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ItemHOW TO KNOW WHEN NOT TO KNOW: Strategic Ignorance When Eliciting for Samoan Migrant Exchanges(Berghan Books, 2000) Gershon, Ilana ItemGenres are the drive belts of the job market(Taylor & Francis, 2022) Gershon, IlanaMany job applicants spend an inordinate amount of time struggling with the task of fashioning the most appealing biography of the increasingly skillful self out of interwoven genres that can also circulate individually. These struggles are most frequently articulated as questions of how best to manage different genres’ chronotopic expectations. Under neoliberalism, how workers are expected to represent their previous work lives has shifted significantly from earlier moments of capitalism: they are now expected to represent themselves as entrepreneurial selves. Over and over again in various workshops about job applicant genres, participants’ concerns over how to represent their employment history via different genres became the focus of the workshop. The focus on mastering a genre’s chronotopic expectations stood in for job applicants’ anxieties over representing themselves as the ideal neoliberal employee. The standardization and abstraction of time and the neoliberal expectations now linked to these genres has led to predictable conceptual quandaries for job applicants about how to connect oneself in appropriate ways to previous contexts that become articulated as dilemmas surrounding the pragmatics of producing genres’ chronotopes. ItemWhen Culture Is Not A System: Why Samoan Cultural Brokers Can Not Do Their Job(Taylor & Francis, 2006) Gershon, IlanaIn independent and American Samoa, Samoan representatives have historically been successful at furthering their communities' interests when dealing with various colonial regimes. Yet during my fieldwork in California, I kept witnessing failed encounters between Samoan migrants and government officials. I argue that government officials helped create these problems through the ways they expected Samoan migrants to act as culture-bearers. I conclude by exploring how cultural mediators become the focal point for tensions generated by the contradictory assumptions government system-carriers and Samoan culture-bearers hold about how to relate to social orders. ItemBullshit Genres: What to Watch for When Studying the New Actant ChatGPT and Its Siblings(Finnish Anthropological Society, 2023) Gershon, IlanaAnother communication technology has been introduced, ChatGPT, drawing the attention of many pundits, occupying valuable space on every op-ed page, and inspiring a Hollywood writers’ strike and endless small talk, all steaming a bit with the intoxicating fumes of moral panic or outsized utopian enthusiasm. Research on artificial intelligence (AI) has existed for decades, entering many people’s daily lives in dribs and drabs. ChatGPT and its siblings, however, have focused so many people’s attention on the potential changes that AI could bring to work lives, entertainment, and social relationships that it seems worthwhile to take a moment now in 2023 to discuss what light linguistic and media anthropologists can shed on what is to come. I say this as one of a handful of media anthropologists also familiar with linguistic anthropology who happened to study people’s use of Facebook (alongside other media) only a few years after its introduction to the US media ecology (Gershon 2010). For more than a decade, I have been thinking about how media ecologies change with each newly introduced medium. Here, I lay out what I believe ethnographers of AI who engage with large language models (LLMs) might want to pay attention to in the next couple of years. My starting point is that it would be helpful to explore how people are responding to ChatGPT in terms of genre, that people’s reactions to ChatGPT is to treat it at its core as though it is a genre machine—that is, a machine intelligence that reproduces and tweaks genres in just the right way for human consumption. ItemPlague jobs: US workers' schismogenetic approaches to social contracts(Slovene Anthropological Society, 2021) Gershon, IlanaIn this homage to David Graeber, I turn to Americans’ experiences working in person during the pandemic as an ethnographic lens for understanding how workers respond when implicit social contracts are violated and when ideas about the common good are being contested. Because the United States federal government and many state governments refused to mandate appropriate pandemic protocols, businesses became the source of pandemic regulation in the United States. During the pandemic, Americans have been made vividly aware of the tacit social contracts shaping their workplace commitments. Building upon Graeber’s insight that at the heart of work is a complex theory of contract and exchange, I explore how contractual sociality shapes Americans’ understandings of the political possibilities available to them at work. I focus in particular on the icon of the Trumpian Republican and how other Americans are responding by turning to historically grounded visions of the common good. In general, this article explores what the pandemic has revealed about Americans’ political imagination, about how to govern and be governed in the workplace, with a Graeberian focus on the role that contractual sociality plays in structuring this imagination. ItemLiving with Monsters: Ethnographic Fiction about Real Monsters(Punctum Books, 2023) Musharbash, Yasmine; Gershon, Ilana ItemImagining Iberia in English and Castilian