“Hiding in the Crowd?” In Pursuit of Perceived Anonymity through a Uniform Visual Presentation on Algorithm-driven Social Media Platforms

Collective anonymity is defined as a large group of social media users collectively adopting a uniform identification presentation (e.g., an identical online pseudonym and avatar). This emerging trend is increasingly prevalent on algorithm-driven social media, proactively leveraged by users to increase perceived anonymity. To conceptualize it and understand its drivers and outcomes, this study investigated one exemplary form of collective anonymity on Xiaohongshu. Using an inductive approach, interview data with fourteen participants was collected and analysed through a thematic approach. Our findings (a) explained the underlying mechanisms of collective anonymity; (b) unpacked users’ internal motivations and extrinsic factors that drive it; (c) uncovered its downstream consequences pertinent to human-human interaction and human-algorithm engagement. Our study also provides important implications on algorithmic regulation and governance, the ethical use of algorithmic recommendations, and the mitigation of disinhibited and deviant behaviour resulting from collective anonymity

The Disability Burden Associated With Stroke Emerges Before Stroke Onset and Differentially Affects Blacks: Results From the Health and Retirement Study Cohort

Background. Few longitudinal studies compare changes in instrumental activities of daily living (IADLs) among stroke-free adults to prospectively document IADL changes among adults who experience a stroke. We contrast annual declines in IADL independence for older individuals who remain stroke-free to those for individuals who experienced a stroke. We also assess whether these patterns differ by sex, race, or Southern birthplace. Methods. Health and Retirement Study participants who were stroke-free in 1998 (n = 17,741) were followed through 2010 (average follow-up = 8.9 years) for self- or proxy-reported stroke. We used logistic regressions to compare annual changes in odds of self-reported independence in six IADLs among those who remained stroke-free throughout follow-up (n = 15,888), those who survived a stroke (n = 1,412), and those who had a stroke and did not survive to participate in another interview (n = 442). We present models adjusted for demographic and socioeconomic covariates and also stratified on sex, race, and Southern birthplace. Results. Compared with similar cohort members who remained stroke-free, participants who developed stroke had faster declines in IADL independence and a lower probability of IADL independence prior to the stroke. After a stroke, independence declined at an annual rate similar to those who did not have a stroke. The black-white disparity in IADL independence narrowed poststroke. Conclusion. Racial differences in IADL independence are apparent long before stroke onset. Poststroke differences in IADL independence largely reflect pre stroke disparities

Masked Lip-Sync Prediction by Audio-Visual Contextual Exploitation in Transformers

Previous studies have explored generating accurately lip-synced talking faces for arbitrary targets given audio conditions. However, most of them deform or generate the whole facial area, leading to non-realistic results. In this work, we delve into the formulation of altering only the mouth shapes of the target person. This requires masking a large percentage of the original image and seamlessly inpainting it with the aid of audio and reference frames. To this end, we propose the Audio-Visual Context-Aware Transformer (AV-CAT) framework, which produces accurate lip-sync with photo-realistic quality by predicting the masked mouth shapes. Our key insight is to exploit desired contextual information provided in audio and visual modalities thoroughly with delicately designed Transformers. Specifically, we propose a convolution-Transformer hybrid backbone and design an attention-based fusion strategy for filling the masked parts. It uniformly attends to the textural information on the unmasked regions and the reference frame. Then the semantic audio information is involved in enhancing the self-attention computation. Additionally, a refinement network with audio injection improves both image and lip-sync quality. Extensive experiments validate that our model can generate high-fidelity lip-synced results for arbitrary subjects.Comment: Accepted to SIGGRAPH Asia 2022 (Conference Proceedings). Project page: https://hangz-nju-cuhk.github.io/projects/AV-CA

Autoimmune hepatitis with confluent necrosis indicates severe liver injury but responds well to standard immunosuppressive therapy

