Visual Appearance Research Articles

Kresba nebo fotomontáž pro děti? Příklady inovativních přístupů ilustrace dětské knihy v meziválečném Československu

The aim of the paper has been to show the plethora of innovative approaches to the illustration of books for children in the interwar period in Czechoslovakia (1918–1938). In a journal focused on education and literature (Úhor [Fallow]), the first synthetic text devoted to the aesthetics of children’s books was published as late as 1935, written by Josef Novák. His text perceives the illustrations of children’s books as an important and distinctive artistic expression dependent on the drawing conception of a form. It highlights the most modern examples in the form of the book of Zdenka Marčanová and Toyen, Náš svět [Our World], but not without reservations; it provides another modern example in Karel Čapek’s Dášeňka, on whose typography Karel Teige worked in 1933. The artistic potential of illustration is thus dominated by the individual approaches of particular authors. As early as 1918, the anthology Nůše pohádek [A Basketful of Fairy Tales] brought some unconventional illustrations, adopting elements from progressive art movements. Jeníkovy pohádky [Jack’s Fairy Tales], written and illustrated by Jan Zrzavý in 1920, enriched the visual appearance of children’s books with variations of dream imagery and with the interconnection of image and text according to the author’s concept with the involvement of a visually dominant and aesthetically modified typeface. In particular in Milada Marešová’s drawings published at the turn of the 1930s, it is possible to observe a new way of working with traditional means of expression. Her drawings were a reaction to the contemporary foreign approaches of the New Objectivity. In the early 1930s, Josef Čapek’s book graphics and illustrations were characterised by a shift towards multimedia. The involvement of the avant-garde painter Toyen in children’s book illustration proceeds from Civilism to Surrealism. A distinctly avant-garde form was given to the experimentally conceived popular-educational book by J. V. Pleva Kapka vody [A Drop of Water] in the graphic design of Zdeňek Rossmann, who creatively combined typography with photomontage. Photomontage was used by Augustin Tschinkel in his popular-educational books, either together with Ladislav Sutnar, for instance in Malá vlastivěda [A Little Civics Reader]), or on his own in the book Zeměpisné rebusy [Geographical Rebuses]. The works of the last three mentioned avant-garde artists are typical examples of the progressive graphic design where graphic symbols have been replaced by illustrations. These publications were created within a new model of cooperation – collaboration between a typographer, designer and illustrator in an authorial whole. Significantly radical experiments applying constructivist aesthetics and involving photography were unique in children’s literature in Czechoslovakia.

Tagged-to-Cine MRI Sequence Synthesis via Light Spatial-Temporal Transformer.

Tagged magnetic resonance imaging (MRI) has been successfully used to track the motion of internal tissue points within moving organs. Typically, to analyze motion using tagged MRI, cine MRI data in the same coordinate system are acquired, incurring additional time and costs. Consequently, tagged-to-cine MR synthesis holds the potential to reduce the extra acquisition time and costs associated with cine MRI, without disrupting downstream motion analysis tasks. Previous approaches have processed each frame independently, thereby overlooking the fact that complementary information from occluded regions of the tag patterns could be present in neighboring frames exhibiting motion. Furthermore, the inconsistent visual appearance, e.g., tag fading, across frames can reduce synthesis performance. To address this, we propose an efficient framework for tagged-to-cine MR sequence synthesis, leveraging both spatial and temporal information with relatively limited data. Specifically, we follow a split-and-integral protocol to balance spatialtemporal modeling efficiency and consistency. The light spatial-temporal transformer (LiST2) is designed to exploit the local and global attention in motion sequence with relatively lightweight training parameters. The directional product relative position-time bias is adapted to make the model aware of the spatial-temporal correlation, while the shifted window is used for motion alignment. Then, a recurrent sliding fine-tuning (ReST) scheme is applied to further enhance the temporal consistency. Our framework is evaluated on paired tagged and cine MRI sequences, demonstrating superior performance over comparison methods.

