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Translanguaging: Uncovering Networks for Unspeakable Significance
No full textThrough case studies of the translanguaging performances of three Latinx bilingual students in U.S. classrooms, as well as an examination of the languaging actions of Hongkongers involved in virtual and public life during a period of social change and protest, the chapter demonstrates how speakers transgress language constraints imposed by institutions and nation-states by expanding or suppressing elements in their repertoire to signify and speak. The chapter shows how speakers' translanguaging creates networks of signification for what had been rendered as indecible/unspeakable by the logic of a colonial, global capitalist society.</p
Performance-limiting metastable intragrain impurity nanoclusters in metal halide perovskites
No full textImpurity control in metal halide perovskite thin films is crucial for advancing the efficiency and long-term stability of perovskite solar cells. While previous efforts have mainly addressed impurities at grain boundaries and heterointerfaces, efforts have rarely been made to reveal and modulate (sub-)nanoscale impurities within grains. In this work, using low-dose scanning transmission electron microscopy, we observed the nontrivial existence of intragrain impurity nanoclusters, identifying a previously unknown, metastable orthorhombic non-perovskite phase with a parallel chain-like structure, in nominally processed Cs-incorporated mixed-cation perovskite films. First-principles calculations and quasi-in situ observations reveal that these intragrain nanoclusters adversely affect the optoelectronic properties and chemical stability of the perovskite. Guided by these insights, we incorporate inner salts during the solution processing, effectively reducing nanocluster density and enhancing device performance. Clarifying unconventional impurities hidden in perovskite crystal grains opens a research avenue in fundamental understanding and nano-engineering for improved perovskite solar cells and optoelectronics.</p
Photochemical transformation of dissolved organic matter: source, particulate matter interaction and disinfection byproduct formation potential
No full textPhotochemical reaction is one of the dominant drivers shaping the molecular identity and ecological fate of dissolved organic matter (DOM). However, the influence of co-occurring particulate matter on these transformation processes and the consequent implications for drinking water safety are not yet fully understood. This study addresses this knowledge gap by coupling high-resolution mass spectrometry and optical analyses to track the evolution of DOM from diverse sources during simulated solar irradiation. The role of particulate matters was further investigated by dosing wastewater with common mineral particles (hematite, montmorillonite and goethite). Results revealed that heteroatom-enriched DOM exhibited high photochemical reactivity, and anthropogenic DOM yielded distinctive molecular products characterized by high O/C and low H/C ratios. Particle addition markedly influenced the photo-induced change of polyphenolics, condensed aromatics and peptide-like molecules, with the extent and direction of change strongly dependent on particle properties. Following irradiation, the total trihalomethane (THM) formation potential increased across all samples, although the trends for individual THM species varied with DOM source. The impact of particles on disinfection byproducts formation potential was particle-specific. Unsaturated compounds rich in oxygen were identified as positive contributor to THM formation and sulfur-containing molecules and SUVA254 were negatively influential indicators. These findings provide new mechanistic insights into DOM photochemistry and its broader environmental implications.</p
Designing a binary sulfide/carbon polyhedron for secondary batteries with high electrochemical and thermal performances
