StoryChat: Designing a Narrative-Based Viewer Participation Tool for Live Streaming Chatrooms

Live streaming platforms and existing viewer participation tools enable users to interact and engage with an online community, but the anonymity and scale of chat usually result in the spread of negative comments. However, only a few existing moderation tools investigate the influence of proactive moderation on viewers' engagement and prosocial behavior. To address this, we developed StoryChat, a narrative-based viewer participation tool that utilizes a dynamic graphical plot to reflect chatroom negativity. We crafted the narrative through a viewer-centered (N=65) iterative design process and evaluated the tool with 48 experienced viewers in a deployment study. We discovered that StoryChat encouraged viewers to contribute prosocial comments, increased viewer engagement, and fostered viewers' sense of community. Viewers reported a closer connection between streamers and other viewers because of the narrative design, suggesting that narrative-based viewer engagement tools have the potential to encourage community engagement and prosocial behaviors

Robust Optical Data Encryption by Projection-Photoaligned Polymer-Stabilized-Liquid-Crystals

The emerging Internet of Things (IoTs) invokes increasing security demands that require robust encryption or anti-counterfeiting technologies. Albeit being acknowledged as efficacious solutions in processing elaborate graphical information via multiple degrees of freedom, optical data encryption and anti-counterfeiting techniques are typically inept in delivering satisfactory performance without compromising the desired ease-of-processibility or compatibility, thus leading to the exploration of novel materials and devices that are competent. Here, a robust optical data encryption technique is demonstrated utilizing polymer-stabilized-liquid-crystals (PSLCs) combined with projection photoalignment and photopatterning methods. The PSLCs possess implicit optical patterns encoded via photoalignment, as well as explicit geometries produced via photopatterning. Furthermore, the PSLCs demonstrate improved robustness against harsh chemical environments and thermal stability, and can be directly deployed onto various rigid and flexible substrates. Based on this, it is demonstrated that single PSLC is apt to carry intricate information, or serve as exclusive watermark with both implicit features and explicit geometries. Moreover, a novel, generalized design strategy is developed, for the first time, to encode intricate and exclusive information with enhanced security by spatially programming the photoalignment patterns of a pair of cascade PSLCs, which further illustrates the promising capabilies of PSLCs in optical data encryption and anti-counterfeiting

Ticagrelor vs Clopidogrel in CYP2C19 loss-of-function carriers with Stroke or TIA

BACKGROUNDComparisons between ticagrelor- aspirin and clopidogrel-aspirin in CYP2C19 loss-of-function carriers have not been well studied for secondary stroke prevention.METHODSWe conducted a randomized, double-blind, placebo-controlled trial of 6,412 patients with a minor ischemic stroke or TIA who carried CYP2C19 LOF alleles determined by point-of-care testing. Patients were randomly assigned within 24 hours after symptom onset, in a 1:1 ratio to receive ticagrelor (180 mg loading dose on day 1 followed by 90 mg twice daily for days 2 through 90) or clopidogrel (300 mg loading dose on day 1 followed by 75 mg per day for days 2 through 90), plus aspirin (75-300 mg loading dose followed by 75 mg daily for 21 days). The primary efficacy outcome was stroke and the primary safety outcome was severe or moderate bleeding, both within 90 days. RESULTSStroke occurred within 90 days in 191 (6.0%) versus 243 (7.6%), respectively (hazard ratio, 0.77; 95% confidence interval, 0.64 to 0.94; P=0.008). Moderate or severe bleeding occurred in 9 patients (0.3%) in the ticagrelor-aspirin group and in 11 patients (0.3%) in the clopidogrel-aspirin group; any bleeding event occurred in 170 patients (5.3%) vs 80 (2.5%), respectively. CONCLUSIONSAmong Chinese patients with minor ischemic stroke or TIA within 24 hours after symptoms onset who were carriers of CYP2C19 loss-of-function alleles, ticagrelor- aspirin was modestly better than clopidogrel-aspirin for reducing the risk of stroke but was associated with more total bleeding events at 90 days. (CHANCE-2 ClinicalTrials.gov number, NCT04078737.

