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In an era of unprecedented global mobility, artists face unique challenges. How does cultural context affect the interpretation of art? What makes artists work transnational or national in character, and how will their visibility be impacted by either label? Art and the Politics of Visibility questions these dynamics, asking how the dissemination of visual culture on a global scale affects art and its institutions. Taking Shanghai-based artist Yang Fudong's practice as a point of departure, this volume focuses on how politically charged images produced in contemporary art, cinema, news media and fashion become widely consumed or marginalised. Through case studies of artists and institutions including Isaac Julien, Wafaa Bilal, Jeremy Deller and the itinerant biennale Manifesta, the book illuminates the relationship between visibility, politics and identity in contemporary art.

Quantum delayed-choice experiments are designed to probe the robustness of the complementarity principle. In this proceeding, we revisit the main ideas reported recently in Ref. [Commun. Phys. 5, 82 (2022)] concerning a setup (quantum-controlled reality experiment) that has the same final visibility as the quantum version of Wheeler’s delayed-choice arrangement. Besides the same final statistics, upon an operational criterion of physical realism, the authors claimed a different state of affairs for the wave-and-particle behavior in delayed-choice experiments. To this end, we put forward an analysis by employing the relative entropy of coherence to study how the local wave and particle coherences when the system is traveling inside the interferometer change accordingly to the final observed visibility.

This work explores precision limits in two-photon Hong-Ou-Mandel interferometry under non-perfect visibility. A theoretical model is developed and experimentally validated using different quantum states. A remarkable ratio of 0.97 between the experimental precision and the quantum limit is observed, establishing a new benchmark in the field.

This review paper summarizes current knowledge available for aviation operations related to meteorology and provides suggestions for necessary improvements in the measurement and prediction of weather-related parameters, new physical methods for numerical weather predictions (NWP), and next-generation integrated systems. Severe weather can disrupt aviation operations on the ground or in-flight. The most important parameters related to aviation meteorology are wind and turbulence, fog visibility, aerosol/ash loading, ceiling, rain and snow amount and rates, icing, ice microphysical parameters, convection and precipitation intensity, microbursts, hail, and lightning. Measurements of these parameters are functions of sensor response times and measurement thresholds in extreme weather conditions. In addition to these, airport environments can also play an important role leading to intensification of extreme weather conditions or high impact weather events, e.g., anthropogenic ice fog. To observe meteorological parameters, new remote sensing platforms, namely wind LIDAR, sodars, radars, and geostationary satellites, and in situ instruments at the surface and in the atmosphere, as well as aircraft and Unmanned Aerial Vehicles mounted sensors, are becoming more common. At smaller time and space scales (e.g., < 1 km), meteorological forecasts from NWP models need to be continuously improved for accurate physical parameterizations. Aviation weather forecasts also need to be developed to provide detailed information that represents both deterministic and statistical approaches. In this review, we present available resources and issues for aviation meteorology and evaluate them for required improvements related to measurements, nowcasting, forecasting, and climate change, and emphasize future challenges.

Extreme smog in India widely impacts air quality in late autumn and winter months. While the links between emissions, air quality and health impacts are well-recognized, the association of smog and its intensification with climatic trends in the lower troposphere, where aerosol pollution and its radiative effects manifest, are not understood well. Here we use long-term satellite data to show a significant increase in aerosol exceedances over northern India, resulting in sustained atmospheric warming and surface cooling trends over the last two decades. We find several lines of evidence suggesting these aerosol radiative effects have induced a multidecadal (1980–2019) strengthening of lower tropospheric stability and increase in relative humidity, leading to over fivefold increase in poor visibility days. Given this crucial aerosol-radiation-meteorological feedback driving the smog intensification, results from this study would help inform mitigation strategies supporting stronger region-wide measures, which are critical for solving the smog challenge in India.

Given a graph , a mutual-visibility coloring of is a coloring of the vertices of satisfying the following. Two vertices can be colored with the same color, if there is a shortest -path whose internal vertices have different colors than and . The smallest number of colors among all mutual-visibility colorings of is the mutual-visibility chromatic number of , which is denoted by . Relationships between and its two parent ones, the chromatic number and the mutual-visibility number, are presented. Graphs of diameter two are considered, and in particular, the asymptotic growth of the mutual-visibility number of the Cartesian product of complete graphs is determined. A greedy algorithm that finds a mutual-visibility coloring is designed, and several possible scenarios on its efficiency are discussed. Several bounds are given in terms of other graph parameters such as the diameter, the order, the maximum degree, the degree of regularity of regular graphs, and/or the mutual-visibility number. For the corona products, it is proved that the value of its mutual-visibility chromatic number depends on that of the first factor of the product. Graphs for which are also considered.

The aim of this paper is to investigate the relationship between environmental, social, and governance (ESG) controversies and firm market value. We use a unique dataset of more than 4000 firms from 58 countries during 2002-2011. Primary analysis surprisingly shows that ESG controversies are associated with greater firm value. However, when interacted with the corporate social performance (CSP) score, ESG controversies are found to have no direct effect on firm value while the interaction appears to be highly and significantly positive. Building on this evidence, we attempt to explore the channels through which CSP may enhance market value. Conducting sample split analysis indicates that higher CSP score has an impact on market value only for high-attention firms, those firms which are larger, perform better, located in countries with greater press freedom, more searched on the Internet, more followed by analysts, and have an improved corporate social reputation. Thus, our findings provide new insights on the role of firm visibility through which firms can profit from their CSP.

