Metal requirements for building electrical grid systems of global wind power and utility-scale solar photovoltaic until 2050

Wind and solar photovoltaic (PV) power form vital parts of the energy transition toward renewable energy systems. The rapid development of these two renewables represents an enormous infrastructure construction task including both power generation and its associated electrical grid systems, which will generate demand for metal resources. However, most research on material demands has focused on their power generation systems (wind turbines and PV panels), and few have studied the associated electrical grid systems. Here, we estimate the global metal demands for electrical grid systems associated with wind and utility-scale PV power by 2050, using dynamic material flow analysis based on International Energy Agency's energy scenarios and the typical engineering parameters of transmission grids. Results show that the associated electrical grids require large quantities of metals: 27-81 Mt of copper cumulatively, followed by 20-67 Mt of steel and 11-31 Mt of aluminum. Electrical grids built for solar PV have the largest metal demand, followed by offshore and onshore wind. Power cables are the most metal-consuming electrical components compared to substations and transformers. We also discuss the decommissioning issue of electrical grids and their recovery potential. This study would deepen the understanding of the nexus between renewable energy, grid infrastructure, and metal resources.Industrial Ecolog

Characterization of bulk hexagonal boron nitride single crystals grown by the metal flux technique

The optical and physical properties of hexagonal boron nitride single crystals grown from a molten metal solution are reported. The hBN crystals were grown by precipitation from a nickel-chromium flux with a boron nitride source, by slowly cooling from 1500 °C at 2-4°C/h under a nitrogen flow at atmospheric pressure. The hBN crystals formed on the surface of the flux with an apparent crystal size up to 1 to 2 mm in diameter. Individual grains were as large as 100-200 µm across. Typically, the flakes removed from the metal were 6 to 20 µm thick. Optical absorption measurements suggest a bandgap of 5.8 eV by neglecting the binding energy of excitons in hBN. The highest energy photoluminescence peak was at 5.75 eV at room temperature. The hBN crystals typically had a pit density of 5 x 10⁶ cm⁻² after etching in a molten eutectic mixture of potassium hydroxide and sodium hydroxide. The quality of these crystals suggests they are suitable as substrates for two dimensional materials such as graphene and gallium nitride based devices

Modeling the competition between multiple Automated Mobility on-Demand operators: an agent-based approach

Automated Mobility-on-Demand (AMoD) systems, in which fleets of automated vehicles provide on-demand services, are expected to transform urban mobility systems. Motivated by the rapid development of AMoD services delivered by self-driving car companies, an agent-based model (ABM) has been developed to study the coexistence phenomena of multiple AMoD operators competing for customers. The ABM is used to investigate how changes in pricing strategies, assignment methods, and fleet sizes affect travelers' choice of different AMoD services and the operating performance of competing operators in the case-study city of The Hague, in the Netherlands. Findings suggest that an optimal assignment algorithm can reduce the average waiting time by up to 24% compared to a simple heuristic algorithm. We also find that a larger fleet could increase demand but lead to higher waiting times for its users and higher travel times for competing operators' users due to the added congestion. Notably, pricing strategies can significantly affect travelers' choice of AMoD services, but the effect depends strongly on the time of the day. Low-priced AMoD services can provide high service levels and effectively attract more demand, with up to 64.7% of customers choosing the very early morning service [5:30 AM,7:20 AM]. In the subsequent morning hours, high-priced AMoD services are more competitive in attracting customers as more idle vehicles are available. Based on the quantitative analysis, policies are recommended for the government and service operators. (C) 2022 The Author(s). Published by Elsevier B.V.Industrial Ecolog

Assessing the potential of the strategic formation of urban platoons for shared automated vehicle fleets

