Global Cluster Research Articles

The Global Innovation Clusters: Canadian Experience of Public-Private Partnership

Purpose of the article is the research of the modern trends of global innovation clusters development in Canada that based on public-private partnership model, and to identify their features during last years. The hypothesis is that it is possible to formulate the hypothesis that at the postwar period, Ukraine would form a new innovation strategy that will push country to become global competitively and innovatively. The methods of scientific research were applied to research the global innovation system of Canada and the development of Canada's superclusters: theoretical generalization, empirical method and methods of statistical analysis. The supercluster is a new initiative promoted by the Canadian federal government to strengthen Canada’s most promising clusters and allow innovative firms to operate more productively in sourcing inputs and accessing information, knowledge, and technology. The Innovation superclusters have many positive characteristics as a new framework to rethink Canada’s innovation strategy based on public-private partnership model. The specific measures for development of industrial clusters in Ukraine at the postwar period, and elaboration of national strategy for the development of innovation system in Ukraine can be research objects in future research.

M ycobacterium avium complex genomics and transmission in a London hospital.

Non-tuberculous mycobacteria (NTM) are environmental microorganisms and opportunistic pathogens in individuals with pre-existing lung conditions such as cystic fibrosis (CF) and non-CF bronchiectasis. While recent studies of Mycobacterium abscessus have identified transmission within single CF centres as well as nationally and globally, transmission of other NTM species is less well studied. To investigate the potential for transmission of the Mycobacterium avium complex (MAC) we sequenced 996 isolates from 354 CF and non-CF patients at the Royal Brompton Hospital (London, UK; collected 2013-2016) and analysed them in a global context. Epidemiological links were identified from patient records. Previously published genomes were used to characterise global population structures. We identified putative transmission clusters in three MAC species, although few epidemiological links could be identified. For M. avium, lineages were largely limited to single countries, while for Mycobacterium chimaera, global transmission clusters previously associated with heater-cooler units (HCUs) were found. However, the immediate ancestor of the lineage causing the major HCU-associated outbreak was a lineage already circulating in patients. CF and non-CF patients shared transmission chains, although the lack of epidemiological links suggested that most transmission is indirect and may involve environmental intermediates or asymptomatic carriage in the wider population.

Global Cluster Analysis and Network Visualization in Musculoskeletal Pain Management: A Scientometric Mapping.

Musculoskeletal pain is the most prominent clinical manifestation of more than 150 musculoskeletal disease conditions, and its effective long-term management poses a great challenge to healthcare systems globally. For this, it is important to understand current research progress on musculoskeletal pain management. The purpose of the present study is to provide a comprehensive insight into the current state of research and global trends in musculoskeletal pain management. Publications on musculoskeletal pain management from 1972 to 2021 were retrieved from the Science Citation Index-Expanded (SCIE) database. Included articles were any article type related to aspects of musculoskeletal pain management, including etiology, mechanisms, epidemiology, treatment, outcomes, side effects, and patient compliance. Publication data were analyzed using bibliometric methods. The software VOSviewer was employed to perform bibliographic coupling, co-authorship, co-citation, and co-occurrence analysis, and to visualize publication tendencies in musculoskeletal pain management. A total of 5475 articles were included in this study. The number of global publications on musculoskeletal pain management has escalated annually. Based on the number of publications and citations from the published literature, as well as the H-index, the United States led global contributions in this area. The institutions making the highest contributions were the League of European Research Universities (LERU), the University of Sydney, and Harvard University. The journal BMC Musculoskeletal Disorders published the highest number of articles in this area. The published studies fall under six groups: "Prevention and rehabilitation," "Etiology and diagnosis," "Clinical study," "Epidemiology," "Mental health," and "Education." High-quality primary studies and epidemiology are predicted to be the next prevailing topics in this field of research. Based on current global trends, the number of publications on musculoskeletal pain management will continue to increase. Future studies will likely place more emphasis on high-quality randomized controlled trials (RCTs) and epidemiological studies.

