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Historically, physics education primarily consisted of lectures in which students have a largely passive role. Proponents of educational reform have rallied around active learning to increase engagement and retention in STEM fields, particularly advocating peer interactions to build a foundation of deep understanding. However, little is known about how students' prior preparation for introductory courses impacts their mastery of course material when instructors incorporate active learning. In the present study, we examine learning outcomes in two sections of an introductory mechanics course at an institution with a wide range of students' prior mathematics preparation as assessed by quantitative SAT scores. For each of three years, one section was taught using peer instruction in which much of the class time was spent in small-group discussions between students. The other section was taught by the same instructor using interactive lectures in which discussions primarily took place between volunteers from the class and the instructor. We find that students enrolled in the peer instruction sections earned lower grades in the course than did students in the interactive sections. We also find students in the peer instruction sections with lower quantitative SAT scores showed lower gains in understanding foundational concepts as assessed by the Force Concept Inventory and were less likely to earn an A in the course than comparable students in the interactive sections. While further research is needed to confirm these results, this study suggests that peer instruction might not be the optimal pedagogy for heterogeneous populations. 

The expression of a few key genes determines the body plan of the fruit fly. We show that the spatial expression patterns for several of these genes scale precisely with embryo size. Discrete positional markers such as the peaks in striped patterns or the boundaries of expression domains have positions along the embryo’s major axis proportional to embryo length, accurate to within 1%. Further, the information (in bits) that graded patterns of expression provide about a cell’s position can be decomposed into information about fractional or scaled position and information about absolute position or embryo length; all information available is about scaled position, with $<$2% error. These findings imply that the underlying genetic network’s behavior exhibits scale invariance in a more precise mathematical sense. We argue that models that can explain this scale invariance also have a “zero mode” in the dynamics of gene expression, and this connects to observations on the spatial correlation of fluctuations in expression levels. 

It has been argued that the historical nature of evolution makes it a highly path-dependent process. Under this view, the outcome of evolutionary dynamics could have resulted in organisms with different forms and functions. At the same time, there is ample evidence that convergence and constraints strongly limit the domain of the potential design principles that evolution can achieve. Are these limitations relevant in shaping the fabric of the possible? Here, we argue that fundamental constraints are associated with the logic of living matter. We illustrate this idea by considering the thermodynamic properties of living systems, the linear nature of molecular information, the cellular nature of the building blocks of life, multicellularity and development, the threshold nature of computations in cognitive systems and the discrete nature of the architecture of ecosystems. In all these examples, we present available evidence and suggest potential avenues towards a well-defined theoretical formulation. 

Developing a mathematical understanding of autocatalysis in reaction networks has both theoretical and practical implications. We review definitions of autocatalytic networks and prove some properties for minimal autocatalytic subnetworks (MASs). We show that it is possible to classify MASs in equivalence classes, and develop mathematical results about their behavior. We also provide linear-programming algorithms to exhaustively enumerate them and a scheme to visualize their polyhedral geometry and combinatorics. We then define cluster chemical reaction networks, a framework for coarse-graining real chemical reactions with positive integer conservation laws. We find that the size of the list of minimal autocatalytic subnetworks in a maximally connected cluster chemical reaction network with one conservation law grows exponentially in the number of species. We end our discussion with open questions concerning an ecosystem of autocatalytic subnetworks and multidisciplinary opportunities for future investigation. 

Summary The cohesin complex is critical for genome regulation, relying on specialized co-factors to mediate its diverse functional activities. Here, by analyzing patterns of similar gene requirements across cell lines, we identify PRR12 as a regulator of cohesin and genome integrity. We show that PRR12 interacts with cohesin and PRR12 loss results in a reduction of nuclear-localized cohesin and an accumulation of DNA lesions. We find that different cell lines across human and mouse exhibit significant variation in their sensitivity to PRR12 loss. Unlike the modest phenotypes observed in human cell lines, PRR12 depletion in mouse cells results in substantial genome instability. Despite a modest requirement in human cell lines, mutations in PRR12 lead to severe developmental defects in human patients, suggesting context-specific roles in cohesin regulation. By harnessing comparative studies across species and cell lines, our work reveals critical insights into how cohesin is regulated across diverse cellular contexts. 

Prior research on evolutionary mechanisms during the origin of life has mainly assumed the existence of populations of discrete entities with information encoded in genetic polymers. Recent theoretical advances in autocatalytic chemical ecology establish a broader evolutionary framework that allows for adaptive complexification prior to the emergence of bounded individuals or genetic encoding. This framework establishes the formal equivalence of cells, ecosystems and certain localized chemical reaction systems as autocatalytic chemical ecosystems (ACEs): food-driven (open) systems that can grow due to the action of autocatalytic cycles (ACs). When ACEs are organized in meta-ecosystems, whether they be populations of cells or sets of chemically similar environmental patches, evolution, defined as change in AC frequency over time, can occur. In cases where ACs are enriched because they enhance ACE persistence or dispersal ability, evolution is adaptive and can build complexity. In particular, adaptive evolution can explain the emergence of self-bounded units (e.g. protocells) and genetic inheritance mechanisms. Recognizing the continuity between ecological and evolutionary change through the lens of autocatalytic chemical ecology suggests that the origin of life should be seen as a general and predictable outcome of driven chemical ecosystems rather than a phenomenon requiring specific, rare conditions. 

Abstract Evidence of fluctuations in transport have long been predicted in³He. They are expected to contribute only within 100μK ofT_cand play a vital role in the theoretical modeling of ordering; they encode details about the Fermi liquid parameters, pairing symmetry, and scattering phase shifts. It is expected that they will be of crucial importance for transport probes of the topologically nontrivial features of superfluid³He under strong confinement. Here we characterize the temperature and pressure dependence of the fluctuation signature, by monitoring the quality factor of a quartz tuning fork oscillator. We have observed a fluctuation-driven reduction in the viscosity of bulk³He, finding data collapse consistent with the predicted theoretical behavior. 

We provide the conversion parameters to allow a $^3$$He melting curve thermometer to be used to calibrate secondary thermometers to the PLTS2000 temperature scale \cite{rusby2007realization}. Additional fits to the phase diagram of superfluid $$^3$He are also provided using the melting curve $P,T$ measurements and of the phase diagram of superfluid $^3$He as a bridge. Further the melting curve measurements of Osheroff and Yu are also used to extend the scale below 0.9 mK.