Continuous-Wave Multiphoton Photoemission from Plasmonic Nanostars

Highly nonlinear optical processes, such as multiphoton photoemission, require high intensities, typically achieved with ultrashort laser pulses and, hence, were first observed with the advent of picosecond laser technology. An alternative approach for reaching the required field intensities is offered by localized optical resonances such as plasmons. Here, we demonstrate localized multiphoton photoemission from plasmonic nanostructures under continuous-wave illumination. We use synthesized plasmonic gold nanostars, which exhibit sharp tips with structural features smaller than 5 nm, leading to near-field-intensity enhancements exceeding 1000. This large enhancement facilitates 3-photon photoemission driven by a simple continuous-wave laser diode. We characterize the intensity and polarization dependencies of the photoemission yield from both individual nanostars and ensembles. Numerical simulations of the plasmonic enhancement, the near-field distributions, and the photoemission intensities are in good agreement with experiment. Our results open a new avenue for the design of nanoscale electron sources

Proposal Of New Turkish Production System NTPS: Integration And Evolution Of Japanese And Turkish Production System

The authors propose a New Turkish Production System (NTPS) with the objective of the integration and evolution of the Toyota Production System, the leading Japanese production system, and the Traditional Turkish Production System, for the growth of the next-generation automobile industry in the Republic of Turkey

Circular (de)construction matchmaking:A matter of space and time

Industrial symbiosis (IS) facilitates the transition toward a circular built environment. Following IS principles, multiple buildings can be symbiotically linked via closed-loop material flows beyond the boundaries of individual projects. However, there are few IS matchmaking methods that support the identification of IS opportunities among multiple deconstruction and construction projects. This research develops an agent-based model to fill this gap. The agent architecture is designed based on the concept of shearing layers. Circularity hubs are proposed to support IS matchmaking by allowing larger transportation ranges and keeping IS requests active for longer periods. The model's applicability is demonstrated through an industrial–urban symbiosis case in Enschede, the Netherlands. The model simulates the spatial–temporal dynamics of IS matchmaking as an emergent phenomenon under future scenarios. The results show operational evidence of IS matchmaking via the strategic implementation of circularity hubs. Overall, this research provides a new methodological perspective to explore the circularity in the built environment at scale.</p

Circularity Reinforcement of Critical Raw Materials in Europe: A Case of Niobium

Critical Raw Materials attract increasing attention due to their depleting reserves and low recyclability. Niobium, one of the most rare and vital elements, is primarily found in Brazil. This research explores the potential impact of Circular Economy (CE) strategies on mitigating niobium's criticality within Europe. First, a niobium supply chain is designed and analysed by Enterprise Input–Output modelling. Second, the supply risk is calculated based on the criticality matrix proposed by the European Commission under three scenarios associated with resources, technologies, and policies. The results show that urban mining is a potential solution to reduce niobium’s criticality and mitigate its environmental impacts. A higher recycling input rate and/or a mix of recycling and substitution strategies is necessary to offset niobium’s criticality. Aligned with the CE action plan, the research offers a scientific foundation to strategically prevent the risk of niobium supply shortages

Solubility and decomposition of organic compounds in subcritical water

In this article, studies on organic solubility and stability in subcritical water reported during the past 25 years have been reviewed. Data on the solubility and decomposition of organic compounds in subcritical water, a green solvent, are needed in environmental remediation, chemistry, chemical engineering, medicine, polymer, food, agriculture, and many other fields. For solubility studies, the experimental systems used to measure solubility, mathematical equations derived and applied for the modeling of the experimentally determined solubility data, and the correlation between the predicated and experimental data have been summarized and discussed. This paper also reviewed organic decomposition under subcritical water conditions. In general, the solubility of organics is significantly enhanced with increasing water temperature. Likewise, the percentage of organic decomposition also increases with higher temperature

Prior Knowledge based Advanced Persistent Threats Detection for IoT in a Realistic Benchmark

