Harvesting entropy and quantifying the transition from noise to chaos in a photon-counting feedback loop

Many physical processes, including the intensity fluctuations of a chaotic laser, the detection of single photons, and the Brownian motion of a microscopic particle in a fluid are unpredictable, at least on long timescales. This unpredictability can be due to a variety of physical mechanisms, but it is quantified by an entropy rate. This rate, which describes how quickly a system produces new and random information, is fundamentally important in statistical mechanics and practically important for random number generation. We experimentally study entropy generation and the emergence of deterministic chaotic dynamics from discrete noise in a system that applies feedback to a weak optical signal at the single-photon level. We show that the dynamics transition from shot noise to chaos as the photon rate increases and that the entropy rate can reflect either the deterministic or noisy aspects of the system depending on the sampling rate and resolution.Continuous variables and dynamical equations are often used to model systems whose time evolution is composed of discrete events occurring at random times. Examples include the flow of ions across cell membranes (1), the dynamics of large populations of neurons (2), the birth and death of individuals in a population (3), traffic flow on roads (4), the trading of securities in financial markets (5, 6), infection and transmission of disease (7), and the emission and detection of photons (8). We can identify two sources of unpredictability in these systems: the noise associated with the underlying random occurrences that comprise these signals, which are often described by a Poisson process, and the macroscopic dynamics of the system, which may be chaotic. When both effects are present, the macroscopic dynamics can alter the statistics of the noise, and the small-scale noise can in turn feed the large-scale dynamics. This can lead to subtle and nontrivial effects including stochastic resonance and coherence resonance (9, 10). Dynamical unpredictability and complexity are quantified by Lyapunov exponents and dimensionality, whereas shot noise is characterized by statistical metrics like average rate, variance, and signal-to-noise ratio. Characterizing the unpredictability of a system with both large-scale dynamics and small-scale shot noise remains an important challenge in many disciplines including statistical mechanics and information security.Many cryptographic applications, including public key encryption (11), use random numbers. Because the unpredictability of these numbers is essential, physical processes are sometimes used as a source of random numbers (12–25). Physical random number generators are usually tested using the National Institute of Standards and Technology (26) and Diehard (27) test suites, which assess their ability to produce bits that are free of bias and correlation. These tests are an excellent assessment of the performance of a physical random number generator in practical situations but leave an important and fundamental problem unaddressed. Deterministic postprocessing procedures, such as hash functions (25), are often used to remove bias and correlation. Because these procedures are algorithmic and reproducible, they cannot in principle increase the entropy rate of a bit stream. Thus, the reliability of a physical random number generator depends on an accurate assessment of the entropy rate of physical process that generated the numbers (28). It remains difficult to assess the unpredictability of a system based on physical principles.Evaluation of entropy rates from an information-theoretic perspective is also centrally important in statistical mechanics (29–36). One might expect that the unpredictability of a system with both small-scale shot noise and large-scale chaotic dynamics would depend on the scale at which it is observed. In many systems, the dependence of the entropy rate on the resolution, ε, and the sampling interval, τ, can reflect the physical origin of unpredictability (37–40). This dependence has been studied experimentally in Brownian motion, RC circuits, and Rayleigh–Bénard convection (34, 35, 37, 41, 42).Here, we present an experimental exploration and numerical model of entropy production in a photon-counting optoelectronic feedback oscillator. Optoelectronic feedback loops that use analog detectors and macroscopic optical signals produce rich dynamics whose timescales and dimensionality are highly tunable (43–47). Our system applies optoelectronic feedback to a weak optical signal that is measured by a photon-counting detector. The dynamic range of this system (eight orders of magnitude in timescale and a factor of 256 in photon rate) allows us to directly observe the transition from shot noise-dominated behavior to a low-dimensional chaotic attractor with increasing optical power—a transition that, to our knowledge, has never been observed experimentally. We show that the entropy rate can reflect either the deterministic or stochastic aspects of the system, depending on the sampling rate and measurement resolution, and describe the importance of this observation for physical random number generation.     

Kirigami-based metastructures with programmable multistability

Multistability plays an important role in advanced engineering applications such as metastructures, deployable structures, and reconfigurable robotics. However, most existing multistability design is based on the two-dimensional (2D)/3D series or parallel combinations of bistable unit cells, which are derived from snap-through instability, nonrigid foldable origami structures, and compliant mechanism, due to the lack of a generic multistable unit cell. Here, we develop a tristable kirigami cuboid by creating a set of elastic joints only effective in a specific motion range which integrates the elastic sheets and switchable hinge axes inspired by the kinematic behaviors of a kirigami cuboid with thick facets. The energy barriers between the stable states can be programmed by the geometric design parameters and material properties of the elastic joints. Taking the tristable cuboid as a unit cell, we construct a family of metastructures with multiple stable states. The number of stable states, the combination of unit stable states, and their transform sequences can be programmed by the number of unit cells, unit design parameters, and loading modes and loading sequences. We also apply this tristable cuboid to the design of frequency reconfigurable antenna with three programmable working frequencies, which demonstrates that such versatile multistability and structural diversity facilitate the development of multifunctional materials and devices.

