Catalytic Decomposition of Ozone by CuO/MnO2-Performance, Kinetics and Application Analysis

AbstractOzone as a major ambient gas pollutant needs to be removed for many indoor environments due to its adverse health effect. The objective of this study is to investigate the ozone removal performance of a Hopcalite catalyst CuO/MnO2 under different operation conditions. The effect of relative humidity (15-80%), temperature (30-160°C) and ozone concentration (200-2000ppb) was experimentally tested. Then the catalyst was coated on fiberglass media for application. The influence of preparation method was also investigated. Finally, the application analysis of such material is discussed for building environment control situation

An Experimental and Modelling Study on the Adsorption Characteristics of Activated Carbon under Different Challenge Concentration Levels

Applying air cleaning devices is an effective approach to control targeted indoor gaseous pollutants. It is important to understand the adsorption characteristics of filter media (e.g, activated carbon) at typical indoor application conditions as well as standard test conditions. Tests per ASHRAE Standard 145.1 for filter media performance evaluation can provide a relative comparison among different media. However, as the tests are conducted at elevated gas concentrations (1~100 ppm), they do not represent the media performance under lower concentrations typical of indoor applications

Decoupling Recognition from Detection: Single Shot Self-Reliant Scene Text Spotter

Typical text spotters follow the two-stage spotting strategy: detect the precise boundary for a text instance first and then perform text recognition within the located text region. While such strategy has achieved substantial progress, there are two underlying limitations. 1) The performance of text recognition depends heavily on the precision of text detection, resulting in the potential error propagation from detection to recognition. 2) The RoI cropping which bridges the detection and recognition brings noise from background and leads to information loss when pooling or interpolating from feature maps. In this work we propose the single shot Self-Reliant Scene Text Spotter (SRSTS), which circumvents these limitations by decoupling recognition from detection. Specifically, we conduct text detection and recognition in parallel and bridge them by the shared positive anchor point. Consequently, our method is able to recognize the text instances correctly even though the precise text boundaries are challenging to detect. Additionally, our method reduces the annotation cost for text detection substantially. Extensive experiments on regular-shaped benchmark and arbitrary-shaped benchmark demonstrate that our SRSTS compares favorably to previous state-of-the-art spotters in terms of both accuracy and efficiency.Comment: To be appeared in the Proceedings of the ACM International Conference on Multimedia (ACM MM), 202

Facile fabrication of lightweight porous FDM-printed polyethylene/graphene nanocomposites with enhanced interfacial strength for electromagnetic interference shielding

In order to shield the massive electromagnetic perturbations and meet the more and more stringent requirement for advanced electronic equipment, development of diverse, lightweight and high-performance electromagnetic interference (EMI) shielding materials is urgent but still challenging. Herein, the facile and green method which combines fused deposition modeling (FDM) 3D printing, ball milling and microwave (MW) irradiation technology was proposed to fabricate exfoliated graphene nanoplatelets (GNPs) incorporated liner low density polyethylene (LLDPE) nanocomposite lightweight parts with porous and complex geometry structure. FDM 3D printing possesses high flexibility for structure design, which can significantly broaden the application of materials in various fields. Benefiting from design of a unique porous lamellar structure, the printed LLDPE/GNPs nanocomposite parts can achieve a prominent EMI shielding effectiveness (SE) of ~32.4 dB (with thickness-normalized specific EMI SE (SSE/t) of 318 dB cm2/g) in the range of 8.2–12.4 GHz. This remarkable characteristic is due to internal multiple reflections and absorption of electromagnetic (EM) waves. In addition, the specific FDM 3D-printed porous parts prepared by our strategy exhibit a relatively higher EMI SE at a lower density than those lightweight EMI shields in literatures. The use of MW irradiation technology improves mechanical properties, especially for the interfacial bonding strength between filaments. More importantly, this strategy is highly favorable for the fabrication of lightweight porous EMI shields with tailorable and optimized shape/structure, which could be expected to be applied in aerospace fields, portable electronic devices, smart devices and so on

