Health worker registries: managing the health care workforce

Registries play an instrumental role in facilitating the transfer, aggregation, and analysis of standardized data in health information exchange (HIE). One such example is a health worker registry (HWR), a central, authoritative registry that maintains the unique identities of health workers according to a defined, minimum data set. Currently, data comprising workers' information—such as education, licensure, and place of employment—are collected through disparate methods and maintained in a variety of information systems. Harmonization of these data via an HWR can support interoperability and comparability of worker information across systems, thereby facilitating efficient workforce enumeration, planning, regulation and deployment, verification of training and education, identification of workforce shortages, and rapid communication and coordination of emergency response. In fact, HWR technologies played a role in coordinating response to both Ebola in West Africa in 2014 and more recently in response to COVID-19, making a HWR integral to nations' infrastructure upgrades postpandemic. This chapter identifies who is considered a "health worker” and why a registry of these individuals is a useful component of an HIE, especially in the wake of the COVID-19 pandemic. It also provides guidance on selection of data elements and standards to include in the development of an HWR. © 2023 Elsevier Inc. All rights reserved.

Probing environmental and tectonic changes underneath Mexico City with the urban seismic field

The sediments underneath Mexico City have unique mechanical properties that give rise to strong site effects. We investigated temporal changes in the seismic velocity at strong-motion and broadband seismic stations throughout Mexico City, including sites with different geologic characteristics ranging from city center locations situated on lacustrine clay to hillside locations on volcanic bedrock. We used autocorrelations of urban seismic noise, enhanced by waveform clustering, to extract subtle seismic velocity changes by coda wave interferometry. We observed and modeled seasonal, co- and post-seismic changes, as well as a long-term linear trend in seismic velocity. Seasonal variations can be explained by self-consistent models of thermoelastic and poroelastic changes in the subsurface shear wave velocity. Overall, sites on lacustrine clay-rich sediments appear to be more sensitive to seasonal surface temperature changes, whereas sites on alluvial and volcaniclastic sediments and on bedrock are sensitive to precipitation. The 2017 Mw 7.1 Puebla and 2020 Mw 7.4 Oaxaca earthquakes both caused a clear drop in seismic velocity, followed by a time-logarithmic recovery that may still be ongoing for the 2017 event at several sites or that may remain incomplete. The slope of the linear trend in seismic velocity is correlated with the downward vertical displacement of the ground measured by interferometric synthetic aperture radar, suggesting a causative relationship and supporting earlier studies on changes in the resonance frequency of sites in the Mexico City basin due to groundwater extraction. Our findings show how sensitively shallow seismic velocity and, in consequence, site effects react to environmental, tectonic and anthropogenic processes. They also demonstrate that urban strong-motion stations provide useful data for coda wave monitoring given sufficiently high-amplitude urban seismic noise.

Digital topics on cultural heritage investigated: how can data-driven and data-guided methods support to identify current topics and trends in digital heritage?

In research and policies, the identification of trends as well as emerging topics and topics in decline is an important source of information for both academic and innovation management. Since at present policy analysis mostly employs qualitative research methods, the following article presents and assesses different approaches – trend analysis based on questionnaires, quantitative bibliometric surveys, the use of computer-linguistic approaches and machine learning and qualitative investigations. Against this backdrop, this article examines digital applications in cultural heritage and, in particular, built heritage via various investigative frameworks to identify topics of relevance and trendlines, mainly for European Union (EU)-based research and policies. Furthermore, this article exemplifies and assesses the specific opportunities and limitations of the different methodical approaches against the backdrop of data-driven vs. data-guided analytical frameworks. As its major findings, our study shows that both research and policies related to digital applications for cultural heritage are mainly driven by the availability of new technologies. Since policies focus on meta-topics such as digitisation, openness or automation, the research descriptors are more granular. In general, data-driven approaches are promising for identifying topics and trendlines and even predicting the development of near future trends. Conversely, qualitative approaches are able to answer "why” questions with regard to whether topics are emerging due to disruptive innovations or due to new terminologies or whether topics are becoming obsolete because they are common knowledge, as is the case for the term "internet”.

