Translation and Validation of a State-Measure of Body Image Satisfaction: The Body Image State Scale

The aim of the present study is to test the validity and reliability of the French Body Image State Scale (F-BISS). The scale was translated using a back-translation technique, with discrepancies being settled through consensus. Three hundred and twelve female participants were recruited. Convergent validity was assessed using eating disorder evaluation and social comparison. Exploratory and confirmatory factor analyses were also conducted. The translated Body Image State Scale (BISS) demonstrated good psychometric properties, with good internal consistency (α = 0.83), and adequate goodness-of-fit. The translated BISS presented a unifactorial structure, with one factor explaining 56% of the variance. The exploratory factor analysis led to the removal of a single item due to insufficient factor loading (<0.45). Its convergent validity seems consistent with previous literature. Discriminant analyses showed a significant difference in F-BISS score between participants relative to eating disorder symptomatology (t = 11.65; p < 0.001). This translation could prove useful in both research and clinical settings to assess state body satisfaction in French populations.

A Convolutional Neural Network-Based Classification and Decision-Making Model for Visible Defect Identification of High-Speed Train Images

In high-speed train safety inspection, two changed images which are derived from corresponding parts of the same train and photographed at different times are needed to identify whether they are defects. The critical challenge of this change classification task is how to make a correct decision by using bitemporal images. In this paper, two convolutional neural networks are presented to perform this task. Distinct from traditional classification tasks which simply group each image into different categories, the two presented networks are capable of inherently detecting differences between two images and further identifying changes by using a pair of images. In doing so, even in the case that abnormal samples of specific components are unavailable in training, our networks remain capable to make inference as to whether they become abnormal using change information. This proposed method can be used for recognition or verification applications where decisions cannot be made with only one image (state). Equipped with deep learning, this method can address many challenging tasks of high-speed train safety inspection, in which conventional methods cannot work well. To further improve performance, a novel multishape training method is introduced. Extensive experiments demonstrate that the proposed methods perform well.

Negative ion formation by neutral hydrogen atom grazing scattering from a LiF(100) surface

H− conversion during H0 grazing scattering on a LiF(100) surface, includes H− affinity electron loss to a surface image state.

Improving Color Space Conversion for Camera-Captured Images via Wide-Gamut Metadata

Color space conversion is the process of converting color values in an image from one color space to another. Color space conversion is challenging because different color spaces have different sized gamuts. For example, when converting an image encoded in a medium-sized color gamut (e.g., AdobeRGB or Display-P3) to a small color gamut (e.g., sRGB), color values may need to be compressed in a many-to-one manner (i.e., multiple colors in the source gamut will map to a single color in the target gamut). If we try to convert this sRGB-encoded image back to a wider gamut color encoding, it can be challenging to recover the original colors due to the color fidelity loss. We propose a method to address this problem by embedding wide-gamut metadata inside saved images captured by a camera. Our key insight is that in the camera hardware, a captured image is converted to an intermediate wide-gamut color space (i.e., ProPhoto) as part of the processing pipeline. This wide-gamut image representation is then saved to a display color space and saved in an image format such as JPEG or HEIC. Our method proposes to include a small sub-sampling of the color values from the ProPhoto image state in the camera to the final saved JPEG/HEIC image. We demonstrate that having this additional wide-gamut metadata available during color space conversion greatly assists in constructing a color mapping function to convert between color spaces. Our experiments show our metadata-assisted color mapping method provides a notable improvement (up to 60% in terms of E) over conventional color space methods using perceptual rendering intent. In addition, we show how to extend our approach to perform adaptive color space conversion based spatially over the image for additional improvements.

Novel Deep Level Image State Ensemble Enhancement Method for M87 Imaging

Standard spatial domain filters fail to adequately denoise and enhance the contrast of an image. These filters have drawbacks like oversmoothing, diminished texture, and lack of generative capabilities. This paper proposes a new method of image reconstruction, Image State Ensemble Enhancement (ISEE), based on our previous work, Image State Ensemble Decomposition (ISED). Deep level ISEE and ISED have been developed to produce a class of filters that can address these issues. Full-reference and no-reference quality metrics are used to assess the image, and the full reference metrics showed a marked improvement, while the no-reference metrics were often better than the test image. The test image was taken from the Spitzer Space Telescope (SST), and ISEE reconstruction yielded improved structural detail over that of ISED and the original test image. Glare and noise were reduced in a narrow bandwidth, which led to the discovery of a vortex-shaped structure and an outburst in M87′s dusty infrared core. The vortex is located over M87′s visible core and black hole. This is verified with an SST and Hubble Space Telescope (HST) overlay, ISEE processed image. A counter-jet channel was also discovered, and it appears to be the path of the unobservable superluminal counter-jet.

