Institute for Advanced Study

The classical filtering and prediction problem is re-examined using the Bode-Shannon representation of random processes and the “state-transition” method of analysis of dynamic systems. New results are: (1) The formulation and methods of solution of the problem apply without modification to stationary and nonstationary statistics and to growing-memory and infinite-memory filters. (2) A nonlinear difference (or differential) equation is derived for the covariance matrix of the optimal estimation error. From the solution of this equation the co-efficients of the difference (or differential) equation of the optimal linear filter are obtained without further calculations. (3) The filtering problem is shown to be the dual of the noise-free regulator problem. The new method developed here is applied to two well-known problems, confirming and extending earlier results. The discussion is largely self-contained and proceeds from first principles; basic concepts of the theory of random processes are reviewed in the Appendix.

BACKGROUND: T cells that have been modified to express a CD19-specific chimeric antigen receptor (CAR) have antitumor activity in B cell malignancies; however, identification of the factors that determine toxicity and efficacy of these T cells has been challenging in prior studies in which phenotypically heterogeneous CAR-T cell products were prepared from unselected T cells. METHODS: We conducted a clinical trial to evaluate CD19 CAR-T cells that were manufactured from defined CD4+ and CD8+ T cell subsets and administered in a defined CD4+:CD8+ composition to adults with B cell acute lymphoblastic leukemia after lymphodepletion chemotherapy. RESULTS: The defined composition product was remarkably potent, as 27 of 29 patients (93%) achieved BM remission, as determined by flow cytometry. We established that high CAR-T cell doses and tumor burden increase the risks of severe cytokine release syndrome and neurotoxicity. Moreover, we identified serum biomarkers that allow testing of early intervention strategies in patients at the highest risk of toxicity. Risk-stratified CAR-T cell dosing based on BM disease burden decreased toxicity. CD8+ T cell-mediated anti-CAR transgene product immune responses developed after CAR-T cell infusion in some patients, limited CAR-T cell persistence, and increased relapse risk. Addition of fludarabine to the lymphodepletion regimen improved CAR-T cell persistence and disease-free survival. CONCLUSION: Immunotherapy with a CAR-T cell product of defined composition enabled identification of factors that correlated with CAR-T cell expansion, persistence, and toxicity and facilitated design of lymphodepletion and CAR-T cell dosing strategies that mitigated toxicity and improved disease-free survival. TRIAL REGISTRATION: ClinicalTrials.gov NCT01865617. FUNDING: R01-CA136551; Life Science Development Fund; Juno Therapeutics; Bezos Family Foundation.

Modern microscopic techniques following the stochastic motion of labelled tracer particles have uncovered significant deviations from the laws of Brownian motion in a variety of animate and inanimate systems. Such anomalous diffusion can have different physical origins, which can be identified from careful data analysis. In particular, single particle tracking provides the entire trajectory of the traced particle, which allows one to evaluate different observables to quantify the dynamics of the system under observation. We here provide an extensive overview over different popular anomalous diffusion models and their properties. We pay special attention to their ergodic properties, highlighting the fact that in several of these models the long time averaged mean squared displacement shows a distinct disparity to the regular, ensemble averaged mean squared displacement. In these cases, data obtained from time averages cannot be interpreted by the standard theoretical results for the ensemble averages. Here we therefore provide a comparison of the main properties of the time averaged mean squared displacement and its statistical behaviour in terms of the scatter of the amplitudes between the time averages obtained from different trajectories. We especially demonstrate how anomalous dynamics may be identified for systems, which, on first sight, appear to be Brownian. Moreover, we discuss the ergodicity breaking parameters for the different anomalous stochastic processes and showcase the physical origins for the various behaviours. This Perspective is intended as a guidebook for both experimentalists and theorists working on systems, which exhibit anomalous diffusion.

The replicability of some scientific findings has recently been called into question. To contribute data about replicability in economics, we replicated 18 studies published in the American Economic Review and the Quarterly Journal of Economics between 2011 and 2014. All of these replications followed predefined analysis plans that were made publicly available beforehand, and they all have a statistical power of at least 90% to detect the original effect size at the 5% significance level. We found a significant effect in the same direction as in the original study for 11 replications (61%); on average, the replicated effect size is 66% of the original. The replicability rate varies between 67% and 78% for four additional replicability indicators, including a prediction market measure of peer beliefs.

