Now that JWST has commenced science operations, we are able to observe exoplanets at previously uncharted wavelengths and spectral resolutions. Here we report time-series observations of the transiting exoplanet WASP-39b using JWST’s Near InfraRed Camera (NIRCam). The long-wavelength spectroscopic and short-wavelength photometric light curves span 2.0–4.0 micrometres, exhibit minimal systematics and reveal well defined molecular absorption features in the planet’s spectrum. Specifically, we detect gaseous water in the atmosphere and place an upper limit on the abundance of methane. The otherwise prominent carbon dioxide feature at 2.8 micrometres is largely masked by water. The best-fit chemical equilibrium models favour an atmospheric metallicity of 1–100-times solar  and a substellar C/O ratio. The inferred high metallicity and low C/O ratio may indicate significant accretion of solid materials during planet formation  or disequilibrium processes in the upper atmosphere .Measuring the metallicity and carbon-to-oxygen (C/O) ratio in exoplanet atmospheres is a fundamental step towards constraining the dominant chemical processes at work and, if in equilibrium, revealing planet formation histories. Transmission spectroscopy (for example, refs.  Time-series observations from the JWST of the transiting exoplanet WASP-39b show gaseous water in the planet’s atmosphere and place an upper limit on the abundance of methane. The JWST director’s discretionary Early Release Science (ERS) programme provides the scientific community with observations of typical targets quickly enough to inform planning for the telescope’s second cycle of scheduled observations. The primary goals of the Transiting Exoplanet Community ERS programme  are to demonstrate instrument capabilities, quickly build community experience and seed initial discovery in transiting exoplanetary science9. The Panchromatic Transmission programme observed a single exoplanet, WASP-39b, in transmission using four different instrument modes. It included overlapping wavelength coverage to cross-compare and validate all three near-infrared instruments for time-series observations. The observations presented here form one-quarter of this programme, demonstrating the capacity of the JWST Near-InfraRed Camera (NIRCam) for transiting exoplanet atmospheric characterization.JWST has demonstrated the necessary precision and wavelength coverage to make bulk characterization of hot exoplanet atmospheres routine10. We selected WASP-39b for its inactive host star and prominent spectroscopic features, which trace the atmospheric composition of the planet. We confirmed the star’s relative inactivity through a photometric monitoring campaign using the Next-Generation Transit Survey (NGTS)11 and Transiting Exoplanet Survey Satellite (TESS)12  and other Saturn-mass exoplanets.WASP-39b is a highly inflated exoplanet of roughly Saturn mass, orbiting its G7 main-sequence star with a 4.05-day period(TESS)12 . Reporteut). The Grism R and F322W2 filter in the long-wavelength (LW) channel dispersed light from 2.420–4.025 µm at a spectral resolution R of 1,570–2,594 over 1,023 resolution elements. The short-wavelength (SW) channel allowed the simultaneous measurement of light, that is photometry, spanning 2.0–2.2 µm using the WLP8 weak lens and F210M filter. See We observed a single transit of WASP-39b with JWST’s NIRCam instrument on 22–23 July 2022 , customizing the JWST Science Calibration Pipeline (jwst) to allow for minor adaptations to default steps and values worked best . The wavf noise , which describes the detector’s correlated read noise26. For NIRCam, this manifests as weak structures in the dispersion direction, as shown in Fig. f noise in the final LW reduction because it did not impact the precision reached by individual spectroscopic light curves . We removed structures due to 1/f noise in the SW reduction . The right-axis scale is in equivalent scale heights, where one scale height is approximately 800 km.Figure To interpret the presence of other molecules within the planetary atmosphere, we compared the Eureka! transit spectrum with a set of independently computed atmospheric model grids that spanned a range of cloud properties, metallicity values and carbon-to-oxygen (C/O) ratios . Figure 2O), carbon dioxide (CO2) and methane (CH4). From our model grid search, we definitively confirm the presence of H2O at nearly 16σ. Water vapour was previously identified in the atmosphere of WASP-39b using the Hubble Space Telescope (HST) Wide Field Camera 3 (WFC3) observations taken at shorter wavelengths  at 4.3 µm (ref. 7), but the overlap between the CO2 feature at 2.8 µm and the broad H2O feature  version 3.0 model  to determine an upper limit on the abundance of CH4 at 1 mbar, where it contributes most strongly to the spectrum. Within our single best-fit model scaling, we find an upper limit on CH4 abundance at 1 mbar of 5.5 × 10−5 (or 55 ppm) volume mixing ratio, above which the goodness of fit per free parameter, 4 abundances, but found they did not have any statistical significance.In a hot  solar-metallicity atmosphere with a stellar C/O ratio, CH4 upper limit, the single best fit from each grid favours the lowest C/O ratio  within that grid. These best-fit point values for C/O from the three grids agree well with the value of 13. We examined the effect of an even lower C/O grid point by computing the best-fit PICASO 3.0 model with a C/O of 0.115, but found no discernible difference in the transit spectrum. Comparing our inferred C/O ratio for WASP-39b’s atmosphere with that of its host star, we see that it is substellar ). We also note that the C/O ratio shown here represents the C/O fraction of the planet’s upper atmosphere rather than that of the whole atmosphere, as these NIRCam observations probe approximately the 0.1–10 mbar pressure range. WASP-39b’s temperature–pressure profile is cool enough for the formation of silicate  cloud species at depth, which would deplete oxygen from the upper atmosphere and actually increase the C/O ratio aloft compared with the bulk planetary envelope28.Driven by this CH30). Similar measurements have been difficult to achieve from HST alone. Even in the Solar System gas giants, such constraints have proved difficult from both remote sensing and in situ missions, as the low temperatures of Jupiter, Saturn, Uranus and Neptune lead to condensation of most O-bearing species  at high altitudes, prohibiting accurate measurement of the O abundance .Figure 4 in the upper atmosphere could explain the absence of a CH4 peak at 3.3 µm . The most likely immediate products of CH4 photolysis, such as hydrogen cyanide (HCN) or acetylene (C2H2), would be produced in abundances too small  to be robustly detected with a single NIRCam transit, even from complete CH4 conversion. Alternatively, much of the C available from CH4 photolysis could have been oxidized by photodissociated H2O to form carbon monoxide (CO) and CO2 (refs. 35), although the absolute abundances of these two C reservoirs would not have been meaningfully altered as their abundances under chemical equilibrium are already higher than that of CH4. Other proposed disequilibrium chemistry processes could reduce the CH4 abundance at the terminator without also decreasing the C/O ratio39. We defer the exploration of complex disequilibrium models to atmospheric retrieval analyses using the full set of data provided by the Transiting Exoplanet Community ERS programme. That dataset will also constrain the presence of additional O- and C-bearing species to provide a more robust constraint on the C/O ratio than we can obtain here. However, the C/O ratio estimate we report from NIRCam is broadly consistent with the C/O ratio found from the other individual ERS WASP-39b datasets, which range from best fits that are subsolar (Near InfraRed Imager and Slitless Spectrograph (NIRISS)/Single Object Slitless Spectroscopy (SOSS)40; NIRSpec/PRISM 3.0–5.0 µm (ref. 7); NIRSpec/G39541) to a slightly super-solar upper limit (NIRSpec/PRISM 0.5–5.5 µm (ref. 42)).The apparent substellar C/O ratio inferred from chemical equilibrium models may trace photochemical processes in the planet’s upper atmosphere. For example, photochemical destruction of CH44. Taken as such, JWST observations could offer important clues regarding the degree to which hot-Jupiter atmospheres undergo solid accretion during their early evolution.If disequilibrium chemistry is not prevalent in the planet’s upper atmosphere, the inferred high metallicity and low C/O ratio can be tied back to the formation of WASP-39b. The most prominent scenario is that WASP-39b formed by core accretion exterior to the water-ice line and accreted low-C/O solid material in situ and/or while migrating inwards within the protoplanetary disk45, the future promises many exciting discoveries and major advancements in the formation, evolution and atmospheric chemistry of hot Jupiters.Here we have demonstrated the excellent performance of NIRCam for exoplanet transmission spectroscopy. With the first JWST exoplanet spectra now comparable to the first near-infrared Jupiter spectraAs part of this article’s Reproducible Research Compendium, located on Zenodo at 10.5281/zenodo.7101283, we provide saved outputs from various pipeline stages and the data used to generate relevant figures, as well as a Jupyter Notebook with step-by-step data reduction instructions replicating our chosen analysis (10.5281/zenodo.7510106).11. Monitoring began at the end of April 2022 and continued until late August, spanning the JWST ERS transit observations of WASP-39b in July. We used one camera on most photometric nights to take a series of 10-s images lasting on average for 2 h. The resulting monitoring light curve is plotted in Extended Data Fig. 12, which is binned to 2 h to be comparable to NGTS. Both light curves have been detrended against sky brightness. They show evidence for stellar activity, but only with a low amplitude of 0.06% in NGTS.To confirm that WASP-39 is a relatively inactive star, and that the JWST observations were not adversely affected by stellar activity, we carried out photometric monitoring with the ground-based NGTS51, which is otherwise limited by atmospheric scintillation52. The transit models were generated from the system parameters listed in Extended Data Table Also plotted in Extended Data Fig. The transit observations in Extended Data Fig. 54. The LW channel used the Grism R + F322W2 filter to observe a wavelength range of 2.420–4.025 µm with a spectroscopic resolving power of R ≈ 1,600 at 4 µm , which we briefly summarize here. jwst is a Python software suite for processing data from all JWST instruments and observing modes, and is organized into three stages. Stage 1 takes in uncal.fits files and performs detector-level corrections and ramp fitting for individual exposures . Stage 2 takes in slope images (ramps) from Stage 1 and performs an assignment of the world coordinate system, flat fielding and assignment of a wavelength solution. Stage 3 takes in calibrated