Policymakers frequently analyze air quality and climate change in isolation, disregarding their interactions. This study explores the influence of specific climate factors on air quality by contrasting a regression model with K-Means Clustering, Hierarchical Clustering, and Random Forest techniques. We employ Physics-based Deep Learning (PBDL) and Long Short-Term Memory (LSTM) to examine the air pollution predictions. Our analysis utilizes ten years (2009-2018) of daily traffic, weather, and air pollution data from three major cities in Norway. Findings from feature selection reveal a correlation between rising heating degree days and heightened air pollution levels, suggesting increased heating activities in Norway are a contributing factor to worsening air quality. PBDL demonstrates superior accuracy in air pollution predictions compared to LSTM. This paper contributes to the growing literature on PBDL methods for more accurate air pollution predictions using environmental variables, aiding policymakers in formulating effective data-driven climate policies.

One hundred eighty-nine new packages made it to CRAN in June. Here are my “Top 40” selections in eleven categories: Computational Methods, Data, Ecology, Genomics, Machine Learning, Mathematics, Medicine, Statistics, Time Series, Utilities, and Visualizations. Computational Methods itp v1.2.0: Implements the interpolate, truncate, project root-finding algorithm developed by Oliveira & Takahashi (2021). The vignette provides an overview. QR v0..1.3: Provides a function to perform QR factorization without pivoting to a real or complex matrix. It is based on LAPACK. See the vignette. qsplines v1.0.0: Provides functions to create quaterion splines. See Barry & Goldman (1988) and Kochanek & Bartels (1984) for the details and look here for an example. VMDecomp v1.0.1: Implements the variational mode decomposition and two-dimensional variational mode decomposition algorithm. See Dragomiretskiy & Zosso (2014) for background and the vignette for examples. Data cmch v0.2.0: Implements a wrapper around the Canadian Mortgage and Housing Corporation web interface and enables programmatic and reproducible access to a wide variety of housing data. See the vignette for examples. EDIutils v1.0.1: Implements a client for the Environmental Data Initiative repository REST API and provides access to ecological data and metadata. There are five short vignettes: Evaluate & upload, Citation Metrics, Download Metrics, Search andaccess, and Tests. globaltrends v0.0.12: Provides functions to access global search volumes from the Google Trends portal. This working paper outlines the package’s methodological foundations and potential applications. See the vignette to get started. kaigiroku v0.5: Allows users to search and download data from the API for Japanese Diet proceedings. Look here for examples. NasdaqDataLink v1.0.0: Provides functions to interact directly with the Nasdaq Data Link API and obtain data in a number of formats. Look here for API documentation and here for package information. stortingscrape v0.1.1: Provides functions for retrieving data from the Norwegian Parliament, through the Norwegian Parliament API. See the vingette for an introduction. Ecology PointedSDMs v1.0.6: Provides tools to build integrated species distribution models and includes tools to run spatial cross-validation and plotting. See Issac et al. (2020) for and introduction to the methods. There is a Setophaga Example and an example for the Solitary Tinamou. restoptr v1.0.1: Implements a flexible framework for ecological restoration planning that aims to identify priority areas for restoration efforts using optimization algorithms described in Justeau-Allaire et al. 2021. See the vignette to get started. Genomics scapGNN v0.1.1: Implements a single cell active pathway analysis tool based on the graph neural network algorithm described in Scarselli et al. (2009) and Kipf & Welling (2017). This may be used to construct a gene-cell association network, infer pathway activity scores from different single cell modalities data and more. See the vignette for an overview and examples. SRTsim v0.99.2: Implements an independent, reproducible, and flexible Spatially Resolved Transcriptomics simulation framework that can be used to facilitate the development analytical methods and for a wide variety of SRT-specific analyses. See the vignette. xQTLbiolinks v1.1.1: Implements tools to query, download, and visualize of molecular quantitative trait locus and gene expression data from public resources through the GTEx API. There is a Quick Start Guide and vignettes on Colocalization, Specivicity, and Visualization. Machine Learning agua v0.0.1: Enables users to specify h2o as an engine for several tidymodels modeling methods. See README for examples. MagmaClustR V1.0.0: Implements two main algorithms, called Magma (Leroy et al. (2022) and MagmaClust (Leroy et al. (2020)), using a multi-task Gaussian processes (GP) model to perform predictions for supervised learning problems. See README for examples. openai v0.1.0: Provides a wrapper for OpenAI API endpoints including engines, completions, edits, files, fine-tunes, embeddings and legacy searches, classifications, and answers endpoints. See README to get started. sketching v0.1.0: Provides functions to construct sketches of data via random subspace embeddings. See Lee & Ng (2022) for the theory and the vignette for examples. webmorphR v0..1.1: Provides functions to create reproducible image stimuli, specialised for face images with psychomorph or webmorph templates. See README to get started. Mathematics GeneralizedWendland v0.5-2: Implements the fully parameterized generalized Wendland covariance function for use in Gaussian process models, as well as multiple methods for approximating it via covariance interpolation. The