Fast-changing Area Research Articles

Geographical distribution of COVID-19 infection across Saudi Arabia

Background. Saudi Arabia, a large country in terms of population size and geographical area, is divided into administrative areas and governorates. It has metropolises, cities (large, medium sized, and small), towns, villages and rural neighborhoods, classifiable into well equipped, rapidly expanding, and others. The COVID-19 epidemics spread all over the country with differentials in infection rates, percentages, and affected persons, alongside daily increases. This analysis, focused on administrative areas, aimed to comprehend the spread and escalation of the epidemic, in addition to highlighting the distribution of the infected population with a special emphasis on geographical spread and seasonal variations. Materials and methods. This analysis of data compiled from COVID-19 daily reports published by the Saudi Arabian Ministry of Health considers into account administrative areas and localities (neighborhoods) to demonstrate the distribution of spread, increase in infection, and the proportion of population infected between March 21, 2020 and May 4, 2023. Results. A large majority of the infected cases were reported in three major administrative areas including Riyadh, Makkah, and the Eastern Region. Other regions had a smaller number of infected cases. However, some locations, especially medium-sized upcoming towns and neighborhoods experienced greater number of people seriously affected at a rapid pace, with seasonal differentials, in medium sized upcoming cities — the governorate headquarters and promising future cities, apart from the major cities. Conclusions. COVID-19 spread in the country followed a certain regional pattern. Beyond the populous administrative areas, upcoming cities in fast changing areas had a high impact. Thus, having a categorization of major, medium or low spread is necessary. Such detailing of COVID-19 infection would be useful not only to develop combating strategies but also to create epidemic and emergency preparedness.

NDVI Analysis for Monitoring Land-Cover Evolution on Selected Deglaciated Areas in the Gran Paradiso Group (Italian Western Alps)

The ongoing climate warming is affecting high-elevation areas, reducing the extent and the duration of glacier and snow covers, driving a widespread greening effect on the Alpine region. The impact assessment requires therefore the integration of the geomorphological context with altitudinal and ecological features of the study areas. The proposed approach introduces chronologically-constrained zones as geomorphological evidence for selecting deglaciated areas in the alpine and non-alpine belts. In the present study, the protected and low-anthropic-impacted areas of the Gran Paradiso Group (Italian Western Alps) were analysed using Landsat NDVI time series (1984–2022 CE). The obtained results highlighted a progressive greening even at a higher altitude, albeit not ubiquitous. The detected NDVI trends showed, moreover, how the local factors trigger the greening in low-elevation areas. Spectral reflectance showed a general decrease over time, evidencing the progressive colonisation of recently deglaciated surfaces. The results improved the discrimination between different greening rates in the deglaciated areas of the Alpine regions. The geomorphological-driven approach showed significant potential to support the comprehension of these processes, especially for fast-changing areas such as the high mountain regions.

How Can IJDS Authors, Reviewers, and Editors Use (and Misuse) Generative AI?

How Can <i>IJDS</i> Authors, Reviewers, and Editors Use (and Misuse) Generative AI?

Machine Learning in Cyber-Security Threats

Cyber-security is a fast-changing area of discussion due to advanced technologies that have given room for many cybercriminals and attacks in recent years. Cloud computing and increased levels of machine-to-machine interactions have created potential loopholes for invasion. Therefore, it is important to secure the user’s privacy, data, and devices in cyberspace. Recent years have seen tremendous change and increase in machine learning (ML) algorithms that are solving four main cyber-security issues, such as IDS, Android malware detection, spam detection, and malware analysis. The study analyzed these algorithms using a knowledge base system and data mining of information collected from various sources. The outcomes have shown that ML is an efficient way to address cyber-security risks.

Teacher Educators and Expansive Learning in the Workplace and Beyond

Research on the professional learning of teacher educators is a relatively young and under-researched area, despite the importance of this occupational group in the fast-changing area of teacher education internationally. Past provision for learning has often focused on either one-off professional development events or workplace learning. Aiming to develop new knowledge and understanding of professional learning for teacher educators, this article attempts firstly, to analyse the impact of a one-off learning event, offered by the European InFo-TED group, on its participants, and secondly, to look at where and how the learning generated there developed further learning back in the workplace. Deploying a conceptual framework emphasising participatory professional learning and Engestrom’s concept of expansive learning, we explore how these two forms of learning might be planned and implemented in order to provide integrated, professionally relevant and enduring forms of learning.