Invariant features of temporally varying signals are useful for analysis and classification. Slow feature analysis (SFA) is a new method for learning invariant or slowly varying features from a vectorial input signal. It is based on a nonlinear expansion of the input signal and application of principal component analysis to this expanded signal and its time derivative. It is guaranteed to find the optimal solution within a family of functions directly and can learn to extract a large number of decorrelated features, which are ordered by their degree of invariance. SFA can be applied hierarchically to process high-dimensional input signals and extract complex features. SFA is applied first to complex cell tuning properties based on simple cell output, including disparity and motion. Then more complicated input-output functions are learned by repeated application of SFA. Finally, a hierarchical network of SFA modules is presented as a simple model of the visual system. The same unstructured network can learn translation, size, rotation, contrast, or, to a lesser degree, illumination invariance for one-dimensional objects, depending on only the training stimulus. Surprisingly, only a few training objects suffice to achieve good generalization to new objects. The generated representation is suitable for object recognition. Performance degrades if the network is trained to learn multiple invariances simultaneously.

Levels of genetic differentiation between populations can be highly variable across the genome, with divergent selection contributing to such heterogeneous genomic divergence. For example, loci under divergent selection and those tightly physically linked to them may exhibit stronger differentiation than neutral regions with weak or no linkage to such loci. Divergent selection can also increase genome-wide neutral differentiation by reducing gene flow (e.g. by causing ecological speciation), thus promoting divergence via the stochastic effects of genetic drift. These consequences of divergent selection are being reported in recently accumulating studies that identify: (i) 'outlier loci' with higher levels of divergence than expected under neutrality, and (ii) a positive association between the degree of adaptive phenotypic divergence and levels of molecular genetic differentiation across population pairs ['isolation by adaptation' (IBA)]. The latter pattern arises because as adaptive divergence increases, gene flow is reduced (thereby promoting drift) and genetic hitchhiking increased. Here, we review and integrate these previously disconnected concepts and literatures. We find that studies generally report 5-10% of loci to be outliers. These selected regions were often dispersed across the genome, commonly exhibited replicated divergence across different population pairs, and could sometimes be associated with specific ecological variables. IBA was not infrequently observed, even at neutral loci putatively unlinked to those under divergent selection. Overall, we conclude that divergent selection makes diverse contributions to heterogeneous genomic divergence. Nonetheless, the number, size, and distribution of genomic regions affected by selection varied substantially among studies, leading us to discuss the potential role of divergent selection in the growth of regions of differentiation (i.e. genomic islands of divergence), a topic in need of future investigation.

Determining whether speciation and extinction rates depend on the state of a particular character has been of long-standing interest to evolutionary biologists. To assess the effect of a character on diversification rates using likelihood methods requires that we be able to calculate the probability that a group of extant species would have evolved as observed, given a particular model of the character's effect. Here we describe how to calculate this probability for a phylogenetic tree and a two-state (binary) character under a simple model of evolution (the "BiSSE" model, binary-state speciation and extinction). The model involves six parameters, specifying two speciation rates (rate when the lineage is in state 0; rate when in state 1), two extinction rates (when in state 0; when in state 1), and two rates of character state change (from 0 to 1, and from 1 to 0). Using these probability calculations, we can do maximum likelihood inference to estimate the model's parameters and perform hypothesis tests (e.g., is the rate of speciation elevated for one character state over the other?). We demonstrate the application of the method using simulated data with known parameter values.

Abstract All soils harbor microaggregates, i.e ., compound soil structures smaller than 250 µm. These microaggregates are composed of diverse mineral, organic and biotic materials that are bound together during pedogenesis by various physical, chemical and biological processes. Consequently, microaggregates can withstand strong mechanical and physicochemical stresses and survive slaking in water, allowing them to persist in soils for several decades. Together with the physiochemical heterogeneity of their surfaces, the three‐dimensional structure of microaggregates provides a large variety of ecological niches that contribute to the vast biological diversity found in soils. As reported for larger aggregate units, microaggregates are composed of smaller building units that become more complex with increasing size. In this context, organo‐mineral associations can be considered structural units of soil aggregates and as nanoparticulate fractions of the microaggregates themselves. The mineral phases considered to be the most important as microaggregate forming materials are the clay minerals and Fe‐ and Al‐(hydr)oxides. Within microaggregates, minerals are bound together primarily by physicochemical and chemical interactions involving cementing and gluing agents. The former comprise, among others, carbonates and the short‐range ordered phases of Fe, Mn, and Al. The latter comprise organic materials of diverse origin and probably involve macromolecules and macromolecular mixtures. Work on microaggregate structure and development has largely focused on organic matter stability and turnover. However, little is known concerning the role microaggregates play in the fate of elements like Si, Fe, Al, P, and S. More recently, the role of microaggregates in the formation of microhabitats and the biogeography and diversity of microbial communities has been investigated. Little is known regarding how microaggregates and their properties change in time, which strongly limits our understanding of micro‐scale soil structure dynamics. Similarly, only limited information is available on the mechanical stability of microaggregates, while essentially nothing is known about the flow and transport of fluids and solutes within the micro‐ and nanoporous microaggregate systems. Any quantitative approaches being developed for the modeling of formation, structure and properties of microaggregates are, therefore, in their infancy. We respond to the growing awareness of the importance of microaggregates for the structure, properties and functions of soils by reviewing what is currently known about the formation, composition and turnover of microaggregates. We aim to provide a better understanding of their role in soil function, and to present the major unknowns in current microaggregate research. We propose a harmonized concept for aggregates in soils that explicitly considers the structure and build‐up of microaggregates and the role of organo‐mineral associations. We call for experiments, studies and modeling endeavors that will link information on aggregate forming materials with their functional properties across a range of scales in order to better understand microaggregate formation and turnover. Finally, we hope to inspire a novel cohort of soil scientists that they might focus their research on improving our understanding of the role of microaggregates within the system of aggregates and so help to develop a unified and quantitative concept of aggregation processes in soils.