Displaying and Experiencing Dress Identities in Museums: Case Studies from the Etruscan Period to Modern Times

Dress, clothes, and accessories receive and give meaning through their nearness to the human body. As P. Stallybrass writes: “Bodies come and go: the clothes that have received those bodies survive.” It is through the close interaction between dress and person that they both receive their meaning. Clothes shape the human body, and we in return shape our clothes. Dress communicates class, gender, nationality, and marital status, and we leave behind parts of us in its smell, wrinkles, wear, and tear: “Clothes receive the human imprint.” Archaeological and historical dress — no matter how ancient — remain intrinsically linked to their wearers. These are objects of use, affection, value, and memory, and through the study of the dress of past people, we may wear their habits and inhabit their spaces however briefly. The visual appearance of people, in more recent times as well as throughout history, is a clear marker of identity and an important communication medium. For this reason, costume and jewelry serve as an “anchor point” to involve people of the 21st century in studies of the life of prehistoric and ancient societies. This is worth considering, as archaeological textile research needs a strong commitment to public outreach and education, as well as to be integrated into the challenges of our time and to participate in current debates. Through the lens of deep history, it can inspire people to think about such questions as identity, resource use, and shared heritage, among others. Dissemination of textiles and clothing for the broader public in museums is realized through various channels. These range from the exhibition of individual objects, such as textiles, garments, jewelry, and dress accessories, to virtual recreations, and encompasses workshops, citizen science projects for the recreation of historical garments, media-effective historical fashion shows, and reinterpretations of aspects of historical garments through contemporary fashion. This remains an ongoing process, since the interpretation of the past will never be complete, and every generation formulates new approaches. The EuroWeb COST Action (2020–2024) serves as an innovative hub to gain understanding of historical as well as recent dress identities. For this contribution, different aspects of the history of fashion from various museums have been selected as case studies, to demonstrate the wide span of possibilities for displaying and experiencing Dress Identities. Our journey starts with Etruscan jewelry as displayed at the Staatliche Antikensammlungen in Munich (Germany), leading to Early Medieval dress, recreated from various sources as a physical dress ensemble as well as a virtual one, and used for science communication at the Natural History Museum Vienna (Austria) and Halle an der Saale (Germany). As both of the first examples derive from archaeological contexts, we do not have complete garments. This was why we also wanted to explore the possibilities for dissemination of “folk historic costumes”, like a traditional mourning dress as displayed at the Museum Amager (Denmark).

PH-Responsive textile with anthocyanin-laden hydrogel yarns: a colorimetric and feasibility study

Abstract Responsive materials can transform their visual appearance in reaction to environmental stimuli. One example of such responsiveness involves the use of plant-based anthocyanins as pH-mediated allochroic pigments. Despite the increasing interest and applications of this pigment, its applications in urban contexts are very limited. By using pH-mediated colour change as a phenomenon to trial a colourimetric quantitative framework, this study seeks to bridge smart material design with colour science approaches to enable future scale-up applications. The colour values of anthocyanins immobilised in sodium alginate-based hydrogel discs and yarns were measured in response to varying pH values. The colourimetric measurements in CIELAB colour space provided a device for setting independent colour values that demonstrated a clear pattern across the pH range of 1–12. The colour difference (ΔE00) of mean colour values was perceivably different across the pH scale, with a minimum value of 2.7. Key variables of the process have been summarised, and their relationships have been discussed. Finally, a proof-of-concept small-scale textile prototype encompassing anthocyanin-laden hydrogel yarns was developed. The findings of this study contribute towards the integration of non-destructive means of colour measurement as a quantitative tool for biochemical process evaluation.

Multimodal Distillation Pre-training Model for Ultrasound Dynamic Images Annotation.

With the development of medical technology, ultrasonography has become an important diagnostic method in doctors' clinical work. However, compared with the static medical image processing work such as CT, MRI, etc., which has more research bases, ultrasonography is a dynamic medical image similar to video, which is captured and generated by a real-time moving probe, so how to deal with the video data in the medical field and cross modal extraction of the textual semantics in the medical video is a difficult problem that needs to be researched. For this reason, this paper proposes a pre-training model of multimodal distillation and fusion coding for processing the semantic relationship between ultrasound dynamic Images and text. Firstly, by designing the fusion encoder, the visual geometric features of tissues and organs in ultrasound dynamic images, the overall visual appearance descriptive features and the named entity linguistic features are fused to form a unified visual-linguistic feature, so that the model obtains richer visual, linguistic cues aggregation and alignment ability. Then, the pre-training model is augmented by multimodal knowledge distillation to improve the learning ability of the model. The final experimental results on multiple datasets show that the multimodal distillation pre-training model generally improves the fusion ability of various types of features in ultrasound dynamic images, and realizes the automated and accurate annotation of ultrasound dynamic images.