Multistability is a characteristic of structures with more than one stable equilibrium configuration, which can realize the rapid structural reconfiguration to meet certain functional requirements. Recently, multistable structures have been used to design mechanical structural materials with shape reconfiguration (1–3) and negative stiffness (4) for trapping elastic strain energy (5), energy absorption (6–8), and ternary logic operation (9); robots (10–14) for simplifying actuators, reducing power consumption, and improving the locomotion speed and motion integration; soft media (15) and mechanical diodes (16, 17) for the propagation of mechanical signals; devices for mechanical memory storage (18); deployable structures for self-locked configuration (19, 20) and rapid deployment (21); and other potential applications (22).However, most existing multistability is based on the two-dimensional (2D)/3D series or parallel combinations of bistable unit cells, which are derived from snap-through instability (1, 8, 17, 23–27), nonrigid foldable origami structures (28–32), and compliant mechanisms including rigid origami (33–37). Among them, the snap-through instable beam or structure is the most commonly used fundamental unit in construction with planer motifs or spatial topologies to form 1D, 2D, and 3D multistable structures with unidirectional (1, 24), bidirectional, and multidirectional multistability (2, 4, 6, 9), such as the multistable 1D cylindrical structures, 2D square lattices, and 3D cubic/octahedral lattices (9). Recently, nonrigid origami structure is an emerging resource for designing bistable units based on the elastic deformation of origami facets, such as the Kresling pattern (11, 18, 20, 38) and the hypar pattern (30, 39). Multiple Kresling units can be assembled in series to construct multistable structures (18, 31), and multiple hypar-origami units can be tessellated in plane to be a multistable metasurface (30). Meanwhile, compliant mechanisms derived from mechanisms by introducing spring hinges with compliant segments (34, 36) or torsional springs (40) to store energy have been used to propose bistable unit cells, such as four-bar developable mechanisms (37), Sarrus linkages (41), twisting and rotational mechanisms (42, 43), rotating polygon embedded magnets (44–46), the waterbomb unit (34), and the Miura-ori unit (47, 48). The Miura-ori units have been stacked to be multilayer multistable structures (16, 33, 47).Besides few tristable units with nonzero energy stable states (32, 41), there is no generic tristable or multistable structure which itself is a basic unit rather than constructing with bistable units. On the other hand, most of the bistable unit cells are accompanied by large deformation on beams or facets, while few are derived from the design of joints. One such example is quadrastable overconstrained spatial Sarrus mechanisms with compliant joints (41), whose stable states are also nonzero energy ones, except the initial fabrication state. Therefore, in this paper, we are aiming to develop a generic tristable kirigami cuboid with a set of specially designed elastic joints based on its kinematic behaviors. By combining the tristable kirigami cuboid in series, multistable structures with programmable stable configurations, transformation sequence, and stiffness are constructed. This work paves the way to design multistable metastructures, which facilitates the development of functional materials and devices.     

miR-182 targeting reprograms tumor-associated macrophages and limits breast cancer progression

The protumor roles of alternatively activated (M2) tumor-associated macrophages (TAMs) have been well established, and macrophage reprogramming is an important therapeutic goal. However, the mechanisms of TAM polarization remain incompletely understood, and effective strategies for macrophage targeting are lacking. Here, we show that miR-182 in macrophages mediates tumor-induced M2 polarization and can be targeted for therapeutic macrophage reprogramming. Constitutive miR-182 knockout in host mice and conditional knockout in macrophages impair M2-like TAMs and breast tumor development. Targeted depletion of macrophages in mice blocks the effect of miR-182 deficiency in tumor progression while reconstitution of miR-182-expressing macrophages promotes tumor growth. Mechanistically, cancer cells induce miR-182 expression in macrophages by TGFβ signaling, and miR-182 directly suppresses TLR4, leading to NFκb inactivation and M2 polarization of TAMs. Importantly, therapeutic delivery of antagomiR-182 with cationized mannan-modified extracellular vesicles effectively targets macrophages, leading to miR-182 inhibition, macrophage reprogramming, and tumor suppression in multiple breast cancer models of mice. Overall, our findings reveal a crucial TGFβ/miR-182/TLR4 axis for TAM polarization and provide rationale for RNA-based therapeutics of TAM targeting in cancer.

It is well known that the nonmalignant stromal components in tumors play pivotal roles in tumor progression and therapeutic responses (1, 2). Macrophages are a major component of tumor microenvironment and display considerable phenotypic plasticity in their effects toward tumor progression (3–5). Classically activated (M1) macrophages often exert direct tumor cytotoxic effects or induce antitumor immune responses by helping present tumor-related antigens (6, 7). In contrast, tumoral cues can polarize macrophages toward alternative activation with immunosuppressive M2 properties (6–8). Numerous studies have firmly established the protumor effects of M2-like tumor-associated macrophages (TAMs) and the association of TAMs with poor prognosis of human cancer (9–11). However, how tumors induce the coordinated molecular and phenotypic changes in TAMs for M2 polarization remains incompletely understood, impeding the designing of TAM-targeting strategies for cancer intervention. In addition, drug delivery also represents a hurdle for therapeutic macrophage reprogramming.Noncoding RNAs, including microRNAs, have been shown to play vital roles in various pathological processes of cancer (12). The microRNA miR-182 has been implicated in various developmental processes and disease conditions (13–15). Particularly, it receives extensive attention in cancer studies. Prevalent chromosomal amplification of miR-182 locus and up-regulation of its expression in tumors have been observed in numerous cancer types including breast cancer, gastric cancer, lung adenocarcinoma, colorectal adenocarcinoma, ovarian carcinoma, and melanoma (16–21). miR-182 expression is also linked to higher risk of metastasis and shorter survival of patients (20, 22–24). Functional studies showed that miR-182 expression in cancer cells plays vital roles in various aspects of cancer malignancy, including tumor proliferation (25–29), migration (30, 31), invasion (16, 32, 33), epithelial-mesenchymal transition (34–36), metastasis (21, 37, 38), stemness (30, 39, 40), and therapy resistance (41, 42). A number of target genes, including FOXO1/3 (18, 21, 43–45), CYLD (46), CADM1 (47), BRCA1 (27, 48), MTSS1 (34), PDK4 (49), and SMAD7 (35), were reported to be suppressed by miR-182 in cancer cells. Our previous work also proved that tumoral miR-182 regulates lipogenesis in lung adenocarcinoma and promotes metastasis of breast cancer (34, 35, 49). Although miR-182 was established as an important regulator of cancer cell malignancy, previous studies were limited, with analyses of miR-182 in cultured cancer cells and transplanted tumors. Thus, the consequences of miR-182 regulation in physiologically relevant tumor models, such as genetically modified mice, have not been shown. More importantly, whether miR-182 also plays a role in tumor microenvironmental cell components is unknown.In this study, we show that miR-182 expression in macrophages can be induced by breast cancer cells and regulates TAM polarization in various tumor models of mice. In addition, miR-182 inhibition with TAM-targeting exosomes demonstrates promising efficacy for cancer treatment.     