This paper addresses the problem of studying the impacts of the strategic formation of platoons in automated mobility-on-demand (AMoD) systems in future cities. Forming platoons has the potential to improve traffic efficiency, resulting in reduced travel times and energy consumption. However, in the platoon formation phase, coordinating the vehicles at formation locations for forming a platoon may delay travelers. In order to assess these effects, an agent-based model has been developed to simulate an urban AMoD system in which vehicles travel between service points transporting passengers either forming or not forming platoons. A simulation study was performed on the road network of the city of The Hague, Netherlands, to assess the impact on traveling and energy usage by the strategic formation of platoons. Results show that forming platoons could save up to 9.6% of the system-wide energy consumption for the most efficient car model. However, this effect can vary significantly with the vehicle types and strategies used to form platoons. Findings suggest that, on average, forming platoons reduces the travel times for travelers even if they experience delays while waiting for a platoon to be formed. However, delays lead to longer travel times for the travelers with the platoon leaders, similar to what people experience while traveling in highly congested networks when platoon formation does not happen. Moreover, the platoon delay increases as the volume of AMoD requests decreases; in the case of an AMoD system serving only 20% of the commuter trips (by private cars in the case-study city), the average platoon delays experienced by these trips increase by 25%. We conclude that it is beneficial to form platoons to achieve energy and travel efficiency goals when the volume of AMoD requests is high.Industrial Ecolog

Cycle-Consistent Generative Adversarial Network: Effect on Radiation Dose Reduction and Image Quality Improvement in Ultralow-Dose CT for Evaluation of Pulmonary Tuberculosis

OBJECTIVE: To investigate the image quality of ultralow-dose CT (ULDCT) of the chest reconstructed using a cycle-consistent generative adversarial network (CycleGAN)-based deep learning method in the evaluation of pulmonary tuberculosis. MATERIALS AND METHODS: Between June 2019 and November 2019, 103 patients (mean age, 40.8 ± 13.6 years; 61 men and 42 women) with pulmonary tuberculosis were prospectively enrolled to undergo standard-dose CT (120 kVp with automated exposure control), followed immediately by ULDCT (80 kVp and 10 mAs). The images of the two successive scans were used to train the CycleGAN framework for image-to-image translation. The denoising efficacy of the CycleGAN algorithm was compared with that of hybrid and model-based iterative reconstruction. Repeated-measures analysis of variance and Wilcoxon signed-rank test were performed to compare the objective measurements and the subjective image quality scores, respectively. RESULTS: With the optimized CycleGAN denoising model, using the ULDCT images as input, the peak signal-to-noise ratio and structural similarity index improved by 2.0 dB and 0.21, respectively. The CycleGAN-generated denoised ULDCT images typically provided satisfactory image quality for optimal visibility of anatomic structures and pathological findings, with a lower level of image noise (mean ± standard deviation [SD], 19.5 ± 3.0 Hounsfield unit [HU]) than that of the hybrid (66.3 ± 10.5 HU, p 0.908). The CycleGAN-generated images showed the highest contrast-to-noise ratios for the pulmonary lesions, followed by the model-based and hybrid iterative reconstruction. The mean effective radiation dose of ULDCT was 0.12 mSv with a mean 93.9% reduction compared to standard-dose CT. CONCLUSION: The optimized CycleGAN technique may allow the synthesis of diagnostically acceptable images from ULDCT of the chest for the evaluation of pulmonary tuberculosis

Nonparametric Segment Detection

Algorithms and the Foundations of Software technolog

Determination of energy-band offsets between GaN and AlN using excitonic luminescence transition in AlGaN alloys

We report the determination of the energy-band offsets between GaN and AlN using the linewidth (full width at half maximum) of an extremely sharp excitonic luminescence transition in Alx Ga1-x N alloy with x=0.18 at 10 K. Our sample was grown on C -plane sapphire substrate by metal-organic chemical-vapor deposition at 1050 °C. The observed value of the excitonic linewidth of 17 meV is the smallest ever reported in literature. On subtracting a typical value of the excitonic linewidth in high-quality GaN, namely, 4.0 meV, we obtain a value of 13.0 meV, which we attribute to compositional disorder. This value is considerably smaller than that calculated using a delocalized exciton model [S. M. Lee and K. K. Bajaj, J. Appl. Phys. 73, 1788 (1993)]. The excitons are known to be strongly localized by defects and/or the potential fluctuations in this alloy system. We have simulated this localization assuming that the hole, being much more massive than the electron, is completely immobile, i.e., the hole mass is treated as infinite. Assuming that the excitonic line broadening is caused entirely by the potential fluctuations experienced by the conduction electron, the value of the conduction-band offset between GaN and AlN is determined to be about 57% of the total-band-gap discontinuity. Using our model we have calculated the variation of the excitonic linewidth as a function of Al composition in our samples with higher Al content larger than 18% and have compared it with the experimental data. We also compare our value of the conduction-band offset with those recently proposed by several other groups using different techniques. © 2006 American Institute of Physics

