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Future time perspective extension is an individual's perception of the psychological distance between future goals. The concept of extension can be expanded to include how far into the future an individual habitual time space extends and the diffusion of goals within that time space. This alignment and distance may be related to the individual episodic future thinking, the pre-experiencing of future events. Research in FTP and EFT are typically siloed; considering both approaches to future thinking provides not only greater insight into the two constructs but may also provide avenues for developing interventions. Participants in this study (n = 13) were recruited from a scholarship program designed to provide them with financial support as they progress from community college to high-wage careers in science and engineering. Students were transitioning from two-year programs at local community colleges to science degree programs at a large four-year research university. Students’ narratives of their future lives were collected using an interview format, participants also completed a digital survey to quantitatively measure their future time perspective. Qualitative data were analyzed using a deductive thematic analytic approach and a content analytic approach. Students’ profiles differed in extension (how far into the future students' project) and diffusion (how many potential future careers are considered). Findings suggest that students with more extended, vivid, and specific career narratives. have higher career commitment and self-efficacy. The study concludes that understanding the intersection of FTPE and EFT can inform educational interventions to support students in visualizing and planning for their careers, particularly in science and engineering fields. 

Abstract The observational link between long gamma-ray bursts (GRBs) and broad-lined stripped-envelope core-collapse supernovae (SNe Ic-BL) is well established. Significant progress has been made in constraining what fraction of SNe Ic-BL may power high- or low-luminosity GRBs when viewed at small off-axis angles. However, the GRB–SN connection still lacks a complete understanding in the broader context of massive-star evolution and explosion physics. Models predict a continuum of outcomes for the fastest ejecta, from choked to ultrarelativistic jets, and observations from radio to X-rays are key to probing these scenarios across a range of viewing angles and velocities. Here, we present results from a coordinated radio-to-X-ray campaign targeting nearby (z ≲ 0.1) SNe Ic-BL designed to explore this diversity. With eight new radio-monitored events and updated data for one previously observed SN, we further tighten constraints on the fraction of SNe Ic-BL as relativistic as SN 1998bw (GRB 980425). We identify SN 2024rjw as a new radio-loud event likely powered by strong interaction with circumstellar material, and add evidence supporting a similar interpretation for SN 2020jqm. We also establish new limits on the properties of radio-emitting ejecta with velocities consistent with cocoons from choked jets, highlighting SN 2022xxf as a promising cocoon-dominated candidate. These results refine our understanding of the continuum linking ordinary SNe Ic-BL, engine-driven explosions, and GRBs, and contribute to building a sample that will inform future multimessenger searches for electromagnetic counterparts to high-energy neutrinos. 

Abstract Herein high-strength composites are prepared from elemental sulfur, sunflower oil, and wastewater sludge. Fats extracted from dissolved air flotation (DAF) solids were reacted with elemental sulfur to yield compositeDAFS(10 wt% DAF fats and 90 wt% sulfur). Additional composites were prepared from DAF fat, sunflower oil and sulfur to giveSunDAF_x(x = wt% sulfur, varied from 85–90%). The composites were characterized by spectroscopic, thermal, and mechanical methods. FT-IR spectra revealed a notable peak at 798 cm^–1indicating a C–S stretch inDAFS,SunDAF₉₀, andSunDAF₈₅indicating successful crosslinking of polymeric sulfur with olefin units. SEM/EDX analysis revealed homogenous distribution of carbon, oxygen, and sulfur inSunDAF₉₀andSunDAF₈₅. The percent crystallinity exhibited byDAFS(37%),SunDAF₉₀(39%), andSunDAF₈₅(45%) was observed to be slightly lower than that of previous composites prepared from elemental sulfur and fats and oils.DAFSandSunDAF_xdisplayed compressive strengths (26.4–38.7 MPa) of up to 227% above that required (17 MPa) of ordinary Portland cement for residential building foundations. The composite decomposition temperatures ranged from 211 to 219 °C, with glass transition temperatures of − 37 °C to − 39 °C. These composites thus provide a potential route to reclaim wastewater organics for use in value-added structural materials having mechanical properties competitive with those of commercial products. 