two-dimensional images from Stage 2 and extracts a time series of one-dimensional spectra. The default pipeline settings include a flux calibration step at Stage 2. In all data reductions presented below, we skipped that step, as it introduced scatter in the extracted spectral time series. This is justified because the transit depths we compute are relative, rather than absolute, flux measurements.Many of the reductions presented below used intermediate data products from or made minor edits to the JWST Science Calibration Pipeline  that has tools to modify the jwst pipeline and performs  photometric and optimal spectral extraction of light curves.tshirt is an open-source pipeline . The ROEBA correction happens after the bias subtraction step. First, the median of all even columns’ background rates is subtracted from all even columns and the median of all odd columns’ background rates is subtracted from all odd columns to remove most pre-amp reset offsets and odd/even pixel effects. Next, the median of each column’s background rate is subtracted from each row to remove the 1/f noise for timescales longer than a row read time (5.24 ms). The correction was applied to each group so that 1/f noise would not be detected as spurious jumps or cosmic rays by the pipeline. We used all pixels more than 201 pixels from the source to estimate the background and 1/f noise, then subtracted the median of each row from all pixels in that row. Stage 2 of jwst was skipped, as it only changes the rates from analogue-to-digital units (ADU) per second to physical units and conducts flat fielding. This does not affect the relative measurements of the light curve (due to the high pointing precision) and allows for comparison with detector-level effects.In the stage 1 SW analysis, tshirt applied a row-by-row, odd/even-by-amplifier (ROEBA) subtraction algorithm that used background pixels to reduce the 1/For the photometric extraction, we used a source radius of 79 pixels and a background annulus of 79 pixels to 100 pixels. We performed a two-dimensional Gaussian fit to determine the centre of the aperture.We performed three independent LW data reductions, using the Eureka!, Atmospheric Transmission Spectroscopy Analysis Code (HANSOLO) and tshirt pipelines.x coordinate (the dispersion direction), but this is not strictly accurate at the blue end. For all methods, we use commissioning programme 1076 to derive a third-degree polynomial wavelength solution that uses the Pfund and Bracket hydrogen series in the planetary nebula IRAS 05248−7007. The residuals in this solution are ≲0.1 nm and the stellar absorption lines in WASP-39 agree with the solution to within 1 nm. The difference between the corrected wavelengths and the original wavelength solution is almost zero at the red end of the spectrum, but increases to about 50 nm at the blue end.The reference files in the Calibration Reference Data System at the time of our analysis included a linear solution for wavelength as a function of We investigated several variations of the Eureka! LW data reduction to minimize the median absolute deviation (MAD) of the final extracted light curves, with different settings for cosmic-ray jump detection, identifying the spectral trace, the aperture size for spectral extraction, the region for background subtraction and limits for outlier rejection. Here we present details of the data reduction that produced the spectrum shown in the main body of the paper.σ. In Stage 3, we first trimmed the data to a subarray extending from pixels 4–64 in the cross-dispersion direction and 4–1,704 in the spectral direction. We then masked any pixels with not a number (NaN) values for the flux or error. We fit the spectral trace with a Gaussian profile and corrected for the curvature of the trace to the nearest integer pixel. We excluded a 14-pixels-wide region on either side of the spectral trace from the background calculation and performed a column-by-column linear fit to subtract the background. We used a double-iteration 7σ threshold for outlier rejection of the sky background along the time axis during background subtraction. In addition, we used a 7σ threshold for outlier rejection during the polynomial fit to the background. To obtain the spectrum, we constructed a normalized spatial profile using the median of all data frames, then used optimal extraction56 on an aperture with a half-width of 9 pixels. For the optimal extraction, we rejected outliers above a 10σ threshold. Extended Data Fig. Stages 1 and 2 were identical to the jwst pipeline, with the exception of increasing the rejection threshold during jump detection to 658 and was adapted to enable its use on NIRCam data. HANSOLO begins with the calibrated rateints.fits outputs of jwst Stage 1.The HANSOLO pipeline was originally developed to analyse ground-based transmission spectra observed with 8-m-class telescopes59 to remove cosmic-ray effects from the two-dimensional images and identified the spectral trace using a Moffat function fit to each column. To remove the sky, we fitted and subtracted a linear trend from each column, excluding from the fit a region of 20 pixels on either side of the trace centre. We then extracted the spectrum by summing over an aperture with a half-width of 3 pixels. The spectra from different images were aligned with each other using cross-correlation. To correct outlier pixels, each spectrum was normalized to account for the effect of the transit on the time series. Outliers >3σ away from the mean were removed from the time series of each wavelength point in the normalized spectra and replaced with the median value over time. We then rescaled the spectra to their original amplitudes.We used the LACOSMIC algorithmf noise (described above for photometry); however, only pixels 1,847 to 2,044, which are on the rightmost amplifier, are available as low-illumination background.As with the SW reduction, a few modifications were made to the Stage 1 jwst ramps-to-slopes pipeline. ROEBA subtraction reduced 1/26. We used a spectral aperture centred at pixel 34 in the spatial direction with a half-width of 5 pixels. We selected the background region to extend between pixels 5–24 and 44–65 in the spatial direction. The background was fit with a column-by-column linear trend with 3σ clipping. For the spectral extraction, we fit the spatial profile with a cubic spline with 20 knots and an outlier rejection threshold of 30σ. If a pixel was deemed an outlier either by the ‘DO_NOT_USE’ data quality flag or by the spatial profile outlier detection, the rest of the spatial profile was weighted by the reference profile to ensure that the flux was conserved. For the covariance weighting, a correlation of 8% was assumed between pixels as measured by background pixels’ noise properties.For Stage 3, tshirt performed optimal spectral extraction weighted by the covariance between pixelsWe used both Eureka! and tshirt to fit the SW light curves. In both cases, the light curves were fit with models that included both the transit and the systematic noise. However, to investigate the effect of different systematic models on the resulting spectra, each fit used a slightly different noise model. Extended Data Table For the LW fits, we summed the data into 15 nm bins (about 15 pixels). We experimented with bins as small as 10 nm, but found that reducing the bin size below 15 nm led to poor constraints on the limb darkening and added additional scatter to the resulting spectrum. Extended Data Fig. https://github.com/catrionamurray/chromatic_fitting/) Python tool to perform light-curve fitting, built on the data visualizer chromatic . For this work, chromatic-fitting light-curve fitting was applied to a Eureka! data reduction. As with the SW fits, we fit the LW light curves with models that include different noise parameterizations. Extended Data Table We fit the LW light curves using four independent pipelines: chromatic-fitting, Eureka!, HANSOLO and tshirt. chromatic-fitting is an open-source (60 (for fits performed with Eureka!), the pymc3 Python package61  or the CONAN Python package58 (for fits performed with HANSOLO). The number of free parameters and the resulting differential MADs of the light curves from each fit are also listed in Extended Data Tables For all fits, the parameters were estimated with a Markov chain Monte Carlo fit, using either the emcee Python package66 could result in a biased planet spectrum and might present a higher level of time-correlated noise in the residuals. We attribute this to a combination of JWST’s high-precision light curves and deficiencies in the stellar limb-darkening models to accurately represent WASP-3968. Therefore, the results presented here use the quadratic limb-darkening law, in its classical form or reparameterized by ref. 69, with one or both coefficients as free parameters. We confirmed that these parameterizations produce transmission spectra that are consistent both with each other and with the spectra resulting from using more complex limb-darkening parameterizations, such as a four-parameter law with either fixed or free parameters70. We therefore recommend that future transmission spectrum analyses with NIRCam use similar methods. Limb-darkening conclusions from the full Transiting Exoplanet Community ERS programme will be discussed further by N. Espinoza et al. (manuscript in preparation).In the process of performing the fits to the LW data, we regularly found that the best-fit transmission spectra were shifted vertically for different limb-darkening parameterizations and, for some reductions, exhibited changes in the apparent size of the water feature. In particular, we found that light-curve fits with all limb-darkening coefficients fixed to outputs from ExoTiC-LDσ (using the maximum error at each point), which demonstrates a remarkable level of agreement. In addition, the residuals showed no evidence for time-correlated noise, as shown in Extended Data Fig. The final fitted light curves are shown in Extended Data Fig. For ease of interpretation, we compared our atmospheric models with only one transmission spectrum. We selected the Eureka! spectrum, as it was on average nearest the median spectrum (the median transit depth at each bin).