Geospatial, earth observations and statistical data integration in the Cortés department, Honduras

Proper territorial data management is critical for territorial planning projects, research, innovation, and the appropriate follow-up to act for the well-being of populations. A multidisciplinary team of professionals established a pilot project named Cortes Data Hub (Centro de Datos de Cortés). It presents several dashboards that show official statistics on the energy sector, mapping the region's energy demand, data on COVID-19 cases and vaccination rates by municipality or department, and a project using Google Earth that combines post-Eta and Iota observations and a social media campaign for disaster awareness and for the promotion of activities to develop tourism in the San Manuel Municipality. This pilot project shows the importance to observe and monitor various key environmental, health, and socioeconomic data. This will help improve initiatives for local development, disaster prevention and control, and the promotion of the One Health approach. The challenges to overcome are the quality and timing of data. Training more academics, government teams, and decision-makers in the use of new tools for data integration with earth observations are important for the Cortés department's development. © 2022 IEEE.

Outreach for Science Facilities: Armagh Observatory and Planetarium's programme for the Cherenkov Telescope Array

We describe an outreach programme being delivered by the Armagh Observatory and Planetarium (AOP) for the Cherenkov Telescope Array (CTA). Founded in 1790 and with a rich astronomical heritage, AOP today combines the research and education arms of our organisation to bring a research-informed outreach programme to the public, most often through our planetarium-related activities. We have developed and written, in-house, a short full dome planetarium show ("Exploring the High-Energy Universe”) that describes the science of gamma-ray astronomy and introduces the CTA as the first ground-based gamma-ray observatory open to the whole scientific community. In parallel, we are engaged in developing a series of short videos to introduce the scientists and the science of the UK CTA consortium, again designed for public audiences. These videos can be accessed through our social media channels. Delivery of such outreach programme in bite-sized pieces is an essential element in attracting and engaging audiences. We explain how we have developed the skill set to do this in our Education Team at AOP whilst our facility has been closed for the past year, a result of the Covid-pandemic. There is also scope in extending these concepts for providing outreach support for other science facilities. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0)

Towards a New MAX-DOAS Measurement Site in the Po Valley: NO2 Total VCDs

Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instruments are used worldwide to retrieve pollutant information from visible (VIS) and ultra-violet (UV) diffuse solar spectra. A similar instrument, able to meet the Fiducial Reference Measurements for DOAS (FRM4DOAS) standard requirements, is not yet present in the Po Valley (Italy), one of the most polluted regions in Europe. Our purpose is to close this gap exploiting the SkySpec-2D, a FRM4DOAS-compliant MAX-DOAS instrument bought by the Italian research institute CNR-ISAC in May 2021. As a first step, SkySpec-2D was involved in two measurement campaigns to assess its performance: the first one in August 2021 in Bologna where TROPOGAS, a research-grade custom-built MAX-DOAS instrument is located;the second one in September 2021 at the BAQUNIN facility at La Sapienza University (Rome) near the Pandora#117 instrument. Both campaigns revealed a good quality of SkySpec-2D measurements. Indeed, good agreement was found with TROPOGAS (correlation 0.77), Pandora#117 (correlation 0.9) and satellite (TROPOMI and OMI) measurements. Having assessed its performance, the SkySpec-2D was permanently moved to the “Giorgio Fea” observatory in San Petro Capofiume, located in the middle of the Po Valley, where it has been continuously acquiring zenith and off-axis diffuse solar spectra from the 1 October 2021. Nowadays, its MAX-DOAS measurements are routinely provided to the FRM4DOAS team with the purpose to be soon included in the FRM4DOAS validation network.

Measurements of natural airflow within a Stevenson screen and its influence on air temperature and humidity records

