COMPARISON OF LEFT-WING AND RIGHT-WING MEDIA COVERAGE ON CORONAVIURS IN EARLY 2020

The study focuses on how different media stations framed coronavirus from 21st January – 30th April 2020 along three topic areas: risk, mitigation, and blame. In this paper, I choose ABC News and Fox News representing left-wing and right-wing media respectively and adopt content analysis to extract information from news coverages. While both stations recommended the same preventative measures and mirrored CDC guidelines, risk and blame were very different depending on if the coverage came from ABC or Fox News.Master of Science in Information Scienc

Driving Simulation Study on Speed-change Lanes of the Multi-lane Freeway Interchange

AbstractBecause of the interactions of the multi-lane freeway mainline, upstream, downstream, the diversity of environmental conditions, as well as the complexity of geometric configuration, speed-change lanes of the multi-lane freeway interchange present greatest safety and operational challenges for drivers. Most freeway crashes occur in the vicinity of interchange diverging and merging areas, especially in speed-change lanes. In this paper, the UC-win/Road5 software was used as the technical tool, and a three-dimensional driving scene was built. Multi-lane freeway field data were used for the calibration of model parameters. The geometry configuration of the speed-change lanes as well as the driving behavior characteristics such as speed, acceleration rate, glancing in the diverging and merging areas were studied in this paper. Based on the driving simulation study in the areas, results supply a valuable technical reference for speed-change lane geometry configuration, the length design of speed-change lane, the operational safety evaluation of multi-lane freeway diverging and merging areas, also the operation and management of multi-lane freeways

Game-based Platforms for Artificial Intelligence Research

Games have been the perfect test-beds for artificial intelligence research for the characteristics that widely exist in real-world scenarios. Learning and optimisation, decision making in dynamic and uncertain environments, game theory, planning and scheduling, design and education are common research areas shared between games and real-world problems. Numerous open-sourced games or game-based environments have been implemented for studying artificial intelligence. In addition to single- or multi-player, collaborative or adversarial games, there has also been growing interest in implementing platforms for creative design in recent years. Those platforms provide ideal benchmarks for exploring and comparing artificial intelligence ideas and techniques. This paper reviews the game-based platforms for artificial intelligence research, discusses the research trend induced by the evolution of those platforms, and gives an outlook

Enable High-resolution, Real-time Ensemble Simulation and Data Assimilation of Flood Inundation using Distributed GPU Parallelization

Numerical modeling of the intensity and evolution of flood events are affected by multiple sources of uncertainty such as precipitation and land surface conditions. To quantify and curb these uncertainties, an ensemble-based simulation and data assimilation model for pluvial flood inundation is constructed. The shallow water equation is decoupled in the x and y directions, and the inertial form of the Saint-Venant equation is chosen to realize fast computation. The probability distribution of the input and output factors is described using Monte Carlo samples. Subsequently, a particle filter is incorporated to enable the assimilation of hydrological observations and improve prediction accuracy. To achieve high-resolution, real-time ensemble simulation, heterogeneous computing technologies based on CUDA (compute unified device architecture) and a distributed storage multi-GPU (graphics processing unit) system are used. Multiple optimization skills are employed to ensure the parallel efficiency and scalability of the simulation program. Taking an urban area of Fuzhou, China as an example, a model with a 3-m spatial resolution and 4.0 million units is constructed, and 8 Tesla P100 GPUs are used for the parallel calculation of 96 model instances. Under these settings, the ensemble simulation of a 1-hour hydraulic process takes 2.0 minutes, which achieves a 2680 estimated speedup compared with a single-thread run on CPU. The calculation results indicate that the particle filter method effectively constrains simulation uncertainty while providing the confidence intervals of key hydrological elements such as streamflow, submerged area, and submerged water depth. The presented approaches show promising capabilities in handling the uncertainties in flood modeling as well as enhancing prediction efficiency

H2O+: An Improved Framework for Hybrid Offline-and-Online RL with Dynamics Gaps

Solving real-world complex tasks using reinforcement learning (RL) without high-fidelity simulation environments or large amounts of offline data can be quite challenging. Online RL agents trained in imperfect simulation environments can suffer from severe sim-to-real issues. Offline RL approaches although bypass the need for simulators, often pose demanding requirements on the size and quality of the offline datasets. The recently emerged hybrid offline-and-online RL provides an attractive framework that enables joint use of limited offline data and imperfect simulator for transferable policy learning. In this paper, we develop a new algorithm, called H2O+, which offers great flexibility to bridge various choices of offline and online learning methods, while also accounting for dynamics gaps between the real and simulation environment. Through extensive simulation and real-world robotics experiments, we demonstrate superior performance and flexibility over advanced cross-domain online and offline RL algorithms

Exercise for prevention of falls and fall-related injuries in neurodegenerative diseases and aging-related risk conditions: a meta-analysis