available methods are linear interpolation, polynomial interpolation, and cubic spline interpolation. See Bevilacqua et al. (2022) and the vignette for examples. jacobi v2.0.0: Evaluates Jacobi theta functions and related functions including the Weierstrass elliptic function, the Weierstrass sigma function, the Weierstrass zeta function, the Klein j-function, the Dedekind eta function, the lambda modular function, Jacobi elliptic functions, Neville theta functions, and the Eisenstein series for real and complex variables. Look here for some images. Medicine clinicalsignificance v1.0.0: Implements the clinical significance algorithm proposed by Jacobson et al. (1984) to determine if an intervention has a meaningful practical effect. There is a Getting Started Guide and vignettes on Cutoffs and Plots. PlatformDesign v1.0.1: Provides functions to calculate design parameters for an optimal two-period, multi-arm platform design allowing pre-planned deferred arms to be added during the trial. See Dunnett (1955) for background and the vignette for some theory and examples. Statistics bayesassurance v0.1.0: Provides functions to compute Bayesian assurance under various settings characterized by different assumptions and objectives, including precision-based conditions, credible intervals, and goal functions. See Pan & Banerjee (2021) for the theory. There are vignettes for using closed form solutions, the conjugate linear model, and precision based conditions. DSSP v0.1.1: Provides functions to draw samples from the direct sampling spatial prior model as described in White, Sun, & Speckman (2019). See the vignette for examples. edibble v0.1.0: Implements a system to facilitate designing comparative experiments using the grammar of experimental designs. See the edibble-book for documentation. mixgb v0.1.0: Implements a method for multiple imputation using XGBoost, bootstrapping and predictive mean matching as described in Deng and Lumley (2021). There is an Introduction and a vignette on Imputing new data with a saved imputer. outerbase v0.1.0: Implements in new method for high-dimensional regression using outer product models. See Plumlee (2014) and Plumlee et al. (2021) for background. There is a Getting started guide, a Base walkthrough, and vignettes on Learning from data and Speeding up inference. PFIM v5.0: Provides functions to evaluate or optimize designs for nonlinear mixed effects models using the Fisher Information matrix. See Malle & Baccar D (1997) and Retout et al. (2007) for background and the vignettes Design evaluation and optimixation (01), Design evaluation and optimixation (02), and Library of models for examples. VirtualPop v1.0.2: Provides functions to generate lifespans and fertility histories in continuous time using individual-level state transition (multi-state) models and data. See the vignettes on Simulation of life histories, Sampling from waiting time distributions, Simulation of individual fertility careers, and Validation. Time Series kssa v0.0.1: Implements the known sub-sequence algorithm described in Benavides et al. (2022), which helps to automatically identify and validate the best method for missing data imputation in a time series. Look here for examples. ts2net v0.1.0: Implements methods to transform time series into networks, a technique which may be useful for complex systems modeling, time series data mining, or time series analysis using networks. For an introduction to the topic and descriptions of the methods see Mitchell (2006), Silva & Zhao (2016), and Silva et al. (2021). See README to get started. Utilities cppchedkR Allows users to run Cppcheck on C/C++ files as an R command or an RStudio addin. See README. . gtExtras v0.4.1: Provides additional functions for creating tables with gt. See README for examples. . Visualization ggpie v0.2.2: Provides functions for creating pie, donut and rose pie plots with ggplot2. See the vignette. ggtrace v0.2.0: Provides ggplot2 geoms that allow groups of data points to be outlined or highlighted for emphasis. See the vignettes Trace lines and Trace points. Morphoscape v1.0.0: Implements adaptive landscape methods first described by Polly et al. (2016) for the integration, analysis and visualization of biological trait data on a phenotypic morphospace which are typically defined by shape metrics. See the vignette. r3js v0.0.1: Provides R and JavaScript functions to allow WebGL-based 3D plotting using the three.js library. See the vignettes: Getting Started, Creating a plot from scratch, and Grouping plot elements. rgl2gltf v1.0.0: Provides functions to work with glTF files which are used to describe 3D models. See the vignette for examples.. . shapviz v0.2.0: Provides functions to visualize SHapley Additive exPlanations (SHAP), such as waterfall plots, force plots, various types of importance plots, and dependence plots. See Lundberg & Lee (2017) for background and the vignette for examples.

The Aker group and the World Economic Forum (WEF) will develop what they call the Centre for the Fourth Industrial Revolution Norway (C4IR Norway), as part of efforts to preserve the ocean through advanced technology. Through the partnerships, the Centre aims to develop governance frameworks and solutions for a sustainable and profitable ocean economy, using digital technology ranging from Artificial Intelligence (AI) to Blockchain. The Centre will provide a platform for partnerships on governance policies, research and business solutions that can stimulate the application of science, data and technology in the public interest. The C4IR Norway will join the WEF's global C4IR Network and collaborate with the Government of Norway and the High Level Panel for a Sustainable Ocean Economy. The Centre will be an independent non-profit foundation, financed initially by founding partner the Aker group.