Climate science depends upon accurate measurements of air temperature and humidity, the majority of which are still derived from sensors exposed within passively ventilated louvred Stevenson-type thermometer screens. It is well-documented that, under certain circumstances, air temperatures measured within such screens can differ significantly from “true” air temperatures measured by other methods, such as aspirated sensors. Passively ventilated screens depend upon wind motion to provide ventilation within the screen and thus airflow over the sensors contained therein. Consequently, instances of anomalous temperatures occur most often during light winds when airflow through the screen is weakest, particularly when in combination with strong or low-angle incident solar radiation. Adequate ventilation is essential for reliable and consistent measurements of both air temperature and humidity, yet very few systematic comparisons to quantify relationships between external wind speed and airflow within a thermometer screen have been made. This paper addresses that gap by summarizing the results of a 3-month field experiment in which airflow within a UK-standard Stevenson screen was measured using a sensitive sonic anemometer and comparisons made with simultaneous wind speed and direction records from the same site. The mean in-screen ventilation rate was found to be 0.2 m s-1 (median 0.18 m s-1), well below the 1 m s-1 minimum assumed in meteorological and design standard references, and only about 7 % of the scalar mean wind speed at 10 m. The implications of low in-screen ventilation on the uncertainty of air temperature and humidity measurements from Stevenson-type thermometer screens are discussed, particularly those due to the differing response times of dry- and wet-bulb temperature sensors and ambiguity in the value of the psychrometric coefficient.

Sub-mesoscale observations of convective cold pools with a dense station network in Hamburg, Germany

From June to August 2020, an observational network of 103 meteorological ground-based stations covered the greater area (50 km × 35 km) of Hamburg (Germany) as part of the Field Experiment on Sub-mesoscale Spatio-Temporal variability at Hanseatic city of Hamburg (FESST@HH). The purpose of the experiment was to shed light on the sub-mesoscale (O(100) m–O(10) km) structure of convective cold pools that typically remain under-resolved in operational networks. During the experiment, 82 custom-built, low-cost APOLLO (Autonomous cold POoL LOgger) stations sampled air temperature and pressure with fast-response sensors at 1 s resolution to adequately capture the strong and rapid perturbations associated with propagating cold pool fronts. A secondary network of 21 weather stations with commercial sensors provided additional information on relative humidity, wind speed, and precipitation at 10 s resolution. The realization of the experiment during the COVID-19 pandemic was facilitated by a large number of volunteers who provided measurement sites on their premises and supported station maintenance. This article introduces the novel type of autonomously operating instruments, their measurement characteristics, and the FESST@HH data set10.25592/UHHFDM.10172;. A case study demonstrates that the network is capable of mapping the horizontal structure of the temperature signal inside a cold pool, and quantifying a cold pool's size and propagation velocity throughout its life cycle. Beyond its primary purpose, the data set offers new insights into the spatial and temporal characteristics of the nocturnal urban heat island and variations of turbulent temperature fluctuations associated with different urban and natural environments.

Observational data from uncrewed systems over Southern Great Plains

Uncrewed Systems (UxS), including uncrewed aerial systems (UAS) and tethered balloon/kite systems (TBS), are significantly expanding observational capabilities in atmospheric science. Rapid adaptation of these platforms and the advancement of miniaturized instruments have resulted in an expanding number of datasets captured under various environmental conditions by the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility. In 2021, observational data collected using ARM UxS platforms, including seven TigerShark UAS flights and 133 tethered balloon system (TBS) flights, were archived by the ARM Data Center (https://adc.arm.gov/discovery/#/, last access: 11 February 2022) and made publicly available at no cost for all registered users (10.5439/1846798) (Mei and Dexheimer, 2022). These data streams provide new perspectives on spatial variability of atmospheric and surface parameters, helping to address critical science questions in Earth system science research. This paper describes the DOE UAS/TBS datasets, including information on the acquisition, collection, and quality control processes, and highlights the potential scientific contributions using UAS and TBS platforms.

An Application of Artificial Neural Network to Evaluate the Influence of Weather Conditions on the Variation of PM2.5-Bound Carbonaceous Compositions and Water-Soluble Ionic Species

Previous studies have determined biomass burning as a major source of air pollutants in the ambient air in Thailand. To analyse the impacts of meteorological parameters on the variation of carbonaceous aerosols and water-soluble ionic species (WSIS), numerous statistical models, including a source apportionment analysis with the assistance of principal component analysis (PCA), hierarchical cluster analysis (HCA), and artificial neural networks (ANNs), were employed in this study. A total of 191 sets of PM2.5 samples were collected from the three monitoring stations in Chiang-Mai, Bangkok, and Phuket from July 2020 to June 2021. Hotspot numbers and other meteorological parameters were obtained using NOAA-20 weather satellites coupled with the Global Land Data Assimilation System. Although PCA revealed that crop residue burning and wildfires are the two main sources of PM2.5, ANNs highlighted the importance of wet deposition as the main depletion mechanism of particulate WSIS and carbonaceous aerosols. Additionally, Mg2+ and Ca2+ were deeply connected with albedo, plausibly owing to their strong hygroscopicity as the CCNs responsible for cloud formation.

