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The spectral analysis of dynamical systems is a staple technique for analyzing a vast range of systems. But beyond its analytical utility, it is also the primary lens through which many physical phenomena are defined and interpreted. The turbulent energy cascade in fluid mechanics, a dynamical consequence of the three-dimensional Navier–Stokes equations in which energy “cascades” from large injection scales to smaller dissipation scales, is a well-known example that is precisely defined only in reciprocal space. Related techniques in the context of networked dynamical systems have been employed with great success in deriving reduced order models. But what such techniques gain in analytical tractability, they often lose in interpretability and locality, as the lower degree of freedom system frequently contains information from all nodes of the network. Here, we demonstrate that a network of nonlinear oscillators exhibits spectral energy transfer facilitated by an effective force akin to the Reynolds stress in turbulence, an example of an emergent higher order interaction. Then, introducing a filter-based decomposition motivated by large eddy simulation, we show that such higher order interactions can be localized to individual nodes and study the effects of local topology on such interactions.

This study presents the first model intercomparison of aerosol‐cloud‐turbulence interactions in a controlled cloudy Rayleigh‐Bénard Convection chamber environment, utilizing the Pi Chamber at Michigan Technological University. We analyzed simulated cloud chamber‐averaged statistics of microphysics and thermodynamics in a warm‐phase, cloudy environment under steady‐state conditions at varying aerosol injection rates. Simulation results from seven distinct models (DNS, LES, and a 1D turbulence model) were compared. Our findings demonstrate that while all models qualitatively capture observed trends in droplet number concentration, mean radius, and droplet size distributions at both high and low aerosol injection rates, significant quantitative differences were observed. Notably, droplet number concentrations varied by over two orders of magnitude between models for the same injection rates, indicating sensitivities to the model treatments in droplet activation and removal and wall fluxes. Furthermore, inconsistencies in vertical relative humidity profiles and in achieving steady‐state liquid water content suggest the need for further investigation into the mechanisms driving these variations. Despite these discrepancies, the models generally reproduced consistent power‐law relationships between the microphysical variables. This model intercomparison underscores the importance of controlled cloud chamber experiments for validating and improving cloud microphysical parameterizations. Recommendations for future modeling studies are also highlighted, including constraining wall conditions and processes, investigating droplet/aerosol removal (including sidewall losses), and conducting simplified experiments to isolate specific processes contributing to model divergence and reduce model uncertainties. Plain Language Summary Understanding how tiny particles (aerosols) interact with clouds and turbulence is essential for improving weather forecasts and climate predictions, as these interactions play a crucial role in determining the properties and evolution of clouds. In this study, we compared different numerical cloud models that simulate these interactions within a controlled laboratory environment, the Pi Chamber at Michigan Technological University. We examined how these models simulated the formation and growth of cloud droplets when aerosols were injected at different rates into the chamber. Our findings show that while all models generally captured the expected trends in cloud droplet size and number concentrations, there were significant quantitative differences. These differences suggest that model results are sensitive to the different model treatments on how droplets are formed and removed, as well as how fluxes from the chamber walls are represented. Despite these differences, the models generally agreed on the overall relationships between aerosol amounts and cloud properties, matching laboratory observations. This study highlights the value of using cloud chamber experiments to test and improve these models. We suggest that to reduce model uncertainties, future research should focus on better defining the conditions at the chamber walls and investigating how particles are removed from the chamber. Key Points This study presents the first model intercomparison to study aerosol‐cloud‐turbulence interactions in a convection‐cloud chamber All models capture the observed microphysical response to varying aerosol injection rates, but large inter‐model discrepancies are present The study underscores the importance of laboratory experiments for validating and improving microphysical representation in cloud models

A large-eddy simulation model is coupled with a Lagrangian cloud model to study marine fog. In this model, aerosols and droplets are treated from a Lagrangian frame of reference, in contrast to the traditional bulk and bin microphysical models. Droplet growth via condensation is governed by Köhler theory and environmental conditions local to the droplet. Coupling to the vapour and temperature fields of the flow ensures mass, momentum, and energy conservation between the air and droplet phases. Based on the recent C-FOG field campaign, a simulation is performed which highlights the benefits and potential of this type of model. By initializing the simulation with the measured aerosol size distribution and making assumptions about the chemical composition of the multiple peaks, the simulations provide a clear explanation for the observed bimodal droplet distribution during C-FOG: high supersaturation levels cause condensational growth of nearly all coarse-mode aerosols (presumed to be composed of marine salt), as well as a large number of accumulation model aerosols (presumed to be of continental origin with a lower hygroscopicity). The largest peak in the resulting droplet distribution is created from coarse-mode aerosols with high hygroscopicity, while the secondary peak is only possible due to the limited impact of the largest peak on saturation levels inside the fog. Thus, for the simulated levels of supersaturation, it is the limited number of coarse-mode aerosols which is responsible for the emergence of a larger second peak.