IntroductionNeurodegenerative diseases often cause motor and cognitive deterioration that leads to postural instability and motor impairment, while aging-associated frailty frequently results in reduced muscle mass, balance, and mobility. These conditions increase the risk of falls and injuries in these populations. This study aimed to determine the effects of exercise on falls and consequent injuries among individuals with neurodegenerative diseases and frail aging people.MethodsElectronic database searches were conducted in PubMed, Cochrane Library, SportDiscus, and Web of Science up to 1 January 2023. Randomized controlled trials that reported the effects of exercise on falls and fall-related injuries in neurodegenerative disease and frail aging people were eligible for inclusion. The intervention effects for falls, fractures, and injuries were evaluated by calculating the rate ratio (RaR) or risk ratio (RR) with 95% confidence interval (CI).ResultsSixty-four studies with 13,241 participants met the inclusion criteria. Exercise is effective in reducing falls for frail aging people (RaR, 0.75; 95% CI, 0.68–0.82) and participants with ND (0.53, 0.43–0.65) [dementia (0.64, 0.51–0.82), Parkinson’s disease (0.49, 0.39–0.69), and stroke survivors (0.40, 0.27–0.57)]. Exercise also reduced fall-related injuries in ND patients (RR, 0.66; 95% CI, 0.48–0.90) and decreased fractures (0.63, 0.41–0.95) and fall-related injuries (0.89, 0.84–0.95) among frail aging people. For fall prevention, balance and combined exercise protocols are both effective, and either short-, moderate-, or long-term intervention duration is beneficial. More importantly, exercise only induced a very low injury rate per participant year (0.007%; 95% CI, 0–0.016) and show relatively good compliance with exercise (74.8; 95% CI, 69.7%–79.9%).DiscussionExercise is effective in reducing neurodegenerative disease- and aging-associated falls and consequent injuries, suggesting that exercise is an effective and feasible strategy for the prevention of falls

Utility of clinical metagenomics in diagnosing malignancies in a cohort of patients with Epstein-Barr virus positivity

BackgroundsDifferentiation between benign and malignant diseases in EBV-positive patients poses a significant challenge due to the lack of efficient diagnostic tools. Metagenomic Next-Generation Sequencing (mNGS) is commonly used to identify pathogens of patients with fevers of unknown-origin (FUO). Recent studies have extended the application of Next-Generation Sequencing (NGS) in identifying tumors in body fluids and cerebrospinal fluids. In light of these, we conducted this study to develop and apply metagenomic methods to validate their role in identifying EBV-associated malignant disease.MethodsWe enrolled 29 patients with positive EBV results in the cohort of FUO in the Department of Infectious Diseases of Huashan Hospital affiliated with Fudan University from 2018 to 2019. Upon enrollment, these patients were grouped for benign diseases, CAEBV, and malignant diseases according to their final diagnosis, and CNV analysis was retrospectively performed in 2022 using samples from 2018 to 2019.ResultsAmong the 29 patients. 16 of them were diagnosed with benign diseases, 3 patients were diagnosed with CAEBV and 10 patients were with malignant diseases. 29 blood samples from 29 patients were tested for mNGS. Among all 10 patients with malignant diagnosis, CNV analysis suggested neoplasms in 9 patients. Of all 19 patients with benign or CAEBV diagnosis, 2 patients showed abnormal CNV results. The sensitivity and specificity of CNV analysis for the identification for tumors were 90% and 89.5%, separately.ConclusionsThe application of mNGS could assist in the identification of microbial infection and malignancies in EBV-related diseases. Our results demonstrate that CNV detection through mNGS is faster compared to conventional oncology tests. Moreover, the convenient collection of peripheral blood samples adds to the advantages of this approach

How non-public colleges in China cope with inequality and disadvantage in faculty development

University of Technology Sydney. Faculty of Arts and Social Sciences.In the past decade, Non-Public Colleges (NPCs) mushroomed in China and have become an important part of China’s higher education. However, with their fast development, NPCs also faces increasing problems including numerous policy constraints and have been an unequal competitor of public universities and colleges. One of biggest issue faced by NPCs is that the employment status of the teaching staff of NPCs is not equally recognized in public policy as their counterparts in the public sector. The inequality in employment status has significant implications on welfare entitlements and on employment quality, stability and mobility of college teachers in the private sector. As a result, such inequalities have significantly destabilized the employment structure of NPCs. Under existing governing structure and regulatory environment, how NPCs will survive or further develop themselves is calling for solutions. This study, first, through a case study, it examines the inequality and hindrances that Chinese non-public colleges (NPCs) face in the area of welfare and career path for their academic staff. Secondly, the study explores possible solutions to these problems that have been tested in the case study and could contribute to the governmental policy making and to the healthy development of the whole sector

Fringing Electric Field Sensors for Anti-Attack at System-Level Protection

Information system security has been in the spotlight of individuals and governments in recent years. Integrated Circuits (ICs) function as the basic element of communication and information spreading, therefore they have become an important target for attackers. From this perspective, system-level protection to keep chips from being attacked is of vital importance. This paper proposes a novel method based on a fringing electric field (FEF) sensor to detect whether chips are dismantled from a printed circuit board (PCB) as system-level protection. The proposed method overcomes the shortcomings of existing techniques that can be only used in specific fields. After detecting a chip being dismantled from PCB, some protective measures like deleting key data can be implemented to be against attacking. Fringing electric field sensors are analyzed through simulation. By optimizing sensor’s patterns, areas and geometrical parameters, the methods that maximize sensitivity of fringing electric field sensors are put forward and illustrated. The simulation is also reproduced by an experiment to ensure that the method is feasible and reliable. The results of experiments are inspiring in that they prove that the sensor can work well for protection of chips and has the advantage of universal applicability, low cost and high reliability

Research on Green Transformation of Enterprises from the Perspective of Innovation Driving

This paper takes Zhejiang Zhongguang Electric Group Co.Ltd. as an example to explain how enterprises overcome the problems faced in the transformation of green manufacturing, take innovation-driven green manufacturing as the primary premise, and become the pathfinder of innovation-driven green manufacturing in the manufacturing industry. The research in this case found that CGE adheres to the “innovation” driven development, and strives to create a development model of “one main body, innovation driven and five integration” with itself as the main body, innovation driven and five integration complemented; Through the construction of green factories, the design of green parks, the research and development of green products and the operation of green supply chain, the in-depth development of innovation is promoted in an orderly manner, providing valuable experience for the organic integration of green manufacturing and sustainable development. At the same time, the strategic layout of Zhongguang Electric is also improving day by day, constantly pursuing enterprise growth and technological breakthroughs, and integrating green management into enterprise management, product design and production