The World Wide Web as a vehicle for advertising movies to college students: an exploratory study

The purpose of this study is to explore the World Wide Web as a vehicle for advertising movies to college students. Through a survey of LSU students, this study finds that online promotions as vehicles for advertising movies have great potential. Movie promotion websites are rated the second most effective form of movie advertising after television. The study found that people surf movie promotion websites mainly for movie show times, movie plot and cast information to compare film choices, and movie ticket purchases. The huge amount of data available and the 24/7 access to the internet is an important advantage. However, even though the World Wide Web is a proving an excellent media vehicle for movie advertising, it is still too early to determine whether or not it will supplant TV advertising of movies in the near future

Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial

On top of machine learning models, uncertainty quantification (UQ) functions as an essential layer of safety assurance that could lead to more principled decision making by enabling sound risk assessment and management. The safety and reliability improvement of ML models empowered by UQ has the potential to significantly facilitate the broad adoption of ML solutions in high-stakes decision settings, such as healthcare, manufacturing, and aviation, to name a few. In this tutorial, we aim to provide a holistic lens on emerging UQ methods for ML models with a particular focus on neural networks and the applications of these UQ methods in tackling engineering design as well as prognostics and health management problems. Toward this goal, we start with a comprehensive classification of uncertainty types, sources, and causes pertaining to UQ of ML models. Next, we provide a tutorial-style description of several state-of-the-art UQ methods: Gaussian process regression, Bayesian neural network, neural network ensemble, and deterministic UQ methods focusing on spectral-normalized neural Gaussian process. Established upon the mathematical formulations, we subsequently examine the soundness of these UQ methods quantitatively and qualitatively (by a toy regression example) to examine their strengths and shortcomings from different dimensions. Then, we review quantitative metrics commonly used to assess the quality of predictive uncertainty in classification and regression problems. Afterward, we discuss the increasingly important role of UQ of ML models in solving challenging problems in engineering design and health prognostics. Two case studies with source codes available on GitHub are used to demonstrate these UQ methods and compare their performance in the life prediction of lithium-ion batteries at the early stage and the remaining useful life prediction of turbofan engines

A Comprehensive Review of Digital Twin -- Part 1: Modeling and Twinning Enabling Technologies

As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision and policy making, and more, by comprehensively modeling the physical world as a group of interconnected digital models. In a two-part series of papers, we examine the fundamental role of different modeling techniques, twinning enabling technologies, and uncertainty quantification and optimization methods commonly used in digital twins. This first paper presents a thorough literature review of digital twin trends across many disciplines currently pursuing this area of research. Then, digital twin modeling and twinning enabling technologies are further analyzed by classifying them into two main categories: physical-to-virtual, and virtual-to-physical, based on the direction in which data flows. Finally, this paper provides perspectives on the trajectory of digital twin technology over the next decade, and introduces a few emerging areas of research which will likely be of great use in future digital twin research. In part two of this review, the role of uncertainty quantification and optimization are discussed, a battery digital twin is demonstrated, and more perspectives on the future of digital twin are shared

Diagnostic performance and clinical impact of blood metagenomic next-generation sequencing in ICU patients suspected monomicrobial and polymicrobial bloodstream infections

IntroductionEarly and effective application of antimicrobial medication has been evidenced to improve outcomes of patients with bloodstream infection (BSI). However, conventional microbiological tests (CMTs) have a number of limitations that hamper a rapid diagnosis.MethodsWe retrospectively collected 162 cases suspected BSI from intensive care unit with blood metagenomics next-generation sequencing (mNGS) results, to comparatively evaluate the diagnostic performance and the clinical impact on antibiotics usage of mNGS.Results and discussionResults showed that compared with blood culture, mNGS detected a greater number of pathogens, especially for Aspergillus spp, and yielded a significantly higher positive rate. With the final clinical diagnosis as the standard, the sensitivity of mNGS (excluding viruses) was 58.06%, significantly higher than that of blood culture (34.68%, P<0.001). Combing blood mNGS and culture results, the sensitivity improved to 72.58%. Forty-six patients had infected by mixed pathogens, among which Klebsiella pneumoniae and Acinetobacter baumannii contributed most. Compared to monomicrobial, cases with polymicrobial BSI exhibited dramatically higher level of SOFA, AST, hospitalized mortality and 90-day mortality (P<0.05). A total of 101 patients underwent antibiotics adjustment, among which 85 were adjusted according to microbiological results, including 45 cases based on the mNGS results (40 cases escalation and 5 cases de-escalation) and 32 cases on blood culture. Collectively, for patients suspected BSI in critical condition, mNGS results can provide valuable diagnostic information and contribute to the optimizing of antibiotic treatment. Combining conventional tests with mNGS may significantly improve the detection rate for pathogens and optimize antibiotic treatment in critically ill patients with BSI

Broadband Linear-Dichroic Photodetector in a Black Phosphorus Vertical p-n Junction

The ability to detect light over a broad spectral range is central for practical optoelectronic applications, and has been successfully demonstrated with photodetectors of two-dimensional layered crystals such as graphene and MoS2. However, polarization sensitivity within such a photodetector remains elusive. Here we demonstrate a linear-dichroic broadband photodetector with layered black phosphorus transistors, using the strong intrinsic linear dichroism arising from the in-plane optical anisotropy with respect to the atom-buckled direction, which is polarization sensitive over a broad bandwidth from 400 nm to 3750 nm. Especially, a perpendicular build-in electric field induced by gating in black phosphorus transistors can spatially separate the photo-generated electrons and holes in the channel, effectively reducing their recombination rate, and thus enhancing the efficiency and performance for linear dichroism photodetection. This provides new functionality using anisotropic layered black phosphorus, thereby enabling novel optical and optoelectronic device applications.Comment: 18 pages, 5 figures in Nature Nanotechnology 201

The Interplay between Synaptic Activity and Neuroligin Function in the CNS

Neuroligins (NLs) are postsynaptic transmembrane cell-adhesion proteins that play a key role in the regulation of excitatory and inhibitory synapses. Previous in vitro and in vivo studies have suggested that NLs contribute to synapse formation and synaptic transmission. Consistent with their localization, NL1 and NL3 selectively affect excitatory synapses, whereas NL2 specifically affects inhibitory synapses. Deletions or mutations in NL genes have been found in patients with autism spectrum disorders or mental retardations, and mice harboring the reported NL deletions or mutations exhibit autism-related behaviors and synapse dysfunction. Conversely, synaptic activity can regulate the phosphorylation, expression, and cleavage of NLs, which, in turn, can influence synaptic activity. Thus, in clinical research, identifying the relationship between NLs and synapse function is critical. In this review, we primarily discuss how NLs and synaptic activity influence each other