Combining pressure and electrochemistry to synthesize superhydrides

Recently, superhydrides have been computationally identified and subsequently synthesized with a variety of metals at very high pressures. In this work, we evaluate the possibility of synthesizing superhydrides by uniquely combining electrochemistry and applied pressure. We perform computational searches using density functional theory and particle swarm optimization calculations over a broad range of pressures and electrode potentials. Using a thermodynamic analysis, we construct pressure–potential phase diagrams and provide an alternate synthesis concept, pressure–potential (P2), to access phases having high hydrogen content. Palladium–hydrogen is a widely studied material system with the highest hydride phase being Pd₃H₄. Most strikingly for this system, at potentials above hydrogen evolution and ∼ 300 MPa pressure, we find the possibility to make palladium superhydrides (e.g., PdH₁₀). We predict the generalizability of this approach for La-H, Y-H, and Mg-H with 10- to 100-fold reduction in required pressure for stabilizing phases. In addition, the P2 strategy allows stabilizing additional phases that cannot be done purely by either pressure or potential and is a general approach that is likely to work for synthesizing other hydrides at modest pressures.

Hydrides are a large class of materials containing hydrogen, the lightest and most abundant element in the universe. They have attracted much research interest due to their scientific significance and numerous applications. As important hydrogen storage media (1), they are able to store hydrogen at densities higher than that of liquid hydrogen (2). They also find applications in hydrogen compressors (3), refrigeration (4), heat storage (5), thermal engines (6), batteries (7), fuel cells (8), actuators (9), gas sensors (10), smart windows (11), H₂ purification (12), isotope separation (13), alloy processing (14), catalysis (15), semiconductors (16), neutron moderators (17), low-energy nuclear reactions (18), and recently possible high-temperature superconductors with a critical superconducting temperature T_c in the vicinity of room temperature in hydrogen-rich materials under pressure (19–38).In the late 1960s, Neil Ashcroft (19) and Vitaly Ginzburg (20) independently considered the possibility of high-temperature superconductivity in metallic solid hydrogen at high pressure. Later, the idea of chemical precompression was proposed in which chemical “pressure” is exerted to form hydrogen dominant metal hydrides stable at lower pressures (21). Following the successful prediction (22, 23) and confirmation (24) of very high T_c superconductivity in H₃S, near–room-temperature superconductivity was predicted (25, 26), synthesized (27), and discovered (28) in the superhydrides (defined as MH_n, for n > 6) in the La-H system. Later, comparable T_c values were observed experimentally for other La-H (29), Y-H (30–32), and La-Y-H (33) superhydrides, and room-temperature superconductivity was also reported in the C-S-H system (34). In addition, even higher T_c s have been theoretically predicted, such as Li₂MgH₁₆ with T_c as high as ∼ 470 K at 250 GPa (35).High pressures are needed to synthesize superhydrides (38). One major reason is that at lower pressures, the thermodynamic stability of superhydrides is weakened or no longer exists. To overcome such a challenge, it is obvious that more processing variables need to be introduced in addition to chemical composition and pressure. A processing variable that has been largely hidden is the electrical potential when utilizing electrochemistry for synthesis, which has been used in synthesizing palladium hydride at ambient pressure (39). In the present work we show that the synergetic use of pressure and electrical potential can dramatically extend the thermodynamic stability regime of superhydrides to modest pressures, an approach we term P2. This approach opens more opportunities for the creation of superhydrides and other materials by combining pressure and electrochemical loading techniques. We begin by outlining the general thermodynamic framework. We then apply the approach to the Pd-H system, where we also present density functional theory (DFT) predictions of palladium hydrides under pressure. This is followed by predictions for other metal hydride systems and then a discussion of the broad implications.     

The spontaneous emergence of conventions: An experimental study of cultural evolution