Investigating factors affecting HIV/AIDS knowledge among women in low and middle-income countries in Asia.

Sustainable Development Goal 3 focuses on reducing HIV/AIDS spread, for which disseminating correct information on the disease is required. This study investigated factors associated with HIV/AIDS knowledge among women in several Asian LMICs. Global Multiple Indicator Cluster Survey-6 (MICS-6) for Bangladesh, Lao, Mongolia and Nepal were assessed. Bivariate analysis and generalised linear regression models were fitted. Overall, 60% of the respondents were aware or heard of the existence of HIV/AIDS, with 63.2% having transmission knowledge and 80.4% misconception knowledge. Results revealed that several demographic factors such as wealth index, education and access to information had a significant association with HIV/AIDS knowledge. Mongolia and Nepal have formal programmes in place that may provide policy and implementation advantages compared to Bangladesh and Lao.

Key features of pneumococcal isolates recovered in Central and Northwestern Russia in 2011–2018 determined through whole-genome sequencing

Invasive pneumococcal disease remains one of the leading causes of morbidity and mortality worldwide. In Russia, 13- valent pneumococcal conjugate vaccine (PCV13) was introduced into the childhood immunization programme nationwide in 2014. As part of the Global Pneumococcal Sequencing Project (GPS), we used genome data to characterize 179 pneumococcal isolates collected from Russia in 2011-2018 to investigate the circulating pneumococcal strains using a standardized genomic definition of pneumococcal lineages (global pneumococcal sequence clusters, GPSCs), prevalent serotypes and antimicrobial resistance profiles.We observed high serotype and lineage diversity among the 179 isolates recovered from cerebrospinal fluid (n=77), nasopharyngeal swabs (n=99) and other non-sterile site swabs (n=3). Overall, 60 GPSCs were identified, including 48 clonal complexes (CCs) and 14 singletons, and expressed 42 serotypes (including non-typable). Among PCV13 serotypes, 19F, 6B and 23F were the top three serotypes while 11A, 15B/C and 8 were the top three among non-PCV13 serotypes in the collection. Two lineages (GPSC6 and GPSC47) expressed both PCV13 and non-PCV13 serotypes that caused invasive disease, and were penicillin- and multidrug-resistant (MDR), highlighting their potential to adapt and continue to cause infections under vaccine and antibiotic selective pressure. PCV13 serotypes comprised 92 % (11/12) of the CSF isolates from the children aged below 5 years; however, the prevalence of PCV13 serotype isolates dropped to 53 % (31/58) among the nasopharyngeal isolates. Our analysis showed that 59 % (105/179) of the isolates were predicted to be non-susceptible to at least one class of antibiotics and 26 % (46/179) were MDR. Four MDR lineages (GPSC1, GPSC6, GPSC10 and GPSC47) accounted for 65 % (30/46) of the MDR isolates and expressed PCV13 serotypes (93 %, 28/30).This study provides evidence of high genetic and serotype diversity contributed by a mix of globally spreading and regionally circulating lineages in Russia. The observations suggest that the PCV13 vaccine could be important in reducing both invasive disease and antimicrobial resistance. We also identify potential lineages (GPSC6 and GPSC47) that may evade the vaccine.

A cluster analysis of the global wind power industry: Insights for renewable energy business stakeholders and environmental policy decision makers

AbstractIn light of an ongoing climate change and an increasing fragility of fossil energy supply due to global political tensions, the adoption of renewable energy sources is of utmost importance for economic and social prosperity. This study targets to endeavor major value chain configurations within the global wind power industry network based on a data set of 326 relationships established by the 10 globally leading wind turbine firms covering a time span of 15 years. We discuss the demand side and provide an overview of the main wind power investment target countries and compare the importance of different regions. On the supply side, we analyze and identify eight important firm clusters within the global wind power business network. Concerning our sample, we elaborate horizontal and vertical relationship links, their collaboration patterns, regional partner preferences, and their value chain competences, thus providing valuable insights into the competitive structures of the wind power industry. By doing so, we open the debate on appropriate and efficient firm strategies within renewable industries. As consequence, we provide robust empirical evidence on global wind power industry architectures and corresponding competitive firm forces for the future. As we found that the industry is currently divided into eight main global industry clusters, our study delivers valuable industry network insights addressing managerial, political, and socioeconomic decision makers in order to secure future ecological and economic prosperity in a challenging world.