Development of an openEHR Template for COVID-19 Based on Clinical Guidelines.

BackgroundThe coronavirus disease (COVID-19) was discovered in China in December 2019. It has developed into a threatening international public health emergency. With the exception of China, the number of cases continues to increase worldwide. A number of studies about disease diagnosis and treatment have been carried out, and many clinically proven effective results have been achieved. Although information technology can improve the transferring of such knowledge to clinical practice rapidly, data interoperability is still a challenge due to the heterogeneous nature of hospital information systems. This issue becomes even more serious if the knowledge for diagnosis and treatment is updated rapidly as is the case for COVID-19. An open, semantic-sharing, and collaborative-information modeling framework is needed to rapidly develop a shared data model for exchanging data among systems. openEHR is such a framework and is supported by many open software packages that help to promote information sharing and interoperability.ObjectiveThis study aims to develop a shared data model based on the openEHR modeling approach to improve the interoperability among systems for the diagnosis and treatment of COVID-19.MethodsThe latest Guideline of COVID-19 Diagnosis and Treatment in China was selected as the knowledge source for modeling. First, the guideline was analyzed and the data items used for diagnosis and treatment, and management were extracted. Second, the data items were classified and further organized into domain concepts with a mind map. Third, searching was executed in the international openEHR Clinical Knowledge Manager (CKM) to find the existing archetypes that could represent the concepts. New archetypes were developed for those concepts that could not be found. Fourth, these archetypes were further organized into a template using Ocean Template Editor. Fifth, a test case of data exchanging between the clinical data repository and clinical decision support system based on the template was conducted to verify the feasibility of the study.ResultsA total of 203 data items were extracted from the guideline in China, and 16 domain concepts (16 leaf nodes in the mind map) were organized. There were 22 archetypes used to develop the template for all data items extracted from the guideline. All of them could be found in the CKM and reused directly. The archetypes and templates were reviewed and finally released in a public project within the CKM. The test case showed that the template can facilitate the data exchange and meet the requirements of decision support.ConclusionsThis study has developed the openEHR template for COVID-19 based on the latest guideline from China using openEHR modeling methodology. It represented the capability of the methodology for rapidly modeling and sharing knowledge through reusing the existing archetypes, which is especially useful in a new and fast-changing area such as with COVID-19.

Remote Sensing of Time-Varying Tidal Flat Topography, Jiangsu Coast, China, Based on the Waterline Method and an Artificial Neural Network Model

Measurement of beach heights in the intertidal zone has great importance for dynamic geomorphology research, coastal zone management, and the protection of ecological resources. Based on satellite images, the waterline method based on satellite images is one of the most effective methods for constructing digital elevation models (DEMs) for large-scale tidal flats. However, for fast-changing areas, such as Tiaozini in the Jiangsu coast, timely and detailed topographical data are difficult to obtain due to the insufficient images over a short period of time. In this study, as a supplement to the waterline method, an artificial neural network (ANN) model with the multi-layer feed-forward back propagation algorithm was developed to simulate the topography of variable Tiaozini tidal flats. The “7-15-15-1” double hidden layers with optimized training structures were confirmed via continuous training and comparisons. The input parameters included spectral bands (HJ-1 images B1~B4), geographical coordinates (X, Y), and the distance (D) to waterlines, and the output parameter was the elevation. The model training data were the HJ-1 image for 21 March 2014, and the corresponding topographic data obtained from the waterline method. Then, this ANN model was used to simulate synchronous DEMs corresponding to remote sensing images on 11 February 2012, and 11 July 2013, under low tide conditions. The height accuracy (root mean square error) of the two DEMs was about 0.3–0.4 m based on three transects of the in-situ measured data, and the horizontal accuracy was 30 m—the same as the spatial resolution of the HJ-1 image. Although its vertical accuracy is not very high, this ANN model can quickly provide the basic geomorphological framework for tidal flats based on only one image. This model, therefore, provides an effective way to monitor rapidly changing tidal flats.

