FAS Scholarly Articles

Categorization studies, in which stimuli vary along a category continuum, are becoming increasingly popular in psychological science. These studies demonstrate the effect of category ambiguity on various behavioral and neural measures. In such studies, researchers manipulate objective category levels by varying the physical properties of the stimuli, and then use these levels as predictors of behavior—assuming they map directly onto participants’ perceived locations along the category continuum. This approach might not be optimal, considering the variability in participants’ category boundary locations (their point of subjective equality, or PSE). In this tutorial, we propose addressing this issue by estimating participants’ individual points of subjective equality, adjusting category levels relative to these points, and conducting statistical analyses on the subjective category levels. Implementing this method significantly improves the statistical power of the analysis in both experimental and simulated data. Adjusting stimulus levels by the points of subjective equality is highly suited for social categorization studies, in which points of subjective equality vary significantly. On a broader scale, it can be applied to a variety of categorization, discrimination, and decision-making studies.

Settler-colonial theory has become an influential framework in sociology. Yet its central claim—that settler-colonialism is an enduring structure organized by a “logic of elimination”—generates a theoretical paradox. If settler-colonialism is total, how can Indigenous agency be theorized without reproducing the structure it seeks to transcend? I address this tension by bringing sociological theories of structure and agency into dialogue with settler-colonial studies and Indigenous theory. Drawing on William Sewell Jr.’s conception of structure as the coupling of cultural schemas and material resources, I reinterpret two foundational concepts: the logic of elimination and the politics of recognition. Yet Indigenous theorists highlight forms of agency that exceed sociological accounts of action within a shared structural field. I therefore distinguish between interior agency, exercised within settler structures, and exterior agency, which sustains Indigenous worlds beyond them.

Slippery, mucus-coated body surfaces are widespread in aquatic vertebrates, but their contribution to locomotion is unclear. Fish mucus has long been proposed to reduce drag, yet direct experimental evidence of a swimming benefit is limited. A series of four mucus-inspired, lubricant-infused aluminum substrates incorporating SLIPS (slippery liquid-infused porous surfaces) were fabricated to assess the effects of a slippery coating on motion under both static (drag-based) and dynamic (propulsive) conditions. The aluminum substrates were textured by conversion of the surface to nanostructured aluminum oxyhydroxide (boehmite), chemically functionalized, and infused with synthetic Newtonian liquids spanning the viscosity range of measured trout mucus and compared to that of unstructured and lubricant-free controls. Viscosity measurements were also performed on skin mucus collected from brook trout (S. fontinalis). SLIPS-coated surfaces were found to reduce the static drag by up to 9.1% and enhance the lift-to-drag ratio by up to 8.7%. Furthermore, SLIPS coatings improved both the thrust and efficiency of flapping plates actuated in heave and pitch by up to 3.6% and 4.1%, respectively, with performance improvements observed over a broad range of motion parameters, lubricant chemistries, and viscosities. Boundary layer flow measurements over a flat plate revealed that SLIPS experienced a reduced skin friction drag of up to 5.2% under laminar flow conditions. Nanostructured, functionalized, lubricated coatings thus act both to reduce drag and to enhance the propulsive thrust and efficiency of fishlike propulsion, providing one explanation for the presence of such structures on a diversity of animal surfaces.

This contribution explains the function of the term ‘stem’ in Greek morphology. Because the stem is defined in several ways in various morphological theories, a typological presentation of the role of the stem in Greek morphology is attempted here, both synchronically and diachronically. Also, the role of stem allomorphy in the system’s (re)organization is discussed.

The history of medical libraries is closely connected with challenges facing the medical profession at different times. That truism, so general as to be virtually meaningless, can, however, be taken apart and examined in detail. That is what I will do in this essay, with focus on medical libraries in Boston. I will show that medical libraries, like the general libraries of universities, do not automatically develop into oaks from acorns. The creation and survival of medical libraries—plus their precise content--is shaped, by among other factors, the state of medical knowledge and the struggle for status both among different types of physicians and within society, patterns of education, and the desire for unity in a profession characterized in the nineteenth century by different types of practitioners and in the twentieth by increasing specialization. Many of these factors have furthered the development of collections of rare books and medical memorabilia, almost always a consequence of the extraordinary extent--greater than that of other groups—to which physicians have collected rare books.

In recent decades, the United States has experienced substantial changes in population size, composition, and distribution. As growth has slowed, population loss has taken on increased salience, presenting an emerging social, economic, and political challenge and highlighting a need for measures that capture the reality of disparate local population change trajectories. In this paper, we use sequencing and clustering algorithms, paired with contemporary and historical U.S. county-level population data (1950–2020), to show the value of incorporating spatial and temporal context in measures of population change, develop a typology of change trajectories, and evaluate observed pathways of loss and growth. Our analysis identifies 8 distinctive pathways of population change, ranging from emerging localized loss to constant growth. Most pathways are associated with particular geographies (e.g., “persistent loss” counties dominate the landscape of the Great Plains region), illustrating the spatial polarization of the U.S. demographic experience. A comparison of population composition and components of change further reveals notable differences in demographic characteristics across different types of loss and growth counties.

Parallelized DNA synthesis across a dense array of sites is crucial to high-throughput synthetic biology and diagnostics, and could potentially be used for DNA-based data storage. Phosphoramidite synthesis can achieve substantial parallelism, but relies on harmful solvents and centralized facilities. Enzymatic DNA synthesis in mild aqueous solution is safer and could be more accessible, but parallel demonstrations remain modest at an early stage. Here, we show that a complementary metal–oxide–semiconductor (CMOS) chip can be used to perform parallel enzymatic DNA synthesis of up to 64 distinct 38–39-nucleotide sequences (10–11-nucleotide feature sequences). The chip controls an array of 256 ring-electrode pairs (each one a programmable synthesis site) that can create an arbitrary pattern of localized acidity to enable DNA deprotection and subsequent enzymatic nucleotide incorporation. We also illustrate this parallel synthesis for data storage by encoding a 169-byte text. Our mechanistic analysis shows that shifting from an indirect to a direct local-acid chemistry route could lead to higher-throughput enzymatic synthesis that can scale with the CMOS chip.

Design and architectural archives encode expert human knowledge in graphical formats, providing a critical testbed for design-inspired Machine Learning (ML) challenges absent with typical computer vision benchmarks. Building on JONES-19, a small-size image dataset based on The Grammar of Ornament (London, 1857), we evaluate the discriminative performance of Convolutional Neural Networks (CNNs) in two model training strategies: (a) ImageNet pretraining for domain-general “visual common sense,” and (b) learning from scratch on the design data in JONES-19. We find that while domain-general priors improve discriminative performance, learning from scratch augmented with repeated local sampling (multi-crop) effectively recovers these gains. For highly structured design data, local design-driven representations provide sufficient foundation for learning, challenging a reliance on massive general-purpose pretraining. These findings suggest that in specialized design domains, careful curation of smaller high-quality datasets that capture empirical and formal design principles may prove more effective and informative on the nature of a particular design domain than prioritizing large-scale data collection.