Utility of constraints reflecting system stability on analyses for biological models.

Simulating complex biological models consisting of multiple ordinary differential equations can aid in the prediction of the pharmacological/biological responses; however, they are often hampered by the availability of reliable kinetic parameters. In the present study, we aimed to discover the properties of behaviors without determining an optimal combination of kinetic parameter values (parameter set). The key idea was to collect as many parameter sets as possible. Given that many systems are biologically stable and resilient (BSR), we focused on the dynamics around the steady state and formulated objective functions for BSR by partial linear approximation of the focused region. Using the objective functions and modified global cluster Newton method, we developed an algorithm for a thorough exploration of the allowable parameter space for biological systems (TEAPS). We first applied TEAPS to the NF-κB signaling model. This system shows a damped oscillation after stimulation and seems to fit the BSR constraint. By applying TEAPS, we found several directions in parameter space which stringently determines the BSR property. In such directions, the experimentally fitted parameter values were included in the range of the obtained parameter sets. The arachidonic acid metabolic pathway model was used as a model related to pharmacological responses. The pharmacological effects of nonsteroidal anti-inflammatory drugs were simulated using the parameter sets obtained by TEAPS. The structural properties of the system were partly extracted by analyzing the distribution of the obtained parameter sets. In addition, the simulations showed inter-drug differences in prostacyclin to thromboxane A2 ratio such that aspirin treatment tends to increase the ratio, while rofecoxib treatment tends to decrease it. These trends are comparable to the clinical observations. These results on real biological models suggest that the parameter sets satisfying the BSR condition can help in finding biologically plausible parameter sets and understanding the properties of biological systems.

Environmental cluster effects and galaxy evolution: The H i properties of the Abell clusters A85/A496/A2670

ABSTRACT We study the impact of the local environment on the transformation of spiral galaxies in three nearby (z < 0.08) Abell clusters: A85/A496/A2670. These systems were observed in H i with the Very Large Array, covering a volume extending beyond the virial radius and detecting 10, 58, and 38 galaxies, respectively. High fractions (0.40–0.86) of bright spirals [log(M*/M⊙) = 9−10] are not detected in H i. We provide further evidence of environmental effects consisting in significant fractions (0.10–0.33) of abnormal objects and a number of red (passive) spirals, suggesting an ongoing process of quenching. Ram-pressure profiles and the sample of the brightest spirals used as test particles for environmental effects indicate that ram-pressure plays an important role in stripping and transforming late-types. Phase-space diagrams and our search for substructures helped to trace the dynamical stage of the three systems. This was used to compare the global cluster effects versus pre-processing, finding that the former is the dominating mechanism in the studied clusters. By contrasting the global distribution of H i normal versus H i disturbed spirals in the combined three clusters, we confirm the expected correlation of disturbed objects located, on average, at shorter projected radii. However, individual clusters do not necessarily follow this trend, and we show that A496 and A2670 present atypical behaviour. In general, we provide conclusive evidence about the dependence of the transformation of infalling spirals on the ensemble of cluster properties like mass, ICM density, dynamical stage, and surrounding large-scale structure.