χ2 fits to the transmission spectra using three grids of radiative–convective equilibrium models: ATMO73, PHOENIX76 and PICASO 3.078. All models used a common set of planetary parameters, but had differing opacity sources, cloud treatments and grid points, described in detail below. Each model was binned to the resolution of the data to perform the χ2 fitting. We performed these three independent model grid fits to fully vet our inferences about the atmospheric metallicity and the presence of specific molecular features within the data.To interpret the LW data from NIRCAM/F322W2, we performed 77, version 3.078, which was developed from the Fortran-based Extrasolar Giant Planet (EGP) model81. We used PICASO 3.0 to generate one-dimensional temperature–pressure profiles in thermochemical equilibrium. The base PICASO 3.0 forward model grid computes atmospheric mixing ratios using variations of planetary intrinsic temperatures (Tint) of 100 K, 200 K and 300 K; C/O ratios of 0.229, 0.458, 0.687 and 0.916; and atmospheric solar metallicity values of 0.1×, 0.316×, 1.0×, 3.162×, 10.0×, 31.623×, 50.119× and 100× solar. The PICASO grid assumes full day–night energy redistribution. To compute model transmission spectra from the atmospheric profiles, we used opacities described by ref. 81  from refs. 89.Our primary atmospheric model grid is built from the open-source radiative–convective equilibrium code PICASO33 and the cloud modelling code Virga90, which is the Python implementation of the Eddysed cloud code91, to post-process disequilibrium chemistry from mixing and photochemical products as well as the effect of clouds. These additional post-processed grids also include vertically constant eddy diffusivities (Kzz) of 105–1011 cm2 s−1 in steps of 2 dex, and both clear and cloudy models. For the Vulcan disequilibrium runs, we computed model grid points for only a select subset of metallicity values  and C/O ratios . We found that neither the cloudy nor the clear disequilibrium grids from VULCAN offered an improvement in the We then used the one-dimensional CHON-based chemical kinetics code VULCANτcloud) between 1 bar and 0.1 bar ranging from τcloud = 3.2 × 10−6 to 1 in steps of 0.1 dex across all wavelengths. For clouds of specific condensates, we used Virga to compute log-normal particle size distributions using sedimentation efficiency (fsed) values of 0.6 to 10 for MnS, Na2S and MgSiO3 along the range of Kzz. Smaller sedimentation efficiencies, fsed, with larger eddy diffusivities, Kzz, generated more extended cloud decks and stronger cloud opacity.Within PICASO, clouds are implemented both as grey absorbers and as Mie scatterers using temperature-relevant cloud condensate species from Virga. For the grey clouds, the grid specified a cloud optical depth , bulk atmospheric metallicity  and C/O ratio (136 grid points from 0.3 to 1) were varied. Aerosol properties were parameterized through a haze factor (0 and 10× multi-gas Rayleigh scattering) and a grey-cloud-deck pressure level . Models with molecular abundances quenched at 1 bar to simulate vertical mixing were also calculated. The grid also included rainout to account for species sequestered as condensates in the deep atmosphere. Opacities are described by refs. 92 and taken from ref. 88.We also used a grid of atmosphere models from the PHOENIX radiative–convective equilibrium code to fit the data93. The ATMO grid used similar atmospheric and aerosol parameterizations to those used in the PHOENIX grid and also included rainout that accounts for species condensed in the deep atmosphere. Also included are day–night energy redistribution factors , atmospheric metallicity , interior temperature , C/O ratio , cloud scattering factor  and a haze scattering factor (1× and 10× multi-gas Rayleigh scattering). Opacities for H2O, CO2 and CH4 are taken from refs. 86 and for H2S from ref. 88.Similar to the model grids described above, we compared the data to a grid of models from the ATMO radiative–convective–thermochemical equilibrium code7), improving on the wider spread from previous HST-only94 or HST and ground-based optical interpretations16.We applied each of our three grids—ATMO, PHOENIX and PICASO 3.0—to fitting the NIRCam F322W2 spectrum (2.4–4.0 µm). In doing so, we found that the models strongly favoured a solar- or super-solar-metallicity atmosphere (1–100× solar), a substellar C/O ratio (≤0.35) and substantial contribution from clouds, which are parameterized differently by each model grid (see each grid description above). We show the best fits from each model grid in Extended Data Fig. fsed = 0.6 and Kzz = 109 cm s−2. This Virga best-fit model consists of clouds of MnS and MgSiO3 with deep (≥100 bar) cloud bases and diminishing optical depth up to approximately millibar pressures.For the NIRCam-only fit, the PICASO grey-cloud scheme produced a slightly better best fit (95), as well as potentially the sparseness of the model grid.The best-fit equilibrium model from the PHOENIX grid had 100× solar metallicity, a C/O ratio of 0.3 and a cloud deck at 3 mbar. Cloudy models were generally preferred over clear models, but not with statistical significance  were preferred to clear models . High-altitude clouds or hazes can be inferred from their particle sizes, where small particles scatter shorter wavelengths more efficiently , thus enabling the disentanglement of a very cloudy, low-metallicity atmosphere from a less cloudy, high-metallicity atmosphere17.In Extended Data Fig. −3 from 1 bar to 0.1 bar), we used this as a base model to explore the significance of specific molecular detections. First, we tested whether we could improve the best fit in the presence or absence of H2O, CO2, CH4 or H2S. We re-ran the best-fit base model by zeroing out each of these species in turn, shown in Fig. χ2 analysis.Once we found the ‘single best fit’ for the PICASO grid to the NIRCam spectrum , of 123.2 between the Gaussian residual and constant models for H2O over the whole NIRCam wavelength range, corresponding to 15.9σ, a strong detection. For CO2, we find ln(B) of 0.82 between the Gaussian residual and constant models between 2.4 µm and 2.9 µm, or 1.9σ, which is a weak or non-detection98. CO2 is strongly detected at 4.3 µm in the NIRSpec data for WASP-39b42, but the strong overlapping H2O band at 2.8 µm prevents NIRCam from making a significant CO2 detection. Given our upper limit on CH4 abundance, we also performed the same Gaussian residual fitting for CH4 and find a weak or non-detection at approximately 2σ.With the best fit in hand, we investigated the presence of individual molecular species. For molecular detection significances, we performed the same Gaussian residual fitting, shown in Extended Data Fig. 42 observed evidence for a molecular feature near 4.0 µm, which is currently best explained by sulfur dioxide. The reddest data points (>4.025 µm) from NIRCam also show an increase that is consistent with this feature seen in the NIRSpec data. However, as shown in Extended Data Fig. Both WASP-39b NIRSpec datasetsnts >4.02 µm from Any methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at 10.1038/s41586-022-05590-4.


When VO2 is in a metal state, the multi-frequency absorption and LTC polarization conversion can be achieved with different chemical potentials. When VO2 is in the insulator state and the polarization angle of incident wave is 45°, the device can be used to select or isolate the incident waves with different polarization states in the frequency region of 1.2–1.8 THz. Furthermore, when the chemical potentials are 0.05 eV and 1.2 eV, the corresponding transmissions of the TE-polarized wave demonstrate the opposite results, realizing the switching functions in the frequency region of 0.88–1.34 THz. In the frequency region above 2 THz, the multi-frequency rejection filter can be achieved. The designed switchable multifunctional metamaterial device can be widely implemented in radar monitoring and communication systems.Combining tunable properties and various functionalities into a single metamaterial structure has become a novel research hotspot and can be used to tackle great challenges. The multifunctional metamaterial structure that combines absorption, linear-to-circular (LTC) polarization conversion, filtering and switching functions into a single metamaterial device was designed and investigated in this study. The switching of different functions can be achieved based on the phase transition of vanadium dioxide (VO Thus, VO2 enables the switchable and tunable functionalities for smart devices since the conductivity is capable of 4–5 orders of magnitude change, and the phase-change process can be realized in several picoseconds [2 can be used as a promising candidate in several advanced devices, such as optical switches, modulators, absorbers, and polarization converters.Modulating the terahertz waves is particularly important in responding to the increasingly complex electromagnetic environment and communication needs. The absorber, polarization converter, and filter are especially essential devices in the fields of wave modulation. Metamaterials are artificially designed electromagnetic materials that are formed by periodic distribution of subwavelength microstructures. Traditional metamaterial devices, including absorbers, polarization converters, filters, etc., are usually designed for realizing a single function. In recent years, with the introduction of functional materials such as graphene, VOhotspots ,7,8,9,10hotspots . Graphenhotspots . One metoseconds . Inspire2 and graphene in multifunctional metamaterial structures have been put forward. By combing the VO2 and graphene, Zhu et al. designed a switchable terahertz metamaterial structure to realize wide-band and multi-band absorption [2 and graphene to realize dynamically tunable dual-wide-band absorption [2 switches from the metallic phase to the insulator phase, the operation frequency can be changed from the high-frequency to low-frequency region accordingly. By altering the Fermi energy level of graphene, its absorptivity can be continuously varied from 5.2% to 99.8%. Zhao et al. proposed a dynamically switched wide-band metamaterial polarization converter by treating the VO2 and graphene gratings in terahertz region [2 enables the polarization conversion switching between transmissive and reflective modes, and the introduction of double-layer graphene grating should improve the transmittance. Tang et al. designed a multifunctional terahertz metamaterial structure based on the hybrid VO2-graphene integrated structure [2, the asymmetric transmission and two different polarization conversions can be integrated into one device in the terahertz region. Wang et al. realized a dual-functional tunable wide-band absorber/reflector based on the periodic cross-shaped graphene array and a VO2 layer [2 and graphene.Advances toward the combination of VOsorption . Liu et sorption . When thz region . The phatructure . EnabledO2 layer . Most of2 material. Compared to the previously reported metamaterial devices, the proposed scheme here can provide three main advantages, which are as follows: (1) different functions, including multi-frequency absorption and linear-to-circular (LTC) polarization conversion, and different transmission characteristics can be integrated into a single metamaterial structure; (2) when VO2 is in the metal state, the designed structure works in reflection mode, and the functions of the metamaterial structure can switch between absorption (µc = 1.2 eV) and LTC polarization conversion (µc = 0.05 eV) by varying the graphene chemical potential; (3) when VO2 is in the insulator state, the structure works in the transmissive mode, which exhibits different transmission characteristics for different incidences. In addition, the effects of several structure geometrical parameters on the performances have also been investigated. The proposed scheme may pay a new route in designing tunable and switchable multifunctional terahertz metamaterial structures.Within the investigation of this study, we aimed to design a multifunctional metamaterial structure based on the manipulability of the chemical potential of graphene and the phase-transition properties of VO2–graphene-integrated metamaterial structure, which is arranged periodically in the x- and y-direction. The unit cell of the proposed metamaterial structure is composed of five layers from top to bottom: metal split ring resonator, SiO2 spacer, metal split ring resonator, SO2 spacer, and VO2 layer. As depicted in px = py = 80 µm, t1 = 0.2 µm, t2 = 24 µm, t3 = 13 µm, R1 = 30 µm, R2 = 27 µm, and α = 5°. The top and middle metal split rings are 0.2 µm–thick gold microstructures with a conductivity of 4.561 × 107 S/m [2 material with a dielectric constant of εr = 3.75 [2 can be varied by using voltage and temperature, respectively. 