS X-ray flares, lacking direct magnetic field measurements, showed discrepancies from this baseline law, which MHD simulations attribute to unusually strong magnetic fields during flares. To test this, we used nearly simultaneous Chandra X-ray and HET-HPF near-infrared observations of four young Orion stars, measuring surface magnetic fields during or just after powerful PMS X-ray flares. We also modeled these PMS X-ray flares, incorporating their measured magnetic field strengths. Our findings reveal magnetic field strengths at the stellar surface typical of non-flaring PMS stars, ruling out the need for abnormally strong fields during flares. Both PMS and solar flares deviate from the Lx-Phi law, with PMS flares exhibiting a more pronounced deviation, primarily due to their much larger active regions on the surface and larger flaring loop volumes above the surface compared to their solar counterparts. These deviations likely stem from the fact that powerful flares are driven by magnetic reconnection, while baseline X-ray emission may involve less efficient mechanisms like Alfven wave heating. Our results also indicate a preference for dipolar magnetic loops in PMS flares, consistent with Zeeman-Doppler imaging of fully convective stars. This requirement for giant dipolar loops aligns with MHD predictions of strong dipoles supported by polar magnetic surface active regions in fast-rotating, fully convective stars., Comment: 25 pages, 9 figures, 3 tables. Accepted for publication in The Astrophysical Journal, January 1, 2025

We investigate the transport properties of flat-band systems by analyzing a one-dimensional metal/flat-band/metal junction constructed on a Lieb lattice with an infinite band gap. Our study reveals that disorders can induce delocalization and enable the control of transmission through quantum geometry. In the weak disorder regime, transmission is primarily mediated by interface-bound states, whose localization length is determined by the quantum geometry of the system. As disorder strength increases, a zero-energy transmission channel - absent in the clean system - emerges, reaches a maximum, and then diminishes inversely with disorder strength in the strong disorder limit. In the strong disorder regime, the transmission increases with the localization length and eventually saturates when the localization length becomes comparable to the link size. Using the Born approximation, we attribute this bulk transmission to a finite velocity induced by disorder scattering. Furthermore, by analyzing the Bethe-Salpeter equation for diffusion, we propose that the quantum metric provides a characteristic length scale for diffusion in these systems. Our findings uncover a disorder-driven delocalization mechanism in flat-band systems that is fundamentally governed by quantum geometry. This work provides new insights into localization phenomena and highlights potential applications in designing quantum devices., Comment: 4.5 pages and comments are welcome

As part of the BISTRO survey, we present JCMT 850 $\mu$m polarimetric observations towards the Orion Integral-Shaped Filament (ISF) that covers three portions known as OMC-1, OMC-2, and OMC-3. The magnetic field threading the ISF seen in the JCMT POL-2 map appears as a tale of three: pinched for OMC-1, twisted for OMC-2, and nearly uniform for OMC-3. A multi-scale analysis shows that the magnetic field structure in OMC-3 is very consistent at all the scales, whereas the field structure in OMC-2 shows no correlation across different scales. In OMC-1, the field retains its mean orientation from large to small scales, but shows some deviations at small scales. Histograms of relative orientations between the magnetic field and filaments reveal a bimodal distribution for OMC-1, a relatively random distribution for OMC-2, and a distribution with a predominant peak at 90$^\circ$ for OMC-3. Furthermore, the magnetic fields in OMC-1 and OMC-3 both appear to be aligned perpendicular to the fibers, which are denser structures within the filament, but the field in OMC-2 is aligned along with the fibers. All these suggest that gravity, turbulence, and magnetic field are each playing a leading role in OMC-1, 2, and 3, respectively. While OMC-2 and 3 have almost the same gas mass, density, and non-thermal velocity dispersion, there are on average younger and fewer young stellar objects in OMC-3, providing evidence that a stronger magnetic field will induce slower and less efficient star formation in molecular clouds., Comment: published in the ApJ Letters