Emergence of a multidrug-resistant and virulent Streptococcus pneumoniae lineage mediates serotype replacement after PCV13: an international whole-genome sequencing study

SummaryBackgroundSerotype 24F is one of the emerging pneumococcal serotypes after the introduction of pneumococcal conjugate vaccine (PCV). We aimed to identify lineages driving the increase of serotype 24F in France and place these findings into a global context.MethodsWhole-genome sequencing was performed on a collection of serotype 24F pneumococci from asymptomatic colonisation (n=229) and invasive disease (n=190) isolates among individuals younger than 18 years in France, from 2003 to 2018. To provide a global context, we included an additional collection of 24F isolates in the Global Pneumococcal Sequencing (GPS) project database for analysis. A Global Pneumococcal Sequence Cluster (GPSC) and a clonal complex (CC) were assigned to each genome. Phylogenetic, evolutionary, and spatiotemporal analysis were conducted using the same 24F collection and supplemented with a global collection of genomes belonging to the lineage of interest from the GPS project database (n=25 590).FindingsSerotype 24F was identified in numerous countries mainly due to the clonal spread of three lineages: GPSC10 (CC230), GPSC16 (CC156), and GPSC206 (CC7701). GPSC10 was the only multidrug-resistant lineage. GPSC10 drove the increase in 24F in France and had high invasive disease potential. The international dataset of GPSC10 (n=888) revealed that this lineage expressed 16 other serotypes, with only six included in 13-valent PCV (PCV13). All serotype 24F isolates were clustered in a single clade within the GPSC10 phylogeny and long-range transmissions were detected from Europe to other continents. Spatiotemporal analysis showed GPSC10-24F took 3–5 years to spread across France and a rapid change of serotype composition from PCV13 serotype 19A to 24F during the introduction of PCV13 was observed in neighbouring country Spain.InterpretationOur work reveals that GPSC10 alone is a challenge for serotype-based vaccine strategy. More systematic investigation to identify lineages like GPSC10 will better inform and improve next-generation preventive strategies against pneumococcal diseases.FundingBill & Melinda Gates Foundation, Wellcome Sanger Institute, and the US Centers for Disease Control and Prevention.

Applying the Rapid OPPERA Algorithm to Predict Persistent Pain Outcomes Among a Cohort of Women Undergoing Breast Cancer Surgery

Persistent postmastectomy pain after breast surgery is variable in duration and severity across patients, due in part to interindividual variability in pain processing. The Rapid OPPERA Algorithm (ROPA) empirically identified 3 clusters of patients with different risk of chronic pain based on 4 key psychophysical and psychosocial characteristics. We aimed to test this type of group-based clustering within in a perioperative cohort undergoing breast surgery to investigate differences in postsurgical pain outcomes. Women (N = 228) scheduled for breast cancer surgery were prospectively enrolled in a longitudinal observational study. Pressure pain threshold (PPT), anxiety, depression, and somatization were assessed preoperatively. At 2-weeks, 3, 6, and 12-months after surgery, patients reported surgical area pain severity, impact of pain on cognitive/emotional and physical functioning, and pain catastrophizing. The ROPA clustering, which used patients’ preoperative anxiety, depression, somatization, and PPT scores, assigned patients to 3 groups: Adaptive (low psychosocial scores, high PPT), Pain Sensitive (moderate psychosocial scores, low PPT), and Global Symptoms (high psychosocial scores, moderate PPT). The Global Symptoms cluster, compared to other clusters, reported significantly worse persistent pain outcomes following surgery. Findings suggest that patient characteristic-based clustering algorithms, like ROPA, may generalize across diverse diagnoses and clinical settings, indicating the importance of “person type” in understanding pain variability. PerspectiveThis article presents the practical translation of a previously developed patient clustering solution, based within a chronic pain cohort, to a perioperative cohort of women undergoing breast cancer surgery. Such preoperative characterization could potentially help clinicians apply personalized interventions based on predictions concerning postsurgical pain.

