Novel deep learning approach to model and predict the spread of COVID-19

SARS-CoV2, which causes coronavirus disease (COVID-19) is continuing to spread globally, producing new variants and has become a pandemic. People have lost their lives not only due to the virus but also because of the lack of counter measures in place. Given the increasing caseload and uncertainty of spread, there is an urgent need to develop robust artificial intelligence techniques to predict the spread of COVID-19. In this paper, we propose a deep learning technique, called Deep Sequential Prediction Model (DSPM) and machine learning based Non-parametric Regression Model (NRM) to predict the spread of COVID-19. Our proposed models are trained and tested on publicly available novel coronavirus dataset. The proposed models are evaluated by using Mean Absolute Error and compared with the existing methods for the prediction of the spread of COVID-19. Our experimental results demonstrate the superior prediction performance of the proposed models. The proposed DSPM and NRM achieve MAEs of 388.43 (error rate 1.6%) and 142.23 (0.6%), respectively compared to 6508.22 (27%) achieved by baseline SVM, 891.13 (9.2%) by Time-Series Model (TSM), 615.25 (7.4%) by LSTM-based Data-Driven Estimation Method (DDEM) and 929.72 (8.1%) by Maximum-Hasting Estimation Method (MHEM)

Dehalogenation of polychlorinated biphenyls and polybrominated diphenyl ethers using a hybrid bioinorganic catalyst

The environmentally prevalent polybrominated diphenyl ether (PBDE) #47 and polychlorinated biphenyls (PCBs) #28 and #118 were challenged for 24 hours with a novel biomass-supported Pd catalyst (BioPd0). Analysis of the products via GC/MS revealed the BioPd0 to cause the challenged compounds to undergo stepwise dehalogenation with preferential loss of the least sterically hindered halogen atom. A mass balance for PCB #28 showed that it is degraded to three dichlorobiphenyls (33.9 %), two monochlorobiphenyls (12 %), and biphenyl (30.7 %). The remaining mass was starting material. In contrast, while PCB #118 underwent degradation to yield five tetra- and five trichlorinated biphenyls; no less chlorinated products or biphenyl were detected, and the total mass of degraded products was 0.3 %. Although the BioPd0 material was developed for treatment of PCBs, a mass balance for PBDE #47 showed that the biocatalyst could prove a useful method for treatment of PBDEs. Specifically, 10 % of PBDE # 47 was converted to identifiable lower brominated congeners, predominantly the tribrominated BDE 17, and the dibrominated BDE 4, 75 % remained intact, while 15 % of the starting mass was unaccounted for

ACRL/SPARC Forum explores open access models: The future of scholarly publishing

Over the past seven years, SPARC (the Scholarly Publishing and Academic Resources Coalition) and the ACRL Scholarly Communications Committee have hosted a forum exploring scholarly communication issues at the ALA meetings. This June in Washington, D.C., three open access publishers were invited to provide a ?course check? and to discuss issues of sustainability

A changed landscape

This op-ed price suggests that, emerging from the covid-19 pandemic, Open Science is the way forward and shows how this approach can work in harmony with commercial activity which a university might wish to undertake

ACRL/SPARC Forum explores open access models: the future of scholarly publishing

Over the past seven years, SPARC (the Scholarly Publishing and Academic Resources Coalition) and the ACRL Scholarly Communications Committee have hosted a forum exploring scholarly communication issues at the ALA meetings. This June in Washington, D.C., three open access publishers were invited to provide a ?course check? and to discuss issues of sustainability

Probing functional groups on volcanic ash using heteogeneous reactions in a Knudsen flow reactor

Depuis 1964 et la première loi sur l’eau, une attention toujours plus fine est portée à la préservation des milieux aquatiques. La stratégie la plus récente de lutte contre la pollution des milieux récepteurs est l’approche intégrée, consacrée par la directive cadre sur l’eau du 23 octobre 2000. Sa mise en application nécessite l’emploi de techniques d’évaluation des flux de pollutions rejetés dans les milieux récepteurs par l’ensemble du système. Dans ce cadre, la thèse a illustré l’intérêt de la spectrophotométrie UV/Visible et des techniques d’identification de systèmes. La première application concerne la mesure en continu de DCO et MES par spectrophotométrie UV/Visible en entrée de station de traitement des eaux usées. Il a été montré que les performances des modèles statistiques Partial Least Squares (PLS) utilisés pour la mesure des concentrations pouvaient être améliorées par une sélection optimisée des longueurs d’onde. Une démarche d’établissement de domaine de validité des modèles a également été proposée. La détection de pics de pollution bactériologique par spectrophotométrie UV/Visible a ensuite été explorée. Des problèmes expérimentaux ont rendu impossible l’utilisation de méthodes d’analyse multivariables. Enfin, des techniques d’identification de modèle à temps continu ont été appliquées dans le cadre d’une modélisation pluie-débit en contexte urbain. Elles permettent de formaliser le problème mathématique d’estimation paramétrique d’une manière performante et présentent également l’avantage de ne pas fixer a priori la structure mathématique du modèle à identifier, tout en conservant la possibilité d’une interprétation hydrologique.Integrated wastewater system management is the most recent strategy developed in order to minimize wastewater discharges impacts on receiving waters. Global, dynamic and complex, this strategy requires to assess the loads of wastewater discharged by the whole system. Within this framework, the thesis has shown the interest of: a) continuous-time measurements of pollutants by UV/Visible spectroscopy ; b) system identification techniques. The first study carried out concerns the real-time measurement of COD and Suspended Solids at the inlet of a wastewater treatment plant. It has been shown that the performance of PLS models used for the measurement of concentrations can be improved by an optimized selection of wavelengths. Moreover, when the dataset used for calibration is small, it is crucial to restrict the use of models within a validity domain. We propose a methodology mainly based on normalized spectra classification and on comparison of calibration data with statutory measurements. Detection of bacteriological peaks of pollution with UV/Visible spectroscopy has also been investigated. Experimental issues made impossible the calibration of statistical models. Finally, system identification techniques have been applied to the rainfall-runoff modelling of an urban catchment. A continuous-time model taking into account infiltration processes and runoff transfer was identified. This method allows to formalize the mathematical problem of parameter estimation in a elegant and successful way. Another benefit is that the model structure does not need to be fixed a priori, while preserving the possibility of an hydrological interpretation of the identified model