Unsupervised domain adaptive (UDA) algorithms can markedly enhance the performance of object detectors under conditions of domain shifts, thereby reducing the necessity for extensive labeling and retraining. Current domain adaptive object detection algorithms primarily cater to two-stage detectors, which tend to offer minimal improvements when directly applied to single-stage detectors such as YOLO. Intending to benefit the YOLO detector from UDA, we build a comprehensive domain adaptive architecture using a teacher-student cooperative system for the YOLO detector. In this process, we propose uncertainty learning to cope with pseudo-labeling generated by the teacher model with extreme uncertainty and leverage dynamic data augmentation to asymptotically adapt the teacher-student system to the environment. To address the inability of single-stage object detectors to align at multiple stages, we utilize a unified visual contrastive learning paradigm that aligns instance at backbone and head respectively, which steadily improves the robustness of the detectors in cross-domain tasks. In summary, we present an unsupervised domain adaptive YOLO detector based on visual contrastive learning (CLDA-YOLO), which achieves highly competitive results across multiple domain adaptive datasets without any reduction in inference speed.

We present $\sim8-40\,\mu$m SOFIA-FORCAST images of seven regions of ``clustered" star formation as part of the SOFIA Massive (SOMA) Star Formation Survey. We identify a total of 34 protostar candidates and build their spectral energy distributions (SEDs). We fit these SEDs with a grid of radiative transfer models based on the Turbulent Core Accretion (TCA) theory to derive key protostellar properties, including initial core mass, $M_c$, clump environment mass surface density, $\Sigma_{\rm cl}$, and current protostellar mass, $m_*$. We also carry out empirical graybody (GB) estimation of $\Sigma_{\rm cl}$, which allows a case of restricted SED fitting within the TCA model grid. We also release version 2.0 of the open-source Python package \emph{sedcreator}, designed to automate the aperture photometry and SED building and fitting process for sources in clustered environments, where flux contamination from close neighbors typically complicates the process. Using these updated methods, SED fitting yields values of $M_c\sim30-200\:M_{\odot}$, $\Sigma_{\text{cl,SED}}\sim0.1-3\:{\rm{g\:cm}}^{-2}$, and $m_*\sim4-50\:M_{\odot}$. The graybody fitting yields smaller values of $\Sigma_{\text{cl,GB}}\lesssim1\:{\rm{g\:cm}}^{-2}$. From these results, we do not find evidence for a critical $\Sigma_{\rm{cl}}$ needed to form massive ($\gtrsim 8\:M_\odot$) stars. However, we do find tentative evidence for a dearth of the most massive ($m_*\gtrsim30\:M_\odot$) protostars in the clustered regions suggesting a potential impact of environment on the stellar initial mass function., Comment: Submitted to ApJ, comments welcome

We present JWST-NIRCam narrow-band, 4.05 $\mu$m Brackett-$\alpha$ images of the Sgr C HII region, located in the Central Molecular Zone (CMZ) of the Galaxy. Unlike any HII region in the Solar vicinity, the Sgr C plasma is dominated by filamentary structure in both Brackett-$\alpha$ and the radio continuum. Some bright filaments, which form a fractured arc with a radius of about 1.85 pc centered on the Sgr C star-forming molecular clump, likely trace ionization fronts. The brightest filaments form a `$\pi$-shaped' structure in the center of the HII region. Fainter filaments radiate away from the surface of the Sgr C molecular cloud. The filaments are emitting optically thin free-free emission, as revealed by spectral index measurements from 1.28 GHz (MeerKAT) to 97 GHz (ALMA). But, the negative in-band 1 to 2 GHz spectral index in the MeerKAT data alone reveals the presence of a non-thermal component across the entire Sgr C HII region. We argue that the plasma flow in Sgr C is controlled by magnetic fields, which confine the plasma to rope-like filaments or sheets. This results in the measured non-thermal component of low-frequency radio emission plasma, as well as a plasma $\beta$ (thermal pressure divided by magnetic pressure) below 1, even in the densest regions. We speculate that all mature HII regions in the CMZ, and galactic nuclei in general, evolve in a magnetically dominated, low plasma $\beta$ regime., Comment: 31 pages, 19 figures. Accepted for publication in The Astrophysical Journal

