Large pretrained vision foundation models have shown significant potential in various vision tasks. However, for industrial anomaly detection, the scarcity of real defect samples poses a critical challenge in leveraging these models. While 2D anomaly generation has significantly advanced with established generative models, the adoption of 3D sensors in industrial manufacturing has made leveraging 3D data for surface quality inspection an emerging trend. In contrast to 2D techniques, 3D anomaly generation remains largely unexplored, limiting the potential of 3D data in industrial quality inspection. To address this gap, we propose a novel yet simple 3D anomaly generation method, 3D-PNAS, based on Perlin noise and surface parameterization. Our method generates realistic 3D surface anomalies by projecting the point cloud onto a 2D plane, sampling multi-scale noise values from a Perlin noise field, and perturbing the point cloud along its normal direction. Through comprehensive visualization experiments, we demonstrate how key parameters - including noise scale, perturbation strength, and octaves, provide fine-grained control over the generated anomalies, enabling the creation of diver
Multiple object tracking is a critical task in autonomous driving. Existing works primarily focus on the heuristic design of neural networks to obtain high accuracy. As tracking accuracy improves, however, neural networks become increasingly complex, posing challenges for their practical application in real driving scenarios due to the high level of latency. In this paper, we explore the use of the neural architecture search (NAS) methods to search for efficient architectures for tracking, aiming for low real-time latency while maintaining relatively high accuracy. Another challenge for object tracking is the unreliability of a single sensor, therefore, we propose a multi-modal framework to improve the robustness. Experiments demonstrate that our algorithm can run on edge devices within lower latency constraints, thus greatly reducing the computational requirements for multi-modal object tracking while keeping lower latency.
Scientific research is highly dynamic. New areas of science continually evolve;others gain or lose importance, merge or split. Due to the steady increase in the number of scientific publications it is hard to keep an overview of the structure and dynamic development of one's own field of science, much less all scientific domains. However, knowledge of hot topics, emergent research frontiers, or change of focus in certain areas is a critical component of resource allocation decisions in research labs, governmental institutions, and corporations. This paper demonstrates the utilization of Kleinberg's burst detection algorithm, co-word occurrence analysis, and graph layout techniques to generate maps that support the identification of major research topics and trends. The approach was applied to analyze and map the complete set of papers published in the Proceedings of the National Academy of Sciences (PNAS) in the years 1982-2001. Six domain experts examined and commented on the resulting maps in an attempt to reconstruct the evolution of major research areas covered by PNAS.
Nature, Science, and PNAS are the three most prestigious general-science journals, and Nature and Science are among the most influential journals overall, based on the journal Impact Factor (IF). In this paper we perform automatic classification of ~50,000 articles in these journals (published in the period 2005-2015) into 14 broad areas, to explore disciplinary profiles and to determine their field-specific IFs. We find that in all three journals the articles from Bioscience, Astronomy, and Geosciences are over-represented, with other areas being under-represented, some of them severely. Discipline-specific IFs in these journals vary greatly, for example, between 18 and 46 for Nature. We find that the areas that have the highest disciplinary IFs are not the ones that contribute the most articles. We also find that publishing articles in these three journals brings prestige for articles in all areas, but at different levels, the least being for Astronomy. Comparing field-specific IFs of Nature, Science and PNAS to other top journals in six largest areas (Bioscience, Medicine, Geosciences, Physics, Astronomy, and Chemistry) these three journals are always among the top seven journal
The features of collaboration patterns are often considered to be different from discipline to discipline. Meanwhile, collaborating among disciplines is an obvious feature emerged in modern scientific research, which incubates several interdisciplines. The features of collaborations in and among the disciplines of biological, physical and social sciences are analyzed based on 52,803 papers published in a multidisciplinary journal PNAS during 1999 to 2013. From those data, we found similar transitivity and assortativity of collaboration patterns as well as the identical distribution type of collaborators per author and that of papers per author, namely a mixture of generalized Poisson and power-law distributions. In addition, we found that interdisciplinary research is undertaken by a considerable fraction of authors, not just those with many collaborators or those with many papers. This case study provides a window for understanding aspects of multidisciplinary and interdisciplinary collaboration patterns.