Deriving the expansion history of the Universe is a major goal of modern cosmology. To date, the most accurate measurements have been obtained with Type Ia Supernovae (SNe) and Baryon Acoustic Oscillations (BAO), providing evidence for the existence of a transition epoch at which the expansion rate changes from decelerated to accelerated. However, these results have been obtained within the framework of specific cosmological models that must be implicitly or explicitly assumed in the measurement. It is therefore crucial to obtain measurements of the accelerated expansion of the Universe independently of assumptions on cosmological models. Here we exploit the unprecedented statistics provided by the Baryon Oscillation Spectroscopic Survey (BOSS, [1-3]) Data Release 9 to provide new constraints on the Hubble parameter H ( z ) using the cosmic chronometers approach. We extract a sample of more than 130000 of the most massive and passively evolving galaxies, obtaining five new cosmology-independent H ( z ) measurements in the redshift range 0.3 < z < 0.5, with an accuracy of ∼11–16% incorporating both statistical and systematic errors. Once combined, these measurements yield a 6% accuracy constraint of H ( z = 0.4293) = 91.8 ± 5.3 km/s/Mpc. The new data are crucial to provide the first cosmology-independent determination of the transition redshift at high statistical significance, measuring z t = 0.4 ± 0.1, and to significantly disfavor the null hypothesis of no transition between decelerated and accelerated expansion at 99.9% confidence level. This analysis highlights the wide potential of the cosmic chronometers approach: it permits to derive constraints on the expansion history of the Universe with results competitive with standard probes, and most importantly, being the estimates independent of the cosmological model, it can constrain cosmologies beyond—and including—the ΛCDM model.

These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion.

Nanographenes, namely polycyclic aromatic hydrocarbons (PAHs) with nanoscale dimensions (>1 nm), are atomically precise cutouts from graphene. They represent prime models to enhance the scope of chemical and physical properties of graphene through structural modulation and functionalization. Defined nitrogen doping in nanographenes is particularly attractive due to its potential for increasing the number of π-electrons, with the possibility of introducing localized antiaromatic ring elements. Herein we present azomethine ylide homocoupling as a strategy to afford internally nitrogen-doped, non-planar PAH in solution and planar nanographene on surfaces, with central pyrazine rings. Localized antiaromaticity of the central ring is indicated by optical absorption spectroscopy in conjunction with theoretical calculations. Our strategy opens up methods for chemically tailoring graphene and nanographenes, modified by antiaromatic dopants.

In this chapter, we trace the historical and intellectual origins of system justification theory, summarise the basic assumptions of the theory, and derive 18 specific hypotheses from a system justification perspective. We review and integrate empirical evidence addressing these hypotheses concerning the rationalisation of the status quo, the internalisation of inequality (outgroup favouritism and depressed entitlement), relations among ego, group, and system justification motives (including consequences for attitudinal ambivalence, self-esteem, and psychological well-being), and the reduction of ideological dissonance. Turning to the question of why people would engage in system justification--especially when it conflicts with other interests and motives--we propose that system-justifying ideologies serve a palliative function in that they reduce anxiety, guilt, dissonance, discomfort, and uncertainty for those who are advantaged and disadvantaged.

The “second method” of Lyapunov is the most general approach currently in the theory of stability of dynamic systems. After a rigorous exposition of the fundamental concepts of this theory, applications are made to (a) stability of linear stationary, linear nonstationary, and nonlinear systems; (b)estimation of transient behavior; (c) control-system optimization; (d) design of relay servos. The discussion is essentially self-contained, with emphasis on the thorough development of the principal ideas and mathematical tools. Only systems governed by differential equations are treated here. Systems governed by difference equations are the subject of a companion paper.