Acceleration Techniques of Sparse Linear Algebra on Emerging Architectures

Recent years have witnessed a tremendous surge of interest in accelerating sparse linear algebra applications. Sparse linear algebra is a fundamental building block and usually the performance bottleneck of a wide range of applications, such as machine learning, graph processing, and scientific computing. Optimizing sparse linear algebra kernels is thus critical for the efficient computation of these workloads. The key challenge of sparse linear algebra lies in the irregular access pattern induced by the sparseness nature, which renders the deep cache hierarchy in General-Purpose Processors (GPPs) useless and makes sparse linear algebra applications notoriously memory intensive. This dissertation proposes multiple approaches to optimize the performance and efficiency of sparse linear algebra kernels by taking advantage of emerging architecture techniques, including hardware specialization, architecture reconfiguration, and Near-Memory Processing (NMP). Aiming for a balance among efficiency, flexibility, and programmability for architecture designs, this dissertation first proposes Transmuter, a reconfigurable architecture that features massively-parallel Processing Elements (PEs) and a flexible on-chip memory hierarchy that reconfigures the memory type, resource sharing, and dataflow at runtime to adapt to different applications. Transmuter demonstrates significant efficiency gains over the CPU and GPU across a diverse set of commonly-used kernels while offering GPU-like programmability. More importantly, Transmuter retains high performance for sparse linear algebra kernels, achieving an energy efficiency within 4.1x compared to state-of-the-art functionally-equivalent Application Specific Integrated Circuits (ASICs). As the algorithm mapping and hardware configuration play a crucial role in the performance of Transmuter, the next piece of this dissertation proposes the CoSPARSE framework, which guides the runtime reconfiguration of Transmuter to achieve the best performance for graph analytics workloads. During execution, CoSPARSE intelligently reconfigures to the best-performing software algorithm and hardware configuration for Transmuter based on the input characteristics. The synergistic software and hardware reconfiguration amass a net speedup of up to 2.0x, over a naive baseline implementation with no software or hardware reconfiguration. Compared to a recent graph processing framework on a server-class CPU, CoSPARSE achieves an average speedup and energy efficiency improvement of 1.5x and 404.4x, respectively, across a suite of widely-used graph algorithms. The dynamic algorithm reconfiguration of CoSPARSE and many other graph frameworks requires the input graph to be stored in multiple data formats to avoid runtime transposition, trading off storage for performance. As data sizes keep growing, to prevent designs like CoSPARSE from expensive disk accesses when memory storage is limited, the final part of this dissertation presents MeNDA, a scalable near-memory accelerator for sparse matrix transposition and sparse merging dataflows. The wide application of multi-way merge sorting allows MeNDA to be easily adapted to other sparse primitives such as Sparse Matrix-Vector Multiplication (SpMV). Compared to two state-of-the-art implementations of sparse matrix transposition on a CPU and a sparse library on a GPU, MeNDA achieves a speedup of 19.1x, 12.0x, and 7.7x, respectively. Because MeNDA greatly reduces the runtime transposition overhead, integrating MeNDA can save reconfigurable graph frameworks such as CoSPARSE from storing two or more copies of the graph in the main memory with a minor power overhead of 78.6 mW per rank for commodity DRAM devices.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/175690/1/fengsy_1.pd

Multi-objective bike-way network design problem with space–time accessibility constraint

This paper investigates a bike-way network design problem for retrofitting existing cycling infrastructure for commuter cyclists. A multi-objective integer linear programming model is formulated to determine the spatial layout of bike-way networks and types of bike-way links. The objective of the formulation is to maximize the accessibility, minimize the number of intersections, maximize bicycle level of service, and minimize total construction cost subject to space–time constraint and monetary budget. In the formulation, the accessibility measure considers not only connectivity, but also cyclists’ travel time budget between each origin-activity location pair. The problem is solved by augmented ϵ-constraint method to generate a set of non-dominated solutions. Two numerical examples are used to demonstrate the feasibility of the model and solution algorithm. For the hypothetical numerical example based on the bike-way network of Jurong Lake district in Singapore, four alternative non-dominated bike-way design plans are generated.Nanyang Technological UniversityThis study is supported by Nanyang Technological University SUG M4081894

The Carbon Reduction Effect of the Trade of Paper Products in China

Through using the data of import and export trading of China's paper products in 2012, we utilize the method of volume source biomass equation and net primary productivity (NPP) to calculate the carbon reduction effect of papermaking raw materials trade, and utilize the method of IPCC guidelines for inventories to calculate the carbon emission effect of paper and paper products trade. The results show that the distinctive characteristics of China's paper products trade has resulted in the dual effects on the domestic carbon emissions. On the one hand, large imports of paper-making raw materials make China reduce domestic forest felling, with the effect of carbon emission reduction. On the other hand, net exports of paper and paper products increase the domestic carbon emissions, with the effect of carbon emission. The carbon emission reduction effect of China's paper-making raw materials trade is obvious and up to 19.0211 million tons. This is equal to the total volume of 180.5709 million cubic meters forest's annual carbon sequestration. The carbon emission effect of paper and paper products trade is only 0.5136 million tons, which is not significant compared with the former. In general, China's paper product trade causes the significant effect on carbon emission reduction