107 S/m . The gap 107 S/m . In the r = 3.75  and elecThe fast-developing micro–nano-fabrication technology can be used to fabricate the designed multifunctional structures . The desσg = σintra + σinter, can be characterized by the intra-band conductivity, σintra, and the inter-band conductivity, σinter [ω represents the angular frequency of the incident terahertz wave, µc represents the chemical potential or Fermi level of graphene [T denotes the temperature, e represents the electronic charge, kB denotes the Boltzmann constant, Γ = ħ/2π denotes the phenomenology scattering rate, ħ represents the reduced Plank constant, τ = µµc/σigraphene , T denotur study . Moreoveperature . The surperature  or bias perature . Based oBT << µc . Thus, tgε, of the graphene can be described by gε = 1 + jσg/(ε0ωdg) [ε0 represents the vacuum permittivity, and dg denotes the thickness of the graphene material, which is set as 1 nm in the investigation [The effective permittivity, /(ε0ωdg) ,30, whertigation .2 is one of the important phase-transition materials. In general, the permittivity of VO2 in the terahertz region can be characterized by using the Drude model [ε∞ = 12 represents the permittivity at infinite frequency; γ = 5.75 × 1013 rad/s. pω(σ0)), where pω(σ0) = 1.4 × 1015 rad/s. To simulate the insulating-metal phase change characteristics of VO2, different conductivities are used to characterize the different optoelectronic characteristics of VO2. In this study, 5 S/m and 2, respectively. The conductivity of VO2 can be changed by laser radiation, external bias voltage, and thermal control.Besides graphene, VOde model :(4)εVO2== 10 S/m  were usex and y axes to mimic the infinite arrays, and the open boundaries are applied in the z axis. Linearly and circularly polarized terahertz waves transmitting along the -z direction are incident on the metamaterial structure.The metamaterial device was designed and the related simulations were performed by using the finite difference time-domain method. The unit cell boundary conditions are used in 2 and variation of graphene chemical potential, different functions can be integrated into a single metamaterial structure. When VO2 is in the metallic state (5 S/m), according to different chemical potentials, the designed structure can exhibit linear-to-circular (LTC) polarization conversion properties (µc = 0.05 eV) and absorption properties (µc = 1.2 eV), respectively. In 2017, Bezares et al. presented FeCl3-intrcalated graphene as a new plasmonic material with high stability under environmental conditions and carrier concentrations, corresponding to a Fermi energy of 1.21 eV on the two-monolayer sample and 1.4 eV for the bilayer graphene [n = 4 × 1014 cm−2 have been obtained for electrons and holes [14 cm−2 has been realized in experiments [2 is in the insulator state  or TM-polarized  incident terahertz waves with a polarization angle of 0°. In the x–y-coordinate system, for realizing the LTC polarization conversion, the reflection coefficients for co-polarization (TE-to-TE), EEr, and cross-polarization (TE-to-TM), MEr, should be equal, providing a phase difference of Δφ = MEφ − EEφ = 2nπ ± π/2 (n represents an integer), and “−” and “+” define the left-handed and right-handed circularly polarized terahertz waves [When the conductivity of VOtz waves ,39. As gtz waves :(5)S0=|χ = S3/S0 is further given to evaluate the polarization conversion degree. Specifically, χ = −1 and χ = +1 indicate that the reflective wave is a LHCP wave and RHCP wave, respectively. The normalized ellipticity of β) = S3/S0 and introduce the axis ratio AR = 10log(tanβ) to evaluate the circular polarization characteristics [β represents the ellipticity angle. As shown in η = |MEr|2 + |EEr|2. The efficiency of the RHCP is higher than 0.8, and that of the LHCP is larger than 0.7. The results demonstrate that the designed metamaterial structure can realize the high-efficiency conversion operation.In addition, we define sin were studied when the other parameters are fixed as initial settings, and the results are given in R2 rises from 25 to 29 µm, the ellipticity of RHCP wave increases. At the same time, the corresponding bandwidth narrows slightly, which is caused by the red-shift of the overall LHCP frequency band with the augment of R2. Furthermore, as given in t2. The above results demonstrate that the variation of geometric parameters have a certain influence on the operating characteristics, but the influence is acceptable according to the fabricating error.In general, the geometry parameters of the metamaterial device have an effect on the operation performances. In addition, errors can be introduced in the structural dimensional parameters during the device processing. Therefore, the geometric parameters of the metamaterial structure were also investigated. The variations of the ellipticity spectrum of the LTC polarization conversion structure with the geometry parameters A=1−Rx and y axes, and it is very helpful in many practical applications.Next, the absorption properties of the multi-band metamaterial absorber with different polarization angles are studied. t2 and R2 on the absorption performances. As illustrated in t2, the frequency bands around 1.78 THz and 3.35 THz show a slight red-shift trend. From R2 rises from 25 to 29 µm, the frequency band around 1.7 THz illustrates a more obvious change in the absorption performance than that of the other frequency bands. Moreover, the overall absorption spectrum demonstrates a red-shift trend. In addition, we also discussed the effects of the geometric parameters of 2 is 10 S/m and the chemical potentials of graphene are 0.05 and 1.2 eV, the designed metamaterial structure is able to act as a filter, which performs different filtering responses for TE- and TM-polarized incident terahertz waves with the polarization angle of 45°. The device contains a top layer pattern combining metal split ring and graphene filled in gaps, a first lossy SiO2 dielectric layer, a middle layer pattern with the same structure as the top layer, a second lossy SiO2 dielectric layer, and a base VO2 dielectric layer. For different graphene chemical potential values, the responses related to the TE- and TM-polarized terahertz waves are different. When the chemical potential is µc = 0.05 eV, the TE-polarized terahertz waves and TM-polarized terahertz waves have completely different transmission rates in the low frequency band, as depicted in fc, of 2.25 THz (TE-polarization), 2.34 THz (TM-polarization), and 2.54 THz (TM-polarization), the corresponding transmissions of the proposed metamaterial structure are 3.2%, 2.1%, and 5.8%, demonstrating good stop-band characteristics. The corresponding stop-band bandwidths ∆f(−3 dB) are 120, 140, and 50 GHz, and the corresponding quality factors, Q = fc/∆f, are 18.75, 16.71, and 50.8. Moreover, the transmission properties can also enable the construction of a terahertz wave sensor, and the related investigation method can be found in our previous work [When the conductivity of VOous work .µc = 1.2 eV, the TE-polarized terahertz waves and TM-polarized terahertz waves exhibit similar transmission responses in the low frequency region, as given in µc is 1.2 eV, the transmittance of TE-polarized incident wave is lower than 10% in a narrow frequency range (0.88–1.34 THz). It should be noted that the bandwidth can be broadened by further optimization, including changing the structure size and material properties, etc. In practical applications, specific functions can be implemented according to the requirements. In the high frequency range, when µc augments from 0.05 to 1.2 eV, the metamaterial structure changes from a multi-frequency rejection filter to a single-frequency rejection filter. As given in µc rises from 0.05 to 1.2 eV, the structure also changes from a multi-frequency rejection filter to a single-frequency rejection filter.When the chemical potential is t2 and R2) on the filtering characteristics were also investigated. The conductivity of VO2 and chemical potential of graphene are µc = 0.05 eV, respectively, and the polarization angle of incident wave is 45°. As given in t2 result in only a slight effect on the transmission intensity. In the high frequency band, the change of t2 can affect the position of the resonant peaks, causing the transmission spectrum to show a red-shift trend with the augment of t2. As illustrated in R2 rises from 25 to 29 µm, the transmission of the frequency band 1.2–1.8 THz gradually increases, and the frequency band has a red-shift trend. In R2, and the position of the notch resonant frequency does not change significantly. The results demonstrate that the above transmission functions can also be realized when the geometric parameters perform a slight variation.In addition, the influences of geometric parameters (2 and graphene materials that performs the absorption, LTC polarization conversion, filtering, and switch functions in a single metamaterial device. The integration of different functions into a single metamaterial device was realized by using the insulator–metal phase transition of VO2 and variation of graphene chemical potential. When VO2 is in metal state and the chemical potential is 0.05 eV, the RHCP and LHCP can be achieved in the frequency bands of 0.64–1.28 THz and 1.54–1.85 THz, respectively. When the chemical potential rises from 0.05 to 1.2 eV, three absorption peaks at 0.89, 1.78, and 3.31 THz with the corresponding absorptivity of 96.77%, 90.14%, and 97.44% can be obtained. When VO2 is in insulator state and the polarization angle of incident wave is 45°, the maximum transmission of the TE-polarized wave and TM-polarized wave are different in the range of 1.2–1.8 THz, which can be used to distinguish different polarized incident waves. The corresponding transmissions of the TE-polarized wave demonstrate the opposite results with the different chemical potential of graphene, realizing the switching functions in the frequency band of 0.88–1.34 THz. When the operation frequency is above 2 THz, the multi-frequency rejection filter can be achieved. The proposed metamaterial structure can be applied in many advanced fields, including the fronthaul of terahertz communication system, electromagnetic stealth, radar, etc.In conclusion, we proposed a novel kind of multifunctional metamaterial structure based on the combination of VO