Novel Image State Ensemble Decomposition Method for M87 Imaging

This paper proposes a new method of image decomposition with a filtering capability. The image state ensemble decomposition (ISED) method has generative capabilities that work by removing a discrete ensemble of quanta from an image to provide a range of filters and images for a single red, green, and blue (RGB) input image. This method provides an image enhancement because ISED is a spatial domain filter that transforms or eliminates image regions that may have detrimental effects, such as noise, glare, and image artifacts, and it also improves the aesthetics of the image. ISED was used to generate 126 images from two tagged image file (TIF) images of M87 taken by the Spitzer Space Telescope. Analysis of the images used various full and no-reference quality metrics as well as histograms and color clouds. In most instances, the no-reference quality metrics of the generated images were shown to be superior to those of the two original images. Select ISED images yielded previously unknown galactic structures, reduced glare, and enhanced contrast, with good overall performance.

The internal political image of Ukraine as an important factor of modeling state image policy

The article analyses the internal political image of the state and its influence are on the external political image. Interdependence of the internal political and the external political image state is also shown. This article demonstrates once again high actuality and urgency research the internal political image of Ukraine, as an important factor and basis for producing a guided the state image policy. Understanding of the internal political image helps planning the actions for creation actual image of the state on the world arena. It is found out in article, that forming and realization of image policy of the state with every year becomes more actual task for every state in the world. The author offers in the article authorial determinations of "political image of the state" and of "internal policy image of the state". Also the article faces in detail the historical features the perception an image of Ukraine. Although, article shown and analysed the functions of the internal image policy. And on this basis author suggests actual and clear tasks for the improvement of internal image policy of Ukraine. Separate attention in article is spared to consideration of features of mentality of people of Ukrainians. On the analysis of the positive and negative factors of internal image policy, author proposes the most effictive methods of their use. The article determinates the political image of the state and shows its functions. The structure of political image of the state is also considered, that allowed yet deeper to see intercommunication of internal and external image of the state. Also author gives further directions of research, that will allow to create more effective image policy of Ukraine.

Beyond raw-RGB and sRGB: Advocating Access to a Colorimetric Image State

Most modern cameras allow captured images to be saved in two color spaces: (1) raw-RGB and (2) standard RGB (sRGB). The raw-RGB image represents a scene-referred sensor image whose RGB values are specific to the color sensitivities of the sensor's color filter array. The sRGB image represents a display-referred image that has been rendered through the camera's image signal processor (ISP). The rendering process involves several camera-specific photo-finishing manipulations intended to make the sRGB image visually pleasing. For applications that want to use a camera for purposes beyond photography, both the raw-RGB and sRGB color spaces are undesirable. For example, because the raw-RGB color space is dependent on the camera's sensor, it is challenging to develop applications that work across multiple cameras. Similarly, the camera-specific photo-finishing operations used to render sRGB images also hinder applications intended to run on different cameras. Interestingly, the ISP camera pipeline includes a colorimetric conversion stage where the raw-RGB images are converted to a device-independent color space. However, this image state is not accessible. In this paper, we advocate for the ability to access the colorimetric image state and recommend that cameras output a third image format that is based on this device-independent colorimetric space. To this end, we perform experiments to demonstrate that image pixel values in a colorimetric space are more similar across different makes and models than sRGB and raw-RGB.

Outline of an experimental design aimed to detect protein A mirror image in solution

There is abundant theoretical evidence indicating that a mirror image of Protein A may occur during the protein folding process. However, as to whether such mirror image exists in solution is an unsolved issue. Here we provide outline of an experimental design aimed to detect the mirror image of Protein A in solution. The proposal is based on computational simulations indicating that the use of a mutant of protein A, namely Q10H, could be used to detect the mirror image conformation in solution. Our results indicate that the native conformation of the protein A should have a pKa, for the Q10H mutant, at ≈6.2, while the mirror-image conformation should have a pKa close to ≈7.3. Naturally, if all the population is in the native state for the Q10H mutant, the pKa should be ≈6.2, while, if all are in the mirror-image state, it would be ≈7.3, and, if it is a mixture, the pKa should be larger than 6.2, presumably in proportion to the mirror population. In addition, evidence is provided indicating the tautomeric distribution of H10 must also change between the native and mirror conformations. Although this may not be completely relevant for the purpose of determining whether the protein A mirror image exists in solution, it could provide valuable information to validate the pKa findings. We hope this proposal will foster experimental work on this problem either by direct application of our proposed experimental design or serving as inspiration and motivation for other experiments.