A new scanning scheme and flexible retrieval for mean winds and gusts from Doppler lidar measurements

Doppler wind lidars (DWLs) have increasingly been used over the last decade to derive the mean wind in the atmospheric boundary layer. DWLs allow the determination of wind vector profiles with high vertical resolution and provide an alternative to classic meteorological tower observations. They also receive signals from altitudes higher than a tower and can be set up flexibly in any power-supplied location. In this work, we address the question of whether and how wind gusts can be derived from DWL observations. The characterization of wind gusts is one central goal of the Field Experiment on Sub-Mesoscale Spatio-Temporal Variability in Lindenberg (FESSTVaL). Obtaining wind gusts from a DWL is not trivial because a monostatic DWL provides only a radial velocity per line of sight, i.e., only one component of a three-dimensional vector, and measurements in at least three linearly independent directions are required to derive the wind vector. Performing them sequentially limits the achievable time resolution, while wind gusts are short-lived phenomena. This study compares different DWL configurations in terms of their potential to derive wind gusts. For this purpose, we develop a new wind retrieval method that is applicable to different scanning configurations and various time resolutions. We test eight configurations with StreamLine DWL systems from HALO Photonics and evaluate gust peaks and mean wind over 10 min at 90 m a.g.l. against a sonic anemometer at the meteorological tower in Falkenberg, Germany. The best-performing configuration for retrieving wind gusts proves to be a fast continuous scanning mode (CSM) that completes a full observation cycle within 3.4 s. During this time interval, about 11 radial Doppler velocities are measured, which are then used to retrieve single gusts. The fast CSM configuration was successfully operated over a 3-month period in summer 2020. The CSM paired with our new retrieval technique provides gust peaks that compare well to classic sonic anemometer measurements from the meteorological tower.

Building a Global Ecosystem Research Infrastructure to Address Global Grand Challenges for Macrosystem Ecology

The development of several large‐, “continental”‐scale ecosystem research infrastructures over recent decades has provided a unique opportunity in the history of ecological science. The Global Ecosystem Research Infrastructure (GN1 -https://media.proquest.com/media/hms/PFT/1/tH74N?_a=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%2BgIBWYIDA1dlYooDHENJRDoyMDIyMDUyNzE1MjE0NjA4MzoxMjE1MjM%3D&_s=X56Bn7jbW%2FHzqBBHc7s64wnr4lo%3D ERI) is an integrated network of analogous, but independent, site‐based ecosystem research infrastructures (ERI) dedicated to better understand the function and change of indicator ecosystems across global biomes. Bringing together these ERIs, harmonizing their respective data and reducing uncertainties enables broader cross‐continental ecological research. It will also enhance the research community capabilities to address current and anticipate future global scale ecological challenges. Moreover, increasing the international capabilities of these ERIs goes beyond their original design intent, and is an unexpected added value of these large national investments. Here, we identify specific global grand challenge areas and research trends to advance the ecological frontiers across continents that can be addressed through the federation of these cross‐continental‐scale ERIs.

Debunk, Check and Tell Others – New Player in the Fight against Disinformation in Central Europe

Gregus discusses the CEDMO (Central European Digital Media Observatory), a digital media observatory that has been set up within Europe to combat disinformation. It covers Slovakia, the Czech Republic and Poland as linguistically close countries in the region and focuses on debunking disinformation and verifying facts in the context of these nations. The aim of the CEDMO project is also to research the impact of disinformation on the media, communities and society, and also to analyze information disorder trends and raise awareness. A key feature of the project is the use of artificial intelligence to map and detect the spread of disinformation within Central European Slavic languages, as nothing similar exists yet.

