Workers' Compensation

Apresentação do tema em debate sobre a "qualidade da vida"

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

NASA space station automation: AI-based technology review. Executive summary

Research and Development projects in automation technology for the Space Station are described. Artificial Intelligence (AI) based technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics

Symmetry breaking perturbations and strange attractors

The asymmetrically forced, damped Duffing oscillator is introduced as a prototype model for analyzing the homoclinic tangle of symmetric dissipative systems with \textit{symmetry breaking} disturbances. Even a slight fixed asymmetry in the perturbation may cause a substantial change in the asymptotic behavior of the system, e.g. transitions from two sided to one sided strange attractors as the other parameters are varied. Moreover, slight asymmetries may cause substantial asymmetries in the relative size of the basins of attraction of the unforced nearly symmetric attracting regions. These changes seems to be associated with homoclinic bifurcations. Numerical evidence indicates that \textit{strange attractors} appear near curves corresponding to specific secondary homoclinic bifurcations. These curves are found using analytical perturbational tools

Bulk and film synthesis pathways to ternary magnesium tungsten nitrides

Bulk solid state synthesis of nitride materials usually leads to thermodynamically stable, cation-ordered crystal structures, whereas thin film synthesis tends to favor disordered, metastable phases. This dichotomy is inconvenient both for basic materials discovery, where non-equilibrium thin film synthesis methods can be useful to overcome reaction kinetic barriers, and for practical technology applications where stable ground state structures are sometimes required. Here, we explore the uncharted Mg-W-N chemical phase space, using rapid thermal annealing to reconcile the differences between thin film and bulk powder syntheses. Combinatorial co-sputtering synthesis from Mg and W targets in a N$_2$ environment yielded cation-disordered Mg-W-N phases in the rocksalt (0.1< Mg/(Mg+W) <0.9), and hexagonal boron nitride (0.7< Mg/(Mg+W) <0.9) structure types. In contrast, bulk synthesis produced a cation-ordered polymorph of MgWN$_2$ that consists of alternating layers of rocksalt-like [MgN$_6$] octahedra and nickeline-like [WN$_6$] trigonal prisms (denoted "rocksaline"). Thermodynamic calculations corroborate these observations, showing rocksaline MgWN$_2$ is stable while other polymorphs are metastable. We also show that rapid thermal annealing can convert disordered rocksalt films to this cation-ordered polymorph near the MgWN$_2$ stoichiometry. Electronic structure calculations suggest that this rocksalt-to-rocksaline structural transformation should also drive a metallic-to-semiconductor transformation. In addition to revealing three new phases (rocksalt MgWN$_2$ and Mg$_3$WN$_4$, hexagonal boron nitride Mg$_3$WN$_4$, and rocksaline MgWN$_2$), these findings highlight how rapid thermal annealing can control polymorphic transformations, adding a new strategy for exploration of thermodynamic stability in uncharted phase spaces

Noise auto-correlation spectroscopy with coherent Raman scattering

Ultrafast lasers have become one of the most powerful tools in coherent nonlinear optical spectroscopy. Short pulses enable direct observation of fast molecular dynamics, whereas broad spectral bandwidth offers ways of controlling nonlinear optical processes by means of quantum interferences. Special care is usually taken to preserve the coherence of laser pulses as it determines the accuracy of a spectroscopic measurement. Here we present a new approach to coherent Raman spectroscopy based on deliberately introduced noise, which increases the spectral resolution, robustness and efficiency. We probe laser induced molecular vibrations using a broadband laser pulse with intentionally randomized amplitude and phase. The vibrational resonances result in and are identified through the appearance of intensity correlations in the noisy spectrum of coherently scattered photons. Spectral resolution is neither limited by the pulse bandwidth, nor sensitive to the quality of the temporal and spectral profile of the pulses. This is particularly attractive for the applications in microscopy, biological imaging and remote sensing, where dispersion and scattering properties of the medium often undermine the applicability of ultrafast lasers. The proposed method combines the efficiency and resolution of a coherent process with the robustness of incoherent light. As we demonstrate here, it can be implemented by simply destroying the coherence of a laser pulse, and without any elaborate temporal scanning or spectral shaping commonly required by the frequency-resolved spectroscopic methods with ultrashort pulses.Comment: To appear in Nature Physic

The relationship between video display terminals (VDTs) usage and dermatologic manifestations : a cross sectional study

BACKGROUND: Recently, it has been observed that Video Display Terminals (VDTs) usage for long periods can cause some dermatological manifestations on the face. An analytical cross-sectional study was designed in order to determine this relationship. METHODS: In this study, 600 office workers were chosen randomly from an organization in Tehran (Iran). The subjects were then divided into two groups based on their exposure to VDTs. 306 workers were considered exposure negative (non VDT user) who worked less than 7 hours a week with VDTs. The remainders 294 were exposure-positive, who worked 7 hours or more with VDTs. The frequency of dermatologic manifestations was compared in these two groups. RESULTS: In the exposure-positive and exposure-negative groups, the frequency of these dermatologic manifestations were 27 and 5 respectively. After statistical analysis, a P.value of < 0.05 was obtained indicating a statistically significant difference between these two groups for dermatological manifestations. CONCLUSION: According to our study, there is a relationship between dermatologic manifestations on the face and exposure to VDTs

Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions

Recent advances in attention-free sequence models rely on convolutions as alternatives to the attention operator at the core of Transformers. In particular, long convolution sequence models have achieved state-of-the-art performance in many domains, but incur a significant cost during auto-regressive inference workloads -- naively requiring a full pass (or caching of activations) over the input sequence for each generated token -- similarly to attention-based models. In this paper, we seek to enable $\mathcal O(1)$ compute and memory cost per token in any pre-trained long convolution architecture to reduce memory footprint and increase throughput during generation. Concretely, our methods consist in extracting low-dimensional linear state-space models from each convolution layer, building upon rational interpolation and model-order reduction techniques. We further introduce architectural improvements to convolution-based layers such as Hyena: by weight-tying the filters across channels into heads, we achieve higher pre-training quality and reduce the number of filters to be distilled. The resulting model achieves 10x higher throughput than Transformers and 1.5x higher than Hyena at 1.3B parameters, without any loss in quality after distillation