Low visibility conditions due to fog affect air traffic and, in some cases, are the leading cause of aviation accidents. Accurate forecasting of fog can lead to a significant reduction of human and financial losses. Numerical weather prediction (NWP) models have limitations in simulating fog accurately for operational purposes. However, recent studies have confirmed that ensemble‐based forecasts are effective in fog forecasting. In this study, a multi‐physics ensemble prediction system (EPS) was used to simulate the occurrence of several radiation, cloud base lowering (CBL), and advection fog events that occurred at Arak, Ardebil, Hamedan, Orumiyeh, Rasht and Shahrekord airports located across Iran, during January and December 2015. The multi‐physics EPS including a reference deterministic forecast consists of 16 different configurations of the weather research and forecasting (WRF) model and was run from 12 UTC 12 January to 12 UTC 16 January 2015 and from 00 UTC 27 December to 12 UTC 31 December 2015 to simulate fog occurrences at six airports. SW99 and G2009 visibility algorithms were applied to the EPS outputs to predict the fog. The advantages of probabilistic fog forecasting in this study were shown by comparing the reference forecast and the ensemble‐based forecasts of fog events. The results showed that by considering a probability threshold of 37.5%, 50% and 62.5% for the ensemble forecasts, the EPS outperformed the deterministic fog forecasts obtained from a deterministic reference forecast. Such that, with 37.5% and 50% probability thresholds, the equitable threat score (ETS) was much higher than the ETS for the reference deterministic fog forecast. Also, the EPS with 37.5% and 50% probability thresholds could correctly predict 3 and 4 (out of 10) more fog events compared with the reference deterministic forecast. An ensemble prediction system (EPS) is used to simulate the occurrence of ten fog events during January and December 2015 over Iran. The multi‐physics EPS consists of 16 different configurations of the weather research and forecasting (WRF) model. SW99 and G2009 visibility algorithms were applied to the EPS outputs to predict the fog. The advantages of probability fog forecasting in this study were shown by comparing the reference forecast and the ensemble‐based forecasts.

Low-visibility conditions at airports can lead to capacity reductions and, therefore, to delays or cancelations of arriving and departing flights. Accurate visibility forecasts are required to keep the airport capacity as high as possible. We generate probabilistic nowcasts of low-visibility procedure (lvp) states, which determine the reduction of the airport capacity due to low visibility. The nowcasts are generated with tree-based statistical models based on highly-resolved meteorological observations at the airport. Short computation times of these models ensure the instantaneous generation of new predictions when new observations arrive. The tree-based ensemble method boosting provides the highest benefit in forecast performance. For lvp forecasts with lead times shorter than 1 h variables with information of the current lvp state, ceiling, and horizontal visibility are most important. With longer lead times, visibility information of the airport’s vicinity and standard meteorological variables such as humidity also become relevant.

Although a remarkable reduction in the frequency of sand and dust storms (SDSs) in the past several decades has been reported over northern China (NC), two unexpected mega SDSs occurred on 15–20 and 27–29 March 2021 (abbreviated as the “3.15” and “3.27” SDS events), which has reawakened widespread concern. This study characterizes the optical, microphysical, and radiative properties of aerosols and their meteorological drivers during these two SDS events using the Sun photometer observations in Beijing and a comprehensive set of multiple satellite (including MODIS, VIIRS, CALIOP, and Himawari-8) and ground-based observations (including the CMA visibility network and AD-Net) combined with atmospheric reanalysis data. Moreover, a long-term (2000–2021) dust optical depth (DOD) dataset retrieved from MODIS measurements was also utilized to evaluate the historical ranking of the dust loading in NC during dust events. During the 3.15 and 3.27 events, the invasion of dust plumes greatly degraded the visibility over large areas of NC, with extreme low visibility of 50 and 500 m recorded at most sites on 15 and 28 March, respectively. Despite the shorter duration of the 3.27 event relative to the 3.15 event, sun photometer and satellite observations in Beijing recorded a larger peak AOD (∼2.5) in the former than in the latter (∼2.0), which was mainly attributed to the short-term intrusion of coarse-mode dust particles with larger effective radii (∼1.9 µm) and volume concentrations (∼2.0 µm3 µm−2) during the 3.27 event. The shortwave direct aerosol radiative forcing induced by dust was estimated to be −92.1 and −111.4 W m−2 at the top of the atmosphere, −184.7 and −296.2 W m−2 at the surface, and +92.6 and +184.8 W m−2 in the atmosphere in Beijing during the 3.15 and 3.27 events, respectively. CALIOP observations show that during the 3.15 event the dust plume was lifted to an altitude of 4–8 km, and its range of impact extended from the dust source to the eastern coast of China. In contrast, the lifting height of the dust plume during the 3.27 event was lower than that during the 3.15 event, which was also confirmed by ground-based lidar observations. The MODIS-retrieved DOD data registered these two massive SDS events as the most intense episode in the same period in history over the past 2 decades. These two extreme SDS events were associated with both atmospheric circulation extremes and local meteorological anomalies that favored enhanced dust emissions in the Gobi Desert (GD) across southern Mongolia and NC. Meteorological analysis revealed that both SDS events were triggered by an exceptionally strong Mongolian cyclone generated at nearly the same location (along the central and eastern plateau of Inner Mongolia) in conjunction with a surface-level cold high-pressure system at the rear, albeit with differences in magnitude and spatial extent of impact. In the GD, the early melting of spring snow caused by near-surface temperature anomalies over dust source regions, together with negative soil moisture anomalies induced by decreased precipitation, formed drier and barer soil surfaces, which allowed for increased emissions of dust into the atmosphere by strongly enhanced surface winds generated by the Mongolian cyclone.