Case Description. A healthy female patient aged 25 years with a pigmented gingiva seeking gingival depigmentation. On examination, a dark brown ribbon of hyperpigmentation was observed within the mandibular attached gingiva. The case was diagnosed as physiological moderate gingival pigmentation (pigmentation index score = 3). The patient was interested in achieving aesthetic results with minimally invasive, nonexpensive procedures. Based on the patient's concerns, the microneedling technique using vitamin C was suggested and consented. We used a dermapen device to microneedle the gingiva until bleeding pinpoints were observed; then, topical ascorbic acid was applied. After 3 days, our outcomes revealed an excellent aesthetic pink gingival appearance. Conclusions and Practical Implications. Compared to other minimally invasive techniques, our technique is less expensive and more risk-free. Our novel technique of using dermapen and topical ascorbic acid has shown promising results to our case which gives new perspectives for its application in gingival depigmentation.A gingival depigmentation is a periodontal plastic procedure that is performed in order to remove melanocytic pigmentation. A variety of different modalities have been proposed for removing hyperpigmentation involving surgical scraping, gingival autograft, cryotherapy, electrosurgery, and lasers. However, the microneedling technique is a nonsurgical procedure that creates microholes to facilitate the penetration of topical medications across the connective tissues.  Since perioaesthetics have become a major demand in dentistry, treatment protocols should not only address functional and biological problems but also establish harmony between white and pink (teeth and gingiva). A typical macroanatomical feature of healthy gingiva is its pink colour which diverges into various shades depending on the degree of keratinization, the thickness of the gingiva, the degree of vascularization, reduction of haemoglobin, and the presence of melanocytic cells .Hyperpigmented gingiva is caused by a wide range of external or internal influences. It is maybe due to physiological or pathological factors, which cause the excessive deposition of melanin granules in melanocytes in the basal and suprabasal layers of the epithelium . GingivaGingival hyperpigmentation was classified according to melanin index by Hanioka et al.  into thrGingival depigmentation (GD) is considered a periodontal plastic procedure whereby melanocytic pigmentation is removed. A variety of different modalities have been proposed for removing hyperpigmentation involving bur abrasion, surgical scraping, gingival autograft, cryotherapy, electrosurgery, and laser . In addiHowever, the microneedling (MN) technique is a nonsurgical procedure that is known as collagen induction therapy involving repetitive punctures on the skin. In dermatology, MN has been utilized considerably in recent years as it is an effective, simple, economical, well-tolerated, and cosmetically and therapeutically beneficial procedure . The MN However, ascorbic acid (AA) has been demonstrated as a water-soluble antioxidant and an essential nutrient for collagen biosynthesis . It playWhile many clinical investigations have been documented, on the effectiveness of the MN technique in treating scars and wrinkles, promoting skin rejuvenation, and managing pigmentation disorders , 12–14, The purpose of the study was to assess the performance of the microneedling technique using dermapen with topical ascorbic acid paste on gingival depigmentation.A healthy 25-year-old female patient complained of aesthically unappealing dark colour in the lower front gum area . AccordiOn clinical examination, no abnormalities were identified extraorally. Intraoral examination revealed a minimal accumulation of plaque and supragingival calculus, indicating an acceptable level of oral hygiene. She had an average plaque index of 0.8 and an average gingival index of 1 with no bleeding upon probing. Neither clinical attachment loss nor radiographic bone loss was determined. There was only mild marginal gingival inflammation accompanied by rolled margins and blunted interdental papillae.A dark brown ribbon of hyperpigmentation was noticed within the gingival mucosa of the mandibular arch confined to the attached gingiva region from right to left 2nd premolars . The casThe patient was most concerned about achieving aesthetic results with minimally invasive, nonexpensive procedures. In light of the patient's concerns, the MN technique was suggested. The patient was provided with a detailed explanation of this off-label procedure, its instructions, and potential complications. Informed consent was established as well as permission for this off-label procedure, photos, and publication.th mode speed of 700 cycles/min. The dermapen was used in intermittent motion on the sextant gingival area for 30-40 seconds/tooth. When bleeding pinpoints were observed on all areas of pigmented gingiva, the gingival mucosa was irrigated with a saline solution and sterile gauze was applied to dry the area. Then, topical AA powder (1000 mg/ml) was mixed with saline in a small glass dish forming a paste. The mixed slurry paste was applied to the gingival mucosa using for 10 minutes as shown in As a preliminary routine, supragingival scaling was performed and oral hygiene instructions were provided by the dental hygienist. We subsequently scheduled the procedure and performed it aseptically. Local anaesthesia 2% lignocaine  was administered by infiltration technique in the mandibular region. To microneedle the gingival mucosa, we used a dermapen device model M8 with 24 microneedles arranged in rows, which was adjusted with 1.5 mm depth at the 6rd day of the second application. Clinical outcomes showed complete disappearance of gingival pigmentation. Generally, after the first and second application, healing was normal and satisfactory providing excellent aesthetic results where the pigmentation index score decreased to zero with reduction of melanin index (class 0) as presented in Figures th month of the follow-up period, repigmentation of the gingiva was detected showing light brown solitary pigmented areas as depicted in One day after the procedure, the attached gingiva exhibited an increase in volume and an alteration in texture as well as the appearance of white and red-coloured areas, indicating tissue inflammation . NeitherAlthough the GP does not exhibit any medical concerns, patients frequently complain of “black gums” seeking cosmetic solutions. In this case presentation, the patient was diagnosed with physiological pigmentation based on the negative history of any pathological cause, since the physiologic pigmentation is probably genetic in nature.GD is considered a periodontal plastic procedure whereby the gingival hyperpigmentation is removed or reduced through various techniques such as scalpel scraping, bur abrasion, free gingival graft, cryosurgery, electrosurgery, and laser . In the To our knowledge, this is the first study to introduce NM with AA in gingival depigmentation. Nevertheless, there was a study done by Ozsagir et al.  who compAlthough, the FDA has legally authorized microneedling devices to improve the appearance of facial acne scars, facial wrinkles, and abdominal scars in patients aged 22 years or older, these devices are still considered as off-label procedures for oral use. However, there are various types of MN devices including dermaroller, dermastamp, and dermapen. Unlike other MN devices, dermapen is the only device that can be applied intraorally due to its small size, changeable head. This increases the accessibility inside the mouth and makes it easy to be used for a larger number of patients. This device is a wireless electric device with automated features that allow the operator to modify the speeds, pressures, and depth of penetration, thus reducing the probability of operator-related side effects.In the present study, the patient agreed and signed explicit written consent for this off-label procedure being used as a part of research. During the procedure, it was necessary to generate precise bleeding pinpoints by MN to achieve optimal results . These mThen, we used topical AA as a therapeutic medication that was reported to be effective in reducing melanogenesis directly and thus promoting depigmentation, because melanin acts as a reservoir for reactive oxygen species (ROS), Cu, and calcium within the cells. Following AA entry into the target tissue, it binds to melanin causing a deficiency of ROS, Cu, and Ca, resulting in the reduction in melanin production . As to sOur outcomes revealed excellent aesthetic results, and these were in agreement with Yussif et al.  who usedFurthermore, our findings were consistent with the results of Shimada et al.  who applFollowing the first day of the procedure, the gingiva showed an increase in volume and a change in texture with white and red-coloured areas representing gingival inflammation, oedema, and irritation. These results were corresponding with numerous clinical studies in dermatology which revealed that the MN technique can cause postoperative transit oedema and erythema that resolves usually after 1-3 days –25.In contrast to any other depigmentation procedure, the patient was able to see these excellent aesthetic results after 3 days . HoweverCompared to other minimally invasive techniques, our technique poses less risk of complications and is less expensive. However, lasers are considered easy, fast, and efficient modalities that have hemostasis and decontamination effects, but they are expensive and tissues heal within 1-2 weeks , 30. AddPigment recurrence is described as a spontaneous and recurrent process that occurs within 24 hours up to 8 years following the depigmentation procedure which poses a challenge to a dentist . MethodsIn our case report, repigmentation was observed after 6 months . This miHowever, our procedure is well tolerated by patients and can be repeated from time to time for more aesthetic results.Clinical experience, affordability, and personal preferences should be considered when selecting a technique for treating gingival hyperpigmentation. Our novel technique of using dermapen and topical ascorbic acid in the treatment of gingival pigmentation showed promising results, which gives new perspectives for its application. Although our technique is a simple and safe GD method, it should be performed cautiously; otherwise, tissue destruction and gingival recession may result. Our results were limited to this particular case. Therefore, the present findings should be confirmed in future randomized controlled clinical trials, including histological analysis.