Medieval Romance(2023) Houlik-Ritchey, Emily; University of Michigan Press ItemAssociations between teamwork and implementation outcomes in multidisciplinary cross-sector teams implementing a mental health screening and referral protocol(Springer Nature, 2023) McGuier, Elizabeth A.; Aarons, Gregory A.; Byrne, Kara A.; Campbell, Kristine A.; Keeshin, Brooks; Rothenberger, Scott D.; Weingart, Laurie R.; Salas, Eduardo; Kolko, David J.Teams play a central role in the implementation of new practices in settings providing team-based care. However, the implementation science literature has paid little attention to potentially important team-level constructs. Aspects of teamwork, including team interdependence, team functioning, and team performance, may affect implementation processes and outcomes. This cross-sectional study tests associations between teamwork and implementation antecedents and outcomes in a statewide initiative to implement a standardized mental health screening/referral protocol in Child Advocacy Centers (CACs). ItemAtomically precise nanoclusters predominantly seed gold nanoparticle syntheses(Springer Nature, 2023) Qiao, Liang; Pollard, Nia; Senanayake, Ravithree D.; Yang, Zhi; Kim, Minjung; Ali, Arzeena S.; Hoang, Minh Tam; Yao, Nan; Han, Yimo; Hernandez, Rigoberto; Clayborne, Andre Z.; Jones, Matthew R.Seed-mediated synthesis strategies, in which small gold nanoparticle precursors are added to a growth solution to initiate heterogeneous nucleation, are among the most prevalent, simple, and productive methodologies for generating well-defined colloidal anisotropic nanostructures. However, the size, structure, and chemical properties of the seeds remain poorly understood, which partially explains the lack of mechanistic understanding of many particle growth reactions. Here, we identify the majority component in the seed solution as an atomically precise gold nanocluster, consisting of a 32-atom Au core with 8 halide ligands and 12 neutral ligands constituting a bound ion pair between a halide and the cationic surfactant: Au32X8[AQA+•X-]12 (X = Cl, Br; AQA = alkyl quaternary ammonium). Ligand exchange is dynamic and versatile, occurring on the order of minutes and allowing for the formation of 48 distinct Au32 clusters with AQAX (alkyl quaternary ammonium halide) ligands. Anisotropic nanoparticle syntheses seeded with solutions enriched in Au32X8[AQA+•X-]12 show narrower size distributions and fewer impurity particle shapes, indicating the importance of this cluster as a precursor to the growth of well-defined nanostructures. ItemCoupled topological flat and wide bands: Quasiparticle formation and destruction(AAAS, 2023) Hu, Haoyu; Si, QimiaoFlat bands amplify correlation effects and are of extensive current interest. They provide a platform to explore both topology in correlated settings and correlation physics enriched by topology. Recent experiments in correlated kagome metals have found evidence for strange-metal behavior. A major theoretical challenge is to study the effect of local Coulomb repulsion when the band topology obstructs a real-space description. In a variant to the kagome lattice, we identify an orbital-selective Mott transition in any system of coupled topological flat and wide bands. This was made possible by the construction of exponentially localized and Kramers-doublet Wannier functions, which, in turn, leads to an effective Kondo-lattice description. Our findings show how quasiparticles are formed in such coupled topological flat-wide band systems and, equally important, how they are destroyed. Our work provides a conceptual framework for the understanding of the existing and emerging strange-metal properties in kagome metals and beyond. ItemA deep learning solution for crystallographic structure determination(International Union of Crystallography, 2023) Pan, T.; Jin, S.; Miller, M. D.; Kyrillidis, A.; Phillips, G. N.The general de novo solution of the crystallographic phase problem is difficult and only possible under certain conditions. This paper develops an initial pathway to a deep learning neural network approach for the phase problem in protein crystallography, based on a synthetic dataset of small fragments derived from a large well curated subset of solved structures in the Protein Data Bank (PDB). In particular, electron-density estimates of simple artificial systems are produced directly from corresponding Patterson maps using a convolutional neural network architecture as a proof of concept. ItemPME: pruning-based multi-size embedding for recommender systems(Frontiers Media S.A., 2023) Liu, Zirui; Song, Qingquan; Li, Li; Choi, Soo-Hyun; Chen, Rui; Hu, XiaEmbedding is widely used in recommendation models to learn feature representations. However, the traditional embedding technique that assigns a fixed size to all categorical features may be suboptimal due to the following reasons. In recommendation domain, the majority of categorical features' embeddings can be trained with less capacity without impacting model performance, thereby storing embeddings with equal length may incur unnecessary memory usage. Existing work that tries to allocate customized sizes for each feature usually either simply scales the embedding size with feature's popularity or formulates this size allocation problem as an architecture selection problem. Unfortunately, most of these methods either have large performance drop or incur significant extra time cost for searching proper embedding sizes. In this article, instead of formulating the size allocation problem as