The number of Internet of Things (IoT) devices being deployed into networks is growing at a phenomenal level, which makes IoT networks more vulnerable in the wireless medium. Advanced Persistent Threat (APT) is malicious to most of the network facilities and the available attack data for training the machine learning-based Intrusion Detection System (IDS) is limited when compared to the normal traffic. Therefore, it is quite challenging to enhance the detection performance in order to mitigate the influence of APT. Therefore, Prior Knowledge Input (PKI) models are proposed and tested using the SCVIC-APT- 2021 dataset. To obtain prior knowledge, the proposed PKI model pre-classifies the original dataset with unsupervised clustering method. Then, the obtained prior knowledge is incorporated into the supervised model to decrease training complexity and assist the supervised model in determining the optimal mapping between the raw data and true labels. The experimental findings indicate that the PKI model outperforms the supervised baseline, with the best macro average F1-score of 81.37%, which is 10.47% higher than the baseline.Comment: IEEE Global Communications Conference (Globecom), 2022, 6 pages, g figures, 6 table

Machine Learning-Enabled IoT Security: Open Issues and Challenges Under Advanced Persistent Threats

Despite its technological benefits, Internet of Things (IoT) has cyber weaknesses due to the vulnerabilities in the wireless medium. Machine learning (ML)-based methods are widely used against cyber threats in IoT networks with promising performance. Advanced persistent threat (APT) is prominent for cybercriminals to compromise networks, and it is crucial to long-term and harmful characteristics. However, it is difficult to apply ML-based approaches to identify APT attacks to obtain a promising detection performance due to an extremely small percentage among normal traffic. There are limited surveys to fully investigate APT attacks in IoT networks due to the lack of public datasets with all types of APT attacks. It is worth to bridge the state-of-the-art in network attack detection with APT attack detection in a comprehensive review article. This survey article reviews the security challenges in IoT networks and presents the well-known attacks, APT attacks, and threat models in IoT systems. Meanwhile, signature-based, anomaly-based, and hybrid intrusion detection systems are summarized for IoT networks. The article highlights statistical insights regarding frequently applied ML-based methods against network intrusion alongside the number of attacks types detected. Finally, open issues and challenges for common network intrusion and APT attacks are presented for future research.Comment: ACM Computing Surveys, 2022, 35 pages, 10 Figures, 8 Table

Use of emission spectroscopy for real-time assessment of relative wall erosion rate of BHT-200 hall thruster for various regimes of operation

Radiation emission due to Boron atoms sputtered from the Boron-Nitride ceramic walls of a BHT-200 Hall thruster was measured as a diagnostic for real time assessment of thruster wall erosion and to determine the e ects of various operation conditions on thruster lifetime. Boron neutral 249.677 and 249.773nm lines were measured using a high resolution spectrometer. Spectral measurement results and the accompanying analysis and discussion are presented in this study. From the spectral measurements it was observed that the Boron emission intensity significantly increases for increased discharge voltage pointing to a large increase in the thruster wall erosion rate. Additionally, the measurements show that for the nominal discharge voltage and the applied magnetic field intensity, there is an optimum propellant flow rate for minimum Boron emission, thus minimum wall erosion rate. The variation in the current to the magnet coils showed that the Boron emission intensity increases for increased magnetic field and the Boron emission intensity shows similar behavior to that of the Xenon single ion emission line intensity at 248.911nm. The findings of the study show that emission spectroscopy can be used in determining the optimum operational parameters for minimum wall erosion for SPT type Hall thrusters

5IDER: Unified Query Rewriting for Steering, Intent Carryover, Disfluencies, Entity Carryover and Repair

Providing voice assistants the ability to navigate multi-turn conversations is a challenging problem. Handling multi-turn interactions requires the system to understand various conversational use-cases, such as steering, intent carryover, disfluencies, entity carryover, and repair. The complexity of this problem is compounded by the fact that these use-cases mix with each other, often appearing simultaneously in natural language. This work proposes a non-autoregressive query rewriting architecture that can handle not only the five aforementioned tasks, but also complex compositions of these use-cases. We show that our proposed model has competitive single task performance compared to the baseline approach, and even outperforms a fine-tuned T5 model in use-case compositions, despite being 15 times smaller in parameters and 25 times faster in latency.Comment: Interspeech 202