Isolation and molecular characterization of lumpy skin disease virus from hard ticks, Rhipicephalus (Boophilus) annulatus in Egypt

BackgroundLumpy skin disease (LSD), a disease of cattle and buffaloes, has recently become widely prevalent in Egypt. The aim of this study was to ascertain the potential role of Rhipicephalus (Boophilus) annulatus ticks in the transmission of this disease. Samples collected from suspected lumpy skin disease virus (LSDV) infected cows that had previously been vaccinated with the Romanian sheep pox virus (SPPV) in various Egyptian governorates were obtained between May to November over two consecutive years, namely 2018 and 2019. Ticks were morphologically identified and the partial cytochrome oxidase subunit I gene (COI) were sequenced, revealing that they were closely related to R. (Boophilus) annulatus. The G-protein-coupled chemokine receptor (GPCR) gene of the LSDV was used to test hard ticks.ResultsTwo positive samples from Kafr El-Sheikh province and one positive sample from Al-Behera province were reported. BLAST analysis revealed that the positive samples were closely related to the Kazakhstani Kubash/KAZ/16 strain (accession number MN642592). Phylogenetic analysis revealed that the GPCR gene of the LSDV recently circulating in Egypt belongs to a global cluster of field LSDV with a nucleotide identity of 98–100%. LSDV isolation was successfully performed four days after inoculation using 9 to 11-day-old embryonated chicken eggs showing characteristic focal white pock lesions dispersed on the choriallantoic membrane after three blind passages. Intracytoplasmic inclusion bodies, cell rupture, vacuoles in cells, and virus particles ovoid in shape were demonstrated by electron microscopy.ConclusionIn this study the role of hard ticks in the transmission of the LSDV to susceptible animals in Egypt was revealed and confirmed by various methods.

Characterization of Emerging Serotype 19A Pneumococcal Strains in Invasive Disease and Carriage, Belgium.

After switching from 13-valent to 10-valent pneumococcal conjugate vaccine (PCV10) (2015–2016) for children in Belgium, we observed rapid reemergence of serotype 19A invasive pneumococcal disease (IPD). Whole-genome sequencing of 166 serotype 19A IPD isolates from children (n = 54) and older adults (n = 56) and carriage isolates from healthy children (n = 56) collected after the vaccine switch (2017–2018) showed 24 sequence types (STs). ST416 (global pneumococcal sequence cluster [GPSC] 4) and ST994 (GPSC146) accounted for 75.9% of IPD strains from children and 65.7% of IPD (children and older adults) and carriage isolates in the PCV10 period (2017–2018). These STs differed from predominant 19A IPD STs after introduction of PCV7 (2011) in Belgium (ST193 [GPSC11] and ST276 [GPSC10]), which indicates that prediction of emerging strains cannot be based solely on historical emerging strains. Despite their susceptible antimicrobial drug profiles, these clones spread in carriage and IPD during PCV10 use.

Are Chinese MNEs more strongly attracted to global cities and knowledge intensive city clusters than developed market MNEs when undertaking greenfield strategic asset seeking related FDI?

PurposeCities are host to many of the world’s knowledge intensive research and innovation clusters. As such, they are likely to be attractive locations for emerging market multinational enterprises (MNEs) seeking to engage in knowledge seeking “springboard” type firm-level catch-up strategies. The purpose of this study is to therefore explore whether city-based research-intensive clusters containing deep pools of location bounded (i.e. “sticky”) knowledge are a stronger driver for greenfield research and development (R&D)-related FDI projects for Chinese MNEs than they are for developed market MNEs.Design/methodology/approachThe authors use logistic modelling on 97,163 worldwide greenfield FDI projects to explore the relative likelihoods of Chinese MNEs engaging in R&D-related greenfield (i.e. “strategic asset seeking”) FDI projects as well as how city type (global or research-intensive cluster city) moderates this relationship for Chinese MNEs.FindingsThe authors find that Chinese MNEs are more likely to engage in overseas R&D FDI projects (compared with other types of project) than DMNEs and that research-intensive city clusters hold a stronger attraction for Chinese MNEs than developed market MNEs.Research limitations/implicationsThe authors discuss how the research contributes to the debate on emerging market MNE catch-up theory, as well as that on sub-national city location choice, by highlighting the growing importance of sub-national geography to understanding strategic asset seeking related greenfield FDI.Practical implicationsSub-national city location choice is an important driver of strategic asset seeking FDI for Chinese MNEs, one that both national and local city level policymakers should pay attention to.Social implicationsChinese FDI via aggressive mergers and acquisitions to acquire key technologies has been restricted in recent years. Policymakers must consider whether they may also wish to restrict Chinese greenfield FDI in R&D-related projects, which now exhibit a pronounced upward trend.Originality/valueThe authors highlight the growing importance of sub-national geography to understanding strategic asset seeking related greenfield FDI in Chinese MNEs (and how it plays, more generally, a central role in their strategies).

