Princeton University is a private Ivy League research university in Princeton, New Jersey. Founded in 1746 in Elizabeth as the College of New Jersey, Princeton is the fourth-oldest institution of higher education in the United States and one of the nine colonial colleges chartered before the American Revolution.[a] The institution moved to Newark in 1747, and then to the current site nine years later. It officially became a university in 1896 and was subsequently renamed Princeton University. Princeton is often ranked among the best and most prestigious universities in the world.The university is governed by the Trustees of Princeton University and has an endowment of $37.7 billion, the largest endowment per student in the United States. Princeton provides undergraduate and graduate instruction in the humanities, social sciences, natural sciences, and engineering to approximately 8,500 students on its 600 acres (2.4 km2) main campus. It offers postgraduate degrees through the Princeton School of Public and International Affairs, the School of Engineering and Applied Science, the School of Architecture and the Bendheim Center for Finance. The university also manages the Department of Energy's Princeton Plasma Physics Laboratory and is home to the NOAA's Geophysical Fluid Dynamics Laboratory. It is classified among "R1: Doctoral Universities – Very high research activity" and has one of the largest university libraries in the world.Princeton uses a residential college system and is known for its upperclassmen eating clubs. The university has over 500 student organizations. Princeton students embrace a wide variety of traditions from both the past and present. The university is a NCAA Division I school and competes in the Ivy League. The school's athletic team, the Princeton Tigers, has won the most titles in its conference and has sent many students and alumni to the Olympics.As of October 2021, 75 Nobel laureates, 16 Fields Medalists and 16 Turing Award laureates have been affiliated with Princeton University as alumni, faculty members, or researchers. In addition, Princeton has been associated with 21 National Medal of Science awardees, 5 Abel Prize awardees, 11 National Humanities Medal recipients, 215 Rhodes Scholars and 137 Marshall Scholars. Two U.S. Presidents, twelve U.S. Supreme Court Justices (three of whom currently serve on the court) and numerous living industry and media tycoons and foreign heads of state are all counted among Princeton's alumni body. Princeton has graduated many members of the U.S. Congress and the U.S. Cabinet, including eight Secretaries of State, three Secretaries of Defense and two Chairmen of the Joint Chiefs of Staff.S.S.S.S.S.S.S.S.S.S.S.S.S.S.
Industrial robots are increasingly deployed in construction and manufacturing tasks, where the deployment of end-to-end visuomotor policies is challenged by the observation–execution gap induced by observation, inference, and execution latencies. This gap is often significant on industrial robotic arms due to high-level control interfaces and slower closed-loop dynamics, making execution timing a dominant system-level concern. This paper presents a system-level, latency-aware framework for deploying and evaluating visuomotor policies on industrial robotic arms. The framework integrates latency-calibrated multimodal sensing, data synchronization, a unified communication pipeline, and a teleoperation interface for collecting expert demonstrations. Within this framework, we formalize a latency-aware execution strategy that assigns timestamps to policy-predicted action sequences and schedules only temporally feasible actions according to their intended execution time, enabling asynchronous inference and execution without modifying policy architectures or training procedures. We evaluate the framework on a contact-rich assembly task while systematically varying inference latency and compare latency-aware execution against blocking and naive asynchronous baselines using identical policies and sensing modalities. Results show that latency-aware execution preserves smooth motion, compliant contact behavior, and task progression consistent with demonstrations across inference latencies of 100–500 ms. Latency-aware execution maintained task duration and motion smoothness within 13% and 9% of the demonstration reference, respectively, while avoiding the latency-dependent slowdown observed under blocking execution and the large contact-force overshoots produced by naive asynchronous execution. These findings demonstrate that explicit handling of the observation–execution gap is essential for reproducible, closed-loop deployment of visuomotor policies on industrial robotic platforms.