We present the study of seven systems, three of which TOI-2295, TOI-2537, and TOI-5110 are newly discovered planetary systems. Through the analysis of TESS photometry, SOPHIE radial velocities, and high-spatial resolution imaging, we found that TOI-2295b, TOI-2537b, and TOI-5110b are transiting warm Jupiters with orbital periods ranging from 30 to 94 d, masses between 0.9 and 2.9 MJ, and radii ranging from 1.0 to 1.5 RJ. Both TOI-2295 and TOI-2537 each harbor at least one additional, outer planet. Their outer planets TOI-2295c and TOI-2537c are characterized by orbital periods of 966.5 +/- 4.3 and 1920^{+230}_{-140} d, respectively, and minimum masses of 5.61^{+0.23}_{-0.24} and 7.2 +/- 0.5 MJ, respectively. We also investigated and characterized the two recently reported warm Jupiters TOI-1836b and TOI-5076b, which we independently detected in SOPHIE RVs. Additionally, we study the planetary candidates TOI-4081.01 and TOI-4168.01. For TOI-4081.01, despite our detection in radial velocities, we cannot rule out perturbation by a blended eclipsing binary and thus exercise caution regarding its planetary nature. On the other hand, we identify TOI-4168.01 as a firm false positive. Finally, we highlight interesting characteristics of these new planetary systems. The transits of TOI-2295b are highly grazing, with an impact parameter of 1.056$^{+0.063}_{-0.043}$. TOI-2537b, in turn, is a temperate Jupiter with an effective temperature of 307+/-15 K and can serve as a valuable low-irradiation control for models of hot Jupiter inflation anomalies. We also detected significant transit timing variations (TTVs) for TOI-2537b, which are likely caused by gravitational interactions with the outer planet TOI-2537c. Finally, TOI-5110b stands out due to its orbital eccentricity of 0.75+/- 0.03, one of the highest planetary eccentricities discovered thus far., Comment: 46 pages, 21 figures, accepted for publication in A&A

As the infrastructure of police surveillance grows in public schools, communities must be prepared to safeguard the rights and freedoms of students and families. This report is designed to help youth justice advocates, youth leaders, educators, caregivers, and policymakers understand and challenge the impact of school surveillance, data criminalization, and police surveillance technologies in schools. This report includes: (1) An analysis of six key facts about the impacts of data criminalization and school surveillance technologies on education equity; (2) A case study of an AI school surveillance technology that can land children in adult misdemeanor court; and (3) Key recommendations for education policymakers and school district leaders for advancing youth data justice.

In an effort to reduce state spending on special education in public schools, New Jersey moved to census-based funding as part of the new school funding formula, the School Funding Reform Act (SFRA), adopted in 2008. The census approach funds all districts using the statewide average classification rate and a statewide average "excess cost." This report found that: (1) Classification rates for special education vary greatly among school districts, resulting in the inequitable distribution of resources to fund districts' actual special education enrollment; (2) In 2022-23, districts with classification rates higher than the statewide average received $378 million less than if they were funded on their actual special education enrollment; and (3) Districts with higher-than-average classification rates must divert funding from general education programs or raise additional local revenue to fill the gap for unfunded special education students. In this report, the authors show that census-based funding does not meet the needs of New Jersey school districts and the students, in both special and general education, they serve. The analyses presented in this report demonstrate the need for New Jersey to convene school finance and special education experts to explore and recommend alternative funding models for special education that would better meet the needs of the state's school districts.

The School Funding Reform Act (SFRA), New Jersey's school finance law, requires the Governor, in consultation with the Commissioner of Education, to review certain components of the school funding formula every three years. The New Jersey Department of Education (NJDOE) issued four Educational Adequacy Reports (EAR) between 2013 and 2022, but none provided the in-depth analysis that is required to ensure the formula is delivering adequate resources to all students. These reports updated the underlying costs of the formula while failing to consider whether the inputs themselves are adequate for delivering the state's evolving learning standards. These surface-level reviews have left the SFRA out of step with current thinking on the resources needed to meet the state's academic and social-emotional standards. To ensure New Jersey students are receiving a constitutional "thorough and efficient" education, it is time for the NJDOE to conduct a much more thorough analysis. The FY2026 EAR, due to the Legislature in early 2025, provides the long overdue opportunity to do a thorough analysis of the formula and its components to ensure it is calibrated to the resources needed to provide all students with an adequate education aligned with New Jersey's current standards and curriculum.

