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This paper explores the structural characteristics of information dissemination on WhatsApp, focusing particularly on the concepts of "breadth" and "depth." "Breadth" refers to the maximum number of groups to which a message is simultaneously forwarded, while "depth" indicates the maximum number of times a message is forwarded. Using a dataset from 1,600 groups in India comprising over 760,000 messages spanning text, images, and videos, this study employs hashing techniques to track message propagation in a privacy-preserving manner. Analysis of cascade size, breadth, and depth reveals significant trends: text and video messages tend to generate larger cascade sizes compared to images. Contrary to public platforms, depth emerges as the primary driver behind widespread information dissemination (which could be due to WhatsApp's limitations on message broadcasts). Additionally, distinct disparities among message types show depth as the decisive factor in text and video cascades, while both breadth and depth significantly contribute to image cascades. These findings underscore the importance of considering structural nuances in understanding information spread dynamics on private messaging platforms, providing valuable insights for effective dissemination strategies and management in digital communication landscapes. 

Abstract Cell specific-targeted therapy (CSTT) for acute ischemic stroke remains underdeveloped. Cerebrovascular endothelial cells (CECs) are key components of the blood–brain barrier and are the first brain cells affected by ischemic stroke. After stroke, CEC injury causes insufficient energy supply to neurons and leads to cytotoxic and vasogenic brain edema. Aptamers are short single-stranded RNA or DNA molecules that can bind to specific ligands for cell specific delivery. The expression of vascular cell adhesion molecule-1 (VCAM-1) is increased on CECs after stroke. Herein, we report that an RNA-based VCAM-1-aptamer can specifically target CECs in stroke brains following transient middle cerebral artery occlusion in mice. Our data demonstrate the potential of an RNA-based aptamer as an effective delivery platform to target CECs after stroke. We believe this method will allow for the development of CSTT for treatment of patients with stroke. 

Demonstrating veracity of videos is a longstanding problem that has recently become more urgent and acute. It is extremely hard to accurately detect manipulated videos using content analysis, especially in the face of subtle, yet effective, manipulations, such as frame rate changes or skin tone adjustments. In this paper, we present Vronicle, a method for generating provenance information for videos captured by mobile devices and using that information to verify authenticity of videos. A key feature of Vronicle is the use of Trusted Execution Environments (TEEs) for video capture and post-processing. This aids in constructing fine-grained provenance information that allows the consumer to verify various aspects of the video, thereby defeating numerous fake-video creation methods. Another important feature is the use of fixed-function post-processing units that facilitate verification of provenance information. These units can be deployed in any TEE, either in the mobile device that captures the video or in powerful servers. We present a prototype of Vronicle, which uses ARM TrustZone and Intel SGX for on-device and server-side post-processing, respectively. Moreover, we introduce two methods (and prototype the latter) for secure video capture on mobile devices: one using ARM TrustZone, and another using Google SafetyNet, providing a trade-off between security and immediate deployment. Our evaluation demonstrates that: (1) Vronicle's performance is well-suited for non-real-time use-cases, and (2) offloading post-processing significantly improves Vronicle's performance, matching that of uploading videos to YouTube. 

This paper proposes a nested low-density parity-check (LDPC) code design. Combining this nested LDPC code with the random access coding strategy introduced by Yavas, Kostina, and Effros yields a random access LDPC (RA-LDPC) code for reliable communication in random access communication environments where neither the transmitters nor the receiver knows which or even how many transmitters wish to communicate at each moment. Coordination is achieved using sparse scheduled feedback. Bounds on the finite-blocklength performance of the RA-LDPC code under maximum likelihood (ML) decoding are derived using both error exponent and dispersion style analyses. Results include bounds on the penalty of the RA-LDPC code as a function of the LDPC code densities. 

Owing to their excellent mechanical flexibility, mixed-conducting electrical property, and extraordinary chemical turnability, conjugated polymers have been demonstrated to be an ideal bioelectronic interface to deliver therapeutic effect in many different chronic diseases. This review article summarizes the latest advances in implantable electronics using conjugated polymers as electroactive materials and identifies remaining challenges and opportunities for developing electronic medicine. Examples of conjugated polymer-based bioelectronic devices are selectively reviewed in human clinical studies or animal studies with the potential for clinical adoption. The unique properties of conjugated polymers are highlighted and exemplified as potential solutions to address the specific challenges in electronic medicine. 

This paper applies error-exponent and dispersionstyle analyses to derive finite-blocklength achievability bounds for low-density parity-check (LDPC) codes over the point-to-point channel (PPC) and multiple access channel (MAC). The error-exponent analysis applies Gallager's error exponent to bound achievable symmetrical and asymmetrical rates in the MAC. The dispersion-style analysis begins with a generalization of the random coding union (RCU) bound from random code ensembles with i.i.d. codewords to random code ensembles in which codewords may be statistically dependent; this generalization is useful since the codewords of random linear codes such as LDPC codes are dependent. Application of the RCU bound yields finite-blocklength error bounds and asymptotic achievability results for both i.i.d. random codes and LDPC codes. For discrete, memoryless channels, these results show that LDPC codes achieve first- and second-order performance that is optimal for the PPC and identical to the best prior results for the MAC.