How do shared conventions emerge in complex decentralized social systems? This question engages fields as diverse as linguistics, sociology, and cognitive science. Previous empirical attempts to solve this puzzle all presuppose that formal or informal institutions, such as incentives for global agreement, coordinated leadership, or aggregated information about the population, are needed to facilitate a solution. Evolutionary theories of social conventions, by contrast, hypothesize that such institutions are not necessary in order for social conventions to form. However, empirical tests of this hypothesis have been hindered by the difficulties of evaluating the real-time creation of new collective behaviors in large decentralized populations. Here, we present experimental results—replicated at several scales—that demonstrate the spontaneous creation of universally adopted social conventions and show how simple changes in a population’s network structure can direct the dynamics of norm formation, driving human populations with no ambition for large scale coordination to rapidly evolve shared social conventions.Social conventions are the foundation for social and economic life (1–7), However, it remains a central question in the social, behavioral, and cognitive sciences to understand how these patterns of collective behavior can emerge from seemingly arbitrary initial conditions (2–4, 8, 9). Large populations frequently manage to coordinate on shared conventions despite a continuously evolving stream of alternatives to choose from and no a priori differences in the expected value of the options (1, 3, 4, 10). For instance, populations are able to produce linguistic conventions on accepted names for children and pets (11), on common names for colors (12), and on popular terms for novel cultural artifacts, such as referring to junk email as “SPAM” (13, 14). Similarly, economic conventions, such as bartering systems (2), beliefs about fairness (3), and consensus regarding the exchangeability of goods and services (15), emerge with clear and widespread agreement within economic communities yet vary broadly across them (3, 16).Prominent theories of social conventions suggest that institutional mechanisms—such as centralized authority (14), incentives for collective agreement (15), social leadership (16), or aggregated information (17)—can explain global coordination. However, these theories do not explain whether, or how, it is possible for conventions to emerge when social institutions are not already in place to guide the process. A compelling alternative approach comes from theories of social evolution (2, 18–20). Social evolutionary theories maintain that networks of locally interacting individuals can spontaneously self-organize to produce global coordination (21, 22). Although there is widespread interest in this approach to social norms (6, 7, 14, 18, 23–26), the complexity of the social process has prevented systematic empirical insight into the thesis that these local dynamics are sufficient to explain universally adopted conventions (27, 28).Several difficulties have limited prior empirical research in this area. The most notable of these limitations is scale. Although compelling experiments have successfully shown the creation of new social conventions in dyadic and small group interactions (29–31), the results in small group settings can be qualitatively different from the dynamics in larger groups (Model), indicating that small group experiments are insufficient for demonstrating whether or how new conventions endogenously form in larger populations (32, 33). Important progress on this issue has been made using network-based laboratory experiments on larger groups (15, 24). However, this research has been restricted to studying coordination among players presented with two or three options with known payoffs. Natural convention formation, by contrast, is significantly complicated by the capacity of individuals to continuously innovate, which endogenously expands the “ecology” of alternatives under evaluation (23, 29, 31). Moreover, prior experimental studies have typically assumed the existence of either an explicit reward for universal coordination (15) or a mechanism that aggregates and reports the collective state of the population (17, 24), which has made it impossible to evaluate the hypothesis that global coordination is the result of purely local incentives.More recently, data science approaches to studying norms have addressed many of these issues by analyzing behavior change in large online networks (34). However, these observational studies are limited by familiar problems of identification that arise from the inability to eliminate the confounding influences of institutional mechanisms. As a result, previous empirical research has been unable to identify the collective dynamics through which social conventions can spontaneously emerge (8, 34–36).We addressed these issues by adopting a web-based experimental approach. We studied the effects of social network structure on the spontaneous evolution of social conventions in populations without any resources to facilitate global coordination (9, 37). Participants in our study were rewarded for coordinating locally, however they had neither incentives nor information for achieving large scale agreement. Further, to eliminate any preexisting bias in the evolutionary process, we studied the emergence of arbitrary linguistic conventions, in which none of the options had any a priori value or advantage over the others (3, 23). In particular, we considered the prototypical problem of whether purely local interactions can trigger the emergence of a universal naming convention (38, 39).     

Active topolectrical circuits

The transfer of topological concepts from the quantum world to classical mechanical and electronic systems has opened fundamentally different approaches to protected information transmission and wave guidance. A particularly promising emergent technology is based on recently discovered topolectrical circuits that achieve robust electric signal transduction by mimicking edge currents in quantum Hall systems. In parallel, modern active matter research has shown how autonomous units driven by internal energy reservoirs can spontaneously self-organize into collective coherent dynamics. Here, we unify key ideas from these two previously disparate fields to develop design principles for active topolectrical circuits (ATCs) that can self-excite topologically protected global signal patterns. Realizing autonomous active units through nonlinear Chua diode circuits, we theoretically predict and experimentally confirm the emergence of self-organized protected edge oscillations in one- and two-dimensional ATCs. The close agreement between theory, simulations, and experiments implies that nonlinear ATCs provide a robust and versatile platform for developing high-dimensional autonomous electrical circuits with topologically protected functionalities.

Information transfer and storage in natural and man-made active systems, from sensory organs (1–3) to the internet, rely on the robust exchange of electrical signals between a large number of autonomous units that balance local energy uptake and dissipation (4, 5). Major advances in the understanding of photonic (6–9), acoustic (10–12), and mechanical (13–16) metamaterials have shown that topological protection (17–24) enables the stabilization and localization of signal propagation in passive and active (25–27) dynamical systems that violate time-reversal and/or other symmetries. Recent studies have successfully applied these ideas to realize topolectrical circuits (28) in the passive linear (29–34) and passive nonlinear (35, 36) regimes. However, despite substantial progress in the development of topological wave guides (37), lasers (38, 39), and transmission lines (40–43), the transfer of these concepts to active (44, 45) nonlinear circuits made from autonomously acting units still poses an unsolved challenge. From a broader perspective, not only does harnessing topological protection in nonlinear active circuits promise a new generation of autonomous devices, but also understanding their design and self-organization principles may offer insights into information storage and processing mechanisms in living systems, which integrate cellular activity, electrical signaling, and nonlinear feedback to coordinate essential biological functions (46, 47).Exploiting a mathematical analogy with active Brownian particle systems (26), we theoretically develop and experimentally demonstrate general design principles for active topolectrical circuits (ATCs) that achieve self-organized, self-sustained, topologically protected electric current patterns. The main building blocks of ATCs are nonlinear dissipative elements that exhibit an effectively negative resistance over a certain voltage range. Negative resistances can be realized using van der Pol (vdP) circuits (48), tunnel diodes, unijunction transistors, solid-state thyristors (49), or operational amplifiers set as negative impedance converters through current inversion (50), and the design principles described below are applicable to all these systems. Indeed, we expect them to apply to an even broader class of nonlinear systems, as similar dynamics also describe electromagnetic resonators with Kerr-type nonlinearities (51–53).     

Microestimates of wealth for all low- and middle-income countries

Many critical policy decisions, from strategic investments to the allocation of humanitarian aid, rely on data about the geographic distribution of wealth and poverty. Yet many poverty maps are out of date or exist only at very coarse levels of granularity. Here we develop microestimates of the relative wealth and poverty of the populated surface of all 135 low- and middle-income countries (LMICs) at 2.4 km resolution. The estimates are built by applying machine-learning algorithms to vast and heterogeneous data from satellites, mobile phone networks, and topographic maps, as well as aggregated and deidentified connectivity data from Facebook. We train and calibrate the estimates using nationally representative household survey data from 56 LMICs and then validate their accuracy using four independent sources of household survey data from 18 countries. We also provide confidence intervals for each microestimate to facilitate responsible downstream use. These estimates are provided free for public use in the hope that they enable targeted policy response to the COVID-19 pandemic, provide the foundation for insights into the causes and consequences of economic development and growth, and promote responsible policymaking in support of sustainable development.