an architecture selection problem, we approach the problem from a pruning perspective and propose Pruning-based Multi-size Embedding (PME) framework. During the search phase, we prune the dimensions that have the least impact on model performance in the embedding to reduce its capacity. Then, we show that the customized size of each token can be obtained by transferring the capacity of its pruned embedding with significant less search cost. Experimental results validate that PME can efficiently find proper sizes and hence achieve strong performance while significantly reducing the number of parameters in the embedding layer. ItemHandoffs and the challenges to implementing teamwork training in the perioperative environment(Frontiers Media S.A., 2023) Paquette, Shannon; Kilcullen, Molly; Hoffman, Olivia; Hernandez, Jessica; Mehta, Ankeeta; Salas, Eduardo; Greilich, Philip E.Perioperative handoffs are high-risk events for miscommunications and poor care coordination, which cause patient harm. Extensive research and several interventions have sought to overcome the challenges to perioperative handoff quality and safety, but few efforts have focused on teamwork training. Evidence shows that team training decreases surgical morbidity and mortality, and there remains a significant opportunity to implement teamwork training in the perioperative environment. Current perioperative handoff interventions face significant difficulty with adherence which raises concerns about the sustainability of their impact. In this perspective article, we explain why teamwork is critical to safe and reliable perioperative handoffs and discuss implementation challenges to the five core components of teamwork training programs in the perioperative environment. We outline evidence-based best practices imperative for training success and acknowledge the obstacles to implementing those best practices. Explicitly identifying and discussing these obstacles is critical to designing and implementing teamwork training programs fit for the perioperative environment. Teamwork training will equip providers with the foundational teamwork competencies needed to effectively participate in handoffs and utilize handoff interventions. This will improve team effectiveness, adherence to current perioperative handoff interventions, and ultimately, patient safety. ItemEnGens: a computational framework for generation and analysis of representative protein conformational ensembles(Oxford University Press, 2023) Conev, Anja; Rigo, Mauricio Menegatti; Devaurs, Didier; Fonseca, André Faustino; Kalavadwala, Hussain; de Freitas, Martiela Vaz; Clementi, Cecilia; Zanatta, Geancarlo; Antunes, Dinler Amaral; Kavraki, Lydia EProteins are dynamic macromolecules that perform vital functions in cells. A protein structure determines its function, but this structure is not static, as proteins change their conformation to achieve various functions. Understanding the conformational landscapes of proteins is essential to understand their mechanism of action. Sets of carefully chosen conformations can summarize such complex landscapes and provide better insights into protein function than single conformations. We refer to these sets as representative conformational ensembles. Recent advances in computational methods have led to an increase in the number of available structural datasets spanning conformational landscapes. However, extracting representative conformational ensembles from such datasets is not an easy task and many methods have been developed to tackle it. Our new approach, EnGens (short for ensemble generation), collects these methods into a unified framework for generating and analyzing representative protein conformational ensembles. In this work, we: (1) provide an overview of existing methods and tools for representative protein structural ensemble generation and analysis; (2) unify existing approaches in an open-source Python package, and a portable Docker image, providing interactive visualizations within a Jupyter Notebook pipeline; (3) test our pipeline on a few canonical examples from the literature. Representative ensembles produced by EnGens can be used for many downstream tasks such as protein–ligand ensemble docking, Markov state modeling of protein dynamics and analysis of the effect of single-point mutations. ItemFabrication of a multifaceted mapping mirror using two-photon polymerization for a snapshot image mapping spectrometer(Optica Publishing Group, 2023) Lu, Jiawei; Ng, Xue Wen; Piston, David; Tkaczyk, Tomasz S.A design and fabrication technique for making high-precision and large-format multifaceted mapping mirrors is presented. The method is based on two-photon polymerization, which allows more flexibility in the mapping mirror design. The mirror fabricated in this paper consists of 36 2D tilted square pixels, instead of the continuous facet design used in diamond cutting. The paper presents a detailed discussion of the fabrication parameters and optimization process, with particular emphasis on the optimization of stitching defects by compensating for the overall tilt angle and reducing the printing field of view. The fabricated mirrors were coated with a thin layer of aluminum (93 nm) using sputter coating to enhance the reflection rate over the target wave range. The mapping mirror was characterized using a white light interferometer and a scanning electron microscope, which demonstrates its optical quality surface (with a surface roughness of 12 nm) and high-precision tilt angles (with an average of 