Two charged strangeonium-like structures observable in the Y(2175)→ϕ(1020)π+π−Y(2175) \to \phi(1020)\pi^{+} \pi^{-} process

Via the Initial Single Pion Emission (ISPE) mechanism, we study the $\phi(1020)\pi^{+}$ invariant mass spectrum distribution of $Y(2175) \to \phi(1020)\pi^{+} \pi^{-}$. Our calculation indicates there exist a sharp peak structure ($Z_{s1}^+$) close to the $K\bar{K}^\ast$ threshold and a broad structure ($Z_{s2}^+$) near the $K^\ast\bar{K}^\ast$ threshold. In addition, we also investigate the $\phi(1680) \to \phi(1020)\pi^{+} \pi^{-}$ process due to the ISPE mechanism, where a sharp peak around the $K\bar{K}^\ast$ threshold appears in the $\phi(1020)\pi^{+}$ invariant mass spectrum distribution. We suggest to carry out the search for these charged strangeonium-like structures in future experiment, especially Belle II, Super-B and BESIII.Comment: 7 pages, 5 figures. Accepted by Eur. Phys. J.

Development of a regional feature selection-based machine learning system (RFSML v1.0) for air pollution forecasting over China

With the explosive growth of atmospheric data, machine learning models have achieved great success in air pollution forecasting because of their higher computational efficiency than the traditional chemical transport models. However, in previous studies, new prediction algorithms have only been tested at stations or in a small region; a large-scale air quality forecasting model remains lacking to date. Huge dimensionality also means that redundant input data may lead to increased complexity and therefore the over-fitting of machine learning models. Feature selection is a key topic in machine learning development, but it has not yet been explored in atmosphere-related applications. In this work, a regional feature selection-based machine learning (RFSML) system was developed, which is capable of predicting air quality in the short term with high accuracy at the national scale. Ensemble-Shapley additive global importance analysis is combined with the RFSML system to extract significant regional features and eliminate redundant variables at an affordable computational expense. The significance of the regional features is also explained physically. Compared with a standard machine learning system fed with relative features, the RFSML system driven by the selected key features results in superior interpretability, less training time, and more accurate predictions. This study also provides insights into the difference in interpretability among machine learning models (i.e., random forest, gradient boosting, and multi-layer perceptron models).Industrial Ecolog

Performance of screening tests for oesophageal squamous cell carcinoma: a systematic review and meta-analysis

Background and Aims: This systematic review and meta-analysis aims to compare the pooled diagnostic accuracy of the currently available esophageal squamous cell carcinoma (ESCC) screening tests. Methods: A comprehensive literature search of Embase and Medline (up to October 31, 2020) was performed to identify eligible studies. We pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) for ESCC screening tools using a bivariate random-effects model. The summary receiver operating characteristic (sROC) curves with area under the curve (AUC) were plotted for each screening test. Results: We included 161 studies conducted in 81 research articles involving 32,209 subjects. The pooled sensitivity, specificity, and AUC (95% CIs) of the major screening tools were: (1). Endoscopy (per-oral endoscopy): 0.94 (0.87-0.97), 0.92 (0.87-0.95), and 0.97 (0.96-0.99); (2) Endoscopy (transnasal endoscopy): 0.85 (0.70-0.93), 0.96 (0.91-0.98), and 0.97 (0.95, -0.98); (3). MicroRNA: 0.77 (0.75-0.80), 0.78 (0.75-0.80), and 0.85 (0.81-0.87); (4). Autoantibody: 0.45 (0.36-0.53), 0.91 (0.89-0.93), and 0.84 (0.81-0.87); and (5). Cytology: 0.82 (0.60-0.93), 0.97 (0.88-0.99), and 0.97 (0.95-0.98). There was high heterogeneity. Conclusions: The diagnostic accuracy seems comparable between Cytology and endoscopy, whilst autoantibody and microRNAs bear potential as future non-invasive screening tools for ESCC. To reduce ESCC-related death in the high-risk populations, it is important to develop a more accurate and less invasive screening test