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Abstract Human mobility is becoming increasingly complex in urban environments. However, our fundamental understanding of urban population dynamics, particularly the pulsating fluctuations occurring across different locations and timescales, remains limited. Here, we use mobile device data from large cities and regions worldwide combined with a detrended fractal analysis to uncover a universal spatiotemporal scaling law that governs urban population fluctuations. This law reveals the scale invariance of these fluctuations, spanning from city centers to peripheries over both time and space. Moreover, we show that at any given location, fluctuations obey a time-based scaling law characterized by a spatially decaying exponent, which quantifies their relationship with urban structure. These interconnected discoveries culminate in a robust allometric equation that links population dynamics with urban densities, providing a powerful framework for predicting and managing the complexities of urban human activities. Collectively, this study paves the way for more effective urban planning, transportation strategies, and policies grounded in population dynamics, thereby fostering the development of resilient and sustainable cities. 

Generalization to novel object configurations and instances across diverse tasks and environments is a critical challenge in robotics. Keypoint-based representations have been proven effective as a succinct representation for capturing essential object features, and for establishing a reference frame in action prediction, enabling data-efficient learning of robot skills. However, their manual design nature and reliance on additional human labels limit their scalability. In this paper, we propose KALM, a framework that leverages large pre-trained vision-language models (LMs) to automatically generate taskrelevant and cross-instance consistent keypoints. KALM distills robust and consistent keypoints across views and objects by generating proposals using LMs and verifies them against a small set of robot demonstration data. Based on the generated keypoints, we can train keypoint-conditioned policy models that predict actions in keypoint-centric frames, enabling robots to generalize effectively across varying object poses, camera views, and object instances with similar functional shapes. Our method demonstrates strong performance in the real world, adapting to different tasks and environments from only a handful of demonstrations while requiring no additional labels. 

Abstract TheB-field Orion Protostellar Survey (BOPS) recently obtained polarimetric observations at 870μm toward 61 protostars in the Orion molecular clouds with ∼1″ spatial resolution using the Atacama Large Millimeter/submillimeter Array. From the BOPS sample, we selected the 26 protostars with extended polarized emission within a radius of ∼6″ (2400 au) around the protostar. This allows us to have sufficient statistical polarization data to infer the magnetic field strength. The magnetic field strength is derived using the Davis–Chandrasekhar–Fermi method. The underlying magnetic field strengths are approximately 2.0 mG for protostars with a standard hourglass magnetic field morphology, which is higher than the values derived for protostars with rotated hourglass, spiral, and complex magnetic field configurations (≲1.0 mG). This suggests that the magnetic field plays a more significant role in envelopes exhibiting a standard hourglass field morphology, and a value of ≳2.0 mG would be required to maintain such a structure at these scales. Furthermore, most protostars in the sample are slightly supercritical, with mass-to-flux ratios ≲3.0. In particular, the mass-to-flux ratios for all protostars with a standard hourglass magnetic field morphology are lower than 3.0. However, these ratios do not account for the contribution of the protostellar mass, which means they are likely significantly underestimated. 

Abstract We present a study connecting the physical properties of protostellar envelopes to the morphology of the envelope-scale magnetic field. We used the Atacama Large Millimeter/submillimeter Array (ALMA) polarization observations of 61 young protostars at 0.87 mm on ~400–3000 au scales from theB-field Orion Protostellar Survey to infer the envelope-scale magnetic field, and we used the dust emission to measure the envelope properties on comparable scales. We find that protostars showing standard hourglass magnetic field morphology tend to have larger masses, and the nonthermal velocity dispersion is positively correlated with the bolometric luminosity and dust temperature of the envelope. Combining with the disk properties taken from the Orion VLA/ALMA Nascent Disk and Multiplicity survey, we connect envelope properties to fragmentation. Our results show a positive correlation between the fragmentation level and the angle dispersion of the magnetic field, suggesting that the envelope fragmentation tends to be suppressed by the magnetic field. We also find that protostars exhibiting standard hourglass magnetic field structure tend to have a smaller disk and smaller angle dispersion of the magnetic field than other field configurations, especially the rotated hourglass, but also the spiral and others, suggesting a more effective magnetic braking in the standard hourglass morphology of magnetic fields. Nevertheless, significant misalignment between the magnetic field and outflow axes tends to reduce magnetic braking, leading to the formation of larger disks. 

Fungi of the Conidiobolus group belong to the family Ancylistaceae (Entomophthorales, Entomophthoromycotina, Zoopagomycota) and include over 70 predominantly saprotrophic species in four similar and closely related genera, that were separated phylogenetically recently. Entomopathogenic fungi of the genus Batkoa are very close morphologically to the Conidiobolus species. Their thalli share similar morphology, and they produce ballistic conidia like closely related entomopathogenic Entomophthoraceae. Ballistic conidia are traditionally considered as an efficient tool in the pathogenic process and an important adaptation to the parasitic lifestyle. Our study aims to reconstruct the phylogeny of this fungal group using molecular and genomic data, ancestral lifestyle and morphological features of the conidiobolus-like group and the direction of their evolution. Based on phylogenetic analysis, some species previously in the family Conidiobolaceae are placed in the new families Capillidiaceae and Neoconidiobolaceae, which each include one genus, and the Conidiobolaceae now includes three genera. Intermediate between the conidiobolus-like groups and Entomophthoraceae, species in the distinct Batkoa clade now belong in the family Batkoaceae. Parasitism evolved several times in the Conidiobolus group and Ancestral State Reconstruction suggests that the evolution of ballistic conidia preceded the evolution of the parasitic lifestyle. 

In mammals, HP1-mediated heterochromatin forms positionally and mechanically stable genomic domains even though the component HP1 paralogs, HP1α, HP1β, and HP1γ, display rapid on-off dynamics. Here, we investigate whether phase-separation by HP1 proteins can explain these biological observations. Using bulk and single-molecule methods, we show that, within phase-separated HP1α-DNA condensates, HP1α acts as a dynamic liquid, while compacted DNA molecules are constrained in local territories. These condensates are resistant to large forces yet can be readily dissolved by HP1β. Finally, we find that differences in each HP1 paralog’s DNA compaction and phase-separation properties arise from their respective disordered regions. Our findings suggest a generalizable model for genome organization in which a pool of weakly bound proteins collectively capitalize on the polymer properties of DNA to produce self-organizing domains that are simultaneously resistant to large forces at the mesoscale and susceptible to competition at the molecular scale.