Few-shot IoT attack detection based on RFP-CNN and adversarial unsupervised domain-adaptive regularization

The Internet of things (IoT) has attracted extensive research attention in recent years. Cyber-attack protection for IoT devices has become critically important. Malicious users or attackers can take control of IoT devices, thereby putting a wide range of IoT security and privacy data at risk. Thus, the detection and prevention of new attack types are critical in IoT environments. Big data samples are used to train current IoT attack detection models. In certain cases, only few-shot network attack samples can be intercepted. They are susceptible to malicious traffic in an IoT environment, with a reduction in their detection efficiency and accuracy. In this paper, we propose an adversarial unsupervised domain-adaptive regularization and an improved Cascade R-CNN (RFP-CNN) to detect IoT attacks more effectively. First, a feature extraction network (RFP-CNN) is designed. By employing recursive feature pyramids and neural architecture search, the Cascade R-CNN is optimized, and it can extract high-level attack features. Subsequently, an adversarial unsupervised domain-adaptive regularization model is developed, which is known as global cluster center structure regularization. Its purpose is to enable attacks with fewer samples to transfer from other attacks. The model is decoupled into a feature extractor and a domain discriminator using a Siamese network. Finally, our method is validated using four network intrusion datasets pertaining to the IoT. The results demonstrate that our method is capable of extracting time-frequency features. The proposed method exhibits the highest detection accuracy when only a few attack samples are available. It provides excellent anti-noise performance and a short running time when noise is added to the IoT environment. Furthermore, it can be used to detect few-shot IoT attacks in real time.

Distinct Streptococcus pneumoniae cause invasive disease in Papua New Guinea.

Streptococcus pneumoniae is a key contributor to childhood morbidity and mortality in Papua New Guinea (PNG). For the first time, whole genome sequencing of 174 isolates has enabled detailed characterisation of diverse S. pneumoniae causing invasive disease in young children in PNG, 1989-2014. This study captures the baseline S. pneumoniae population prior to the introduction of 13-valent pneumococcal conjugate vaccine (PCV13) into the national childhood immunisation programme in 2014. Relationships amongst lineages, serotypes and antimicrobial resistance traits were characterised, and the population was viewed in the context of a global collection of isolates. The analyses highlighted adiverse S. pneumoniae population associated with invasive disease in PNG, with 45 unique Global Pneumococcal Sequence Clusters (GPSCs) observed amongst the 174 isolates reflecting multiple lineages observed in PNG that have not been identified in other geographic locations. The majority of isolates were from children with meningitis, of which 52% (n=72) expressed non-PCV13 serotypes. Over a third of isolates were predicted to be resistant to at least one antimicrobial. PCV13 serotype isolates had 10.1 times the odds of being multidrug-resistant (MDR) compared to non-vaccine serotype isolates, and no isolates with GPSCs unique to PNG were MDR. Serotype 2 was the most commonly identified serotype; we identified a highly clonal cluster of serotype 2 isolates unique to PNG, and a distinct second cluster indicative of long-distance transmission. Ongoing surveillance, including whole-genome sequencing, is needed to ascertain the impact of the national PCV13 programme upon the S. pneumoniae population, including serotype replacement and antimicrobial resistance traits.

Genetic background of Cambodian pneumococcal carriage isolates following pneumococcal conjugate vaccine 13.