Atopic Dermatitis: Managing the Itch.

Atopic dermatitis has a substantial impact on sleep, appearance, psychological well-being, and other qualities of life. The visual appearance of lichenification, cheilitis, hyperpigmentation, ichthyosis, and erythema can be socially stigmatizing, and treatment of these symptoms is challenging. In managing pruritus in patients, practitioners should assess and document pruritus through questionnaires at each routine visit. Initially, practitioners should advise patients to employ nonpharmaceutical treatments such as emollients with wet wraps, elimination of triggers, changing scratching habits, and psychological interventions. If these methods of treatment are not successful or if the disease presentation is severe, pharmacological therapies should be employed. This chapter describes the therapeutic ladder for pruritus in atopic dermatitis and discusses each treatment modality in further detail for practitioners to advise their patients.First-line topical pharmaceutical agents include topical glucocorticoids and topical calcineurin inhibitors. Second-line topical agents include coal tar, menthol, capsaicin, or doxepin. After the use of topical agents has been exhausted, primary systemic agents can be applied. These include sedating antihistamines, nonsedating antihistamines, oral glucocorticoids, or cyclosporine A. Finally, neuromodulating or immunomodulating agents can be attempted, including SSRI/SNRIs, TCAs, immunosuppressants, neural modulators, and opioid receptor modulators. Outside of pharmacological treatments, phototherapy has been shown to provide a dramatic improvement of pruritus in atopic dermatitis and can be used at any stage of treatment including as a first-line agent.

Effect of oil–water colloidal states in liquid feeds on extrudability and textural attributes of high-moisture meat alternatives

Lipid incorporation into high-moisture meat alternatives by extrusion processing and its effect on extrudability, visual appearance, textural and structural properties is highly dependent on the colloidal state of the oil phase.

Total fractional-order variation and bilateral filter for image denoising

Image denoising stands out as a primary goal in image processing. However, many existing methods encounter challenges in preserving features such as corners and edges of an image while deleting the noise. This study investigates and evaluates a fractional-order derivative based on the total α-order variation (TV) model and the bilateral total variation (BTV) model. This choice is motivated by the proven effectiveness of the TV model in noise removal and edge preservation, with the BTV model further utilized to enhance the restoration of fine and intricate details. The experimental results affirm the efficacy of the proposed model, supported by objective quantitative metrics and subjective assessments of visual appearance.

CSFwinformer: Cross-Space-Frequency Window Transformer for Mirror Detection.

Mirror detection is a challenging task since mirrors do not possess a consistent visual appearance. Even the Segment Anything Model (SAM), which boasts superior zero-shot performance, cannot accurately detect the position of mirrors. Existing methods determine the position of the mirror under hypothetical conditions, such as the correspondence between objects inside and outside the mirror, and the semantic association between the mirror and surrounding objects. However, these assumptions do not apply to all scenarios. For instance, there may be no corresponding real objects to the reflected objects in the scene, or it may be challenging to extract meaningful semantic associations in complex scenes. On the other hand, humans can easily recognize mirrors through the specular texture caused by materials. To mine mirror features in more general scenes, we propose a Cross-Space-Frequency Window Transformer (CSFwinformer) to extract spatial and frequency features for texture analysis. Specifically, we design a Spatial-Frequency Window Alignment module (SFWA) to calculate spatial-frequency feature affinities and learn the difference between mirror and non-mirror textures. We then propose a Dilated Window Attention (DWA) to extract global features to complement the limitation of window alignment. Besides, we propose a Cross-Modality Context Contrast module (CMCC) to fuse cross-modality features and global features, which enables information flow between different windows to take full advantage of cross-modality information. Extensive experiments show that our method performs favorably against state-of-the-art methods on three mirror detection benchmarks and significantly improved SAM performance on mirror detection. The code is available at https://github.com/wangsen99/CSFwinformer.

Semi-Automatic Layout Adaptation for Responsive Multiple-View Visualization Design.

