Intense ultraviolet emission from needle-like WO3 nanostructures synthesized by noncatalytic thermal evaporation

Photoluminescence measurements showed that needle-like tungsten oxide nanostructures synthesized at 590°C to 750°C by the thermal evaporation of WO3 nanopowders without the use of a catalyst had an intense near-ultraviolet (NUV) emission band that was different from that of the tungsten oxide nanostructures obtained in other temperature ranges. The intense NUV emission might be due to the localized states associated with oxygen vacancies and surface states

Programmable spectral shaping to improve the measurement precision of frequency comb mode-resolved spectral interferometric ranging

Comb-mode resolved spectral domain interferometry (CORE-SDI), which is capable of measuring length of kilometers or more with precision on the order of nanometers, is considered to be a promising technology for next-generation length standards, replacing laser displacement interferometers. In this study, we aim to improve the measurement precision of CORE-SDI using programmable spectral shaping. We report the generation of effectively broad and symmetric light sources through the programmable spectral shaping. The light source used here was generated by the spectrally-broadened electro-optic comb with a repetition rate of 17.5 GHz. Through the programmable spectral shaping, the optical spectrum was flattened within 1 dB, resulting in a square-shaped optical spectrum. As a result, the 3-dB spectral width was extended from 1.15 THz to 6.7 THz. We performed a comparison between the measurement results of various spectrum shapes. We confirmed an improvement in the measurement precision from 69 nm to 6 nm, which was also corroborated by numerical simulations. We believe that this study on enhancing the measurement precision of CORE-SDI through the proposed spectral shaping will make a significant contribution to reducing the measurement uncertainty of future CORE-SDI systems, thereby advancing the development of next-generation length standards.Comment: 22 pages, 10 figure

Public-Good Nature of Environmental Conflicts : Individual and Collective Litigations

In environmental conflicts where private citizens sue a polluter, a private citizens participation in the fight for environmental damages is characterized by the public good nature. We examine how the introduction of collective litigation and asymmetric reimbursement rule affects each citizen's choice between free-riding and participation in the collective litigation. Following a Stackelberg model, we assume that citizens move first and the firm follows, while each citizen has to state his environmental damages to the court in the process. Important findings are as follows: First, in the individual litigation, the hungriest citizen who most highly values environmental damages is the only one to participate. Second, in the collective litigation, all citizens participate, provided the total damages of the citizens' group are sufficiently larger than the damages of the hungriest citizen. Third, under certain conditions, introduction of the asymmetric reimbursement rule enhances the possibility that all citizens participate in the collective litigation

Emerging respiratory infections threatening public health in the Asia-Pacific region: a position paper of the Asian Pacific Society of Respirology

In past decades, we have seen several epidemics of respiratory infections from newly emerging viruses, most of which originated in animals. These emerging infections, including severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV) and the pandemic influenza A(H1N1) and avian influenza (AI) viruses, have seriously threatened global health and the economy. In particular, MERS-CoV and AI A(H7N9) are still causing infections in several areas, and some clustering of cases of A(H5N1) and A(H7N9) may imply future possible pandemics. Additionally, given the inappropriate use of antibiotics and international travel, the spread of carbapenem-resistant Gram-negative bacteria is also a significant concern. These infections with epidemic or pandemic potential present a persistent threat to public health and a huge burden on healthcare services in the Asia-Pacific region. Therefore, to enable efficient infection prevention and control, more effective international surveillance and collaboration systems, in the context of the ‘One Health’ approach, are necessary

Multi-task Learning for Real-time Autonomous Driving Leveraging Task-adaptive Attention Generator

Real-time processing is crucial in autonomous driving systems due to the imperative of instantaneous decision-making and rapid response. In real-world scenarios, autonomous vehicles are continuously tasked with interpreting their surroundings, analyzing intricate sensor data, and making decisions within split seconds to ensure safety through numerous computer vision tasks. In this paper, we present a new real-time multi-task network adept at three vital autonomous driving tasks: monocular 3D object detection, semantic segmentation, and dense depth estimation. To counter the challenge of negative transfer, which is the prevalent issue in multi-task learning, we introduce a task-adaptive attention generator. This generator is designed to automatically discern interrelations across the three tasks and arrange the task-sharing pattern, all while leveraging the efficiency of the hard-parameter sharing approach. To the best of our knowledge, the proposed model is pioneering in its capability to concurrently handle multiple tasks, notably 3D object detection, while maintaining real-time processing speeds. Our rigorously optimized network, when tested on the Cityscapes-3D datasets, consistently outperforms various baseline models. Moreover, an in-depth ablation study substantiates the efficacy of the methodologies integrated into our framework.Comment: Accepted at ICRA 202