This is the executive summary for the full report, "Centering Quality, Centering Equity: Lessons Learned in Increasing Early Childhood Educator Credentials." Thriving communities depend on a strong early childhood education (ECE) system--one where both young children and members of the workforce are served and supported. In recent years, state government leaders have increasingly focused on changing qualifications for specific ECE roles, as increasing credential requirements has sometimes been associated with increasing quality. However, across the country, early childhood educators face significant barriers to economic security and continuing education--all while supporting children, parents, and their communities with specialized education services.

Large plume-like features within the Greenland Ice Sheet disrupt radiostratigraphy and complicate the use of isochrones in reconstructions of past ice dynamics. Here we use numerical modeling to test the hypothesis that convection is a viable mechanism for the formation of the large (>1/3 ice thickness) englacial plume-like features observed in north Greenland. Greater horizontal shear and snow accumulation impede formation of convection plumes, while stable and softer ice encourages them. These results potentially explain the dearth of basal plumes in the younger and higher-accumulation southern ice sheet. Leveraging this mechanism to place bounds on ice rheology suggests that -- for north Greenland -- ice viscosity may be ~9-15 times lower than commonly assumed. Softer-than-assumed ice there implies significantly reduced basal sliding compared to standard models. Implementing a softer basal ice rheology in numerical models may help reduce uncertainty in projections of future ice-sheet mass balance.

How Supernova Remnant (SNR) shocks impact nearby molecular clouds is still poorly observationally constrained. It is unclear if SNRs can positively or negatively affect clouds star formation potential. We have studied the dense gas morphology and kinematics toward the Infrared Dark Cloud (IRDC) G034.77-00.55, shock-interacting with the SNR W44, to identify evidence of early stage star formation induced by the shock. We have used high-angular resolution N2H+(1-0) images across G034.77-00.55, obtained with ALMA. N2H+ is a well known tracer of dense and cold material, optimal to identify gas with the highest potential to harbour star formation. The N2H+ emission is distributed into two elongated structures, one toward the dense ridge at the edge of the source and one toward the inner cloud. Both elongations are spatially associated with well-defined mass-surface density features. The velocities of the gas in the two structures i.e., 38-41 km s-1 and 41-43 km s-1 are consistent with the lowest velocities of the J- and C-type parts of the SNR-driven shock, respectively. A third velocity component is present at 43-45.5 km s-1. The dense gas shows a fragmented morphology with core-like fragments of scales consistent with the Jeans lengths, masses $\sim$1-20 M$_{\odot}$, densities (n(H$_2$)$\geq$10$^5$ cm$^{-3}$) sufficient to host star formation in free-fall time scales (few 10$^4$ yr) and with virial parameters that hint toward possible collapse. The W44 driven shock may have swept up the encountered material which is now seen as a dense ridge, almost detached from the main cloud, and an elongation within the inner cloud, well constrained in both N2H+ emission and mass surface density. This shock compressed material may have then fragmented into cores that are either in a starless or pre-stellar stage. Additional observations are needed to confirm this scenario and the nature of the cores., Comment: 12 pages, 8 figures, accepted for publication in A&A

BabyIAXO is the intermediate stage of the International Axion Observatory (IAXO) to be hosted at DESY. Its primary goal is the detection of solar axions following the axion helioscope technique. Axions are converted into photons in a large magnet that is pointing to the sun. The resulting X-rays are focused by appropriate X-ray optics and detected by sensitive low-background detectors placed at the focal spot. The aim of this article is to provide an accurate quantitative description of the different components (such as the magnet, optics, and X-ray detectors) involved in the detection of axions. Our efforts have focused on developing robust and integrated software tools to model these helioscope components, enabling future assessments of modifications or upgrades to any part of the IAXO axion helioscope and evaluating the potential impact on the experiment's sensitivity. In this manuscript, we demonstrate the application of these tools by presenting a precise signal calculation and response analysis of BabyIAXO's sensitivity to the axion-photon coupling. Though focusing on the Primakoff solar flux component, our virtual helioscope model can be used to test different production mechanisms, allowing for direct comparisons within a unified framework., Comment: 36 pages, 18 figures, 4 tables, Submitted to JHEP