Multiple-view (MV) visualizations have become ubiquitous for visual communication and exploratory data visualization. However, most existing MV visualizations are designed for the desktop, which can be unsuitable for the continuously evolving displays of varying screen sizes. In this article, we present a two-stage adaptation framework that supports the automated retargeting and semi-automated tailoring of a desktop MV visualization for rendering on devices with displays of varying sizes. First, we cast layout retargeting as an optimization problem and propose a simulated annealing technique that can automatically preserve the layout of multiple views. Second, we enable fine-tuning for the visual appearance of each view, using a rule-based auto configuration method complemented with an interactive interface for chart-oriented encoding adjustment. To demonstrate the feasibility and expressivity of our proposed approach, we present a gallery of MV visualizations that have been adapted from the desktop to small displays. We also report the result of a user study comparing visualizations generated using our approach with those by existing methods. The outcome indicates that the participants generally prefer visualizations generated using our approach and find them to be easier to use.

Development of New Bio-Based Building Materials by Utilising Manufacturing Waste

Abstract Over the last decade, research has increasingly focused on reducing the use of natural resources and improving waste management in the construction industry. Various possibilities exist for reducing waste in this sector, ranging from using waste as filler materials to developing new binders and building materials. This study focuses on the development of bio-based building materials using waste from the manufacturing of wood-wool cement boards. The binder and filler materials were obtained from the manufacturing waste and used in this research. The developed materials were tested for their visual appearance, macrostructure, material density, thermal conductivity coefficient and compressive strength. The results showed promising data for the self-bearing bio-based building materials, which had similar thermal properties to other bio-based materials and could be used as thermal insulation materials with a thermal conductivity coefficient of 0.0827–0.1172 W/(mK). The material density of the developed bio-based composites was found to be 430–617 kg/m3. By incorporating manufacturing waste into the production process of bio-based building materials, it becomes evident that overall waste from manufacturing plants can be significantly reduced, and the sustainability aspect of wood-cement board manufacturers can be enhanced.

Angle-resolved optical spectroscopy of photonic cellulose nanocrystal films reveals the influence of additives on the mechanism of kinetic arrest.

Cellulose nanocrystals (CNCs) are rod-like nanoparticles whose chiral self-assembly into photonic films has been promoted as a sustainable source of colouration. Upon drying, an aqueous CNC suspension passes through two regimes: first, a liquid phase, where the CNCs self-organise into a cholesteric liquid crystal, followed by a kinetically-arrested phase, where the helicoidal structure compresses upon loss of solvent, resulting in a solid film with vibrant structural colour. The transition between these two regimes plays an important role in the visual appearance of photonic CNC films, but details on when and how kinetic arrest occurs have remained elusive. In this work, we combine angle-resolved optical spectroscopy of photonic films (approx. 100 vol% CNC) with a model for compressed helicoidal structures to retrieve the suspension conditions during kinetic arrest (approx. 10 vol% CNC). This analysis indicates a shift in the mechanism of kinetic arrest from a glass transition at lower ionic strength to gelation at higher ionic strength, explaining the trends in domain size and film colour. In contrast, neutral additives (glucose, poly(ethylene glycol)) appear to primarily reduce the compression upon drying without affecting cholesteric behaviour, as supported by a general analytical model. These findings deepen our understanding of CNC co-assembly with various commonly-used additives, enabling better control over the production of multifunctional structurally coloured materials.

Quantifying and Learning Static Vs. Dynamic Information in Deep Spatiotemporal Networks.

There is limited understanding of the information captured by deep spatiotemporal models in their intermediate representations. For example, while evidence suggests that action recognition algorithms are heavily influenced by visual appearance in single frames, no quantitative methodology exists for evaluating such static bias in the latent representation compared to bias toward dynamics. We tackle this challenge by proposing an approach for quantifying the static and dynamic biases of any spatiotemporal model, and apply our approach to three tasks, action recognition, automatic video object segmentation (AVOS) and video instance segmentation (VIS). Our key findings are: (i) Most examined models are biased toward static information. (ii) Some datasets that are assumed to be biased toward dynamics are actually biased toward static information. (iii) Individual channels in an architecture can be biased toward static, dynamic or jointly encode a combination static and dynamic information. (iv) Most models converge to their culminating biases in the first half of training. We then explore how these biases affect performance on dynamically biased datasets. For action recognition, we propose StaticDropout, a semantically guided dropout that debiases a model from static information toward dynamics. For AVOS, we design a better combination of fusion and cross connection layers compared with previous architectures.

