Search

The article investigates the legacy, in terms of narratives and representations of femininity, of Vogue Italiacovers from the 1960s and 1970s on contemporary Italian young women. To do this, we visually and textually analyse two different corpora: 143 Vogue Italiacovers, retrieved from the Vogue ItaliaArchive and published between 1964 (Vogue’s first publication in Italy) and 1974 and between 2020 and 2022; and 46 mock covers of fashion simulated magazines created by female undergraduate fashion students during the academic years 2020/2021 and 2021/2022. Through the first corpus we examine the hegemonic discourse of Vogue Italia, assuming that it expresses the typical Italian way of creating and expressing female fashion while reflecting the shifting ideologies of the Italian feminist movement over the last century; the second corpus reveals the imaginations and narratives of young girls on fashion, disclosing how women’s – and girls’ – identities have been shaped over time and how the standards for femininity, beauty, happiness and health have been transferred and reworked from one generation to the next. In our study the parallel investigation between the longitudinal analysis of the visual apparatus Vogue Italiaand the covers produced by students shows, first, elements of continuity and similarity in the communicative and instrumental use of fashion, according to the practice of remixing. Second, it demonstrates that students assimilated successfully the narrative codes typical of traditional fashion communication media but they reinterpret the imagery and representations disseminated, thus bringing into the public discourse issues such as sustainability, gender, diversity, body positivity and stereotypes. Therefore, the study also reveals that girls have always been more than simple passive consumers of fashion magazines and cultural products.

The rapid advancement of technology has significantly improved the methods for identifying and counting individuals in indoor environments. This paper presents a systematic review of existing non-intrusive methods and technologies used for indoor detection, counting and identification of people. The review evaluates relevant literature, identifying key technologies that provide accurate detection and practical applications across various domains. The methods are categorized into six groups based on the evaluated parameters: Acoustic-based, Biometric-based, Body Indices-based, Gait-based, Infrared-based, and Smart Device-based. This categorization helps understand each method’s strengths and weaknesses, facilitating future research and development in this field.

Supplemental Digital Content is available in the text

The photoelectrochemical properties of thiophene-triphenylamine (TTPA) sensitizers (TTPA1–3) used in association with different cobalt based mediators, including kinetically fast shuttles such as [Co(bpy)3]3+/2+and [Co(phen)3]3+/2+and sterically hindered couples like [Co(dtb)3]3+/2+were studied by combining molecular modeling, spectroscopic, and photoelectrochemical techniques. The results indicate that the presence of multiple anchoring points on the dye structure improves its adsorption stability onto TiO2but induces a pseudoplanar adsorption geometry which is not suited to insulate properly the surface of the semiconductor and of the back contact, against electron recombination; particularly when kinetically fast shuttles are employed. This drawback could be successfully countered by exploiting both a compact blocking underlayer and the chemisorption of octyl triethoxysilane (Si–C8) acting as a molecular barrier onto the TiO2surface, thus limiting the access of the oxidized mediator to the exposed titania sites. These treatments improve the electron collection efficiency up to 80–90% with the I–/I3–couple and up to 70% when the [Co(dtb)3]3+/2+mediator was used.

The slot region marks the equatorward boundary of the energetic electron precipitation (EEP). There are, however, numerous reports where energetic electrons cross these boundaries and fill the slot region. The ensuing EEP will occur long after the geomagnetic activity subsides. This is a missing energy input in current EEP estimates scaled by geomagnetic indices. This study explores the occurrence rate, duration, and local time dependence of slot region filling events using observations from the National Oceanic and Atmospheric Administration/Polar Orbiting Environmental Satellites over a full solar cycle from 2004 to 2014. The EEP flux estimates are based on the Medium Energy Proton Electron Detector 0° and 90° detectors and the theory of pitch angle diffusion by wave‐particle interaction. The occurrence rates of >43, >114, and >292 keV events are found to be strongly energy and solar cycle dependent. Higher energy events are more likely to be associated with Coronal Mass Ejections and stronger geomagnetic deflections compared to lower energy events. Solar wind speed, Bz, and Ey reveal a calm period before the events, potentially important for preconditioning the ensuing magnetospheric mass convection. The slot region reforms more efficiently closer to the plasmapause, which creates a double EEP band throughout the recovery period. The slot region EEP maximizes around noon throughout the afternoon/evening sector, consistent with pitch angle scattering from plasmaspheric hiss and lightning induced whistler mode waves. Concurrent with slot region filling events, the Michelson Interferometer for Passive Atmospheric Sounding/Envisat nitric oxide density show an increase at <55° corrected geomagnetic latitudes. This demonstrates the importance of including slot region EEP when assessing the EEP impact on the atmosphere. Electron precipitation from slot region filling events increases mesospheric nitric oxide density at corrected geomagnetic latitudes well below 55°The occurrence rate of >292 keV slot region filling events is about half of the >43 keV slot region filling eventsLocal time precipitation pattern is in line with pitch angle scattering by plasmaspheric hiss and lightning‐generated whistler mode waves Electron precipitation from slot region filling events increases mesospheric nitric oxide density at corrected geomagnetic latitudes well below 55° The occurrence rate of >292 keV slot region filling events is about half of the >43 keV slot region filling events Local time precipitation pattern is in line with pitch angle scattering by plasmaspheric hiss and lightning‐generated whistler mode waves

