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The 3α phenomenological model describes the structure of the carbon-12 nucleus as a cluster of three alpha particles. This model includes a pairwise α–α interaction and a three-body force. To fit the three-body potential, the 12C data are used, while ensuring that the pair potential reproduces the α–α scattering data. Alternatively, the mass-energy compensation (MEC) effect can be used to simulate the effect of the three-body potential by adjusting the mass of the α particle within the effective-mass approach. We demonstrate the MEC effect for the 3α ground state by numerically solving the differential Faddeev equation, in which the α–α interaction is described by the Ali-Bodmer potential. The effective masses of α particles are evaluated for the ground and excited 0+ and bound 2+ states. We demonstrate a coupling between the ground and first excited 0+ states, indicated by an anti-crossing of these energy levels in the energy–mass coordinates. A correspondence between the effective mass and a three-body potential is demonstrated. We discuss the results of the 0+2 calculations for various models of the α–α interaction. 

Carbon-based black pigments, a widely used class of pigments, are difficult to differentiate with the noninvasive techniques currently used in cultural heritage science. We use pump-probe microscopy, coupled with a support vector machine, to distinguish common carbon-based black pigments as pure pigments, as two-component black pigment mixtures, and as a mixture of a black and a colorful pigment. This work showcases the potential of pump-probe microscopy to spatially differentiate carbon-based black pigments, which would have interesting applications to works of art. 

In optical experiments, shutters are devices that open or close a path of light. They are often used to limit the duration of light exposure onto a target or onto a detector to reduce possible light-induced damage. Many commercial shutters are available for different applications – some provide very fast opening and closing times, some can handle large optical powers, and others allow for fail-safe operation. Many of these devices are costly and offer limited control options. Here we provide an open-source design for a low-cost, general purpose shutter system based on ubiquitous actuators (servo motors or solenoids) that are connected to an Arduino-based controller. Several shutters can be controlled by one controller, further reducing system cost. The state of the shutters can be controlled via a display built into the controller, by serial commands via USB, or by electrical control lines. The use of a microcontroller makes the shutter controller adaptable – only control options that are used need to be included, and the design accommodates a selection of display and actuator options. We provide designs for all required components, including 3D print files for the actuator holders and cases, the Arduino code, libraries for serial communication (C and python), and example graphical user interfaces for testing. 

Abstract Maintenance of water homeostasis is a fundamental cellular process required by all living organisms. Here, we use the single-celled green algaChlamydomonas reinhardtiito establish a foundational understanding of osmotic-stress signaling pathways through transcriptomics, phosphoproteomics, and functional genomics approaches. Comparison of pathways identified through these analyses with yeast and Arabidopsis allows us to infer their evolutionary conservation and divergence across these lineages. 76 genes, acting across diverse cellular compartments, were found to be important for osmotic-stress tolerance in Chlamydomonas through their functions in cytoskeletal organization, potassium transport, vesicle trafficking, mitogen-activated protein kinase and chloroplast signaling. We show that homologs for five of these genes have conserved functions in stress tolerance in Arabidopsis and reveal a novel PROFILIN-dependent stage of acclimation affecting the actin cytoskeleton that ensures tissue integrity upon osmotic stress. This study highlights the conservation of the stress response in algae and land plants, and establishes Chlamydomonas as a unicellular plant model system to dissect the osmotic stress signaling pathway. 

In recommender systems, preference elicitation (PE) is an effective way to learn about a user’s preferences to improve recommendation quality. Expected value of information (EVOI), a Bayesian technique that computes expected gain in user utility, has proven to be effective in selecting useful PE queries. Most EVOI methods use probabilistic models of user preferences and query responses to compute posterior utilities. By contrast, we develop model-free variants of EVOI that rely on function approximation to obviate the need for specific modeling assumptions. Specifically, we learn user response and utility models from existing data (often available in real-world recommender systems), which are used to estimate EVOI rather than relying on explicit probabilistic inference. We augment our approach by using online planning, specifically, Monte Carlo tree search, to further enhance our elicitation policies. We show that our approach offers significant improvement in recommendation quality over standard baselines on several PE tasks. 