Generalist vision language models (VLMs) have made significant strides in computer vision, but they fall short in specialized fields like healthcare, where expert knowledge is essential. In traditional computer vision tasks, creative or approximate answers may be acceptable, but in healthcare, precision is paramount.Current large multimodal models like Gemini and GPT-4o are insufficient for medical tasks due to their reliance on memorized internet knowledge rather than the nuanced expertise required in healthcare. VLMs are usually trained in three stages: vision pre-training, vision-language pre-training, and instruction fine-tuning (IFT). IFT has been typically applied using a mixture of generic and healthcare data. In contrast, we propose that for medical VLMs, a fourth stage of specialized IFT is necessary, which focuses on medical data and includes information from domain expert models. Domain expert models developed for medical use are crucial because they are specifically trained for certain clinical tasks, e.g. to detect tumors and classify abnormalities through segmentation and classification, which learn fine-grained features of medical data$-$features that are often too intricate for a VLM to capture effectively especially in radiology. This paper introduces a new framework, VILA-M3, for medical VLMs that utilizes domain knowledge via expert models. Through our experiments, we show an improved state-of-the-art (SOTA) performance with an average improvement of ~9% over the prior SOTA model Med-Gemini and ~6% over models trained on the specific tasks. Our approach emphasizes the importance of domain expertise in creating precise, reliable VLMs for medical applications.

The ongoing physical and chemical processes in planet-forming disks set the stage for planet formation. The asymmetric disk around the young star Oph-IRS 48 has one of the most well-characterised chemical inventories, showing molecular emission from a wide variety of species at the dust trap. One of the explanations for the asymmetric structure is dust trapping by a perturbation-induced vortex. We aim to constrain the excitation properties of the molecular species SO$_2$, CH$_3$OH, and H$_2$CO. We further characterise the extent of the molecular emission, through the determination of important physical and chemical timescales at the location of the dust trap. We also investigate whether the potential vortex can influence the observable temperature structure of the gas. Through a pixel-by-pixel rotational diagram analysis, we create rotational temperature and column density maps for SO$_2$ and CH$_3$OH, while temperature maps for H$_2$CO are created using line ratios. We find temperatures of $T\sim$55 K and $T\sim$125 K for SO$_2$ and CH$_3$OH, respectively, while the line ratios point towards temperatures of T$\sim$150-300 K for H$_2$CO. The rotational diagram of CH$_3$OH is dominated by scatter and subsequent non-LTE RADEX calculations suggest that both CH$_3$OH and H$_2$CO must be sub-thermally excited. The temperatures suggest that SO$_2$ comes from a layer deep in the disk, while CH$_3$OH and H$_2$CO originate from a higher layer. While a potential radial gradient is seen in the temperature map of SO$_2$, we do not find any hints of a vortex influencing the temperature structure. The determined turbulent mixing timescale is not able to explain the emitting heights of the molecules, but the photodissociation timescales are able to explain the wider azimuthal extents of SO$_2$ and H$_2$CO compared to CH$_3$OH, where a secondary, gas-phase formation reservoir is required for H$_2$CO., Comment: Accepted for publication in Astronomy and Astrophysics

The formalism of quantum estimation theory with a specific focus on the classical postprocessing of data is applied to a two-level system driven by an external gyrating magnetic field. We employed both Bayesian and frequentist approaches to estimate the unknown transition frequency. In the frequentist approach, we have shown that reducing the distance between the classical and the quantum Fisher information does not necessarily mean that the estimators as functions of the data deliver an estimate with desirable precision. Due to the nonlinearity of the probability mass function of the data on the transition frequency, the minimum variance unbiased estimator may not exist. The maximum likelihood and the maximum a posteriori estimators often result in ambiguous estimates, which in certain cases can be made unambiguous upon changing the parameters of the external field. It is demonstrated that the most promising solution is given by the minimum mean-square error estimator of the Bayesian statistics, which is efficient even for finite data points. In the Bayesian approach, we have considered both informative and noninformative priors, including a uniform prior, Jeffrey's prior, and a Gaussian prior., Comment: 14 pages, 7 figures