Abstract Quasars are bright active galactic nuclei powered by the accretion of matter around supermassive black holes at the center of galaxies. Their stochastic brightness variability depends on the physical properties of the accretion disk and black hole. The upcoming Rubin Observatory Legacy Survey of Space and Time (LSST) is expected to observe tens of millions of quasars, so there is a need for efficient techniques like machine learning that can handle the large volume of data. Quasar variability is believed to be driven by an X-ray corona, which is reprocessed by the accretion disk and emitted as UV/optical variability. We are the first to introduce an auto-differentiable simulation of the accretion disk and reprocessing. We use the simulation as a direct component of our neural network to jointly model the driving variability and reprocessing, trained with supervised learning on simulated LSST-like 10 yr quasar light curves. We encode the light curves using a transformer encoder, and the driving variability is reconstructed using latent stochastic differential equations, a physically motivated generative deep learning method that can model continuous-time stochastic dynamics. By embedding the physical processes of the driving signal and reprocessing into our network, we achieve a model that is more robust and interpretable. We demonstrate that our model outperforms a Gaussian process regression baseline and can infer accretion disk parameters and time delays between wave bands, even for out-of-distribution driving signals. Our approach provides a powerful framework that can be adapted to solve other inverse problems in multivariate time series. 

Large sinusoidal variations in the radio light curves of the blazars PKS J0805–0111 and PKS 2131–021 have recently been discovered with an 18-year monitoring programme at the Owens Valley Radio Observatory, making these systems strong supermassive black hole binary (SMBHB) candidates. The sinusoidal variations in PKS 2131–021 dominate its light curves from 2.7 GHz to optical frequencies. We report sinusoidal variations observed in both objects with the Atacama Cosmology Telescope (ACT) at 95, 147, and 225 GHz consistent with the radio light curves. The ACT 95 GHz light curve of PKS 2131–021 agrees well with the contemporaneous 91.5 GHz ALMA light curve and is comparable in quality, while the ACT light curves of PKS J0805–0111, for which there are no ALMA or other millimetre light curves, show that PKS 2131–021 is not an isolated case, and that this class of AGN exhibits the following properties: (a) the sinusoidal pattern dominates over a broad range of frequencies; (b) the amplitude of the sine wave compared to its mean value is monochromatic (i.e. nearly constant across frequencies); (c) the phase of the sinusoid phase changes monotonically as a function of frequency; (d) the sinusoidal variations are intermittent. We describe a physical model for SMBHB systems, the modified Kinetic Orbital model, that explains all four of these phenomena. The monitoring of ∼8000 blazars by the Simons Observatory over the next decade should provide a large number of SMBHB candidates that will shed light on the nature of the nanohertz gravitational-wave background. 

The construction of bounded-degree plane geometric spanners has been a focus of interest since 2002 when Bose, Gudmundsson, and Smid proposed the first algorithm to construct such spanners. To date, 11 algorithms have been designed with various tradeoffs in degree and stretch-factor. We have implemented these sophisticated spanner algorithms in C ++ using the CGAL library and experimented with them using large synthetic and real-world pointsets. Our experiments have revealed their practical behavior and real-world efficacy. We share the implementations via GitHub for broader uses and future research. We design and engineer EstimateStretchFactor , a simple practical algorithm, which can estimate stretch-factors (obtains lower bounds on the exact stretch-factors) of geometric spanners—a challenging problem for which no practical algorithm is known yet. In our experiments with bounded-degree plane geometric spanners, we found that EstimateStretchFactor estimated stretch-factors almost precisely. Further, it gave linear runtime performance in practice for the pointset distributions considered in this work, making it much faster than the naive Dijkstra-based algorithm for calculating stretch-factors. 

Scorpions are ancient and historically renowned for their potent venom. Traditionally, the systematics of this group of arthropods was supported by morphological characters, until recent phylogenomic analyses (using RNAseq data) revealed most of the higher‐level taxa to be non‐monophyletic. While these phylogenomic hypotheses are stable for almost all lineages, some nodes have been hard to resolve due to minimal taxonomic sampling (e.g. family Chactidae). In the same line, it has been shown that some nodes in the Arachnid Tree of Life show disagreement between hypotheses generated using transcritptomes and other genomic sources such as the ultraconserved elements (UCEs). Here, we compared the phylogenetic signal of transcriptomes vs. UCEs by retrieving UCEs from new and previously published scorpion transcriptomes and genomes, and reconstructed phylogenies using both datasets independently. We reexamined the monophyly and phylogenetic placement of Chactidae, sampling an additional chactid species using both datasets. Our results showed that both sets of genome‐scale datasets recovered highly similar topologies, with Chactidae rendered paraphyletic owing to the placement of Nullibrotheas allenii. As a first step toward redressing the systematics of Chactidae, we establish the family Anuroctonidae (new family) to accommodate the genus Anuroctonus