Many critical decisions require accurate, quantitative data on the local distribution of wealth and poverty. Governments and nonprofit organizations rely on such data to target humanitarian aid and design social protection systems (1, 2); businesses use this information to guide marketing and investment strategies (3); these data also provide the foundation for entire fields of basic and applied social science research (4).Yet reliable economic data are expensive to collect, and only half of all countries have access to adequate data on poverty (5). In some cases, the data that do exist are subject to political capture and censorship (6, 7) and often cannot be disaggregated below the largest administrative level (8). The scarcity of quantitative data impedes policymakers and researchers interested in addressing global poverty and inequality and hinders the broad international coalition working toward the Sustainable Development Goals, in particular toward the first goal of ending poverty in all its forms everywhere (9).To address these data gaps, researchers have developed approaches to construct poverty maps from nontraditional data. These include methods from small area statistics that combine household sample surveys with comprehensive census data (10), as well as more recent use of satellite “nightlights” (11–13), mobile phone data (14, 15), social media (16), high-resolution satellite imagery (17–21), or a combination of these (22, 23). But to date these efforts have focused on a single continent or a select set of countries, limiting their relevance to development objectives that require a global perspective.     

Conditions for metachronal coordination in arrays of model cilia

On surfaces with many motile cilia, beats of the individual cilia coordinate to form metachronal waves. We present a theoretical framework that connects the dynamics of an individual cilium to the collective dynamics of a ciliary carpet via systematic coarse graining. We uncover the criteria that control the selection of frequency and wave vector of stable metachronal waves of the cilia and examine how they depend on the geometric and dynamical characteristics of a single cilium, as well as the geometric properties of the array. We perform agent-based numerical simulations of arrays of cilia with hydrodynamic interactions and find quantitative agreement with the predictions of the analytical framework. Our work sheds light on the question of how the collective properties of beating cilia can be determined using information about the individual units and, as such, exemplifies a bottom-up study of a rich active matter system.

Motile cilia are hair-like organelles that beat with a whip-like stroke that breaks time-reversal symmetry to create fluid flow or propel swimming microorganisms under low Reynolds number conditions (1–3). The beat is actuated by many dynein motors, which generate forces between microtubules that cause the cilium to bend in a robust cyclic manner with moderate fluctuations (4, 5). On surfaces with many cilia, the actuating organelles can coordinate with each other and collectively beat in the form of metachronal waves, where neighboring cilia beat sequentially (i.e., with a phase lag) rather than synchronously (6). The flows created from this coordinated beating are important for breaking symmetry in embryonic development (7, 8), creation of complex and dynamic flow patterns for the cerebrospinal fluid in the brain (9, 10), and providing access to nutrients (11). In microorganisms such as Paramecium and Volvox, the metachronal beating of cilia provides propulsion strategies in viscous environments (12, 13). It has been shown that depending on the parameters, beating ciliary carpets can exhibit globally ordered and turbulent flow patterns (14), which can be stable even with a moderate amount of quenched disorder (15), and that metachronal coordination optimizes the efficiency of fluid pumping (16, 17). Natural cilia have inspired various designs of artificial cilia (18–22), which may be used for pumping fluid (23, 24) and mixing (25), or fabrication of microswimmers (26).Hydrodynamic interactions have been shown to play a key role in coordinated beating of cilia (27, 28) and mediating cell polarity control (29). To achieve synchronization between two cilia via hydrodynamic interactions, it is necessary to break the permutation symmetry between them [e.g., by exploiting the dependence of the drag coefficient on the distance from a surface (30), flexibility of the anchoring of the cilia (31), nonuniform beat patterns (32, 33), or any combination of these effects (34)]. In addition to the hydrodynamic interactions, the basal coupling between cilia can also facilitate the coordination (35–37).How can we predict the collective behavior of arrays of many cilia coordinated by hydrodynamic interactions, and in particular, the properties of the emerging metachronal waves, from the single-cilium characteristics? Extensive numerical simulations using explicitly resolved beating filaments (16, 17, 27, 38–40) and simplified spherical rotors (13, 14, 41, 42) have demonstrated that metachronal coordination emerges from hydrodynamic interactions. However, insight into this complex many-body dynamical system at the level that has been achieved in studies of two cilia is still lacking. Here, we propose a theoretical framework for understanding the physical conditions for coordination of many independently beating cilia, which are arranged on a substrate in the form of a two-dimensional (2D) array immersed in a three-dimensional (3D) fluid. We uncover the physical conditions for the emergence of stable metachronal waves and predict the properties of the wave in terms of single-cilium geometric and dynamic characteristics.     

Dynamics of thin precursor film in wetting of nanopatterned surfaces

The spreading of a liquid droplet on flat surfaces is a well-understood phenomenon, but little is known about how liquids spread on a rough surface. When the surface roughness is of the nanoscopic length scale, the capillary forces dominate and the liquid droplet spreads by wetting the nanoscale textures that act as capillaries. Here, using a combination of advanced nanofabrication and liquid-phase transmission electron microscopy, we image the wetting of a surface patterned with a dense array of nanopillars of varying heights. Our real-time, high-speed observations reveal that water wets the surface in two stages: 1) an ultrathin precursor water film forms on the surface, and then 2) the capillary action by nanopillars pulls the water, increasing the overall thickness of water film. These direct nanoscale observations capture the previously elusive precursor film, which is a critical intermediate step in wetting of rough surfaces.