No full textSodium-ion (Na-ion) batteries are attractive for large-scale energy storage owing to the abundance of Na, its ionization energy comparable to Li, and the low Na+/Na redox potential. However, currently available anode materials remain suboptimal, limited by sluggish ion/electron transport and large volume changes during cycling. Here, we report a heterostructured binary sulfide/carbon (Cu7S4/Co9S8/C) polyhedron for a Na-ion battery anode, which exhibits high performance across diverse cycling rates and temperatures. In situ X-ray diffraction and Raman spectroscopy demonstrate reversible structural evolution during cycling. The Cu7S4/Co9S8/C anode achieves a high capacity of 556 mAh g−1 after 300 cycles at 0.5 A g−1 with a coulombic efficiency >99% and maintains 508 mAh g−1 after 1300 cycles at 3.0 A g−1. It also exhibits strong thermal tolerance, retaining 486 mAh g−1 after 500 cycles at 50 °C. Moreover, pairing the Cu7S4/Co9S8/C anode with a NaVPO4 cathode yields excellent full-cell performance, underscoring practical potential. To further evaluate the thermal properties, the 3ω method is employed to quantify the effective thermal conductivity of the composite. The Cu7S4/Co9S8/C architecture delivers a thermal conductivity of 0.30 W m−1 K−1, improving by ∼25% and ∼20% over Cu7S4/C and Co9S8/C, respectively. These findings highlight a generalizable heterostructure design strategy for high-performance anodes and provide guidance for engineering energy-storage materials and safe secondary batteries.</p
Revisiting the Generation Framework in Generative AI-Based Intelligent Structural Design
No full textGenerative AI is reshaping structural design; however, current generative AI-based methods primarily focus on enhancing the AI models employed, overlooking another critical factor that influences outcomes: the generation framework. Existing frameworks fall into two categories: the end-to-end generation framework incorporating generative AI (EGAI), which includes EGAI-GAN and EGAI-DM, and is widely adopted by nearly all current methods; and the two-stage GAI (TGAI), specifically TGAI-DM + PCDM, proposed by generative AIBIM—one of the most representative pipelines. Generative AIBIM demonstrates, from a theoretical standpoint, that TGAI is more effective than EGAI; however, it lacks empirical validation. This paper designs EGAI-DM + PCDM and conducts a comparative analysis with TGAI-DM + PCDM. The experimental results indicate TGAI-DM + PCDM enables AI models to generate design drawings with greater precision and enhanced perceptual quality compared to EGAI-DM + PCDM. These findings substantiate that TGAI is indeed more effective than EGAI. We believe this conclusion will inspire further exploration and broader applications of TGAI
Evidence for the Collective Nature of Radial Flow in Pb + Pb Collisions with the ATLAS Detector
No full textAnisotropic flow and radial flow are two key probes of the expansion dynamics and properties of the quark-gluon plasma (QGP). While anisotropic flow has been extensively studied, radial flow, which governs the system’s radial expansion, has received less attention. Notably, direct experimental evidence for the global and collective nature of radial flow fluctuations has been lacking. This Letter presents the first measurement of transverse momentum (𝑝T) dependence of radial flow fluctuations (𝑣0(𝑝T)) over 0.5 <𝑝T <10 GeV and demonstrates its collective nature using a two-particle correlation method in Pb+Pb collisions at √𝑠NN=5.02 TeV. The data reveal three key features supporting the collective nature of radial flow: long-range correlation in pseudorapidity, factorization in 𝑝T, and centrality-independent shape in 𝑝T. The comparison with a hydrodynamic model demonstrates the sensitivity of 𝑣0(𝑝T) to bulk viscosity, a crucial transport property of the QGP. These findings establish a new, powerful tool for probing collective dynamics and properties of the QGP.<p/
Aerodynamic characteristics and flow field characteristics of rigid and forced-vibration square cylinders in turbulent flow
No full textFluid–structure interaction (FSI) is a fundamental problem in fluid mechanics, which is prevalent across diverse practical engineering applications and has a significant impact on the safety and reliability of structures. In this study, large eddy simulation is employed to perform numerical simulations of a three-dimensional finite-length isolated square cylinder under varying incoming flow velocities and prescribed crosswind vibration states in a turbulent inflow. This configuration, combining finite-length structure, structural vibration, and turbulent flow, is designed to closely mimic realistic wind-resistant conditions encountered in engineering practice. Based on the mean pressure coefficients and flow field phenomenology, the FSI mechanisms are systematically examined in two distinct regimes. Within the vortex-induced vibration (VIV) velocity range, structural vibration markedly modifies the behavior of the separated shear layers, leading to significant changes in the distributions of mean pressure coefficients, wake topology, vortex shedding, and three-dimensional vortex structures compared with the rigid square cylinder. At high wind velocity, however, the influence of structural vibration becomes weak and the FSI response is instead governed predominantly by the incoming flow, and the flow field exhibits characteristics that are different from those in the VIV regime. This study is expected to deepen understanding of how both structural motion and inflow conditions jointly control the global FSI response under this realistic configuration, and to provide a reference for subsequent related studies.</p