The nonlinear Hall effect refers to the nonlinear voltage response that is transverse to the applied electric field. Recent studies have shown that the quantum geometric quantities on Fermi surfaces serve as fundamental contributors to the nonlinear Hall effect, suggesting that the nonlinear Hall effect occurs mainly in metals. However, in this work, we demonstrate that insulators can also exhibit the nonlinear Hall effect. We find that for an insulator driven at a finite frequency, a series of frequency dependent quantum geometric quantities from the occupied bands can give rise to a nonvanishing nonlinear Hall conductivity. The nonlinear Hall conductivity is frequency dependent: at resonance, it represents the inter-band transition enabled nonlinear Hall current; near resonance, it represents the nonlinear order polarization transverse to the electric field. We further connect the nonlinear Hall conductivity to the Kleinman conjecture in nonlinear optics and point out that the nonlinear Hall effect is generally allowed in insulators given the driving frequency near resonance. For the candidate materials, we consider the biased Bernal bilayer graphene under uniaxial strain and propose polarization resolved second harmonic microscopy to detect the nonlinear Hall effect there., Comment: 7 pages, 4 figures. Comments are welcome

Existing methods for learning urban space representations from Point-of-Interest (POI) data face several limitations, including issues with geographical delineation, inadequate spatial information modelling, underutilisation of POI semantic attributes, and computational inefficiencies. To address these issues, we propose CaLLiPer (Contrastive Language-Location Pre-training), a novel representation learning model that directly embeds continuous urban spaces into vector representations that can capture the spatial and semantic distribution of urban environment. This model leverages a multimodal contrastive learning objective, aligning location embeddings with textual POI descriptions, thereby bypassing the need for complex training corpus construction and negative sampling. We validate CaLLiPer's effectiveness by applying it to learning urban space representations in London, UK, where it demonstrates 5-15% improvement in predictive performance for land use classification and socioeconomic mapping tasks compared to state-of-the-art methods. Visualisations of the learned representations further illustrate our model's advantages in capturing spatial variations in urban semantics with high accuracy and fine resolution. Additionally, CaLLiPer achieves reduced training time, showcasing its efficiency and scalability. This work provides a promising pathway for scalable, semantically rich urban space representation learning that can support the development of geospatial foundation models. The implementation code is available at https://github.com/xlwang233/CaLLiPer., Comment: 19 pages, 5 figures, 7 tables

To a graph $\Gamma$, one can associate a hypertoric variety $\mathcal{M}(\Gamma)$ and its multiplicative version $\mathcal{M}^{\mathrm{mul}}(\Gamma)$. It was shown in [DMS24] that the cohomology of $\mathcal{M}^{\mathrm{mul}}(\Gamma)$ is computed by the CKS complex, which is a finite dimensional complex attached to $\Gamma$. The multiplicative hypertoric variety can be realized as the quotient of a periodized hypertoric variety by a lattice action. In this paper, we show that the group cohomology of the lattice with coefficients in the cohomology of the prequotient is isomorphic to the cohomology of the CKS complex using a spectral sequence argument. Therefore, the group cohomology can serve as an alternative way to compute the cohomology of multiplicative hypertoric varieties. We also found graph-theoretic descriptions for the Euler characteristics of the graded pieces in a certain decomposition of $\mathrm{H}^\bullet(\mathcal{M}^{\mathrm{mul}}(\Gamma))$., Comment: 31 pages, 5 figures