The theory of analytic function of several complex variables, as presented for example in the Cartan seminars First one only studies functions in polycylinders (products of open sets in the different coordinate planes). The extension of the results to more general domains is then achieved by embedding them as submanifolds of polycylinders in spaces of high dimension. The success of this procedure depends of course on the invariance of

It is control that turns scientific knowledge into useful technology: in physics and engineering it provides a systematic way for driving a dynamical system from a given initial state into a desired target state with minimized expenditure of energy and resources. As one of the cornerstones for enabling quantum technologies, optimal quantum control keeps evolving and expanding into areas as diverse as quantum-enhanced sensing, manipulation of single spins, photons, or atoms, optical spectroscopy, photochemistry, magnetic resonance (spectroscopy as well as medical imaging), quantum information processing and quantum simulation. In this communication, state-of-the-art quantum control techniques are reviewed and put into perspective by a consortium of experts in optimal control theory and applications to spectroscopy, imaging, as well as quantum dynamics of closed and open systems. We address key challenges and sketch a roadmap for future developments.

The structure of dendrites and axons plays fundamental roles in synaptic integration and network connectivity. Synergistic advances in neurobiology (e.g., intracellular injections, fluorescent protein expression), microscopy (e.g., multiphoton laser scanning, computer controllers), and imaging

Despite intensive research, hydrogels currently available for tissue repair in the musculoskeletal system are unable to meet the mechanical, as well as the biological, requirements for successful outcomes. Here we reinforce soft hydrogels with highly organized, high-porosity microfibre networks that are 3D-printed with a technique termed as melt electrospinning writing. We show that the stiffness of the gel/scaffold composites increases synergistically (up to 54-fold), compared with hydrogels or microfibre scaffolds alone. Modelling affirms that reinforcement with defined microscale structures is applicable to numerous hydrogels. The stiffness and elasticity of the composites approach that of articular cartilage tissue. Human chondrocytes embedded in the composites are viable, retain their round morphology and are responsive to an in vitro physiological loading regime in terms of gene expression and matrix production. The current approach of reinforcing hydrogels with 3D-printed microfibres offers a fundament for producing tissue constructs with biological and mechanical compatibility. Hydrogels are commonly used materials for tissue engineering, but they can lack the structural properties required for load-bearing and mechanical applications. Here, the authors prepare a polycaprolactone scaffold using melt-electrospinning to reinforce a gelatin methacrylamide hydrogel.

We perform a comprehensive cosmological study of the H 0 tension between the direct local measurement and the model-dependent value inferred from the Cosmic Microwave Background. With the recent measurement of H 0 this tension has raised to more than 3 σ. We consider changes in the early time physics without modifying the late time cosmology. We also reconstruct the late time expansion history in a model independent way with minimal assumptions using distance measurements from Baryon Acoustic Oscillations and Type Ia Supernovae, finding that at z < 0.6 the recovered shape of the expansion history is less than 5% different than that of a standard ΛCDM model. These probes also provide a model insensitive constraint on the low-redshift standard ruler, measuring directly the combination r s h where H 0 = h × 100 Mpc −1 km/s and r s is the sound horizon at radiation drag (the standard ruler), traditionally constrained by CMB observations. Thus r s and H 0 provide absolute scales for distance measurements (anchors) at opposite ends of the observable Universe. We calibrate the cosmic distance ladder and obtain a model-independent determination of the standard ruler for acoustic scale, r s . The tension in H 0 reflects a mismatch between our determination of r s and its standard, CMB-inferred value. Without including high-ℓ Planck CMB polarization data (i.e., only considering the ``recommended baseline" low-ℓ polarisation and temperature and the high ℓ temperature data), a modification of the early-time physics to include a component of dark radiation with an effective number of species around 0.4 would reconcile the CMB-inferred constraints, and the local H 0 and standard ruler determinations. The inclusion of the ``preliminary" high-ℓ Planck CMB polarisation data disfavours this solution.

The application of additive manufacturing (AM) in construction has been increasingly studied in recent years. Large robotic arm- and gantry-systems have been created to print building parts using aggregate-based materials, metals, or polymers. Significant benefits of AM are the automation of the production process, a high degree of design freedom, and the resulting potential for optimization. However, the building components and 3D-printing processes need to be modeled appropriately. In this paper, the current state of AM in construction is reviewed. AM processes and systems as well as their application in research and construction projects are presented. Moreover, digital methods for planning 3D-printed building parts and AM processes are described.