GRIA1 regulates TGN export and secretion of Sonic hedgehog
No full textSonic hedgehog (Shh) signaling orchestrates diverse developmental processes in metazoans and is implicated in numerous human diseases. While downstream signaling in recipient cells have been extensively characterized, the mechanisms governing secretion of newly synthesized Shh from producer cells remain less well understood. Building on our previous identification of a Surfeit locus protein 4 (SURF4)-to-proteoglycan (PG) relay mechanism that mediates endoplasmic reticulum (ER)–to–Golgi transport of the N-terminal Shh fragment (ShhN), we investigated ShhN export from the trans-Golgi network (TGN). We show that ShhN exits the TGN via a clathrin-dependent secretory pathway. Mechanistic analyses identify the transmembrane protein glutamate receptor 1 (GRIA1) as a key mediator: GRIA1 associates with ShhN in Golgi-derived vesicles, physically interacts with ShhN, colocalizes with ShhN after TGN exit, and is required for efficient TGN export and secretion of ShhN. Notably, the Cardin–Weintraub (CW) motif on ShhN, previously shown to engage SURF4 for ER–to–Golgi trafficking, is also essential for TGN export, and PGs are critical for the GRIA1–ShhN interaction. Furthermore, GRIA1 regulates intracellular trafficking of endogenous full length Shh and modulates Shh pathway activity in Neuro-2a (N2A) cells. Together, these findings identify GRIA1 as an important regulator of Shh TGN export and advance our understanding of the molecular mechanisms that control Shh secretion.</p
TrialCompass: Visual Analytics for Enhancing the Eligibility Criteria Design of Clinical Trials
No full textEligibility criteria play a critical role in clinical trials by determining the target patient population, which significantly influences the outcomes of medical interventions. However, current approaches for designing eligibility criteria have limitations to support interactive exploration of the large space of eligibility criteria. They also ignore incorporating detailed characteristics from the original electronic health record (EHR) data for criteria refinement. To address these limitations, we proposed TrialCompass, a visual analytics system integrating a novel workflow, which can empower clinicians to iteratively explore the vast space of eligibility criteria through knowledge-driven and outcome-driven approaches. TrialCompass supports history-tracking to help clinicians trace the evolution of their adjustments and decisions when exploring various forms of data (i.e., eligibility criteria, outcome metrics, and detailed characteristics of original EHR data) through these two approaches. This feature can help clinicians comprehend the impact of eligibility criteria on outcome metrics and patient characteristics, which facilitates systematic refinement of eligibility criteria. Using a real-world dataset, we demonstrated the effectiveness of TrialCompass in providing insights into designing eligibility criteria for septic shock and sepsis-associated acute kidney injury. We also discussed the research prospects of applying visual analytics to clinical trials.</p
Transforming jet flavour tagging at ATLAS
No full textJet flavour tagging enables the identification of jets originating from heavy-flavour quarks in proton–proton collisions at the Large Hadron Collider, playing a critical role in its physics programmes. This paper presents GN2, a transformer-based flavour tagging algorithm deployed by the ATLAS Collaboration that represents a different methodology compared to previous approaches. Designed to classify jets based on the flavour of their constituent particles, GN2 processes low-level tracking information in an end-to-end architecture and incorporates physics-informed auxiliary training objectives to enhance both interpretability and performance. Its performance is validated in both simulation and collision data. The measured c-jet (light-jet) rejection in data is improved by a factor of 3.5 (1.8) for a 70% b-jet tagging efficiency, compared to the previous algorithm. GN2 provides substantial benefits for physics analyses involving heavy-flavour jets, such as measurements of Higgs boson pair production and the couplings of bottom and charm quarks to the Higgs boson, and demonstrates the impact of advanced machine learning methods in experimental particle physics.</p