COIVD-19 IMPACT MONITORING OF ECONOMIC ACTIVITIES

The COVID-19 pandemic has had substantial impacts on the Earth system and socioeconomic activities. Restrictions aimed at reducing the spread of COVID-19 by limiting human interaction have led to significant reductions in air pollution and CO2 emissions, improvement in water quality, changes in agricultural output, and changes in economic activity for certain industries such as airlines and shipping, among others [1, 2, 3, 4, 5]. Those economic impact assessment related information are made available on the trilateral COVID-19 Earth Observing Dashboard (https://eodashboard.org) [6]. The presented use cases in economic activities make full use of the combined satellites fleet of NASA, ESA and JAXA as well as the expertise of the Earth Observation community. © 2021 IEEE.

JAXA’S EARTH OBSERVATION DATA ANALYSIS ON COVID-19

The COVID-19 pandemic has brought difficulties to our daily lives and caused various changes in socio-economic activities and the natural environment. To monitor and record the changes in socio-economic activities and the environment before and during the COVID-19 pandemic, JAXA has collaborated with NASA and ESA in developing a trilateral dashboard to provide socio-economic activities and natural environmental change information derived from earth observation data. JAXA also has analyzed Earth observation data, for example, ALOS-2, GCOM-C, GOSAT and GOSAT-2 and opened at a special website “JAXA for Earth on COVID-19” in the categories of airports, industry, shipping, agriculture, greenhouse gasses and water quality. © 2021 IEEE.

The Rural and Nature Tourism Development Potential in Islands

It has become evident that rural tourism grew significantly during the pandemic compared to mass tourism. However, at this time, all the forecasts were wrapped in considerable uncertainty regarding travel, which is not without the elevated associated risk. Therefore, we assessed the perceptions of the entrepreneurs in relation to rural tourism activities regarding the advantages of their rural tourism activity in the Azores for customers. Furthermore, the potential for developing this typology of tourism is pivotal for obtaining very reliable data and information on this topic and enabling us to provide guidelines for the leading regional players. In this regard, an exploratory method was used to assess the perceptions of the entrepreneurs with rural tourism activities in the Azores Islands regarding the customers’ experiences and some other important aspects concerning the promotion of this type of tourism in the region. Throughout this study, it was possible to verify that the most relevant obstacles to the development of rural tourism in the Azores region are the preservation and conservation of nature and endogenous resources and delivering proper infrastructures and regional accessibilities. Contrarily, the increase in community and regional funding and support for rural tourism could be key to the prosperity of this typology of tourism in this insular territory.

Sustainable urban development observatory of Thessaloniki - lessons learnt from the first year of operation

Sustainable Urban Development Observatory of Thessaloniki (SUDOTh) started operating in the first semester of 2020 with the objective to promote territorial evidence in policy making in urban governance. SUDOTh was developed as part of the Sustainable Urban Development Strategy 2016-2023 of Thessaloniki Metropolitan Area to address the need to obtain, observe and monitor how complex urban functions interact, at a territorial level, with product development (or lagging) effects. In the first year of operation, the Observatory had to set, test and evaluate the system of indicators and indexes it uses. Initially the system was formed in 4 basic sections: 1. Territorial Development and Urban renewal, 2. Urban Mobility, 3. Environmental Conditions and 4. Social Conditions. An extra set of indicators for Urban Governance was also developed. The process of data collection, test and evaluation of indicators was eventually coincided with the COVID-19 pandemic. This situation influenced deeply several urban functions as well as the data collection methodology. The first results and conclusions from the first year of the operation of SUDOTh are presented and discussed further in this paper.

Vida Decision Support System: An International, Collaborative Project for COVID-19 Management with Integrated Modeling