SIM-OFE: Structure Information Mining and Object-Aware Feature Enhancement for Fine-Grained Visual Categorization.

Fine-grained visual categorization (FGVC) aims to distinguish visual objects from multiple subcategories of the coarse-grained category. Subtle inter-class differences among various subcategories make the FGVC task more challenging. Existing methods primarily focus on learning salient visual patterns while ignoring how to capture the object's internal structure, causing difficulty in obtaining complete discriminative regions within the object to limit FGVC performance. To address the above issue, we propose a Structure Information Mining and Object-aware Feature Enhancement (SIM-OFE) method for fine-grained visual categorization, which explores the visual object's internal structure composition and appearance traits. Concretely, we first propose a simple yet effective hybrid perception attention module for locating visual objects based on global-scope and local-scope significance analyses. Then, a structure information mining module is proposed to model the distribution and context relation of critical regions within the object, highlighting the whole object and discriminative regions for distinguishing subtle differences. Finally, an object-aware feature enhancement module is proposed to combine global-scope and local-scope discriminative features in an attentive coupling way for powerful visual representations in fine-grained recognition. Extensive experiments on three FGVC benchmark datasets demonstrate that our proposed SIM-OFE method can achieve state-of-the-art performance.

The Aesthetic Evaluation of the Brow-Eye Continuum After Correction of Severe Congenital Ptosis in Children With Extended Frontalis Muscle Advancement Technique.

Severe congenital ptosis is a common ocular deformity in pediatric patients that can significantly impact visual development and aesthetic appearance, leading to negative psychosocial outcomes. The frontalis muscle advancement technique is a well-established surgical treatment for severe congenital ptosis. Aesthetic changes of the brow-eye continuum often plays an important role in ptosis surgery. We conducted a single-center retrospective case series study of patients with severe congenital ptosis who underwent the frontalis muscle advancement technique at the Department of Plastic and Reconstructive Surgery, Xijing Hospital, Fourth Military Medical University between April 2020 and June 2021. The study aimed to evaluate the aesthetic changes of the eyebrow-eyelid continuum after surgery. The main outcome measurements included marginal reflex distance 1, palpebral fissure height, eyebrow position, upper eyelid to lower eyebrow distance, lower eyelid to upper eyebrow distance, and nasal base to lower eyelid distance. The study included 48 patients (66 eyelids), with 30 unilateral and 18 bilateral patients. Our analysis found that eyebrow height decreased by an average of 4.8% postoperatively relative to preoperatively in all patients. The frontalis muscle advancement technique has demonstrated effectiveness in achieving aesthetically pleasing outcomes in children with severe ptosis. It is crucial to pay careful attention to the brow-eye continuum during the correction process, as its harmony can greatly impact the final result.

The Effect of Free Choice Whole Grain Wheat on Turkey Performance, Caecal Health and Foot Pad Dermatitis

This study was conducted to determine the effect of inclusion of whole grain wheat by a free choice method in the diet of turkey poults on bird performance, caecal health and foot pad dermatitis. A total of 192, four week old, as hatched, commercial line turkeys. Birds were blocked by live weight and then randomly allocated to one of two dietary treatments or whole grain wheat with starter pellet control (CON) treatment. Turkeys were offered their respective treatments for the duration of the study. Feed offered and refused and body weights were determined weekly. Turkeys were fed whole grain wheat (WGW) as free choice, it was observed that intake of WGW was much more variable in birds offered free choice WGW, although mean intake of WGW was greater. Bird performance was better if WGW was not fed. The weight of the (crop, gizzard, liver, pancreas and caecum) were not effect by treatment. Digesta pH was affected by treatment (P=0.045) gizzard digesta pH being lower when birds were offered WGW at 28-48 d old. Cecal content pH, cecal visual appearance scores, cecal content visual appearance scores, foot pad dermatitis were not affected by the WGW to the diet.

