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Tang, Jia-Yu, and Zu-Hui Fan. "Resolved SZE Cluster Count." Chinese Journal of Astronomy and Astrophysics 3, no. 3 (June 2003): 191–202. http://dx.doi.org/10.1088/1009-9271/3/3/191.
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Debackere, Stijn N. B., Joop Schaye, and Henk Hoekstra. "How baryons can significantly bias cluster count cosmology." Monthly Notices of the Royal Astronomical Society 505, no. 1 (May 10, 2021): 593–609. http://dx.doi.org/10.1093/mnras/stab1326.
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ABSTRACT We quantify two main pathways through which baryonic physics biases cluster count cosmology. We create mock cluster samples that reproduce the baryon content inferred from X-ray observations. We link clusters to their counterparts in a dark matter-only universe, whose abundances can be predicted robustly, by assuming the dark matter density profile is not significantly affected by baryons. We derive weak lensing halo masses and infer the best-fitting cosmological parameters Ωm, S8 = σ8(Ωm/0.3)0.2, and w0 from the mock cluster sample. We find that because of the need to accommodate the change in the density profile due to the ejection of baryons, weak lensing mass calibrations are only unbiased if the concentration is left free when fitting the reduced shear with NFW profiles. However, even unbiased total mass estimates give rise to biased cosmological parameters if the measured mass functions are compared with predictions from dark matter-only simulations. This bias dominates for haloes with $m_\mathrm{500c} \lt 10^{14.5} \, \rm h^{-1} \, \mathrm{M_\odot }$. For a stage IV-like cluster survey without mass estimation uncertainties, an area $\approx 15\,000 \, \mathrm{deg^2}$ and a constant mass cut of $m_\mathrm{200m,min} = 10^{14} \,\rm h^{-1} \, \mathrm{M_\odot }$, the biases are $-11 \pm 1 \, \mathrm{per\, cent}$ in Ωm, $-3.29 \pm 0.04 \, \mathrm{per\, cent}$ in S8, and $9 \pm 1.5 \, \mathrm{per\, cent}$ in w0. The statistical significance of the baryonic bias depends on how accurately the actual uncertainty on individual cluster mass estimates is known. We suggest that rather than the total halo mass, the (re-scaled) dark matter mass inferred from the combination of weak lensing and observations of the hot gas, should be used for cluster count cosmology.
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Takkala, Rohit Reddy, and Chris Chu. "CHIP: Clustering Hotspots in Layout Using Integer Programming." Journal of Electrical and Computer Engineering 2019 (January 17, 2019): 1–12. http://dx.doi.org/10.1155/2019/9430593.
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Clustering algorithms have been explored in recent years to solve hotspot clustering problems in integrated circuit design. With various applications in design for manufacturability flow such as hotspot library generation, systematic yield optimization, and design space exploration, generating good quality clusters along with their representative clips is of utmost importance. With several generic clustering algorithms at our disposal, hotspots can be clustered based on the distance metric defined while satisfying some tolerance conditions. However, the clusters generated from generic clustering algorithms need not achieve optimal results. In this paper, we introduce two optimal integer linear programming formulations based on triangle inequality to solve the problem of minimizing cluster count while satisfying given constraints. Apart from minimizing cluster count, we generate representative clips that best represent the clusters formed. We achieve a better cluster count for both formulations in most test cases as compared to the results published in the literature in the ICCAD 2016 contest benchmarks as well as the reference results reported in the ICCAD 2016 contest website.
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Wang, Henry H., Stephen C. Bunt, Aaron J. Zynda, Cason Hicks, Bert Vargas, Kathleen Bell, and Munro Cullum. "MECHANISM OF INJURY AND POST-CONCUSSION SYMPTOMS IN ADOLESCENT SOCCER PLAYERS." Orthopaedic Journal of Sports Medicine 7, no. 3_suppl (March 1, 2019): 2325967119S0000. http://dx.doi.org/10.1177/2325967119s00008.