The wettability of surfaces plays an important role in many natural and industrial processes (1–3). Wetting of a smooth surface by a liquid is commonly described by the Young’s equation, which quantifies the wettability of a solid surface using the contact angle of a liquid droplet (4, 5). When the surfaces are rough, the spreading of a droplet is governed by contact angle and capillary effects, and the droplet spreads via hemiwicking (6, 7). The rough features of the surface act as capillaries, or wicks, that imbibe liquid from the droplet (8–10). Earlier studies show that modifying the surface roughness can be a powerful approach to tuning the surface wettability (11–18), and such surface modifications have been used for applications in biomedicine (19, 20), textile industry (21, 22), and water treatment (23, 24).Despite the recent progress in designing rough superhydrophilic surfaces (17, 24), the nanoscale details of the wicking process on rough surfaces remain unknown because these processes are extremely challenging to visualize. Current approaches to study wetting are based on optical methods (25–28), and, while providing valuable insights, these methods lack the spatial resolution needed to discern the nanoscale details of wetting. Alternative approaches based on scanning probe microscopy techniques provide high spatial resolution but lack temporal resolution and thus have been limited to study the adsorption of water (29) and wetting of smooth surfaces (30, 31). Recent advances in liquid-phase transmission electron microscopy (TEM) (32–36) and fast electron detection cameras (37, 38) enabled direct imaging of the nanoscale dynamics of liquids on surfaces with high temporal and spatial resolutions. Here, we used this liquid-phase TEM approach to study the wetting of patterned nanostructures at high speeds (200 to 300 frames per second [fps]).     

Single nanoparticle detection using split-mode microcavity Raman lasers

Ultrasensitive nanoparticle detection holds great potential for early-stage diagnosis of human diseases and for environmental monitoring. In this work, we report for the first time, to our knowledge, single nanoparticle detection by monitoring the beat frequency of split-mode Raman lasers in high-Q optical microcavities. We first demonstrate this method by controllably transferring single 50-nm–radius nanoparticles to and from the cavity surface using a fiber taper. We then realize real-time detection of single nanoparticles in an aqueous environment, with a record low detection limit of 20 nm in radius, without using additional techniques for laser noise suppression. Because Raman scattering occurs in most materials under practically any pump wavelength, this Raman laser-based sensing method not only removes the need for doping the microcavity with a gain medium but also loosens the requirement of specific wavelength bands for the pump lasers, thus representing a significant step toward practical microlaser sensors.Stimulated Raman scattering holds great potential for various photonic applications, such as label-free high-sensitivity biomedical imaging (1) and for extending the wavelength range of existing lasers (2), as well as for generating ultra-short light pulses (3). In high Q microcavities (4), stimulated Raman scattering, also called Raman lasing, has been experimentally demonstrated to possess ultra-low thresholds (5–12), due to the greatly increased light density in microcavities (13). Such microcavity Raman lasers hold great potential for sensing applications. In principle, Raman lasing initially occurs in the two initially degenerate counter propagating traveling cavity modes. These two modes couple to each other due to backscattering when a nanoscale object binds to the cavity surface. For a sufficiently strong coupling, in which the photon exchange rate between the two initial modes becomes larger than the rates of all of the loss mechanisms in the system, two new split cavity modes form (14–18) and lase simultaneously. Thus, by monitoring the beat frequency of the split-mode Raman lasers, ultrasensitive nanoparticle detection can be realized.In this work, we report, to our knowledge, the first experimental demonstration of single nanoparticle detection using split-mode microcavity Raman lasers. The sensing principle is first demonstrated in air, by controllably binding or removing single 50-nm-radius polystyrene (PS) nanoparticles to and from the cavity surface using a fiber taper (19) and measuring the changes in the beat frequency of the two split Raman lasers. Real-time single nanoparticle detection is then performed in an aqueous environment by monitoring the discrete changes in beat frequency of the Raman lasers, and a detection limit of 20 nm in particle radius is realized. This microcavity Raman laser sensing method holds several advantages. On the one hand, the beat frequency of the Raman lasers, which corresponds to the mode splitting (18), is inherently immune to many noise sources, such as laser frequency noise and thermal noise (including that induced both by the environmental temperature fluctuations and by probe laser heating), which are the main noise sources in sensing systems using the mode shift mechanism (20–30). Over the last few years, significant effort has been made to suppress the laser frequency noise in the mode-shift detection method, such as by using a reference interferometer (27) and by performing backscattering detection with frequency locking techniques (28, 29), but both approaches involve a substantial increase in the complexity of the sensing systems. On the other hand, the intrinsic Raman gain in the cavity provides a perfect means to compensate for the cavity mode loss and thus to lower the detection limit compared with passive mode splitting methods (18, 31–34). Without the need for doping the microcavities with a gain medium (35–37), the fabrication complexity of microcavities is also greatly reduced, and no specific wavelength bands of the pump lasers are required.     

Self-assembly of alkynylplatinum(II) terpyridine amphiphiles into nanostructures via steric control and metal–metal interactions