This article presents GenSQL, a probabilistic programming system for querying probabilistic generative models of database tables. By augmenting SQL with only a few key primitives for querying probabilistic models, GenSQL enables complex Bayesian inference workflows to be concisely implemented. GenSQL’s query planner rests on a unified programmatic interface for interacting with probabilistic models of tabular data, which makes it possible to use models written in a variety of probabilistic programming languages that are tailored to specific workflows. Probabilistic models may be automatically learned via probabilistic program synthesis, hand-designed, or a combination of both. GenSQL is formalized using a novel type system and denotational semantics, which together enable us to establish proofs that precisely characterize its soundness guarantees. We evaluate our system on two case real-world studies—an anomaly detection in clinical trials and conditional synthetic data generation for a virtual wet lab—and show that GenSQL more accurately captures the complexity of the data as compared to common baselines. We also show that the declarative syntax in GenSQL is more concise and less error-prone as compared to several alternatives. Finally, GenSQL delivers a 1.7-6.8x speedup compared to its closest competitor on a representative benchmark set and runs in comparable time to hand-written code, in part due to its reusable optimizations and code specialization. 

Abstract Cadmium sulfide (CdS) pigments have degraded in several well-known artworks, but the influence of pigment properties and environmental conditions on the degradation process have yet to be fully understood. Traditional non-destructive analysis techniques primarily focus on macroscopic degradation, whereas microscopic information is typically obtained with invasive techniques that require sample removal. Here, we demonstrate the use of pump-probe microscopy to nondestructively visualize the three-dimensional structure and degradation progress of CdS pigments in oil paints. CdS pigments, reproduced following historical synthesis methods, were reproduced as oil paints and artificially aged by exposure to high relative humidity and light. The degradation of CdS to CdSO₄·xH₂O was confirmed by both FTIR (Fourier-transform infrared) and XPS (x-ray photoelectron spectroscopy) experiments. During the degradation process, optical pump-probe microscopy was applied to track the degradation progress in single grains, and volumetric imaging revealed early CdS degradation of small particles and on the surface of large particles. This indicates that the particle dimension influences the extent and evolution of degradation of historical CdS. In addition, the pump-probe signal decrease in degraded CdS is observable before visible changes to the eye, demonstrating that pump-probe microscopy is a promising tool to detect early-stage degradation in artworks. 

An investigation of high-transverse-momentum (high- $p_T$) photon-triggered jets in proton-proton ( $p\text{−}p$) and ion-ion ( $A\text{−}A$) collisions at $\sqrt{s_{NN}}=0.2$and $5.02\mathrm{TeV}$is carried out, using the multistage description of in-medium jet evolution. Monte Carlo simulations of hard scattering and energy loss in heavy-ion collisions are performed using parameters tuned in a previous study of the nuclear modification factor ( $R_{AA}$) for inclusive jets and high- $p_T$hadrons. We obtain a good reproduction of the experimental data for photon-triggered jet $R_{AA}$, as measured by the ATLAS detector, the distribution of the ratio of jet to photon $p_T$( $X_{J\gamma }$), measured by both CMS and ATLAS, and the photon-jet azimuthal correlation as measured by CMS. We obtain a moderate description of the photon-triggered jet $I_{AA}$, as measured by STAR. A noticeable improvement in the comparison is observed when one goes beyond prompt photons and includes bremsstrahlung and decay photons, revealing their significance in certain kinematic regions, particularly at $X_{J\gamma }>1$. Moreover, azimuthal angle correlations demonstrate a notable impact of bremsstrahlung photons on the distribution, emphasizing their role in accurately describing experimental results. This work highlights the success of the multistage model of jet modification to straightforwardly predict (this set of) photon-triggered jet observables. This comparison, along with the role played by bremsstrahlung photons, has important consequences on the inclusion of such observables in a future Bayesian analysis. Published by the American Physical Society2025