The strongly correlated spin-triplet superconductor UTe2 hosts an unusual landscape of magnetic-field-sensitive charge density wave (CDW) phases, positioning it as a compelling system for studying intertwined electronic orders. A central challenge is determining whether the observed charge modulations arise from a triplet pair density wave (PDW) order and, if so, how the anisotropic magnetic field response of triplet superconductivity is manifested in the CDW response. Here, using a scanning tunneling microscope equipped with a vector magnetic field, we systematically investigate the evolution and interrelation of distinct CDW orders. Complementing the previously identified incommensurate CDW peaks (qi=1,2,3), we resolve an additional set of nondispersive modulations (pi=1,2,3 and h1,2) with distinct temperature and magnetic field dependencies. The pi CDW peaks vanish near Tc, while the qi peaks survive well above Tc but are progressively suppressed by magnetic field in an anisotropic manner. The critical fields of the qi peaks mirror the directional hierarchy of Hc2, which suggests a PDW is present above the bulk Tc. This is consistent with a Landau free-energy picture where PDWs
In a recent paper, PNAS, 118, e1921529118 (2021), it was argued that while the standard definition of conservation laws in quantum mechanics, which is of a statistical character, is perfectly valid, it misses essential features of nature and it can and must be revisited to address the issue of conservation/non-conservation in individual cases. Specifically, in the above paper an experiment was presented in which it can be proven that in some individual cases energy is not conserved, despite being conserved statistically. It was felt however that this is worrisome, and that something must be wrong if there are individual instances in which conservation doesn't hold, even though this is not required by the standard conservation law. Here we revisit that experiment and show that although its results are correct, there is a way to circumvent them and ensure individual case conservation in that situation. The solution is however quite unusual, challenging one of the basic assumptions of quantum mechanics, namely that any quantum state can be prepared, and it involves a time-holistic, double non-conservation effect. Our results bring new light on the role of the preparation stage of the
A combination of ultrafast, long-range and low-loss excitation energy transfer from the photo-receptor location to a functionally active site is essential for cost-effective polymeric semiconductors. Delocalized electronic wavefunctions along π-conjugated polymer backbone can enable efficient intrachain transport, while interchain transport is generally thought slow and lossy due to weak chain-chain interactions. In contrast to the conventional strategy of mitigating structural disorder, amorphous layers of rigid conjugated polymers, exemplified by highly planar poly(indacenodithiophene-co-benzothiadiazole) (IDT-BT) donor-accepter copolymer, exhibit trap-free transistor performance and charge-carrier mobilities similar to amorphous silicon. Here we report long-range exciton transport in HJ-aggregated IDTBT thin-film, in which the competing exciton transport and exciton-exciton annihilation (EEA) dynamics are spectroscopically separated using a phase-cycling-based scheme and shown to depart from the classical iffusion-limited and strong-coupling regime. In the thin film, we find an annihilation-limited mechanism with a per-encounter annihilation probability of much less than 100%, f
Social networks profoundly influence how humans form opinions, exchange information, and organize collectively. As large language models (LLMs) are increasingly embedded into social and professional environments, it is critical to understand whether their interactions approximate human-like network dynamics. We develop a framework to study the network formation behaviors of multiple LLM agents and benchmark them against human decisions. Across synthetic and real-world settings, including friendship, telecommunication, and employment networks, we find that LLMs consistently reproduce fundamental micro-level principles such as preferential attachment, triadic closure, and homophily, as well as macro-level properties including community structure and small-world effects. Importantly, the relative emphasis of these principles adapts to context: for example, LLMs favor homophily in friendship networks but heterophily in organizational settings, mirroring patterns of social mobility. A controlled human-subject survey confirms strong alignment between LLMs and human participants in link-formation decisions. These results establish that LLMs can serve as powerful tools for social simulatio
The ground state of a one-dimensional spin-1/2 uniform antiferromagnetic Heisenberg chain (AfHc) is a Tomonaga-Luttinger liquid which is quantum-critical with respect to applied magnetic fields upto a saturation field Hs beyond which it transforms to a fully polarised state. Wilson ratio has been predicted to be a good indicator for demarcating these phases [Phys. Rev. B 96, 220401 (2017)]. From detailed temperature and magnetic field dependent magnetisation, magnetic susceptibility and specific heat measurements in a metalorganic complex and comparisons with field theory and quantum transfer matrix method calculations, the complex was found to be a very good realisation of a spin-1/2 AfHc. Wilson ratio obtained from experimentally obtained magnetic susceptibility and magnetic contribution of specific heat values was used to map the magnetic phase diagram of the uniform spin-1/2 AfHc over large regions of phase space demarcating Tomonaga-Luttinger liquid, saturation field quantum critical, and fully polarised states. Luttinger parameter and spinon velocity were found to match very well with the values predicted from conformal field theory.