What is the most robust way to communicate flow trajectories? To answer this question, we employ two neural networks to respectively deconstruct (the encoder) and reconstruct (the decoder) trajectories, where information is passed between the two networks through a low-dimensional latent space in a set-up known as an autoencoder. To ensure that their communications are robust, we add noise to the coded information passed through this latent space. In the low-noise limit the latent space structures are non-spatial in nature, resembling modes of a principle component analysis (PCA). However, as the signal-to-noise ratio is decreased, we uncover Lagrangian coherent structures (LCS) as the most compact representations which still allow the decoder to accurately reconstruct trajectories. This relationship offers increased interpretability to both PCA and LCS analysis, and helps to bridge the gap between two methods of flow analysis.

Large data-driven physics models like DeepMind's weather model GraphCast have empirically succeeded in parameterizing time operators for complex dynamical systems with an accuracy reaching or in some cases exceeding that of traditional physics-based solvers. Unfortunately, how these data-driven models perform computations is largely unknown and whether their internal representations are interpretable or physically consistent is an open question. Here, we adapt tools from interpretability research in Large Language Models to analyze intermediate computational layers in GraphCast, leveraging sparse autoencoders to discover interpretable features in the neuron space of the model. We uncover distinct features on a wide range of length and time scales that correspond to tropical cyclones, atmospheric rivers, diurnal and seasonal behavior, large-scale precipitation patterns, specific geographical coding, and sea-ice extent, among others. We further demonstrate how the precise abstraction of these features can be probed via interventions on the prediction steps of the model. As a case study, we sparsely modify a feature corresponding to tropical cyclones in GraphCast and observe interpretable and physically consistent modifications to evolving hurricanes. Such methods offer a window into the black-box behavior of data-driven physics models and are a step towards realizing their potential as trustworthy predictors and scientifically valuable tools for discovery.

The UN Sustainable Development Goals provide a historic opportunity to implement interventions, at scale, to promote early childhood development. Although the evidence base for the importance of early childhood development has grown, the research is distributed across sectors, populations, and settings, with diversity noted in both scope and focus. We provide a comprehensive updated analysis of early childhood development interventions across the five sectors of health, nutrition, education, child protection, and social protection. Our review concludes that to make interventions successful, smart, and sustainable, they need to be implemented as multi-sectoral intervention packages anchored in nurturing care. The recommendations emphasise that intervention packages should be applied at developmentally appropriate times during the life course, target multiple risks, and build on existing delivery platforms for feasibility of scale-up. While interventions will continue to improve with the growth of developmental science, the evidence now strongly suggests that parents, caregivers, and families need to be supported in providing nurturing care and protection in order for young children to achieve their developmental potential.

LISBON'S ancient Moorish Alfama district is where hanging laundry billows across the narrow labyrinth of cobble serpentine alleys, archways and enchanting little squares. No visitor can help but be dazzled by the profusion of decorative wrought-iron balconies and panels of azulejos, the traditional hand-painted tiles of Portugal. Outside the capital tile-decorated facades are ubiquitous. But, beyond their decorative aspects, azulejos reflect the history of this once-powerful nation. In the early 18th century, in an effort to regain Portuguese control of the market, an artisan named Antonio de Oliveira Bernardes and his son, Policarpo, set up a tile school in Lisbon, creating panels in the baroque style, primarily of Old Testament themes. By 1740 tiles began to be made on an industrial scale, resulting in a rapid deterioration in quality. Then, after the Lisbon earthquake of 1755, which destroyed most of the city and many of the factories, quality, hand-made tiles again became popular. They have remained so ever since. Perhaps the best known of the tilemakers are those of Sant'Anna, which are handmade from start to finish, exactly as they have been since the company was founded in 1741. Their showroom and shop in Lisbon is at 95 Rua do Alecrim, 1200 Lisbon, where beyond a mosaic of sample tiles, there are also handmade and painted ceramic bowls, lavabos, lamps, jars, candlesticks, jardinieres, fountains, chandeliers and figurines. Sant'Anna tiles are available in New York at Country Floors, 15 East 16th Street, New York, N.Y. 10003; 212-627-8300), which, by exclusive contract, buys all tiles exported by the company. The tiles sold in New York (and the store's exclusivity applies only to tiles), are not for sale at Sant'Anna in Lisbon, but there is a wide enough selection of others in Lisbon to suit most tastes and pocketbooks. Individual tiles in Lisbon cost about one-quarter as much as those in New York.