A series of mono- and dinuclear alkynylplatinum(II) terpyridine complexes containing the hydrophilic oligo(para-phenylene ethynylene) with two 3,6,9-trioxadec-1-yloxy chains was designed and synthesized. The mononuclear alkynylplatinum(II) terpyridine complex was found to display a very strong tendency toward the formation of supramolecular structures. Interestingly, additional end-capping with another platinum(II) terpyridine moiety of various steric bulk at the terminal alkyne would lead to the formation of nanotubes or helical ribbons. These desirable nanostructures were found to be governed by the steric bulk on the platinum(II) terpyridine moieties, which modulates the directional metal−metal interactions and controls the formation of nanotubes or helical ribbons. Detailed analysis of temperature-dependent UV-visible absorption spectra of the nanostructured tubular aggregates also provided insights into the assembly mechanism and showed the role of metal−metal interactions in the cooperative supramolecular polymerization of the amphiphilic platinum(II) complexes.Square-planar d⁸ platinum(II) polypyridine complexes have long been known to exhibit intriguing spectroscopic and luminescence properties (1–54) as well as interesting solid-state polymorphism associated with metal−metal and π−π stacking interactions (1–14, 25). Earlier work by our group showed the first example, to our knowledge, of an alkynylplatinum(II) terpyridine system [Pt(tpy)(C ≡ CR)]⁺ that incorporates σ-donating and solubilizing alkynyl ligands together with the formation of Pt···Pt interactions to exhibit notable color changes and luminescence enhancements on solvent composition change (25) and polyelectrolyte addition (26). This approach has provided access to the alkynylplatinum(II) terpyridine and other related cyclometalated platinum(II) complexes, with functionalities that can self-assemble into metallogels (27–31), liquid crystals (32, 33), and other different molecular architectures, such as hairpin conformation (34), helices (35–38), nanostructures (39–45), and molecular tweezers (46, 47), as well as having a wide range of applications in molecular recognition (48–52), biomolecular labeling (48–52), and materials science (53, 54). Recently, metal-containing amphiphiles have also emerged as a building block for supramolecular architectures (42–44, 55–59). Their self-assembly has always been found to yield different molecular architectures with unprecedented complexity through the multiple noncovalent interactions on the introduction of external stimuli (42–44, 55–59).Helical architecture is one of the most exciting self-assembled morphologies because of the uniqueness for the functional and topological properties (60–69). Helical ribbons composed of amphiphiles, such as diacetylenic lipids, glutamates, and peptide-based amphiphiles, are often precursors for the growth of tubular structures on an increase in the width or the merging of the edges of ribbons (64, 65). Recently, the optimization of nanotube formation vs. helical nanostructures has aroused considerable interests and can be achieved through a fine interplay of the influence on the amphiphilic property of molecules (66), choice of counteranions (67, 68), or pH values of the media (69), which would govern the self-assembly of molecules into desirable aggregates of helical ribbons or nanotube scaffolds. However, a precise control of supramolecular morphology between helical ribbons and nanotubes remains challenging, particularly for the polycyclic aromatics in the field of molecular assembly (64–69). Oligo(para-phenylene ethynylene)s (OPEs) with solely π−π stacking interactions are well-recognized to self-assemble into supramolecular system of various nanostructures but rarely result in the formation of tubular scaffolds (70–73). In view of the rich photophysical properties of square-planar d⁸ platinum(II) systems and their propensity toward formation of directional Pt···Pt interactions in distinctive morphologies (27–31, 39–45), it is anticipated that such directional and noncovalent metal−metal interactions might be capable of directing or dictating molecular ordering and alignment to give desirable nanostructures of helical ribbons or nanotubes in a precise and controllable manner.Herein, we report the design and synthesis of mono- and dinuclear alkynylplatinum(II) terpyridine complexes containing hydrophilic OPEs with two 3,6,9-trioxadec-1-yloxy chains. The mononuclear alkynylplatinum(II) terpyridine complex with amphiphilic property is found to show a strong tendency toward the formation of supramolecular structures on diffusion of diethyl ether in dichloromethane or dimethyl sulfoxide (DMSO) solution. Interestingly, additional end-capping with another platinum(II) terpyridine moiety of various steric bulk at the terminal alkyne would result in nanotubes or helical ribbons in the self-assembly process. To the best of our knowledge, this finding represents the first example of the utilization of the steric bulk of the moieties, which modulates the formation of directional metal−metal interactions to precisely control the formation of nanotubes or helical ribbons in the self-assembly process. Application of the nucleation–elongation model into this assembly process by UV-visible (UV-vis) absorption spectroscopic studies has elucidated the nature of the molecular self-assembly, and more importantly, it has revealed the role of metal−metal interactions in the formation of these two types of nanostructures.     

From the Cover: Predicting overfishing and extinction threats in multispecies fisheries

Threats to species from commercial fishing are rarely identified until species have suffered large population declines, by which time remedial actions can have severe economic consequences, such as closure of fisheries. Many of the species most threatened by fishing are caught in multispecies fisheries, which can remain profitable even as populations of some species collapse. Here we show for multispecies fisheries that the biological and socioeconomic conditions that would eventually cause species to be severely depleted or even driven extinct can be identified decades before those species experience high harvest rates or marked population declines. Because fishing effort imposes a common source of mortality on all species in a fishery, the long-term impact of a fishery on a species is predicted by measuring its loss rate relative to that of species that influence the fishery’s maximal effort. We tested our approach on eight Pacific tuna and billfish populations, four of which have been identified recently as in decline and threatened with overfishing. The severe depletion of all four populations could have been predicted in the 1950s, using our approach. Our results demonstrate that species threatened by human harvesting can be identified much earlier, providing time for adjustments in harvesting practices before consequences become severe and fishery closures or other socioeconomically disruptive interventions are required to protect species.Marine fisheries are an important global source of food and livelihoods (1–4), but there are concerns that current fishing practices threaten some marine species with severe depletion or eventual extinction (2–5). Many of the largest commercial fishing methods, such as trawling, longlining, and seining, unavoidably catch multiple species simultaneously (6–9). Multispecies fisheries pose a particular threat of extinction or severe depletion because fishing can remain profitable as long as some valuable species remain abundant, even while others collapse (6–11). In contrast, in a single-species fishery profits tend to fall as the target population declines, thereby removing the incentive to fish before extinction occurs (10). Multispecies fisheries pose a threat to two types of species or stocks (populations): (i) commercially valued species, called “weak stocks”, which are more vulnerable to overharvesting than are other commercially valuable species (6), and (ii) by-catch species, which are caught accidentally and create little economic incentive to cease fishing as their populations collapse because they have little or no commercial value (7–9).Failure to prevent collapse of weak stocks and by-catch species can impose substantial long-term environmental and economic costs. Slow-growing populations are most likely to collapse, but can take several decades to recover (5). Recovery often requires long-term fishery closures or reductions in effort, having substantial economic and social consequences (3, 5). Moreover, population declines caused by one fishery can diminish yields and profits in other commercial or artisanal fisheries that depend on the same species (e.g., ref. 12).Despite these costs, species threatened by fishing have rarely been identified until after their populations have declined substantially (2–5, 7, 8). Assessments of fishery impacts on species mostly focus on estimating current exploitation rates or past population trends (13–15), which identifies already declining species rather than predicting future declines. Data limitations have made empirical prediction of future threats from fishing challenging, particularly for weak stocks and by-catch species. Oceans are difficult to sample extensively, and few economic incentives exist to gather data on species other than the most commercially valued species (7, 8). Some predictive models (e.g., ref. 16) have been developed to forecast the impacts of some fisheries, but these are often data intensive. Some of the characteristics that make a population susceptible to overfishing are well known—for example, low population growth rates (3–11, 17, 18), high value and/or low fishing costs (10, 11, 17–19), and schooling behavior (18). Recently, some correlative approaches based on these characteristics have been developed for assessing likely relative threats to data-poor species (4, 20–22). However, predicting the severity of future threats in absolute terms with this type of approach can be challenging.Here, we present a mechanistic approach that uses readily available data to predict the potential of current fishing practices, if maintained, to eventually cause a population to be driven extinct or “overfished”, here defined as depletion below its maximum sustainable yield (MSY) abundance (N_MSY) (3). Our approach identifies combinations of biological and socioeconomic conditions that are likely to eventually lead to high mortality rates and population declines. As we show, these conditions can be identified long before either occurs.We test the predictive power of our approach on eight tuna and billfish populations of the Western and Central Pacific Ocean fisheries. High-seas tuna and billfish have elicited recent conservation concern due to significant population declines and range contractions found in many species (17, 23, 24). Three of the populations in our study, bigeye tuna (Thunnus obesus) and both the northern and the southern striped marlin (Tetrapturus audax) populations, have been recently identified as experiencing overfishing—meaning their exploitation rates have exceeded the MSY exploitation rate (F_MSY) (24–27). A fourth, blue marlin (Makaira nigricans), whose overfishing status has been subject to considerable uncertainty (28), has undergone a significant population decline and range contraction (13, 23, 28). We determine whether our approach could have predicted threats to these four populations, using data from as early as the 1950s, and assess the threats predicted by the latest available data to all populations.     