Energetic Electron Precipitation (EEP) from the Earth's plasma sheet and the radiation belts is an important feature of atmospheric dynamics through their destruction of ozone in the lower thermosphere and mesosphere. Therefore, understanding the magnitude of the atmospheric impact of the Sun‐Earth interaction requires a comprehensive understanding of the intensity and location of EEP. This study improves the accuracy of a previous pressure‐corrected Dst model that predicts the equatorward extent of >43, >114, and >292 keV EEP using the measurements from the Medium Energy Proton Electron Detector detector of six National Oceanic and Atmospheric Administration/Polar Orbiting Environmental Satellites and EUMETSAT/METOP satellites. The improvement is achieved through multiple linear regression of pressure‐corrected Dst and pressure‐corrected Ring Current (RC) indices. The RC index mitigates the baseline variation of the Dst index that created an inherent solar cycle bias in the previous model. The new model is then extended to the Southern Hemisphere (SH) after removing the South Atlantic Anomaly longitudes from the data. More than 80% of the residuals lie within ±1.8° Corrected Geomagnetic Latitude (CGMLat) in the Northern Hemisphere and within ±1.98° CGMLat in the SH. This study aims to construct a model that predicts the geographic extent of Energetic Electron Precipitation (EEP) from the Earth's radiation belts using measurements from the Medium Energy Proton Electron Detector detector of six National Oceanic and Atmospheric Administration/Polar Orbiting Environmental Satellites and EUMETSAT/METOP satellites. The study enhances the accuracy of the previous pressure‐corrected Dst model. This improvement is implemented using multiple linear regression of pressure‐corrected Dst and pressure‐corrected Ring Current (RC) indices. Additionally, the study extends the model to the Southern Hemisphere after removing the South Atlantic Anomaly longitudes from the data. The result resolves the solar cycle bias that existed in the previous study. An updated model of the equatorward extent of >43 keV electron precipitation has been improved by successfully removing the solar cycle biasIncluding both the Dst* and the Ring Current index reduces the error estimate to ±1.8° Corrected Geomagnetic Latitude (CGMLat) over a full solar cycle (2004–2014)The model is extended to the Southern Hemisphere with an error estimate of ±1.98° CGMLat An updated model of the equatorward extent of >43 keV electron precipitation has been improved by successfully removing the solar cycle bias Including both the Dst* and the Ring Current index reduces the error estimate to ±1.8° Corrected Geomagnetic Latitude (CGMLat) over a full solar cycle (2004–2014) The model is extended to the Southern Hemisphere with an error estimate of ±1.98° CGMLat