Streptococcus pneumoniae (the pneumococcus) is a leading cause of childhood mortality globally and in Cambodia. It is commensal in the human nasopharynx, occasionally resulting in invasive disease. Monitoring population genetic shifts, characterized by lineage and serotype expansions, as well as antimicrobial-resistance (AMR) patterns is crucial for assessing and predicting the impact of vaccination campaigns. We sought to elucidate the genetic background (global pneumococcal sequence clusters; GPSCs) of pneumococci carried by Cambodian children following perturbation by pneumococcal conjugate vaccine (PCV) 13. We sequenced pre-PCV13 (01/2013–12/2015, N=258) and post-PCV13 carriage isolates (01/2016–02/2017, N=428) and used PopPUNK and SeroBA to determine lineage prevalence and serotype composition. Following PCV13 implementation in Cambodia, we saw expansions of non-vaccine type (NVT) serotypes 23A (GPSC626), 34 (GPSC45) and 6D (GPSC16). We predicted antimicrobial susceptibility using the CDC-AMR pipeline and determined concordance with phenotypic data. The CDC-AMR pipeline had >90 % concordance with the phenotypic antimicrobial-susceptibility testing. We detected a high prevalence of AMR in both expanding non-vaccine serotypes and residual vaccine serotype 6B. Persistently high levels of AMR, specifically persisting multidrug-resistant lineages, warrant concern. The implementation of PCV13 in Cambodia has resulted in NVT serotype expansion reflected in the carriage population and driven by specific genetic backgrounds. Continued monitoring of these GPSCs during the ongoing collection of additional carriage isolates in this population is necessary.

Population genomics of pneumococcal carriage in South Africa following the introduction of the 13-valent pneumococcal conjugate vaccine (PCV13) immunization.

Streptococcus pneumoniae is a major human pathogen responsible for over 317000 deaths in children <5 years of age with the burden of the disease being highest in low- and middle-income countries including South Africa. Following the introduction of the 7-valent and 13-valent pneumococcal conjugate vaccine (PCV) in South Africa in 2009 and 2011, respectively, a decrease in both invasive pneumococcal infections and asymptomatic carriage of vaccine-type pneumococci were reported. In this study, we described the changing epidemiology of the pneumococcal carriage population in South Africa, by sequencing the genomes of 1825 isolates collected between 2009 and 2013. Using these genomic data, we reported the changes in serotypes, Global Pneumococcal Sequence Clusters (GPSCs), and antibiotic resistance before and after the introduction of PCV13. The pneumococcal carriage population in South Africa has a high level of diversity, comprising of 126 GPSCs and 49 serotypes. Of the ten most prevalent GPSCs detected, six were predominantly found in Africa (GPSC22, GPSC21, GPSC17, GPSC33, GPSC34 and GPSC52). We found a significant decrease in PCV7 serotypes (19F, 6B, 23F and 14) and an increase in non-vaccine serotypes (NVT) (16F, 34, 35B and 11A) among children <2 years of age. The increase in NVTs was driven by pneumococcal lineages GPSC33, GPSC34, GPSC5 and GPSC22. Overall, a decrease in antibiotic resistance for 11 antimicrobials was detected in the PCV13 era. Further, we reported a higher resistance prevalence among vaccine types (VTs), as compared to NVTs; however, an increase in penicillin resistance among NVT was observed between the PCV7 and PCV13 eras. The carriage isolates from South Africa predominantly belonged to pneumococcal lineages, which are endemic to Africa. While the introduction of PCV resulted in an overall reduction of resistance in pneumococcal carriage isolates, an increase in penicillin resistance among NVTs was detected in children aged between 3 and 5 years, driven by the expansion of penicillin-resistant clones associated with NVTs in the PCV13 era.