USING COHERENT SCATTERERS IN TIME SERIES OF HIGH RESOLUTION SAR IMAGES FOR THE MONITORING OF CONSTRUCTION ACTIVITY

Abstract. In this paper, we present a method for detecting and quantifying changes due to construction activity in time series of high resolution SAR images. We propose to detect these changes by the appearance or disappearance of a large number of coherent scatterers, rather than by looking at changes in SAR amplitude or coherence. These coherent scatterers, which appear mainly in buildings and other man-made structures, will be detected in each individual image by analysing their stability across multiple frequency sub-bands. This implies that long time series are not required, unlike for other similar approaches based in persistent scatterer interferometry, and that this approach can be applied for the monitoring of fast changing areas such as temporary settlements. The presented approach will be applied for monitoring the construction activity taking place during the preparations for two large festivals in Munich, Germany.

Role of Agent Middleware in Teaching Distributed Systems and Agent Technologies

Computer science and information communication technologies are among the fastest changing areas and it is essential to follow this world-wide trend also in education, constantly innovating and adapting curricula. In this paper, we introduce the structure, methodological aspects and educational experiences of teaching two courses on distributed systems and agent technologies at two different universities and countries. The presentation is focused on the role of agent middleware and multi-agent systems in teaching various theoretical and practical aspects of these courses. At the University of Craiova, the conclusion is that the use of agent middleware in general and of JADE platform in particular for teaching the course Distributed Systems certainly brings many advantages, but also has some limitations. At the University of Novi Sad, within the Agent Technologies course, agent middleware, initially developed as part of the research project, has been successfully used for educational purposes, too. For both courses, we present the structure, the tools, teachers' and students' experiences and joint useful conclusions and lessons learned with regard to courses delivery.

Elevation Change Derived from SARAL/ALtiKa Altimetric Mission: Quality Assessment and Performance of the Ka-Band

The waveform retracking algorithm is a key factor that affects the accuracy of elevation change from satellite altimetry over an ice sheet. The elevation change results from four waveform retracker algorithms (ICE1/ICE2/Sea Ice/OCEAN) provided by the Satellite with ARgos and ALtiKa (SARAL/ALtiKa) data were compared using repeated SARAL data between March 2013 and April 2016 to determine the optimal retracker in the crossovers of descending and ascending orbits over a Greenland ice sheet (GrIS). The ICE1 provided slightly better results than the three other algorithms with the lowest standard deviation (SD) of 0.30 m year−1. Further comparison was also conducted between the Satellite with ARgos and ALtiKa (SARAL) and Operation ICEBridge laser data, thereby indicating that ICE1 was the best retracker with an Root Mean Square Error (RMSE) of 0.43 m year−1. The distribution of elevation change rate and uncertainties over Greenland from SARAL were presented using the selected ICE1 retracker with a volume loss of 40 ± 12 km3 year−1. This volume loss did not include the fast-changing coastal areas of the GrIS. A large thinning was observed in Jakobshavn Isbræ, and a trend that extended far inland was also found from 2013–2016. Furthermore, a melting ice sheet was observed in the large areas northwest over the GrIS.

Peer-Review of Digital Educational Resources—A Rigorous Review Process Developed by the Climate Literacy and Energy Awareness Network (CLEAN)

ABSTRACTEducators seek to develop 21st century skills in the classroom by incorporating educational materials other than textbooks into their lessons, such as digitally available activities, videos, and visualizations. A problem that educators face is that no review process similar to the formal adoption processes used for K–12 textbooks or the college-textbook review process exists for these types of online educational resources. However, educators need authoritative high-quality digital teaching materials. The scientific journal peer-review system offers a well-established model to adapt to the requirements of a peer review of educational materials. In this paper, we review ten review processes developed to evaluate digital geoscience educational resources and focus in detail on a rigorous iterative peer-review process recently developed by the Climate Literacy and Energy Awareness Network (CLEAN) project. This process builds upon existing efforts and emphasizes the “curation” of a digital collection that addresses the Essential Principles of Climate Literacy and the Energy Literacy Principles. Providing educators with thoroughly reviewed educational materials is especially important for fast changing, societally important, and sensitive areas such as climate and energy science.

