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For short-wavelength infrared (SWIR) avalanche photodiodes, a separate absorption, charge, and multiplication design is widely used. AlInAsSb on an InP substrate is a potential multiplication layer with a lattice match to absorber candidates across the SWIR. Our new measurements demonstrate that AlInAsSb on InP is a promising multiplier candidate with a relatively low dark current density of 10−4 A/cm2 at a gain of 30; a high gain, measured up to 245 in this study; and a large differentiation of electron and hole ionization leading to a low excess noise, measured to be 2.5 at a gain of 30. These characteristics are all improvements over commercially available SWIR detectors incorporating InAlAs or InP as the multiplier. We measured and analyzed gain for multiple wavelengths to extract the ionization coefficients as a function of an electric field over the range 0.33–0.6 MV/cm. 

Dynamically transitioning between individual and collaborative learning has been hypothesized to have positive effects, such as providing the optimal learning mode based on students’ needs. There are, however, challenges in orchestrating these transitions in real-time while managing a classroom of students. AI-based orchestration tools have the potential to alleviate some of the orchestration load for teachers. In this study, we describe a sequence of three design sessions with teachers where we refine prototypes of an orchestration tool to support dynamic transitions. We leverage design narratives and conjecture mapping for the design of our novel orchestration tool. Our contributions include the orchestration tool itself; a description of how novel tool features were revised throughout the sessions with teachers, including shared control between teachers, students, and AI and the use of AI to support dynamic transitions, and a reflection of the changes to our design and theoretical conjectures. 

Among extant vertebrates, mammals are distinguished by having a chain of three auditory ossicles (the malleus, incus and stapes) that transduce sound waves and promote an increased range of audible—especially high—frequencies. By contrast, the homologous bones in early fossil mammals and relatives also functioned in chewing through their bony attachments to the lower jaw. Recent discoveries of well-preserved Mesozoic mammals have provided glimpses into the transition from the dual (masticatory and auditory) to the single auditory function for the ossicles, which is now widely accepted to have occurred at least three times in mammal evolution. Here we report a skull and postcranium that we refer to the haramiyidan Vilevolodon diplomylos (dating to the Middle Jurassic epoch (160 million years ago)) and that shows excellent preservation of the malleus, incus and ectotympanic (which supports the tympanic membrane). After comparing this fossil with other Mesozoic and extant mammals, we propose that the overlapping incudomallear articulation found in this and other Mesozoic fossils, in extant monotremes and in early ontogeny in extant marsupials and placentals is a morphology that evolved in several groups of mammals in the transition from the dual to the single function for the ossicles. 

Orchestration tools may support K-12 teachers in facilitating student learning, especially when designed to address classroom stakeholders’ needs. Our previous work revealed a need for human-AI shared control when dynamically pairing students for collaborative learning in the classroom, but offered limited guidance on the role each agent should take. In this study, we designed storyboards for scenarios where teachers, students and AI co-orchestrate dynamic pairing when using AI-based adaptive math software for individual and collaborative learning. We surveyed 54 math teachers on their co-orchestration preferences. We found that teachers would like to share control with the AI to lessen their orchestration load. As well, they would like to have the AI propose student pairs with explanations, and identify risky proposed pairings. However, teachers are hesitant to let the AI auto-pair students even if they are busy, and are less inclined to let AI override teacher-proposed pairing. Our study contributes to teachers’ needs, preference, and boundaries for how they want to share the task and control of student pairing with the AI and students, and design implications in human-AI co-orchestration tools. 

Abstract Measuring observables to constrain models using maximum-likelihood estimation is fundamental to many physics experiments. Wilks' theorem provides a simple way to construct confidence intervals on model parameters, but it only applies under certain conditions. These conditions, such as nested hypotheses and unbounded parameters, are often violated in neutrino oscillation measurements and other experimental scenarios. Monte Carlo methods can address these issues, albeit at increased computational cost. In the presence of nuisance parameters, however, the best way to implement a Monte Carlo method is ambiguous. This paper documents the method selected by the NOvA experiment, the profile construction. It presents the toy studies that informed the choice of method, details of its implementation, and tests performed to validate it. It also includes some practical considerations which may be of use to others choosing to use the profile construction. 

A first search for beyond the standard model physics in jet multiplicity patterns of multilepton events is presented, using a data sample corresponding to an integrated luminosity of $138{\mathrm{fb}}^{-1}$of 13 TeV proton-proton collisions recorded by the CMS detector at the LHC. The search uses observed jet multiplicity distributions in one-, two-, and four-lepton events to explore possible enhancements in jet production rate in three-lepton events with and without bottom quarks. The data are found to be consistent with the standard model expectation. The results are interpreted in terms of supersymmetric production of electroweak chargino-neutralino superpartners with cascade decays terminating in prompt hadronic $R$-parity violating interactions. 

A search for the rare decay $D^0\to {\mu }^{+}{\mu }^{-}$is reported using proton-proton collision events at $\sqrt{s}=13.6\mathrm{TeV}$collected by the CMS detector in 2022–2023, corresponding to an integrated luminosity of $64.5{\mathrm{fb}}^{-1}$. This is the first analysis to use a newly developed inclusive dimuon trigger, expanding the scope of the CMS flavor physics program. The search uses $D^0$mesons obtained from $D^{*+}\to D^0{\pi }^{+}$decays. No significant excess is observed. A limit on the branching fraction of $\mathcal{B}(D^0\to {\mu }^{+}{\mu }^{-})<2.4\times {10}^{-9}$at 95% confidence level is set. This is the most stringent upper limit set on any flavor changing neutral current decay in the charm sector. 

A<sc>bstract</sc> A search for a heavy pseudoscalar Higgs boson, A, decaying to a 125 GeV Higgs boson h and a Z boson is presented. The h boson is identified via its decay to a pair of tau leptons, while the Z boson is identified via its decay to a pair of electrons or muons. The search targets the production of the A boson via the gluon-gluon fusion process, gg → A, and in association with bottom quarks,$$\text{b}\overline{\text{b}}\text{A }$$. The analysis uses a data sample corresponding to an integrated luminosity of 138 fb⁻¹collected with the CMS detector at the CERN LHC in proton-proton collisions at a centre-of-mass energy of$$\sqrt{s}=13$$TeV. Constraints are set on the product of the cross sections of the A production mechanisms and the A → Zh decay branching fraction. The observed (expected) upper limit at 95% confidence level ranges from 0.049 (0.060) pb to 1.02 (0.79) pb for the gg → A process and from 0.053 (0.059) pb to 0.79 (0.61) pb for the$$\text{b}\overline{\text{b}}\text{A }$$process in the probed range of the A boson mass,m_A, from 225 GeV to 1 TeV. The results of the search are used to constrain parameters within the$${\text{M}}_{\text{h},\text{EFT}}^{125}$$benchmark scenario of the minimal supersymmetric extension of the standard model. Values of tanβbelow 2.2 are excluded in this scenario at 95% confidence level for allm_Avalues in the range from 225 to 350 GeV.