We aimed to study the effects of different extensive confluent necrosis on complete biochemical response, side effects of immunosuppressants, and outcomes in patients with autoimmune hepatitis (AIH). Patients with liver biopsy, receiving standard immunosuppressive therapy (IST), and regular follow-up were retrospectively recruited. Demographic and clinicopathological characteristics between Ishak confluent necrosis scores ≤4 (the non-severe AIH group) and ≥5 (the severe AIH group) were compared. The Kaplan-Meier Survival analysis, Cox regression analysis, and log-rank test were performed. Bilateral p<0.05 was considered statistical significance. One hundred and forty-two patients were enrolled, the median age was 56.0, and 83.8% were female. There were no significant differences in aminotransferases and immunological markers between the two groups. Patients in the severe AIH group had significantly worse liver synthetic function, a higher proportion of cirrhosis, and histologically a higher degree of portal inflammation, interface hepatitis, fibrosis stage, and a higher histological activity index score (all p<0.05). Patients in the severe AIH group had a lower response than the other group after four weeks (57.1% vs. 86.3%, p=0.002). However, differences in complete biochemical response (CBR) were insignificant. Eight patients experienced end-point events. Kaplan-Meier survival analysis showed no significant difference between the two groups (p=0.343). For adverse effects of IST, patients in the severe group tended toward a higher incidence of corticosteroid adverse effects without statistical significance. Our study indicated that patients with histologically severe confluent necrosis (Ishak score ≥5) had significantly worse liver synthetic function and a higher degree of liver fibrosis before IST. Compared with their counterparts, this subgroup of patients showed delayed biochemical response but eventually comparable CBRs, side effects, and long-term outcome

Gab2 facilitates epithelial-to-mesenchymal transition via the MEK/ERK/MMP signaling in colorectal cancer

Clinicopathologic factors and Gab2 expression in 35 CRC patients. (DOCX 22 kb

High-throughput discovery of chemical structure-polarity relationships combining automation and machine learning techniques

As an essential attribute of organic compounds, polarity has a profound influence on many molecular properties such as solubility and phase transition temperature. Thin layer chromatography (TLC) represents a commonly used technique for polarity measurement. However, current TLC analysis presents several problems, including the need for a large number of attempts to obtain suitable conditions, as well as irreproducibility due to non-standardization. Herein, we describe an automated experiment system for TLC analysis. This system is designed to conduct TLC analysis automatically, facilitating high-throughput experimentation by collecting large experimental data under standardized conditions. Using these datasets, machine learning (ML) methods are employed to construct surrogate models correlating organic compounds' structures and their polarity using retardation factor (Rf). The trained ML models are able to predict the Rf value curve of organic compounds with high accuracy. Furthermore, the constitutive relationship between the compound and its polarity can also be discovered through these modeling methods, and the underlying mechanism is rationalized through adsorption theories. The trained ML models not only reduce the need for empirical optimization currently required for TLC analysis, but also provide general guidelines for the selection of conditions, making TLC an easily accessible tool for the broad scientific community

Make Your Brief Stroke Real and Stereoscopic: 3D-Aware Simplified Sketch to Portrait Generation

Creating the photo-realistic version of people sketched portraits is useful to various entertainment purposes. Existing studies only generate portraits in the 2D plane with fixed views, making the results less vivid. In this paper, we present Stereoscopic Simplified Sketch-to-Portrait (SSSP), which explores the possibility of creating Stereoscopic 3D-aware portraits from simple contour sketches by involving 3D generative models. Our key insight is to design sketch-aware constraints that can fully exploit the prior knowledge of a tri-plane-based 3D-aware generative model. Specifically, our designed region-aware volume rendering strategy and global consistency constraint further enhance detail correspondences during sketch encoding. Moreover, in order to facilitate the usage of layman users, we propose a Contour-to-Sketch module with vector quantized representations, so that easily drawn contours can directly guide the generation of 3D portraits. Extensive comparisons show that our method generates high-quality results that match the sketch. Our usability study verifies that our system is greatly preferred by user.Comment: Project Page on https://hangz-nju-cuhk.github.io

Transition-Metal-Free Borylation of Alkyl Iodides via a Radical Mechanism

We describe an operationally simple transition-metal-free borylation of alkyl iodides. This method uses commercially available diboron reagents as the boron source and exhibits excellent functional group compatibility. Furthermore, a diverse range of primary and secondary alkyl iodides could be effectively transformed to the corresponding alkylboronates in excellent yield. Mechanistic investigations suggest that this borylation reaction proceeds through a single-electron transfer mechanism featuring the generation of an alkyl radical intermediate