2.03% deviation). Finally, the incorporation of one of the 3D printed mapping mirrors into an image mapping spectrometer prototype allowed for the acquisition of high-quality images of the USAF resolution target and bovine pulmonary artery endothelial cells stained with three fluorescent dyes, demonstrating the potential of this technology for practical applications. ItemProbing Heavy Majorana Neutrinos and the Weinberg Operator through Vector Boson Fusion Processes in Proton-Proton Collisions at √s=13 TeV(American Physical Society, 2023) CMS CollaborationThe first search exploiting the vector boson fusion process to probe heavy Majorana neutrinos and the Weinberg operator at the LHC is presented. The search is performed in the same-sign dimuon final state using a proton-proton collision dataset recorded at √s=13 TeV, collected with the CMS detector and corresponding to a total integrated luminosity of 138 fb−1. The results are found to agree with the predictions of the standard model. For heavy Majorana neutrinos, constraints on the squared mixing element between the muon and the heavy neutrino are derived in the heavy neutrino mass range 50 GeV–25 TeV; for masses above 650 GeV these are the most stringent constraints from searches at the LHC to date. A first test of the Weinberg operator at colliders provides an observed upper limit at 95% confidence level on the effective μμ Majorana neutrino mass of 10.8 GeV. ItemLeveraging mesh modularization to lower the computational cost of localized updates to regional 2D hydrodynamic model outputs(Taylor & Francis, 2023) Garcia, M.; Juan, A.; Doss-Gollin, J.; Bedient, P.Hydrodynamic model outputs are used in urban flood risk modelling, flood alert systems, and Monte Carlo hazard assessment. This study tackles an under-explored challenge wherein regular updates to the spatial characteristics of the watershed – due to factors such as changing land use – alter the watershed’s response to rainfall forcing, thus rendering existing model outputs obsolete. Because state-of-the-art hydrodynamic models are computationally expensive, frequently re-running simulations can be costly. Modularization addresses this problem by requiring re-computation only for a limited domain affected by the land use changes. This article introduces a novel approach by modularizing the 2D domain into independent sub-domains before (‘discrete’) and after (‘abstract’) the numerical computations. Using the Hydrologic Engineering Center River Analysis System (HEC-RAS) 2D model of a large urban watershed in Houston as an illustrative and generalizable testbed, we show that both the discrete and abstract modularization closely approximates the results from re-running the entire model. The computational cost of modularization scales linearly with model size for memory requirements as storing the solution on the interior boundaries (discrete) or throughout the domain (abstract) are necessary. This trade-off of memory for computation may facilitate advances in surrogate modelling or Monte Carlo flood risk assessment. ItemSearching for Heavy Dark Matter near the Planck Mass with XENON1T(American Physical Society, 2023) XENON CollaborationMultiple viable theoretical models predict heavy dark matter particles with a mass close to the Planck mass, a range relatively unexplored by current experimental measurements. We use 219.4 days of data collected with the XENON1T experiment to conduct a blind search for signals from multiply interacting massive particles (MIMPs). Their unique track signature allows a targeted analysis with only 0.05 expected background events from muons. Following unblinding, we observe no signal candidate events. This Letter places strong constraints on spin-independent interactions of dark matter particles with a mass between 1×1012 and 2×1017 GeV/c2. In addition, we present the first exclusion limits on spin-dependent MIMP-neutron and MIMP-proton cross sections for dark matter particles with masses close to the Planck scale. ItemNature and Origin of Magnetic Lineations Within Valdivia Bank: Ocean Plateau Formation by Complex Seafloor Spreading(Wiley, 2023) Thoram, S.; Sager, W. W.; Gaastra, K.; Tikoo, S. M.; Carvallo, C.; Avery, A.; Del Gaudio, Arianna V.; Huang, Y.; Hoernle, K.; Höfig, T. W.; Bhutani, R.; Buchs, D. M.; Class, C.; Dai, Y.; Valle, G. Dalla; Fielding, S.; Han, S.; Heaton, D. E.; Homrighausen, S.; Kubota, Y.; Li, C.-F.; Nelson, W. R.; Petrou, E.; Potter, K. E.; Pujatti, S.; Scholpp, J.; Shervais, J. W.; Tshiningayamwe, M.; Wang, X. J.; Widdowson, M.Valdivia Bank (VB) is a Late Cretaceous oceanic plateau formed by volcanism from the Tristan-Gough hotspot at the Mid-Atlantic Ridge (MAR). To better understand its origin and evolution, magnetic data were used to generate a magnetic anomaly grid, which was inverted to determine crustal magnetization. The magnetization model reveals quasi-linear polarity zones crossing the plateau and following expected MAR paleo-locations, implying formation by seafloor spreading over ∼4 Myr during the formation of anomalies C34n-C33r. Paleomagnetism and biostratigraphy data from International Ocean Discovery Program Expedition 391 confirm the magnetic interpretation. Anomaly C33r is split into two negative bands, likely by a westward ridge jump. One of these negative anomalies coincides with deep rift valleys, indicating their age and mechanism of formation. These findings imply that VB originated by seafloor spreading-type volcanism during a plate reorganization, not from a vertical stack of lava flows as expected for a large volcano.