To have enough financial literacy, an investor must be able to make intelligent investment choices, and on the other hand, the heuristic bias, the framing effect, cognitive illusions, and herd mentality are all variables that contribute to the formation of behavioral biases, also known as illogical conduct, in the decision-making process. The current research looks specifically at behavioral biases and financial literacy influence investment choices, particularly on stock market investment. For the research, a representative sample of 450 individual investors was evaluated. A structured questionnaire was designed using the Likert’s scale method to elicit the research variables, and the data acquired were analyzed using the SEM method. According to the findings, there was a statistically significant link between heuristic bias and the development of behavioral bias in decision-making. Nevertheless, cognitive illusions, the herd mentality, and the framing effect all have a deleterious impact on behavioral biases. In addition, investors often adhere to heuristic biases rather than other irrational strategies when making investment judgments. Therefore, individual investors’ financial literacy level greatly influences the choices made about investments in the stock market. Over the period, financial markets have evolved with technological development and the information accessible to consumers has also become more complicated since people can now choose from various alternatives in the financial markets . The conThe irrationality of investors and the biases that investors are prone to are considered in behavioral finance, a subfield of finance. Investors’ incapacity causes these cognitive biases to forecast the market’s movements, forcing them to make biased investing choices . The subChoosing investments is the result of a psychological and mental process known as decision making, which ultimately leads to the selection of those assets. When making investment judgments, the behavioral finance approach pays little attention to individual investors and does not consider fundamental or technical research. Those who subscribe to the behavioral hypothesis believe that investors act in fundamentally predictable ways whenever they make investing decisions. This demonstrates that investors often purchase equities when their value increases and sell the same stocks when their value decreases. Recently, academics and industry professionals have been trying to find out how emotions and biases influence the overall behavior of individual investors. They emphasized the significance of heuristics, cognitive illusions, the framing effect, and herd mentality in influencing irrational investment judgments .When taken into consideration as a whole, the level of financial literacy possessed by individual investors significantly influences investing choices. This investigation investigates the relationship between financial literacy and behavioral biases in investing choices. Financially savvy persons may, to some degree, prevent illogical conduct . FinanciIn the past, investors lacked the knowledge to analyze a company’s fundamentals, industry, and economy. Ideally, people would mix technical considerations with irrational conduct while making financial decisions. Despite this, contemporary investors have access to enough information and a high degree of financial literacy, which they often use while making investment choices. Therefore, the influence of financial literacy and behavioral biases provides the necessary impetus for initiating such an important empirical study. This research assesses the investing decision-making aptitude of Indian investors. It is feasible to quantify the degree to which individuals prioritize financial literacy in decision-making and the effect of behavioral biases. In addition, it aids in determining if individual investors make sensible or irrational investing choices owing to a lack of financial literacy.The motivation of the study is to gauge the effects of financial literacy and behavioral Biases on investment decisions considering a sample of 450 small investors in India. The elasticities of explanatory variables on investor behavior have been derived with the implementation of structural equation modeling (SEM). Following the estimation output, the study revealed that financial literacy and cognitive behavior positively influenced investment decisions, while the impact of behavioral biases established averse assertion with framing effects. In terms of implication of the study findings, the study advocated that understanding and knowledge of financial information and jargon assist investors in making an appropriate decision with the trade-off between risk-return.The remaining study structure is as follows: section “Literature review and hypothesis development” deals with a relevant literature survey and hypothesis development. The veritable definition and methodology are explained in section “Methodology.” Model estimation and interpretation are displayed in section “Estimation and interpretation.” Discussion and Conclusion are reported in section “Discussion,” and Research Implication is available in section “Conclusion.”The heuristic bias, also known as a rule of thumb, is a method that simplifies the decision-making process for investors, particularly in uncertain and complex circumstances. This method reduces the complexity involved in evaluating the possibilities and predicting the benefits, enabling investors to reach decisions more quickly. This is particularly important for investors who must make judgments in complicated and unpredictable situations . There iIn a study, Only investors are willing to make a commitment of this kind, and representativeness may be characterized as the committed inclination to link new events to those with which one is already aware. Only investors are prepared to commit to this nature . In orde1: Anchoring bias, representativeness, and overconfidence collectively form the heuristic bias in investment decision-making.H2: Heuristic bias has a significant favorable influence on behavioral biases.HThe “framing effect,” which describes how investors cope with unpredictability and risk in their investments, is sometimes referred to by the phrase “prospect theory,” which is typically used to refer to that impact. According to the framing effect, deciding which investments to make may be divided into two stages: the phase in which the framing effect is considered and the phase in which the evaluation impact is considered . In addiCorporate financial activity is tracked and evaluated using traditional accounting methods in firms. In contrast, mental accounting relates to how individuals carry out these tasks in their own lives. According to In Regret aversion is a common psychological phenomenon that affects those who make mistakes in their decision-making process, such as investors. The psychological phenomenon known as regret aversion causes individuals who invest money to feel remorse about specific investing decision-making processes. This phenomenon is described as failing to generate the anticipated return . Neverth3: Mental accounting, the endowment effect, and regret aversion collectively form the framing effect in investment decision-making.H4: The framing effect has a significant favorable influence on behavioral biases.HBehavioral finance is a framework that augments and substitutes some elements of conventional finance. It portrays the interaction between investors and management in financial and capital markets. Investors make illogical investing choices because decision-making is the art of navigating difficult circumstances . TherefoCognitive illusion results from a person’s sensitivity about what he already bought and what he could have bought and does not get as per expectations, therefore feeling bad about his choices. Learning cognitive theory is essential to apprehend as it offers investors to understand unimagined outliers in the rise and fall of stock markets. Cognitive illusions affect the willingness of investors to accept investment options and their ability to grasp and assess such choices . CognitiThe mental process known as conservatism is one in which investors rely on their previous perspectives to make predictions about new information and acquire new ideas. When it comes to investing, experience is much more valuable than acquiring new skills for most investors. The choice based on one’s past experiences did not provide sufficient consistency; investors’ preferences will be determined by their stringent conservative bias. The existence of conservatism demonstrates that financial market participants failed to assimilate new information by clinging to their previous forecasts . People For investors to make informed decisions, they need to have easy access to stock data, an in-depth grasp of the companies they are investing in, and the capacity to forecast the performance of other businesses. Confirmation bias causes investors to be more prone to look just at evidence that supports their prior opinions, which may lead to poor investment decisions. Confirmation bias may be what causes investment bubbles . People 5: Conservatism, confirmation, and hindsight bias form cognitive illusions in investment decision-making.H6: Cognitive illusions have a significant favorable influence on behavioral biases.HAmong the more recent subfields of economics, behavioral finance focuses on financial markets and investors. This method combines the conventional disciplines of economics and finance with psychology and the decision-making sciences. Behavioral finance is comprised of two subfields: macro behavioral finance and micro behavioral finance. Behavioral finance is an attempt to explain observed and verified market anomalies. The area of finance contains these findings and reports. Behavioral finance investigates how investors create opinions or “mental mistakes” in financial decisions . AccordiThe phrase “herd mentality” refers to the phenomena in which rational investors tend to act irrationally to emulate other investors’ judgments in deciding how to invest their money. This occurs when investors are pressured to make investment decisions . Herd meThe bandwagon effect may impact the mental condition of market participants like traders and investors. The feeling investors get when they discover that their choice is consistent with others is known as the “bandwagon effect,” a term derived from “jump on the bandwagon.” However, the outcome of jumping on the bandwagon is often the motivation for these behaviors. When investors see a company’s share price rise, they worry that they will lose out on the rewards. As a result, rather than focusing on the company’s fundamentals, they begin purchasing shares because they think everyone else is doing the same thing . There i7: Information processing, bandwagon effect, and social groups collectively form herd mentality in investment decision making.H8: Herd mentality has a significant favorable influence on behavioral biases.H9: Behavioral biases have a significant favorable influence on the investment decisions of the individual investor.HThe act of decision-making is a convoluted and involved procedure, yet it plays an essential role in studying behavioral finance. The behavior of investors is determined by various variables in addition to the volatility of the market and the potential for profit maximization . The levIn the case of UAE investors, the study of The study’s goal was to establish the extent to which different behavioral biases and financial literacy levels are associated with individual investors’ investment decisions. The study contributes to a better understanding of the many shapes that behavioral biases may take, as well as the potential impact of such biases on investment decisions . In a si10: Financial literacy has a significant favorable influence on the investment decisions of the individual investor.HThis important research analyzes how behavioral biases and financial literacy influence the investment decisions of individual investors. The goal of this study is to gather information from individual investors. Individual investors were acknowledged at the offices of financial advisors, portfolio managers, and stock trading terminals. The study used a personal interview approach by distributing a questionnaire to investors. The questionnaire survey was conducted to enhance data precision and reduce interviewer bias since respondents were permitted to use their democratic rights while answering the questions. From September 2021 to January 2022, the method for gathering data was completed. The first sample consisted of 450 randomly selected individual investors from Northern Indian states. The terms and terminology used in the study were explained, and the suspicious replies were addressed in front of the participants, facilitating the collection of questionnaire responses with no omissions.Sample selection is mostly based on investors’ experience and location, with a preference given to those with at least 2 years’ worth of trading experience and a Northern state residence . The study utilized an experimental research methodology, and the sample was chosen using a basic random sampling procedure. The questionnaire was designed on a 5-point Likert scale, with a score of 5 indicating strong agreement and a score of 1 indicating strong disagreement, to ensure as much consistency as possible among the replies as possible. Investors were also assured that their responses to the questionnaire would be kept confidential. Additionally, 50 local investors were used as a pilot group to assess the poll’s content and face validity before the main survey was conducted. Experts, academics, and investment advisers in the financial sector were consulted over the choice of terminology, the interpretation of terms, and the selection of metrics for the financial sector. Because of this, individual investors could complete the questionnaire with the help of clarification in questions and applicable directions.For investors to make intelligent, risk-free, and productive judgments, they need the knowledge and a grasp of a wide array of financial concepts and facts. Students will gain an understanding of economics and the many ways in which economic factors may play a role in individual decision-making via the completion of this course . FinanciEveryday investing decisions are impacted by various factors, including inclination, motivation, excitement, and social contact, in addition to the available cash, time horizon, and financial objectives . InvestoInvestors base their selections on their stock market expertise and experience. Behavioral finance studies people’s real behaviors and how they process financial information to make informed judgments. Due to its substantial effect on their decisions, investors are starting to accord behavioral finance greater importance. Using hypothetical investment possibilities assists investors in selecting superior stocks . The preThe study administered Structural Equation Modeling (SEM) to concurrently assess and examine how the process of investors’ decision-making was associated with financial literacy and behavioral biases. An amazing statistical tool for studying and measuring relationships between variables is the structural equation model (SEM). On the other hand, latent variables are often not directly observable and must be inferred from other variables. On the other hand, more aspects may be evaluated by empirical observation and measurement. Confirmatory modeling is where structural equation modeling shines, which is used more often in theoretical testing than in actual product development. The measurement model clarifies the relationship between the latent variables and their component indicators, whereas the structural equation model (SEM) conveys the causal relationships between the latent variables. The study has developed a conceptual model to describe investment evaluation and support investing behavior, allowing for predicting the impact of financial literacy and behavioral biases on investment decisions in the stock market .The study applied multivariate analysis, such as confirmatory factor analysis and structural equation modeling, using AMOS 22.0 software to scrutinize the research objectives. In SEM, the relationship between theoretical constructs is designated by the path or regression coefficients between the factors presented. Using SEM, data analysis was conducted in two phases. Overall measurement quality was evaluated by confirmatory factor analysis, and concurrently reliability and validity of the instrument had also been measured. Subsequently, structural equation modeling was applied to determine if the model fitted the results of the proposed theoretical models. The study also applied CFI, NFI, TLI, PNFI, PCFI, RFI, IFI, CMIN/DF, and RMSEA to measure the model’s fit. Further, independent association between the different variables had also been investigated.The socio-economic background of individual investors is examined by using percentage analysis. The results are furnished in There are a total of 84% male investors and just 16% female investors, as shown in SEM offers a method for identifying the impact of an external component on investment decisions by laying out a path for the rapid examination of the whole model that seeks multiple hypothetical linkages. There are two components to the analysis: first, a measurement model with a latent construct is looked at, and then a structural equation model is looked at, which considers all constructs and their potential connections. With the theories mentioned above in mind, I use 15 independent variables to develop five latent constructs: heuristic bias, framing effect, cognitive illusions, herd mentality, and financial literacy. A measurement model was developed to evaluate the reliability and validity of the latent variables. The results may be seen in p = 0.000, CFI = 0.903, and RMSEA = 0.067. Additionally, the value of CFI is 0.903. In addition, the findings indicate that CFI = 0.903 and RMSEA = 0.067 respectively. As a direct result, the scores obtained from the goodness of fit test suggest a model almost perfectly suited to its data. After determining the reliability and validity of each component, the next step is to analyze the model as a whole.As shown in Because the suggested measurement model accords with the available data, the study hypotheses may be evaluated. The model results are shown in The results of the goodness-of-fit test for the SEM are shown in Coefficient values for anchoring bias (0.795), overconfidence (0.572), and representativeness (0.773) due to heuristic bias are shown in The confirmation bias coefficient for cognitive illusions is 0.311, the hindsight bias coefficient is 0.669, and the conservatism bias coefficient is 0.506. Evidence supports that cognitive illusions are strongly related to their contexts (H5). The correlation between cognitive illusions and prejudices in conduct is negative (-0.274), yet we still support the hypothesis (H6) about the relationship between cognitive illusions and behavioral biases. The results are consistent with The value of the coefficient for financial literacy is 0.48 when it comes to financial competence, -0.108 when it comes to financial proficiency, and 0.005 when it comes to financial opportunity. Although this hypothesis (H10) is accepted, it should be noted that the conceptions of financial literacy directly influence the level of sufficient financial knowledge required when making investment choices. The finding supports the accepted hypothesis that financial literacy has a coefficient value of 0.051 for investment decisions and has a favorable impact on investment decisions (H11). The results are consistent with those of The disparities between heuristic bias and framing effect are shown in This research investigates financial literacy and behavioral biases’ role in the illogical behaviors people sometimes engage in while making decisions. A large amount of behavioral bias is included in investors’ investment judgments. Financial literacy enables one to rationalize such illogical conduct and arrive at a conclusion that is more likely to bring about the intended increase in profit. In light of this fact, the research extends the application of behavioral economics to the process of decision-making about investments among individual investors . Eleven The study’s findings demonstrated that three cognitive biases—anchoring, representativeness, and overconfidence—directly contribute to bad investment decisions based on incorrect perceptions about past success. The study finding is supported by the existing literature such as In the financial markets, emotional decision-making is common due largely to cognitive biases. Investment in a business is fraught with cognitive illusions due to factors such as conservativeness, confirmation bias, and hindsight bias. Our study findings are in line with Therefore, investors may better judge stock buy/sell timing, portfolio risk, and projected return with a firm knowledge of financial fundamentals. Understanding the financial markets and gaining the information, talent, and opportunity that come with it may boost an investor’s likelihood of making profitable investment selections. Behavioral biases include heuristic bias, the framing effect, cognitive illusions, and herd mentality. It lends credence to the notion that investors depend on heuristics rather than frames, illusions, or herd mentality. When it comes to individual investors, however, the heuristic bias has a disproportionately negative effect on intelligence. As a result, investors rely heavily on the rule of thumb as a guiding principle for making important decisions. To some extent, investors form their expectations based on their market knowledge. Trusting and implementing previously known plans might be less of a mental strain for investors than developing novel ways of choosing equities. People sometimes fall prey to herd mentality rather than using their critical thinking abilities in the face of repeated losses or traumatic situations. It has been shown that behavioral biases significantly impact economic choices.Investing decisions are heavily influenced by people’s lack of knowledge about finance and their susceptibility to various forms of prejudice. Behavioral biases may give some foundational ideas that might help investors make better investment choices, and investors may benefit from financial literacy coaching to comprehend the investing environment better. The significant independent connection between the variables indicates that heuristic bias substantially affects both the framing effect and cognitive illusions when making judgments. However, this has negative effects on the “herd mentality.” Cognitive illusions are bolstered by the framing effect, whereas the herd mentality is diminished. Investors should guard against the herd mentality that might arise from succumbing to cognitive illusions in the stock market. Individual investors’ irrational conduct in the stock market is not surprising, given market participants’ high level of financial knowledge.Investment decision-making is how investors weigh both logical and emotional factors. While it is true that investors do not always make the most logical decisions, standard financial theories assume that they do. Nevertheless, modern financial theories propose that one’s gut rather than one’s head should be the deciding factor when making financial decisions. Our study finding of financial literacy increases the accuracy in prediction for investment is supported by the existing literature . For exaInvestors’ decision-making is a complex and complicated process governed by several behavioral facts, including understanding financial information, attitude to assessment, and the capacity to capitalize correctly. The motivation of the study is to evaluate the effects of financial literacy and the behavioral basis on investment decisions. As a sample for research data collection, the study considered 475 small investors, and with the application of SEM, the expected hypothesis has been evaluated and investigated.In terms of the hypothesis assessment, the study documented that financial literacy has positively connected to the investment decision, suggesting that investors’ understanding of financial information is appropriately guided toward appropriate investment decisions. Further, the findings point to the following avenues for study and advancement in the field. The process of assigning value to an asset in the context of a purchasing decision is a challenging one for individual investors. Given that nobody can know which way stock prices will go in the future, successful traders must develop their methods or study those already proven effective. Rule of thumb, personal calculation, and past experiences have all been used by successful investors to construct their methods. By making the most educated choices feasible, investors may maximize their returns.Successful investing in the stock market requires knowledge of the ever-changing market and the ability to generate viable investment ideas. If investors have access to the correct data, stock market education might be more beneficial. Those who put their money into the stock market often have an irrational mindset since they have not been taught otherwise. While illogical wagers may provide short-term gains, they would ultimately prove costly. Academics, legislators, and experts need to provide more opportunities for training and growth so that investors may make better decisions.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.MQ: methodology, interpretation, first draft, and final draft. RK: introduction and data curation. SW: literature survey and methodology of the study. WR: literature survey, data curation, and final draft. All authors contributed to the article and approved the submitted version.