The Vida Decision Support System (Vida) is an application of the Environment-Vulnerability-Decision-Technology (EVDT) integrated modeling framework specifically aimed at COVID-19 impact and response analysis. The development of Vida has been an international collaboration involving multidisciplinary teams of academics, government officials (including public health, economics, environmental, and demographic data collection officials), and others from six states: Angola, Brazil, Chile, Indonesia, Mexico, and the United States. These collaborators have been involved with the identification of decision support needs, the surfacing and creation of relevant data products, and the evaluation of prototypes, with the vision of creating an openly available online platform that integrates earth observation instruments (Landsat, VIIRs, Planet Lab's PlanetScope, NASA's Socioeconomic Data and Applications Center, etc.) with in-situ data sources (COVID-19 case data, local demographic data, policy histories, mobile device-based mobility indices, etc.). Vida both visualizes historical data of relevance to decision-makers and simulates possible future scenarios. The modeling techniques used include system dynamics for public health, EO-based change detection and machine learning for environmental analysis, and discrete-event simulation of policy changes and impacts. In addition to the direct object of this collaboration (the development of Vida), collaborators have also benefited from sharing individual COVID-19-related insights with the network and from considering COVID-19 response in a more integrated fashion. This work outlines the Vida Decision Support System concept and the EVDT framework on which it is based. The international team is using Vida to evaluate the outcomes in several large cities regarding COVID cases, environmental changes, economic changes and policy decisions. It provides an overview of the overlapping and diverging needs and data sources of each of the collaborating teams, as well as how each of those teams have contributed to the development of Vida. The current state of the Vida prototypes and plans for future development will be presented. Additionally, this work will discuss the lessons learned from this development process and their relevance to other integrated applications. Copyright © 2021 by the International Astronautical Federation (IAF). All rights reserved.

Mitigating the impacts of pandemics on the supply chain using Earth Observation Data

With sudden changes in demand for certain goods, strict border control, and movement restrictions, pandemics can cause an immense disruption of the supply chain especially as it pertains to sustenance goods and job security. The most important recommendations on how this disruption can be mitigated by applying Remote Sensing have been outlined. Earth Observation (EO) and ground data can be used to mitigate the effects of pandemics on the interconnected global and local supply chain;with the COVID-19 pandemic as a case study. The scope of effects by COVID-19 includes issues in the supply chain, operational logistics, and goods production. EO data can be used to track goods like foods, medical kits, hand sanitizers, etc. which in turn aids the reallocation of high-demand goods to areas with limited supply. Satellite-based communication channels will be useful for more remote areas. The supply chain deals with adequate production, the food security issues faced by a significant part of the world's population, can be tackled with an integrated approach. An integrated application of Remote Sensing, (IoT), and Machine Learning is proposed for food security. EO can be used for agricultural monitoring using GNSS coupled with available tools to assess and predict produce status. This is useful in disaster management during restrictions of pandemics;machine learning models can be deployed in conjunction with IoT systems to help with farm monitoring watering of crops using weather data, environment monitoring and fertilizer requirement reminders, and triggering of risk management protocols during disasters. Copyright © 2021 by the International Astronautical Federation (IAF). All rights reserved.

Pollen observations at four EARLINET stations during the ACTRIS-COVID-19 campaign

Lidar observations were analysed to characterize atmospheric pollen at four EARLINET (European Aerosol Research Lidar Network) stations (Hohenpeißenberg, Germany;Kuopio, Finland;Leipzig, Germany;and Warsaw, Poland) during the ACTRIS (Aerosol, Clouds and Trace Gases Research Infrastructure) COVID-19 campaign in May 2020. The reanalysis (fully quality-assured) lidar data products, after the centralized and automatic data processing with the Single Calculus Chain (SCC), were used in this study, focusing on particle backscatter coefficients at 355 and 532 nm and particle linear depolarization ratios (PDRs) at 532 nm. A novel method for the characterization of the pure pollen depolarization ratio was presented, based on the non-linear least square regression fitting using lidar-derived backscatter-related Ångström exponents (BAEs) and PDRs. Under the assumption that the BAE between 355 and 532 nm should be zero (±0.5) for pure pollen, the pollen depolarization ratios were estimated: for Kuopio and Warsaw stations, the pollen depolarization ratios at 532 nm were of 0.24 (0.19–0.28) during the birch-dominant pollen periods, whereas for Hohenpeißenberg and Leipzig stations, the pollen depolarization ratios of 0.21 (0.15–0.27) and 0.20 (0.15–0.25) were observed for periods of mixture of birch and grass pollen. The method was also applied for the aerosol classification, using two case examples from the campaign periods;the different pollen types (or pollen mixtures) were identified at Warsaw station, and dust and pollen were classified at Hohenpeißenberg station.