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Background: In contact sports such as soccer, a variety of mechanisms exist in which a sport-related concussion (SRC) may be sustained. This includes striking the ball with the head, whether unintentional or in the act of heading, striking the ground, and hitting other players’ bodies or heads. There are limited data examining whether different mechanisms of injury have an effect on post-concussion symptoms. The purpose of this study was to explore the relationship between concussion injury mechanism and symptom clusters in adolescent soccer players. Methods: Data were collected from subjects enrolled in the North Texas Concussion Network Registry (ConTex). Subjects were included if they were age 12-18 and diagnosed with a SRC while playing soccer. Upon clinical visit, subjects completed a self-reported symptom evaluation and relevant medical and concussion history. Symptoms were divided into three clusters: physical, cognitive, and emotional. A symptom count for each cluster was calculated along with a sum of reported symptom level. These values were compared to injury mechanism (collision with another player’s body, ground, ball, etc.) using one-way ANCOVA which controlled for differences in body mass index (BMI). For analyses in which BMI had no main effect, the covariate was removed from the model and ANOVA was performed. For analyses with significant Levene’s values, a Kruskal-Wallis H Test was used to verify the main effect of the independent variable. Pairwise comparisons with Bonferroni correction were used to analyze the data. Results: A total of 169 (57 male, 112 female) subjects met inclusion criteria. The mean age of the group was 13.9 years (range: 12-18). Of all the subjects, 42 (24.9%) experienced a collision with another player, 20 (11.8%) experienced a head-to-head collision, 49 (29.0%) were struck in the head by the ball unintentionally, 47 (27.8%) hit their heads on the ground, and 11 (6.5%) were intentionally heading the ball. Mechanism of injury had a significant effect on Physical Cluster Symptom count (p=.005), Cognitive Cluster Symptom count (p=.004), and Emotional Cluster Symptom count (p=.003) and Emotional Symptom sum (p=.013). Hitting the head to the ground was associated with a higher Physical Cluster Symptom count (p=.015), Cognitive Cluster Symptom count (p=.004), and Emotional Cluster Symptom count (p=.002) and Emotional Cluster Symptom sum (p=.009) than unintentional ball strikes. Additionally, hitting the ground resulted in a higher Emotional Cluster Symptom count than hitting another player’s body (p=.017). No other effects of mechanism on symptoms were seen. Conclusions: These findings suggest that there is a significant effect for some injury mechanisms and symptom clusters in adolescent soccer players. In this sample, a greater number of physical, cognitive, and emotional symptoms as well as a greater sum of emotional symptoms were reported by subjects who hit their head on the ground than subjects who experienced other mechanisms of injury such as being incidentally struck by the ball or colliding with another player. The outcomes of this analysis encourage the consideration of mechanism of injury when evaluating symptoms for SRC in soccer.
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Magnussen, Steen. "Prediction of 2 × 2 tables of change from repeat cluster sampling of marginal counts." Canadian Journal of Forest Research 34, no. 8 (August 1, 2004): 1703–13. http://dx.doi.org/10.1139/x04-041.
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Repeat cluster sampling of a binary (0,1) attribute at time 1 (Y1) and time 2 (Y2) in a finite population of discrete units is considered. All clusters contain m units and a cluster provides the marginal count of ones and zeroes at the two time points only. From these counts, we seek to predict a 2 × 2 table of the rates of no change (π11 = E[Y1Y2], π00 = E[(1 Y1)(1 Y2)]) and change (π10 = E[Y1(1 Y2)], 01 = E[(1 Y1)Y2]). Two predictors are proposed; one is derived from the temporal correlation of marginal counts and the second from the odds ratio of no change that maximizes a (pseudo-) likelihood of a non-central, hypergeometric distribution. The bias of the first is positive when there is a positive intracluster correlation of Y1, Y2, and Y1Y2, while the bias of the second is negative when the odds ratio of no change is >1. A proposed combined estimator worked well in three examples of change analysis with paired, classified Landsat images of forest cover type and cluster sampling with 3 × 3 arrays of 30 m × 30 m units (pixels). 2 × 2 tables obtained from marginal counts were superior, in terms of mean absolute error, to estimates based on a direct unit-by-unit count when the time 2 image had a root mean square registration error of 0.5 pixel relative to the time 1 image. The proposed method is intended for settings where a direct unit-by-unit estimation of the 2 × 2 table is either compromised or when data (by design) consist of marginal counts from a repeat cluster sampling.