The deformation mechanism in amorphous solids subjected to external shear remains poorly understood because of the absence of well-defined topological defects mediating the plastic deformation. The notion of soft spots has emerged as a useful tool to characterize the onset of irreversible rearrangements and plastic flow, but these entities are not clearly defined in terms of geometry and topology. In this study, we unveil the phenomenology of recently discovered, precisely defined topological defects governing the microscopic mechanical and yielding behavior of a model 3D glass under shear deformation. We identify the existence of vortex-like and anti-vortex-like topological defects within the 3D non-affine displacement field. The number density of these defects exhibits a significant anti-correlation with the plastic events, with defect proliferation-annihilation cycles matching the alternation of elastic-like segments and catastrophic plastic drops, respectively. Furthermore, we observe collective annihilation of these point-like defects via plastic events, with large local topological charge fluctuations in the vicinity of regions that feature strong non-affine displacements. We
Quantum computers have been proposed to solve a number of important problems such as discovering new drugs, new catalysts for fertilizer production, breaking encryption protocols, optimizing financial portfolios, or implementing new artificial intelligence applications. Yet, to date, a simple task such as multiplying 3 by 5 is beyond existing quantum hardware. This article examines the difficulties that would need to be solved for quantum computers to live up to their promises. I discuss the whole stack of technologies that has been envisioned to build a quantum computer from the top layers (the actual algorithms and associated applications) down to the very bottom ones (the quantum hardware, its control electronics, cryogeny, etc.) while not forgetting the crucial intermediate layer of quantum error correction.
Direct detection of spontaneous spin fluctuations, or "magnetization noise", is emerging as a powerful means of revealing and studying magnetic excitations in both natural and artificial frustrated magnets. Depending on the lattice and nature of the frustration, these excitations can often be described as fractionalized quasiparticles possessing an effective magnetic charge. Here, by combining ultrasensitive optical detection of thermodynamic magnetization noise with Monte Carlo simulations, we reveal emergent regimes of magnetic excitations in artificial "tetris ice". A marked increase of the intrinsic noise at certain applied magnetic fields heralds the spontaneous proliferation of fractionalized excitations, which can diffuse independently, without cost in energy, along specific quasi-1D spin chains in the tetris ice lattice.