Background and objective This study presents a computationally and physiologically grounded framework for electromyography (EMG) simulation to examine how assumed cortical and subcortical inputs shape bilateral EMG and intermuscular coherence during bimanual coordination. Methods Simulated first dorsal interosseous (FDI) EMG was generated for a 1:2 force coordination task (approximately 40% maximum voluntary contraction) using motor unit models incorporating (i) variable cortical and subcortical drive weighting, (ii) narrowband versus broadband cortical drive (13–30 vs. 13–60 Hz), and (iii) asymmetric bilateral coupling. Intermuscular EMG–EMG wavelet coherence was computed across α, β, low-γ, and high-γ bands. Model outputs were validated against experimental human EMG at the signal level, comparing simulated and recorded bipolar first dorsal interosseous traces across eight amplitude and frequency-domain signal features. Results Coherence magnitude increased with greater modeled neural crosstalk and cortical weighting. The frequency band most sensitive to drive weighting depended on cortical bandwidth: β-band coherence (13–30 Hz) best differentiated cortical and subcortical influences under narrowband drive, whereas low-γ (30–60 Hz) was most informative under broadband conditions. α-band coherence showed minimal sensitivity to subcortical modulation in this context. Conclusions Within this simulation framework, intermuscular coherence was sensitive to modeled bilateral coupling and cortical-subcortical weighting, with diagnostic sensitivity depending on the spectral bandwidth of cortical drive. Thus, the model should be interpreted as a hypothesis generating, signal level framework rather than a direct neural measurement. This open-source framework bridges computational modeling and biomarker signal analysis, supporting reproducible, hypothesis driven biomarker development for neuromotor disorders such as Parkinson’s disease, spinal cord injury, and stroke.
Radiative emissions from flame chemiluminescence, soot, and high-temperature combustor walls were characterized in two swirl combustors-one premixed gas-fueled and one liquid-fueled-using two pre-calibrated spectrometers spanning 400-2,150 nm range. The measurements resolved radical emission bands (CH*, and C2*) in the visible range (VIS), continuum soot radiation, and near-infrared (NIR) ro-vibrational emissions from H2O and CO2. Across all operating conditions investigated in this study, NIR combustion-product gas emission bands were significant contributors to the total flame radiance, whereas the soot radiation fraction varied substantially with fuel type and operating conditions. In the liquid kerosene-fueled swirl flame, soot radiance accounted for up to 90% of the VIS-NIR flame radiance at a combustor pressure of 12 bar. By contrast, hydrogen enrichment in the premixed methane combustor enhanced NIR H2O emission and increased soot temperature while reducing the effective soot loading parameter fvL, thereby lowering the soot radiation fraction to below 5% of the total flame radiance under fuel-rich conditions. The spectrally resolved datasets obtained in this study provide a valuable benchmark for validating radiation models and for assessing the relative contributions of chemiluminescence, product gas emission bands, and soot emission in both gas- and liquid- fueled swirl combustors.
Spontaneous thought is often considered an unconstrained, internally generated mode of thinking that is independent of the present perceptual environment, making it difficult to study empirically. However, recent accounts have raised the possibility that the generation and content of spontaneous thought can be shaped by even weak perceptual constraints. We leveraged this new perspective to develop a novel approach using music, a ubiquitous stimulus that permeates our everyday environments, as a window into the mechanisms supporting spontaneous thought content. Adults spanning four age groups listened to music from ten different genres and completed the open-ended task of writing descriptions of any thoughts that arose. By applying natural language processing analysis to the spontaneous thought descriptions, we found that thoughts sustained while hearing music from the same genre shared greater semantic similarity than those sustained while hearing music from different genres, and participants from the same age group experienced more similar thoughts than those from different age groups. Properties that varied naturally with genre, including the music’s auditory features, expressed emotions, and contextual associations, all contributed significantly to explaining the greater semantic similarity of thoughts within genres. These results demonstrate that spontaneous thought is jointly shaped by perceptual and experiential constraints, opening new avenues for understanding when and why particular thoughts come to mind, with implications for creativity and mental health.
A novel autoignition-assisted, high-temperature High-Pressure Well-Stirred Turbulent Combustor (HP-WSTC) has been developed for detailed kinetic studies of fuels under gas-turbine conditions that were difficult to obtain with conventional reactors and flame chemistry facilities. It is designed for operations at 1–20 atm, 1200–2200 K, and residence times of 1–100 ms, enabling treatment as a zero-dimensional premixed-combustion system. Methane combustion experiments at 1–10 atm were compared with 0D simulations, showing good agreement for major species across a wide equivalence-ratio range, demonstrating the reliability of the HP-WSTC. Although methane combustion kinetics are well established, NO predictions still show large discrepancies, even at atmospheric pressure. Sensitivity analyses identify CH-pool reactions, including CH2 + O2 = CH2O + O and CH + CO2 = HCO + CO, as key uncertain reactions. The developed HP-WSTC provides a new platform for fuel kinetic investigations and bridges the gap between reactor and flame facilities for high-temperature kinetic studies under gas-turbine conditions.