We extend our recently identified dynamical edge mode boundary condition to $p$-form gauge theories, revealing their edge modes as Goldstone bosons arising from gauge transformations with support on the boundary. The symplectic conjugates of these edge modes correspond to the electric-field-like components normal to the boundary. We demonstrate that both the symplectic form and the Hamiltonian naturally decompose into bulk and edge parts. When the boundary is a stretched horizon, we show that the thermal edge partition function reduces to that of a codimension-two ghost $(p-1)$-form residing on the bifurcation surface. These findings provide a dynamical framework that elucidates observations made by several authors. Additionally, we generalize Donnelly and Wall's non-dynamical approach to obtain edge partition functions for both massive and massless $p$-forms. In the context of a de Sitter static patch, these results are consistent with the edge partition functions found by several authors in arbitrary dimensions., Comment: 36 pages + 3 appendices; 1 figure

We present 850 $\mu$m polarization observations of the IC 348 star-forming region in the Perseus molecular cloud as part of the B-fields In STar-forming Region Observation (BISTRO) survey. We study the magnetic properties of two cores (HH 211 MMS and IC 348 MMS) and a filamentary structure of IC 348. We find that the overall field tends to be more perpendicular than parallel to the filamentary structure of the region. The polarization fraction decreases with intensity, and we estimate the trend by power-law and the mean of the Rice distribution fittings. The power indices for the cores are much smaller than 1, indicative of possible grain growth to micron size in the cores. We also measure the magnetic field strengths of the two cores and the filamentary area separately by applying the Davis-Chandrasekhar-Fermi method and its alternative version for compressed medium. The estimated mass-to-flux ratios are 0.45-2.20 and 0.63-2.76 for HH 211 MMS and IC 348 MMS, respectively, while the ratios for the filament is 0.33-1.50. This result may suggest that the transition from subcritical to supercritical conditions occurs at the core scale ($\sim$ 0.05 pc) in the region. In addition, we study the energy balance of the cores and find that the relative strength of turbulence to the magnetic field tends to be stronger for IC 348 MMS than HH 211 MMS. The result could potentially explain the different configurations inside the two cores: a single protostellar system in HH 211 MMS and multiple protostars in IC 348 MMS., Comment: Accepted for publication in ApJ. 21 pages, 12 figures

Different camera sensors have different noise patterns, and thus an image denoising model trained on one sensor often does not generalize well to a different sensor. One plausible solution is to collect a large dataset for each sensor for training or fine-tuning, which is inevitably time-consuming. To address this cross-domain challenge, we present a novel adaptive domain learning (ADL) scheme for cross-domain RAW image denoising by utilizing existing data from different sensors (source domain) plus a small amount of data from the new sensor (target domain). The ADL training scheme automatically removes the data in the source domain that are harmful to fine-tuning a model for the target domain (some data are harmful as adding them during training lowers the performance due to domain gaps). Also, we introduce a modulation module to adopt sensor-specific information (sensor type and ISO) to understand input data for image denoising. We conduct extensive experiments on public datasets with various smartphone and DSLR cameras, which show our proposed model outperforms prior work on cross-domain image denoising, given a small amount of image data from the target domain sensor., Comment: 13 pages, 3 figures, accepted by neurips 2024

Massive star-forming regions exhibit a rich chemistry with complex gas distributions, especially on small scales. While surveys have yielded constraints on typical gas conditions, they often have coarse spatial resolution and limited bandwidths. Thus, to establish an interpretative framework for these efforts, detailed observations that simultaneously provide high sensitivity, spatial resolution, and large bandwidths for a subset of diverse sources are needed. Here, we present wideband (32 GHz) Submillimeter Array observations of four high-mass star-forming regions (G28.20-0.05, G20.08-0.14 N, G35.58-0.03, W33 Main) at subarcsecond resolution, where we detect and spatially-resolve 100s of lines from over 60 molecules, including many complex organic molecules (COMs). The chemical richness of our sample is consistent with an evolutionary sequence from the line-rich hot cores and HC HII regions of G28.20-0.05 and G20.08-0.14 N to the more chemically-modest UC HII regions in G35.58-0.03, followed by the molecule-poor HII region W33 Main. We detect lines across a range of excitation conditions (Eu=20 to >800 K) and from numerous isotopologues, which enables robust estimates of gas properties. We derive nearly constant COM column density ratios that agree with literature values in other low- and high-mass protostellar cores, supporting the idea that COM abundances are set during the pre-stellar phase. In all regions, we identify spatial offsets among different molecular families, due to a combination of source physical structure and chemistry. In particular, we find potential evidence of carbon grain sublimation in G28.20-0.05 and identify an elemental oxygen gradient and rich sulfur-chemistry in G35.58-0.03. Overall, these results demonstrate that the SMA's wide bandwidth is a powerful tool to untangle the complex molecular gas structures associated with massive star formation., Comment: 47 pages, 36 figures, accepted for publication in ApJS. Data and image cubes available at https://zenodo.org/records/13342640