Regulating Genetic Information in Germany and Israel: Towards a Policy Network Comparative Analysis

This article explores genetic information and database policy-making in Germany and Israel using policy network analysis. The article demonstrates that the policy network model could be a useful heuristic device for analyzing the complex relationships between government and non-governmental actors involved in formulating regulations within the context of a fast-changing area such as that of genetic information testing and databases. The comparative analysis of Israeli and German regulation of genetic information has shown that issue networks have been conducive to statutory regulation in genetic information policy domains such as privacy protection and non-discrimination. Thus, this article raises the need to widen the scope of statutory legislation of genetic information to include benefit-sharing guidelines to justify the voluntary participation of individuals and communities, without which genetic information databases could not exist.

Least-Squares-Based Switching Structure for Lossless Image Coding

Many coding methods are more efficient with some images than others. In particular, run-length coding is very useful for coding areas of little changes. Adaptive predictive coding achieves high coding efficiency for fast changing areas like edges. In this paper, we propose a switching coding scheme that will combine the advantages of both run-length and adaptive linear predictive coding. For pixels in slowly varying areas, run-length coding is used; otherwise least-squares (LS)-adaptive predictive coding is used. Instead of performing LS adaptation in a pixel-by-pixel manner, we adapt the predictor coefficients only when an edge is detected so that the computational complexity can be significantly reduced. For this, we use a simple yet effective edge detector using only causal pixels. This way, the proposed system can look ahead to determine if the coding pixel is around an edge and initiate the LS adaptation in advance to prevent the occurrence of a large prediction error. With the proposed switching structure, very good prediction results can be obtained in both slowly varying areas and pixels around boundaries. Furthermore, only causal pixels are used for estimating the coding pixels in the proposed encoder; no additional side information needs to be transmitted. Extensive experiments as well as comparisons to existing state-of-the-art predictors and coders will be given to demonstrate its usefulness.

Software and expert system for the management of chronic hepatitis B

Whereas the doubling time of overall biomedical knowledge bases has been estimated at about 19 years, the body of indexed information related to HBV has doubled in the last 8 years; the one related to HBV and antivirals has doubled in the last 5 years and the one related to Interferon and contraindications has doubled in less than 48 months. In Hepatology, as well as in other fast changing areas of medicine, the demand that clinical decision should always be based on the best verified knowledge available, is becoming more and more difficult to comply with. The Italian network of competence for hepatic diseases (Liver Unit Networks Association or LUNA) was established in 2003 with the patronage of the Italian Ministry of Health, with the primary goal of promoting advanced clinical research and real-time information exchange among the participating centres, facilitating knowledge sharing and identification of best practices. The ICT infrastructure designed for this purpose includes four sets of online accessible software tools: o (1) Tools for the establishment and maintenance, by a team of recognized experts, of an essential corpus of validated scientific knowledge limited to the area of competence and therefore easy to search and navigate, though considering different points of view (clinical, radiological, surgical) and open to users' comments and objections, to be used as both a study and a reference tool in a multidisciplinary inter-professional perspective. (2) Tools for the management of large-scale multicentre studies allowing for participation in the research of motivated professionals irrespective of their affiliation to research institutions or smaller clinical centres. (3) Tools to make consensus and guideline definition a more participative and transparent process. (4) Tools to organize and manage team consultation between clinician and researchers on practice cases. Each set of tools is described and discussed in some detail.

DNA Microarrays and Bacterial Gene Expression

This chapter focuses on the construction and utilization of two-color-spotted DNA microarrays in the analysis of bacterial gene expression. These microarrays consist of either polymerase chain reaction (PCR) products or long oligonucleotides spotted on an amine-coated glass surface. The chapter reviews the DNA microarrays holding much promise as a tool to approach biological problems on a genome-wide level. The ability to investigate regulatory networks on a whole-genome level is already providing key insights in transcription factor function. The microarray field is a fast-changing area in which many new technical and statistical tools are being developed at a rapid pace. Because of the diverse technical and analytical challenges encountered when using microarrays, a team effort with expertise in biology, bioinformatics, and statistics is required to successfully utilize this technology and incorporate new advances.