Beyond Sharing: Conflict-Aware Multivariate Time Series Anomaly Detection

Massive key performance indicators (KPIs) are monitored as multivariate time series data (MTS) to ensure the reliability of the software applications and service system. Accurately detecting the abnormality of MTS is very critical for subsequent fault elimination. The scarcity of anomalies and manual labeling has led to the development of various self-supervised MTS anomaly detection (AD) methods, which optimize an overall objective/loss encompassing all metrics' regression objectives/losses. However, our empirical study uncovers the prevalence of conflicts among metrics' regression objectives, causing MTS models to grapple with different losses. This critical aspect significantly impacts detection performance but has been overlooked in existing approaches. To address this problem, by mimicking the design of multi-gate mixture-of-experts (MMoE), we introduce CAD, a Conflict-aware multivariate KPI Anomaly Detection algorithm. CAD offers an exclusive structure for each metric to mitigate potential conflicts while fostering inter-metric promotions. Upon thorough investigation, we find that the poor performance of vanilla MMoE mainly comes from the input-output misalignment settings of MTS formulation and convergence issues arising from expansive tasks. To address these challenges, we propose a straightforward yet effective task-oriented metric selection and p&s (personalized and shared) gating mechanism, which establishes CAD as the first practicable multi-task learning (MTL) based MTS AD model. Evaluations on multiple public datasets reveal that CAD obtains an average F1-score of 0.943 across three public datasets, notably outperforming state-of-the-art methods. Our code is accessible at https://github.com/dawnvince/MTS_CAD.Comment: 11 pages, ESEC/FSE industry track 202

Social Media Usage and Influenza Beliefs, Risk Perceptions and Behavioral Intentions Among Students at a University in Southeastern US

Background: To document social media usage for the retrieval of health information among college students; and to understand the beliefs, risk perceptions and behavioral intentions among participants who retrieved CDC influenza information via social media. Methods: We conducted an online survey to a convenience sample of students at a university in Southeastern United States during Spring 2015. The survey was self-administered and every matriculating student received an electronic invitation to participate at least once. Results: A total of 930 students completed the online survey. Most participants (n=905, 97.3%) reported that they had used a social networking site in the previous 12 months. However, only one-third (n=317, 34.1%) reported that they used social networking sites to read CDC health information or messages. Nearly one-fifth of participants (n=172, 18.5%) reported reading CDC influenza information during the 2014-15 influenza season. Among the subset of readers of CDC influenza information during the 2014-15 influenza season (N=153), 77 (50.99%) reported that it was likely they would get the influenza vaccine in the next 12 months. Women reported stronger risk perceptions and behavioral intentions than men. Blacks/African Americans reported more negative influenza-related beliefs and weaker risk perceptions compared to Whites. Conclusions: While social media penetration is high among university students in Southeastern US, only a minority of survey participants retrieved CDC influenza information via social media. Among these individuals, about half reported that they intended to vaccinate against influenza. Further research is needed to enhance CDC social media penetration among college students

Social Media Usage and Influenza Beliefs, Risk Perceptions and Behavioral Intentions Among Students at a University in Southeastern US

Background: To document social media usage for the retrieval of health information among college students; and to understand the beliefs, risk perceptions and behavioral intentions among participants who retrieved CDC influenza information via social media. Methods: We conducted an online survey to a convenience sample of students at a university in Southeastern United States during Spring 2015. The survey was self-administered and every matriculating student received an electronic invitation to participate at least once. Results: A total of 930 students completed the online survey. Most participants (n=905, 97.3%) reported that they had used a social networking site in the previous 12 months. However, only one-third (n=317, 34.1%) reported that they used social networking sites to read CDC health information or messages. Nearly one-fifth of participants (n=172, 18.5%) reported reading CDC influenza information during the 2014-15 influenza season. Among the subset of readers of CDC influenza information during the 2014-15 influenza season (N=153), 77 (50.99%) reported that it was likely they would get the influenza vaccine in the next 12 months. Women reported stronger risk perceptions and behavioral intentions than men. Blacks/African Americans reported more negative influenza-related beliefs and weaker risk perceptions compared to Whites. Conclusions: While social media penetration is high among university students in Southeastern US, only a minority of survey participants retrieved CDC influenza information via social media. Among these individuals, about half reported that they intended to vaccinate against influenza. Further research is needed to enhance CDC social media penetration among college students

Predicting Absolute Rate Constants for Huisgen Reactions of Unsaturated Iminium Ions with Diazoalkanes

The kinetics and stereochemistry of the reactions of iminium ions derived from cinnamaldehydes and MacMillan's imidazolidinones with diphenyldiazomethane and aryldiazomethanes were investigated experimentally and with DFT calculations. The reactions of diphenyldiazomethane with iminium ions derived from MacMillan's second-generation catalysts gave 3-aryl-2,2-diphenylcyclopropanecarbaldehydes with yields >90 % and enantiomeric ratios of >= 90:10. Predominantly 2:1 products were obtained from the corresponding reactions with monoaryldiazomethanes. The measured rate constants are in good agreement with the rate constants derived from the one-center nucleophilicity parameters N and s(N) of diazomethanes and the one-center electrophilicity parameters E of iminium ions as well as with quantum chemically calculated activation energies