Volcanically driven lacustrine ecosystem changes during the Carnian Pluvial Episode (Late Triassic)

The Late Triassic Carnian Pluvial Episode (CPE) saw a dramatic increase in global humidity and temperature that has been linked to the large-scale volcanism of the Wrangellia large igneous province. The climatic changes coincide with a major biological turnover on land that included the ascent of the dinosaurs and the origin of modern conifers. However, linking the disparate cause and effects of the CPE has yet to be achieved because of the lack of a detailed terrestrial record of these events. Here, we present a multidisciplinary record of volcanism and environmental change from an expanded Carnian lake succession of the Jiyuan Basin, North China. New U–Pb zircon dating, high-resolution chemostratigraphy, and palynological and sedimentological data reveal that terrestrial conditions in the region were in remarkable lockstep with the large-scale volcanism. Using the sedimentary mercury record as a proxy for eruptions reveals four discrete episodes during the CPE interval (ca. 234.0 to 232.4 Ma). Each eruptive phase correlated with large, negative C isotope excursions and major climatic changes to more humid conditions (marked by increased importance of hygrophytic plants), lake expansion, and eutrophication. Our results show that large igneous province eruptions can occur in multiple, discrete pulses, rather than showing a simple acme-and-decline history, and demonstrate their powerful ability to alter the global C cycle, cause climate change, and drive macroevolution, at least in the Triassic.

The Carnian Pluvial Episode (CPE; ca. 234 to ∼232 Ma; Late Triassic) was an interval of significant changes in global climate and biotas (1, 2). It was characterized by warming (3, 4) and enhancement of the hydrological cycle (5–7), linked to repeated C isotope fluctuations (8–11) and accompanied by increased rainfall (1), intensified continental weathering (9, 12), shutdown of carbonate platforms (13), widespread marine anoxia (4), and substantial biological turnover (1, 2, 10). Available stratigraphic data indicate that the Carnian climatic changes broadly coincide with, and could have been driven by, the emplacement of the Wrangellia large igneous province (LIP) (2, 4, 7, 8, 10, 14, 15) (Fig. 1A). It is postulated that the voluminous emission of volcanic CO₂, with consequent global warming and enhancement of a mega-monsoonal climate, was responsible for the CPE (9, 16), although the link is imprecise (2, 17) because the interval of Wrangellian eruptions have not yet been traced in the sedimentary records encompassing the CPE.Open in a separate windowFig. 1.Location and geological context for the study area. (A) Paleogeographic reconstruction for the Carnian (∼237 to 227 Ma) Stage (Late Triassic), showing locations of the study area and volcanic centers (revised after ref. 4, with volcanic data from refs. 4, 7, 49, and 50). (B) Tectono-paleogeographic map of the NCP during the Late Triassic (modified from ref. 21), showing the location of the study area. (C) Stratigraphic framework of the Upper Chunshuyao Formation (CSY) to the Lower Yangshuzhuang (YSZ) Formation from the Jiyuan Basin (modified from ref. 20). Abbreviations: LIP, Large Igneous Province; QDOB, Qingling-Dabie Orogenic Belt; S-NCP, southern NCP; SCP, South China Plate; Fm., Formation; m & s, coal, mudstone, and silty mudstone; s., sandstone; c, conglomerate; Dep. env., Depositional environment; and C.-P., Coniopteris-Phoenicopsis.The CPE was originally identified because of changes in terrestrial sedimentation, but most subsequent studies have been on marine strata (2, 4, 7–10). By contrast, much less is known about the effects of this climatic episode on terrestrial environments (2), although there were major extinctions and radiations among animals (including dinosaurs, crocodiles, turtles, and the first mammals and insects) and modern conifer families (2). Some of the new organisms may have flourished because of the spread of humid environments, such as the turtles and metoposaurids (18, 19).In this study, we have investigated terrestrial sediments from the Zuanjing-1 (ZJ-1) borehole in the Jiyuan Basin of the southern North China Plate (NCP) and use zircon U–Pb ages from two tuffaceous claystone horizons, fossil plant biostratigraphy, and organic C isotope (δ¹³C_org) and Hg chemostratigraphy to identify the CPE and volcanic activity.