Gender, Work, and Post-Fordism: The EC Context

Gender relations in employment are one of the fastest changing areas of social relations in both the United Kingdom and the rest of Europe, and face even greater changes as there is closer integration in the EC and as the organization of employment relations is restructured. Three related is sues are addressed here. First, there is an apparent paradox: While there has been an enormous increase in the extent of women's paid employ ment in the United Kingdom and much of the rest of the EC, there has only been a very slight closing of the equity gap between men and women in employment in these countries. Second, what is and will be the impact of increasing European integration, especially within the EC, on the position of women in employment? Third, are the political pres sures represented in the Social Charter and Article 119 of the Treaty of Rome for equal opportunities likely to achieve their aims since they are predicated on a Fordist employment structure, just as the EC moves in a post-Fordist direction? The main focus here is on the United Kingdom as a member state of the EC, with some reference to other EC and other European countries. The article is divided into two sections: the first deals with the substantive points of change; the second focuses on the theoretical issues involved.

Tracking areas of strategic importance using scientometric journal mappings

In science policy, it is often important to track emerging developments: new fields, fast-changing areas that are the focus of special funding efforts, or areas of growth or decline. This article presents methods to produce literature-based indicators for such areas using journal-to-journal citations. Using case studies of AIDS, superconductivity, and oncogenes, we posit that the inclusion of a new journal can be used as an indicator of structural change if the addition indicates the emergence of a new journal category. Using the cases of robotics and artificial intelligence, we illustrate the development of areas chosen for priority funding. Again using artificial intelligence, we demonstrate the importance of constructing even such simple measures of scientific performance as publication counts using dynamic rather than constant journal sets. Change in performance within a subfield can be systematically distinguished from change in the delineations among subfields over time.

Costs and financing of adult education: A case study of Shenzhen, China

Analyses of costs and financing are a neglected area in the literature on adult education and training (AET). This paper presents a study of the costs and financing of AET in Shenzhen, a high-growth and fast-changing area in China. Based on a survey of trainees, and administrators, as well as interviews with administrators, managers, and trainees from three different types of AET centers in Shenzhen, the study addressed three research questions: What are the costs of AET? How are resources utilized in AET centers? How is AET financed in a fastchanging area? The study demonstrates some of the methodological difficulties in cost estimation; it provides preliminary evidence of the existence of economies of scale in the operation of AET; and it finds that enterprises and trainees are the major financial sources and that the government has a very limited financing role. The implications of the findings for policy analysis in AET are discussed.

Literature review of hydrogel presbyopic correction

There are several lens options for the practioner undertaking hydrogel lens correction of a presbyope. Therefore, this is a fast-changing area of clinical concern. This paper summarizes the research available on bifocal contact lenses. The articles are divided into introductory, theoretical, and clinical research. The information is then summarized to guide the practitioner in choosing the proper lens type for a particular patient. Additional areas of research are also suggested.

A basis for increasing public access to federal electronic information

The Joint Committee on Printing requested that $800,000 be allocated in FY 1988 for 16 pilot projects involving the electronic dissemination of government information to depository libraries. That request was deferred by legislative appropriations subcommittees in both Houses of Congress pending completion of OTA’s report on electronic dissemination options. Originally expected in the fall of 1987, the report, titled Informing the Nation: Federal Information Dissemination in an Electronic Age, was finally released in October 1988. Was the wait worthwhile? Clearly, precious time and some important opportunities have been lost. However, the Federal government and the public at large should benefit significantly from the report ifit is used as a heuristic device for developing new policies in a fast-changing area of government responsibility. It is also valuable for scholars as a state-of-the-art description of new information technologies and as a case study of organizational adaptation to electronic technologies. Much has changed already in the short period since the subcommittees decided to delay “without prejudice” the provision of $800,000 for pilot projects. First, the Glenerin Declaration, signed by the United States, Canada, and Great Britain in December 1987, has established a general framework for information policy development in those countries, should its guidelines be followed. Second, a legislative-executive budget “summit agreement,” also in December 1987, has imposed some voluntary constraints upon funding for new programs. Third, the Reagan administration’s efforts to privatize the National Technical Information Service (NTIS) have probably been sidetracked permanently by legislative provisions in the trade bill and the National Bureau of Standards authorization act. Fourth, the Department of Commerce has issued its own draft proposal