This study proposes an innovative use of a modified version of photovoice for cross‐national qualitative research that allows participants to express their ideas, experiences, and emotions about a topic through photographic language. We examine factors affecting social service providers' work on people experiencing homelessness in Europe. We highlight five advantages of using photovoice in cross‐national research: visual language, methodological flexibility, participatory data analysis, the bottom‐up process, and the promotion of social change. Moreover, we identify key stages of the process: writing a detailed protocol for the implementation and fidelity of the projects, using two levels of data analysis, and disseminating the results. This study provides lessons learned for others who may want to use photovoice in cross‐national research. Qualitative methods provide a detailed understanding of people's experiences across countries.This article offers an example of using photovoice to study homeless services in Europe.This study showed the benefit of using photovoice in comparative qualitative research across nations.This study provides recommendations for those who may want to use photovoice in cross‐national research. In an increasingly multi‐cultural world where interventions transcend national boundaries, international research collaborations involving multiple countries are increasing  to evidence‐based intervention practices such as Housing First  perspectives  multi‐method project funded by the program “Horizon 2020” .The number of service providers: ideally, at least four staff members from each program should be involved.Length of service: only staff members who have worked in the organization for at least 6 months (so that they had enough work experience to report on) and who worked together as a team, meeting regularly should be included.Direct service: participants should be engaged in direct service with users, not merely administration.The HOME_EU partners in each country selected organizations that worked with people experiencing homelessness. Although sampling was based on availability, we recommended specific criteria for the selection of organizations and participants. When, due to peculiarities of services in a specific country, it was not possible to respect one or more of these criteria, we asked partners to provide information about the choices made about sampling. The criteria were as follows:Before proceeding with the photovoice projects, we asked partners to tell us about any issues and update us on sampling and photovoice meetings. Throughout the project phase, we stayed in touch with HOME_EU Consortium partners via email, and we discussed projects together in face‐to‐face meetings every six months. One photovoice project in an HF service and a photovoice project in TS were conducted in most countries. Exceptions were Italy, where two HF and one TS photovoice projects were conducted, and Poland, where two TS photovoice projects occurred since there were no HF programs in the country yet.For each phase of the research, we provided templates of consent forms in English, which were translated and adapted by partners based on their country's laws. Informed consent forms were provided for the organizations involved, the research participants, and any individuals who could be photographed by the participants (to give consent to be photographed and to use the photograph in the project).Next, the protocol detailed the procedure for the photovoice groups, as summarized in Table lingua franca for the project. Then, professional translators performed back translations, which were checked by the local research partners. Translations were modified as necessary so that the original meaning and cultural nuances were retained.The translation procedure followed the best practices  were included in the data analysis.All countries successfully implemented the phases of the photovoice, producing rich data for cross‐national analysis. It was impossible to find organizations willing to participate in more than three meetings in one country. Therefore, both groups had three face‐to‐face meetings, and the sharing of results was done online. The changes were not as disruptive as to be considered in the analysis. We had no other reports of major changes to the protocol concerning photovoice meetings, but in most countries, groups stopped after analyzing their data and preparing a report, rather than using photovoice to move to action. Thus, the lack of social change actions could be because, at the country level, photovoice was considered more as a research method to investigate obstacles and facilitators of social service providers' work and not as a participatory action research methodology. As we will see in the results, in only three countries, the groups present their results to politicians and citizens. In one country, the project facilitated advocacy with respect to a new model of homeless services, and another participant developed operational proposals for change in their own organizations.Moreover, cross‐national data has enabled the identification of a European culture of homeless services and the development of policy guidelines to assist in transitioning from TS to evidence‐based programs such as HF.First, data analysis was conducted within each country and within each photovoice group in collaboration with participants , and this may have also influenced the style of conducting the photovoice projects. In addition, only the lead group in the study had experience with the photovoice methodology. Even though all team partners were experienced in homelessness, this was the first time they had used photography methodology. The lack of effort in producing social change may also be due to facilitators' lack of background and experience with participatory action research methodologies in most countries.The results of this study can be summarized in two main aspects:In Italy, Poland, and France, participants and researchers organized exhibitions in strategic places to present the photovoice results to the community and local politicians. These exhibitions have been an opportunity to raise community awareness of homelessness. The exhibitions were visited by citizens, providers in other community services, mass media, and local politicians. As is often the case with a photovoice project, dissemination has led to a change. For example, in an Italian photovoice project, the participants elaborated four proposals for change in their organization: internal communications, the relationship between providers and volunteers, the need for constant updates on the clients' process, and training and psychosocial supervision of the team. Photovoice results and proposals were presented during a meeting with the organization's leaders and shown in an exhibition associated with a conference with citizens and providers from other services. In a follow‐up evaluation one year later, most of the proposals identified through the photovoice had been implemented. Further, in Poland, reflection on photos contributed to the spread of advocacy initiatives that have led to the implementation of HF , while also bringing out their emotions  documented long‐term changes in an organization involved. More training to partners on the guiding principles of the methodology and the importance of participatory action research could have helped them understand the potential of photovoice. The project also contributed to change at a cross‐national level by contributing to the development of European guidelines for implementing services to tackle homelessness .Social change is the most fundamental aspect of photovoice, but it is also the most difficult to achieve because it requires time, resources, and a reflective approach from researchers  support in the process, (b) promotion of social change, (c) analysis of photographs, and (d) the comparison between nations.First, regarding the support in the process, this research was made possible by the continual interactions among the project's consortium members and was based on a common detailed protocol about planning , process (detailed explanation of each step of the photovoice method), and data analysis. This ensured that the research was methodologically solid, balancing the need for the research to be structured enough to allow cross‐national comparisons while ensuring that it was grounded in local contexts. Nevertheless, it was sometimes difficult to know in detail how photovoice projects were progressing. In addition, the country reports of themes varied considerably in length across the photovoice groups. It is possible that groups with short reports also discussed some of the themes apparent in the lengthier reports, but did not deem them sufficiently central to mention. It is also possible that facilitators who drafted the reports and translated them into English had different understandings of the amount of detail it would be valuable to include, or, because of differential levels of comfort in English, chose shorter or longer presentations.Moreover, regarding the second lesson learned, we note that not all countries fully realized the social change goal of photovoice. Future studies using this methodology would benefit from a better balance between research and action by using research findings to inform organizational and community changes based on scientific knowledge. Greater support in learning about the guiding principles of the methodology and how to support social change might have helped more countries realize this goal .In the future, we suggest starting with a workshop—at least a one day workshop  was not shared with all photovoice project participants. Only a few participants saw the European exhibition in Padua. Member‐checking is an important way to assure the trustworthiness of qualitative research , and to promote shared guidelines for intervention between countries.As we pointed out in the introduction, cross‐national research poses some important challenges that concern sampling, study management, language, and cultural norms. As a participatory action research methodology that uses photographic language, photovoice can overcome these challenges through the use of visual language, flexibility, data analysis with participants, bottom‐up processes, and promotion of social change.The importance of sharing the guiding principles of photovoice, not just the methodology to promote social change;The need to provide local researchers with both a country report template that contains the results of the project and one to describe reflections of the researchers who conducted the project;The need to conduct frequent interpretation sessions with all the partners to discuss key concepts in‐depth;The importance of engaging all photovoice participants for confirmation of cross‐national results.Through our experience in social service providers of homeless services in eight European countries, we have reflected on the feasibility of using photovoice to increase knowledge on a European phenomenon, highlighting some strengths and providing recommendations for those who would like to use this method at a cross‐national level. Our recommendations start with the reflections made during the implementation of the European project and concern. The reflections include the following:Overall, the implementation of photovoice projects is not only about the adaptability of a method but also the reflective capacity of researchers on the importance of using this methodology to promote social change.In conclusion, implementing a photovoice in a cross‐national context involves challenges. Nevertheless, the study demonstrated the benefits and feasibility of using photographs in comparative qualitative research across nations, languages, and cultures, not only to facilitate local change but also to understand a common European culture of a phenomenon and to contribute to the elaboration of policy guidelines shared among countries.This research was funded by the European Commission through a grant, as part of H2020 research project HOME_EU: Reversing Homelessness in Europe H2020‐SC6‐REVINEQUAL‐2016/GA726997. The grant agreement between the European Commission and each research unit involved allows complete liberty and autonomy of researchers in the design of the study; the European Commission will take no part in data collection procedures, analyses, interpretation of the data, or decision to submit results.The authors declare no conflict of interests.