Spatial Grid-Based Position Calculation Method for Satellite-Ground Communication Links

With the rapid development of global satellite constellation clusters and the popularity of ground-based intelligent terminals, the interconnection between large-scale low Earth orbit satellites and ground base stations has become more frequent. The calculation of satellite position requires a large number of floating point square calculations and coordinate system conversions, with high computational complexity and long computation time. Based on the grid encoding method of GeoSOT, we propose a GeoSOT-based grid calculation for a satellite-ground position (GCSGP) model. We use binary bit operations instead of complex topological operations and floating point calculations, and use grid distance calculations instead of existing angle calculations. Thus, the relative positions of satellites to the ground can be quickly calculated and thus connected to more suitable satellites quickly. The results of the grid calculation were verified by simulation experiments. The calculation speed was improved by about 82% compared with the traditional method. The test accuracy error of the 10-level grid at a terminal 45° inclination was less than 1% at all heights, and the maximum error of the 10-level grid within a 10–45° inclination was 7.2% at 10,000 km altitude, which provides theoretical support for the subsequent grid space calculation.

Equity market integration in emerging economies: a network visualization approach

PurposeThe authors examine network features such as connectivity, centrality, adjacency matrices, closeness and betweenness measures through a variety of indicators. The results of the study indicate that over time there is a tendency for markets to integrate and segment due to various factors such as pandemics, financial crises, global trade relations and international investments.Design/methodology/approachThis paper employs a visualized network technique to study the dynamics of integration and comovements in global equity markets of emerging economies. Daily closing prices of stock market indices of 24 countries from January 2013 to July 2020 are used to construct a minimum spanning tree network (MSTN) and graph network (GN).FindingsThe authors identify India and China as global power hubs and clusters among the emerging economies. India and Bangladesh serve as bridging countries connecting to various other clusters. Bosnia serves as a center in the European region owing to Bosnia's trade relations with neighboring countries. Although Brazil has witnessed the worst recession in the early years of the decade, Brazil has risen to be a central cluster among the Latin American countries. Finally, the authors find that African countries tend to form links with the rest of the world rather than with economies within the Africa continent.Originality/valueThis is the pioneering study that uses network models such as MSTN and GN supplemented with measures of centrality and connectivity to study financial market integration in emerging countries. Against this backdrop, this paper aims to work on a network visualization strategy to examine global stock market integration. The authors also try to use graphs and the spanning trees instead of the correlation models to understand the association between the markets, avoiding the downsides of the existing models. The authors' approach tries to visualize the network integration to examine the interconnectedness in the global stock market.

Global polygons for terrain classification divided into uniform slopes and basins

Global terrain classification data have been used for various issues related to topography such as the estimation of soil types and of ground vulnerability to earthquakes and the creation of seismic hazard maps. However, due to the resolution of digital elevation models (DEMs), the terrain classification data from previous studies could not discriminate small landforms such as plains at the bottom of narrow valleys and small rises in plains. Owing to the greater regional variation of small landforms, there is trade-off between DEMs of higher resolution and the creation of global geomorphological legends. To address this problem, we first merged regions with similar topographic characteristics using slope gradients and HAND (height above the nearest drainage) calculated by the 90-m-spatial-resolution DEMs interpolated from the multi-error-removed improved-terrain DEM (MERIT DEM), and united the polygons with the unit catchments of the MERIT-Basins dataset, so that the polygons contain calculated terrain measurements (slope gradient, HAND, surface texture, local convexity, sinks) and noise types as attributes, as well as the ID number of the unit catchment. In addition, we performed k-means clustering on the dataset using slope gradient, HAND, and surface texture, which can be combined with the dataset as a simple terrain classification. The clustering results were prepared in 15 and 40 global uniform clusters and 15 and 40 clusters for each basin to understand the global appearance of the terrain and provide zoning data for regional problem-solving. The 15 clusters were prepared to observe the outline of the terrain without any processing, whereas the 40 clusters were prepared to group and reclassify the polygons to create zoning data for each region. This dataset showed improvements in terms of capturing the small rises in plains compared to the authors' previous global terrain classification data. This dataset can be used as a proxy and is expected to contribute to modeling and estimation in various applications that are known to be related to topography. The datasets of this article are available at [https://gisstar.gsi.go.jp/terrain2021/].