Nonequilibrium quantum dynamics of many-body systems is the frontier of condensed matter physics; recent advances in various time-resolved spectroscopic techniques continue to reveal rich phenomena. Angle-resolved photoemission spectroscopy (ARPES) as one powerful technique can resolve electronic energy, momentum, and spin along the time axis after excitation. However, dynamics of spin textures in momentum space remains mostly unexplored. Here we demonstrate theoretically that the photoexcited surface state of genuine or magnetically doped topological insulators shows novel topological spin textures, i.e., tornado-like patterns, in the spin-resolved ARPES. We systematically reveal its origin as a unique nonequilibrium photoinduced topological winding phenomenon. As all intrinsic and extrinsic topological helicity factors of both material and light are embedded in a robust and delicate manner, the tornado patterns not only allow a remarkable tomography of such important system information, but also enable various unique dichroic topological switchings of the momentum-space spin texture. These results open a new direction of nonequilibrium topological spin states in quantum materials
Many of the unusual properties of Pluto's orbit are widely accepted as evidence for the orbital migration of the giant planets in early solar system history. However, some properties remain an enigma. Pluto's long term orbital stability is supported by two special properties of its orbit that limit the location of its perihelion in azimuth and in latitude. We revisit Pluto's orbital dynamics with a view to elucidating the individual and collective gravitational effects of the giant planets on constraining its perihelion location. While the resonant perturbations from Neptune account for the azimuthal constraint on Pluto's perihelion location, we demonstrate that the long term and steady persistence of the latitudinal constraint is possible only in a narrow range of additional secular forcing which arises fortuitously from the particular orbital architecture of the other giant planets. Our investigations also find that Jupiter has a largely stabilizing influence whereas Uranus has a largely destabilizing influence on Pluto's orbit. Overall, Pluto's orbit is rather surprisingly close to a zone of strong chaos.
This is a commentary on two papers (PNAS 117 (51) 32244-32250 (2020) and arXiv:2011.06721), which observed a series of ordering transitions in a strongly correlated two-dimensional electron system confined to a AlAs quantum well. We summarize the main discoveries (electron nematicity, insulating ferromagnetism, etc.) of them and speculate on $T-r_s$ phase diagram based on theoretical considerations.
The bacterial flagellar motor drives the rotation of flagellar filaments and enables many species of bacteria to swim. Torque is generated by interaction of stator units, anchored to the peptidoglycan cell wall, with the rotor. Recent experiments [Yuan, J. & Berg, H. C. (2008) PNAS 105, 1182-1185] show that near zero load the speed of the motor is independent of the number of stators. Here, we introduce a mathematical model of the motor dynamics that explains this behavior based on a general assumption that the stepping rate of a stator depends on the torque exerted by the stator on the rotor. We find that the motor dynamics can be characterized by two time scales: the moving-time interval for the mechanical rotation of the rotor and the waiting-time interval determined by the chemical transitions of the stators. We show that these two time scales depend differently on the load, and that their crossover provides the microscopic explanation for the existence of two regimes in the torque-speed curves observed experimentally. We also analyze the speed fluctuation for a single motor using our model. We show that the motion is smoothed by having more stator units. However, the mecha
It is pointed out that the mystery of how biological systems measure their lengths vanishes away if one premises that they have discovered a way to generate linear waves analogous to compressional sound. These can be used to detect length at either large or small scales using echo timing and fringe counting. It is shown that suitable linear chemical potential waves can, in fact, be manufactured by tuning to criticality conventional reaction-diffusion with a small number substances. Min oscillations in E. coli are cited as precedent resonant length measurement using chemical potential waves analogous to laser detection. Mitotic structures in eucaryotes are identified as candidates for such an effect at higher frequency. The engineering principle is shown to be very general and functionally the same as that used by hearing organs. PNAS Significance Statement: This paper invokes physical principles to address the question of how living things might use reaction-diffusion to measure out and regulate the many thousands of lengths required to make their body parts and internal organs. It argues that two ideas have been missing. One is that oscillation is necessary to achieve the necessar
Whether aneuploid cells with diverse karyotypes have any properties in common has a been a subject of intense interest. A recent study by Terhorst et al. (1) reinvestigated the common aneuploidy gene expression (CAGE), disputing the conclusion of our recent work (2). In this short article, which has been submitted to PNAS as a Letter to the Editor, we explain our major concerns about Terhorst et al. and why we believe that our previous conclusion stands valid.
Convection is the mechanism by which energy is transported through the outermost 30% of the Sun. Solar turbulent convection is notoriously difficult to model across the entire convection zone where the density spans many orders of magnitude. In this issue of PNAS, Hanasoge et al. (2012) employ recent helioseismic observations to derive stringent empirical constraints on the amplitude of large-scale convective velocities in the solar interior. They report an upper limit that is far smaller than predicted by a popular hydrodynamic numerical simulation.