Medium Energy Electron (MEE) precipitation (≳30 keV) ionizes the mesosphere and initiates chemical reactions, which ultimately can reduce mesospheric and stratospheric ozone. Currently, there are considerable differences in how existing parameterizations represent flux response, timing, and duration of MEE precipitation, especially considering its high‐energy tail (≳300 keV). This study compares the nature of ≳300 to ≳30 keV electron fluxes to better understand differences within MEE precipitation. The MEE fluxes are estimated from measurements by the Medium Energy Proton and Electron Detector (MEPED) onboard the Polar Orbiting Environmental Satellite (POES) from 2004 to 2014. The fluxes are explored in the context of solar wind drivers: corotating high‐speed solar wind streams (HSSs) and coronal mass ejections (CMEs) alongside their associated solar wind properties. Three key aspects of ≳300 keV electron fluxes are investigated: maximum response, peak timing, and duration. The results reveal a structure‐dependent correlation (0.89) between the peak fluxes of ≳30 and ≳300 keV electrons. The epsilon coupling function correlates well (0.84) with the ≳300 keV peak flux, independent of solar wind structure. The ≳300 keV flux peaks 0–3 days after the ≳30 keV flux peaks. The highest probability (∼42%) occurs for a 1‐day delay, while predictive capabilities increase when accounting for solar wind speed. The ≳300 keV flux response has the highest probability of lasting 4 days for both CMEs and HSSs. The results form a base for a stochastic MEE parameterization that goes beyond the average picture, enabling realistic flux variability on both daily and decadal scales. Electrons with energies >30 keV precipitating into the Earth's atmosphere is known as medium energy electron (MEE) precipitation. Solar wind properties drive the rate and energy of MEE. MEE precipitation is a relevant solar forcing as it produces ozone‐depleting substances. Variations in ozone concentration can modify the atmospheric temperature profile and lead to changes in atmospheric circulation that can map down onto surface climate. The community's capability of parameterizing MEE precipitation is an active field of research. This study aims to build a foundation for an MEE parameterization that represents realistic variability on daily and decadal scales by exploring the variability in the context of different solar wind properties. The study focuses on three key aspects regarding the differences within the energy spectrum of MEE precipitation: maximum response, timing, and duration. The key aspects are evaluated regarding the probability of a specific response. This study looks at an entire solar cycle (11 yr). It is found that solar wind properties, such as solar wind speed, can help determine the probability of a particular MEE response. The results from this paper will be key elements for constructing an MEE precipitation parameterization to be applied in a chemistry‐climate model. The solar wind parameter εbest predicts the peak flux of the >292 keV electron precipitation independent of solar wind structureThe delay in the peak flux of >292 keV electron precipitation relative to that of >43 keV electrons is influenced by solar wind speedOn average, electron precipitation >292 keV persists 2–3 days longer than electron precipitation >43 keV The solar wind parameter εbest predicts the peak flux of the >292 keV electron precipitation independent of solar wind structure The delay in the peak flux of >292 keV electron precipitation relative to that of >43 keV electrons is influenced by solar wind speed On average, electron precipitation >292 keV persists 2–3 days longer than electron precipitation >43 keV

Energetic Electron Precipitation (EEP) from the plasma sheet and the radiation belts ionizes the polar lower thermosphere and mesosphere. EEP increases the production of NOxand HOx, which will catalytically destroy ozone, an important element of atmospheric dynamics. Therefore, measurement of the latitudinal extent of the precipitation boundaries is important in quantifying the atmospheric effects of the Sun‐Earth interaction. This study uses measurements by the Medium Energy Proton Electron Detector (MEPED) of six NOAA/POES and EUMETSAT/METOP satellites from 2004 to 2014 to determine the latitudinal boundaries of EEP and their variability with geomagnetic activity and solar wind drivers. Variation of the boundaries for different electron energies and Magnetic Local Time (MLT) is studied. Regression analyses are applied to determine the best predictor variable based on solar wind parameters and geomagnetic indices. The highest correlation was found for the pressure‐corrected Dst index when applying a linear regression model. A model of the equatorward EEP boundary is developed separately for three different energy channels, >43, >114, and >292 keV, and for 3 hour MLT sectors. For >43 keV EEP, 80% of the equatorward boundaries predicted by the model are within ±2.2° cgmlat. The model exhibits a solar cycle bias where it systematically exaggerates the equatorward movement of the EEP region during solar minimum. The highest accuracy of the model is found in periods dominated by corotating interaction regions/high speed solar wind streams. The result will be a key element for constructing a model of EEP variability to be applied in atmosphere climate models. Charged particles trapped in the Earth's magnetic field get accelerated to high energies through various magnetospheric processes. They can eventually precipitate into the Earth’s atmosphere in a process known as Energetic Electron Precipitation or EEP. EEP deposits energy in the mesosphere and lower thermosphere which increase the production of ozone‐depleting substances. Vertical transport of these, in particular during winter, can lead to indirect destruction of stratospheric ozone, a crucial element of atmospheric dynamics. Therefore, measurement of the latitudinal extent of EEP is important in quantifying the atmospheric effects of the Sun‐Earth interaction. We use measurements from six NOAA/POES and EUMETSAT/METOP satellites from 2004 to 2014 to determine the equatorward latitudinal boundaries of EEP. We investigate how they correlate with solar wind parameters and geomagnetic indices to identify the best predictor for EEP boundaries. The result will be a key element for constructing a model of EEP variability to be applied in atmosphere climate models. A model predicting equatorward extent of >43 keV electron precipitation is developed based on pressure‐corrected DstThe model has an error estimate of ±2.2° cgmlat over a full solar cycle (2004–2014)The model has the highest accuracy during periods dominated by high‐speed solar wind streams A model predicting equatorward extent of >43 keV electron precipitation is developed based on pressure‐corrected Dst The model has an error estimate of ±2.2° cgmlat over a full solar cycle (2004–2014) The model has the highest accuracy during periods dominated by high‐speed solar wind streams