Mediport use as a clinical option for the administration of chimeric antigen receptor T cell (CAR T cell) therapy in patients with B-cell malignancies has yet to be standardized. Concern for mediport dislodgement, cell infiltration, and ineffective therapy delivery to systemic circulation has resulted in variable practice with intravenous administration of CAR T cell therapy. With CAR T cell commercialization, it is important to establish practice standards for CAR T cell delivery. We conducted a study to establish usage patterns of mediports in the clinical setting and provide a standard of care recommendation for mediport use as an acceptable form of access for CAR T cell infusions. In this retrospective cohort study, data on mediport use and infiltration rate was collected from a survey across 34 medical centers in the Pediatric Real-World CAR Consortium, capturing 504 CAR T cell infusion routes across 489 patients. Data represents the largest, and to our knowledge sole, report on clinical CAR T cell infusion practice patterns since FDA approval and CAR T cell commercialization in 2017. Across 34 sites, all reported tunneled central venous catheters, including Broviac and Hickman catheters, as accepted standard venous options for CAR T cell infusion. Use of mediports as a standard clinical practice was reported in 29 of 34 sites (85%). Of 489 evaluable patients with reported route of CAR T cell infusion, 184 patients were infused using mediports, with no reported incidences of CAR T cell infiltration. Based on current clinical practice, mediports are a commonly utilized form of access for CAR T cell therapy administration. These findings support the safe practice of mediport usage as an accepted standard line option for CAR T cell infusion.

Somatosensory perception largely emerges from diverse peripheral sensory neurons whose cell bodies reside in dorsal root ganglia (DRG). Damage or dysfunction of DRG neurons is a major cause of chronic pain and sensory loss. In mice, deep single-cell transcriptomic profiling and genetically defined models have offered important clues into DRG function, but in humans, the cellular and molecular landscape of DRG neurons remains less understood. Here, we constructed a reference cell atlas of the human DRG by profiling transcriptomes of cells and nuclei from 126 donors sampled across cervical, thoracic, and lumbar DRGs. This atlas resolves 22 neuronal subtypes, including known and previously unrecognized subtypes linked to nociception, mechanosensation, thermosensation, and proprioception, as well as 10 types of non-neuronal cells. Cross-species integration, spatial transcriptomics, and microneurography enabled cell-type-specific comparisons of soma size and conduction velocity between species. Human DRG somata are larger across all cell types than their mouse counterparts, and the conduction velocities of human hair follicle innervating A-fibers are faster than in mice, suggesting a functional shift in rapid mechanical detection in humans. This integrated human DRG reference cell atlas provides a resource for exploring new molecular and physiological features of human DRG, which could help identify new strategies for treating chronic pain and other diseases of the peripheral nervous system.

Beyond are the recently added descending tiers of fountains and symmetrical parterres of flowers, not quite successful, but intended as a concession to tourism, according to Jean de Montpellier. ''Tourists love lots of flowers, so we have had to install them,'' he said. During July and August the gardens are illuminated and open at night. The next chateau to visit is Spontin, about a half-hour drive along the Meuse, and then through the surrounding hills and valleys. The countryside here is an amalgam of forests and farmland, planted with wheat, hops and golden-flowered colza, whose seeds produce an ultrafine oil used in such delicate mechanisms as watches. En route, you'll pass through a scarlet poppy-strewn Bruegelian landscape dotted with castle farms, ubiquitous in Belgium. Since there are more cas-tles per square mile in Belgium than anywhere else in Europe, far too many to preserve as national monuments, many ancient keeps and castles are simply used as barns by the farmers who own them. Next day, head west out of Namur beyond [Huy] toward Liege. Just beyond Huy is Aigremont, a two-story rose-brick, early 18th-century chateau, built on a steep cliff overlooking the Meuse. Aigremont is one of only three chateaus out of over 100 in Belgium that is owned and maintained by the Royal Association of Historic Houses. Like the other chateaus visited, Aigremont has its own particular character, in this case a near-perfectly preserved 18th-century interior as well as exterior. The foyer wall surrounding an intricate, monumental staircase was painted in trompe l'oeil style in 1720 and has never been restored. Nor has the 18th-century ceiling rendered in the style of the Italian master Tiepolo. A clock in one of the anterooms has been ticking for several hundred years and has never been repaired. The Delft-style tiles were made in 18th-century Liege. All furnishings, chandeliers, fireplaces and mantles, floors, carpets and boiserie are 18th century. The Count's own artistic contributions are seen in the garden, where he has installed extensive wrought-iron work of his own design, rare trees, fountains, cascades and many of his whimsical bronzes, such as his sleeping Venus reposed in the middle of a pool, usually covered with ducks who find her voluptuous form a perfect place to bask in the sun. A VISITOR'S GUIDE TO CHATEAUS Chateaus Following is a guide to chateaus in the Meuse Valley. The exchange rate used was $1 to 36.1 Belgian francs. The area code is 32. Aigremont. Open from Easter to Oct. 31, every day except Monday, from 10 to 12 and from 2 to 6. It is advisable to call in advance. Admission $1.70, children under 12, 50 cents. Telephone 41.36.16.87. Annevoie. Gardens: March 30 to Nov. 3 every day from 9 to 7. Guided visits from May 1 to Aug. 31, on request in April, September and October. Castle: from Easter to June 30 and Sept. 1 to 30 on weekends and holidays from 9:30 to 1 and from 2 to 6:30. In July and August open daily the same hours. Admission, gardens only, $3.90, castle only $2.50, both $4.70. Admission for children, gardens only, $1.95, castle only $1.25, both $2. 35.82.61.15.55.