3D object detection is an essential task for computer vision applications in autonomous vehicles and robotics. However, models often struggle to quantify detection reliability, leading to poor performance on unfamiliar scenes. We introduce a framework for quantifying uncertainty in 3D object detection by leveraging an evidential learning loss on Bird's Eye View representations in the 3D detector. These uncertainty estimates require minimal computational overhead and are generalizable across different architectures. We demonstrate both the efficacy and importance of these uncertainty estimates on identifying out-of-distribution scenes, poorly localized objects, and missing (false negative) detections; our framework consistently improves over baselines by 10-20% on average. Finally, we integrate this suite of tasks into a system where a 3D object detector auto-labels driving scenes and our uncertainty estimates verify label correctness before the labels are used to train a second model. Here, our uncertainty-driven verification results in a 1% improvement in mAP and a 1-2% improvement in NDS.

Evidence for similar chemical characteristics around low- and high-mass protostars has been found: in particular, a variety of carbon-chain species and complex organic molecules (COMs) are formed around them. On the other hand, the chemical compositions around intermediate-mass (IM; $2 M_{\odot} < m_* <8 M_{\odot}$) protostars have not been studied with large samples. In particular, it is unclear the extent to which carbon-chain species are formed around them. We aim to obtain the chemical compositions, particularly focusing on carbon-chain species, towards a sample of IM protostars. We have conducted Q-band (31.5-50 GHz) line survey observations towards eleven mainly intermediate-mass protostars with the Yebes 40 m radio telescope. The target protostars were selected from a sub-sample of the source list of the SOFIA Massive (SOMA) Star Formation project. Nine carbon-chain species (HC$_3$N, HC$_5$N, C$_3$H, C$_4$H, $linear-$H$_2$CCC, $cyclic-$C$_3$H$_2$, CCS, C$_3$S, and CH$_3$CCH), three COMs (CH$_3$OH, CH$_3$CHO, and CH$_3$CN), H$_2$CCO, HNCO, and four simple sulfur (S)-bearing species ($^{13}$CS, C$^{34}$S, HCS$^+$, H$_2$CS) have been detected. The rotational temperatures of HC$_5$N are derived to be $\sim20-30$ K in three IM protostars and they are very similar compared to those around low- and high-mass protostars. These results indicate that carbon-chain molecules are formed in lukewarm ($\sim20-30$ K) gas around the IM protostars by the Warm Carbon-Chain Chemistry (WCCC) process. Carbon-chain formation occurs ubiquitously in the warm gas around protostars across a wide range of stellar masses. Carbon-chain molecules and COMs coexist around most of the target IM protostars, which is similar to the situation in low- and high-mass protostars. The chemical characteristics around protostars are common in the low-, intermediate- and high-mass regimes., Comment: Accepted for publication in the Astronomy and Astrophysics (A&A)

Aligning AI agents with human values is challenging due to diverse and subjective notions of values. Standard alignment methods often aggregate crowd feedback, which can result in the suppression of unique or minority preferences. We introduce Interactive-Reflective Dialogue Alignment, a method that iteratively engages users in reflecting on and specifying their subjective value definitions. This system learns individual value definitions through language-model-based preference elicitation and constructs personalized reward models that can be used to align AI behaviour. We evaluated our system through two studies with 30 participants, one focusing on "respect" and the other on ethical decision-making in autonomous vehicles. Our findings demonstrate diverse definitions of value-aligned behaviour and show that our system can accurately capture each person's unique understanding. This approach enables personalized alignment and can inform more representative and interpretable collective alignment strategies., Comment: 19 pages, 16 figures