Morphology of Kisaran City: The Circulation System in Urban Transformation 1929-2022

The rapid economic growth and significant urbanization in Kisaran City have posed several challenges in urban planning, including adequate housing, health facilities, education, and transportation. The city's development was also influenced by its colonial history, with the dominance of colonial power regulating the production and trade of plantation products as well as the lives of local people. The morphological transformation of the city from 1929 to 2022 reflects the challenges related to infrastructure, visual appearance, and the growth of the commercial sector, which have affected the lives of citizens and demanded the city's adaptation to the development of the times. Historical events, such as colonization by foreign powers and Chinese immigration, have affected the population growth of Kisaran and caused pressure on infrastructure and socio-economic inequality. This study aims to understand the morphology of Kisaran City and the factors that influence its transformation by using the methods of literature study, synchronic approach, and diachronic approach. The results of the study concluded that the morphological transformation of Kisaran City was influenced by the circulation system, which adapted to the needs and trends of society, and interacted with each other in forming the morphology of Kisaran City that continues to develop over time.

Pharmaceutical Evaluation and Comparison of Popular Herbal Shampoo Brands with Synthetic Shampoo Brands of India

The most popular type of hair care is shampooing. Shampoos are basically hair and scalp washing agents. There are numerous shampoo brands on the market that cater to various hair issues. One such categorization is herbal and synthetic shampoos where former claim to be prepared from natural ingredients and more safer for human use while latter are prepared entirely from range of synthetic chemicals/compounds and sometimes assumed to show allergic reaction or side effects on hair and scalp in long run usage. This study intends to assess specific shampoos based on their physicochemical characteristics, pH measurement, percentage of solid content, cleansing performance, dirt dispersion, foaming ability and foam persistence, and skin irritancy. These parameters were selected to cover evaluation of visual appearance, efficacy as well as safety issues related to herbal and synthetic class and how far they justify their claims. Six shampoo brands from each category i.e. Patanjali’s Keshkanti, Vatika, Chik hair solutions from herbal category and Clinic Plus, Dove, Sunsilk from synthetic category were procured from market and evaluated for above said tests. All shampoos were found to perform well in most tests with some surpassing others in one or another factor with mild variation. But since none particular test be considered more important than other hence giving a composite score to shampoos based on all tests is impossible. Overall, all shampoos of both categories were found to contain each ingredient within specified limit and none showed skin irritancy hence could be considered safe.

Date Fruit Classification using K-Nearest Neighbor with Principal Component Analysis and Binary Particle Swarm Optimization

Various cultivars of date fruits distributed throughout exhibit diverse complexity and unique attributes, including color, flavor, shape, and texture. These distinctive characteristics and appearance occasionally lack variability in date fruits, since various kinds of date fruit may have subtle differences in color, shape, and texture. To overcome the difficulty of sorting and classifying multiple types of date fruit, a classification model was developed to categorize date fruit according to their visual appearances and digital characteristics. This study proposes a classification system that categorizes date fruit into five distinct types. The system achieves this by extracting features related to date fruit images' color, shape, and texture. Specifically, color moments, HOG descriptors, and circularity are used for feature extraction. The resulting high-quality training data is then used to train a K-Nearest-Neighbor (KNN) classifier. Considering the parameters applied to develop the proposed classification model is essential. Therefore, the proposed KNN model will be optimized by Principal Component Analysis (PCA) and Binary Particle Swarm Optimization (BPSO). PCA is employed for dimensionality reduction, whereas BPSO is implemented to discover the optimal neighbors. The experimental results demonstrated that the classification model achieved an accuracy of 93.85%, a considerable improvement of 12% over barebone KNN.

Hybrid model for brain age prediction on MRI images with modified texture features

Machine learning (ML) and diffusion magnetic resonance imaging (dMRI) approaches can be employed to identify individual brain aging conditions in both healthy people and patients with brain diseases. This research establishes a new brain age prediction system, which comprises different phases like pre-processing, feature extraction, feature selection, and prediction. The original magnetic resonance imaging (MRI) picture is first carried out in a pre-processing stage, which enhances image quality as well as visual appearances. Following that, the shape, intensity, as well as texture-based characteristics are retrieved. Furthermore, texture features like modified entropy, as well as modified correlation are retrieved along with the traditional features. Then, a modified principle component analysis (PCA) method is utilized for feature selection stage. In the prediction phase, hybrid classifiers such as multi-layer perception (MLP) as well as long short term memory (LSTM) are used. The weight of LSTM and MLP is optimally tuned with the aid of an implemented self-updated red deer algorithm (SURDA) model to make an accurate prediction. Moreover, the suggested work outperforms other traditional works in terms of MSE, MAPE, MSLE, and MAE, correspondingly.