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Vedder, C. J. G., and N. E. Chisari. "Galaxy clusters as intrinsic alignment tracers: present and future." Monthly Notices of the Royal Astronomical Society 500, no. 4 (November 26, 2020): 5561–69. http://dx.doi.org/10.1093/mnras/staa3633.
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ABSTRACT Galaxies and clusters embedded in the large-scale structure of the Universe are observed to align in preferential directions. Galaxy alignment has been established as a potential probe for cosmological information, but the application of cluster alignments for these purposes remains unexplored. Clusters are observed to have a higher alignment amplitude than galaxies, but because galaxies are much more numerous, the trade-off in detectability between the two signals remains unclear. We present forecasts comparing cluster and galaxy alignments for two extragalactic survey set-ups: a currently available low-redshift survey (Sloan Digital Sky Survey, SDSS) and an upcoming higher redshift survey (Legacy Survey of Space and Time, LSST). For SDSS, we rely on the publicly available redmapper catalogue to describe the cluster sample. For LSST, we perform estimations of the expected number counts while we extrapolate the alignment measurements from SDSS. Clusters in SDSS have typically higher alignment signal-to-noise ratio (S/N) than galaxies. For LSST, the cluster alignment signals quickly wash out with redshift due to a relatively low number count and a decreasing alignment amplitude. Nevertheless, a potential strong suit of clusters is in their interplay with weak lensing: intrinsic alignments can be more easily isolated for clusters than for galaxies. The S/N of cluster alignment can in general be improved by isolating close pairs along the line of sight.
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Bozanta, Aysun, and Birgul Kutlu. "Do Twitter phenomena check-in popular venues on Foursquare too?" Information Discovery and Delivery 46, no. 3 (August 20, 2018): 137–46. http://dx.doi.org/10.1108/idd-04-2018-0012.
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Purpose The purpose of this study is to figure out the visiting behaviors of the users who have different characteristics on Twitter. Design/methodology/approach The visit history of users who share their Foursquare check-ins on Twitter and the characteristics of visited venues (category, check-in count, tip count, like count, rating, and price tier) was collected with Foursquare API. In addition, the number of followers, friends, tweets and favorite-count were collected via Twitter API. First, users were clustered according to their Twitter related attributes. After that, profiling was applied on clusters according to the characteristics of the venues that were visited by the users. Findings Clustering analysis generated three clusters, namely, ordinary, talkative and popular. For each cluster, the visited venues were investigated according to the price classification, check-in, like, tip counts and the categories. The users in ordinary class prefer cheaper venues rather than talkative and popular users. On the other hand, popular users prefer the venues with the highest average number of check-ins, likes and tip counts. The top two categories for all clusters are cafe and shopping mall. Originality/value This study differentiates from the other studies in the literature by examining the data from Twitter with clustering and profiling these clusters with Foursquare data to understand venue preferences of Twitter users having various characteristics. The findings of this study will provide new insights for business owners to understand the customers more comprehensively and design better marketing strategies.
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Abdulnassar, A. A., and Latha R. Nair. "A Comprehensive Study on the Importance of the Elbow and the Silhouette Metrics in Cluster Count Prediction for Partition Cluster Models." Revista Gestão Inovação e Tecnologias 11, no. 4 (July 29, 2021): 3792–806. http://dx.doi.org/10.47059/revistageintec.v11i4.2408.
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Proper selection of cluster count gives better clustering results in partition models. Partition clustering methods are very simple as well as efficient. Kmeans and its modified versions are very efficient cluster models and the results are very sensitive to the chosen K value. The partition clustering algorithms are more suitable in applications where the data are arranged in a uniform manner. This work aims to evaluate the importance of assigning cluster count value in order to improve the efficiency of partition clustering algorithms using two well known statistical methods, the Elbow method and the Silhouette method. The performance of the Silhouette method and Elbow method are compared with different data sets from the UCI data repository. The values obtained using these methods are compared with the results of cluster performance obtained using the statistical analysis tool Weka on the selected data sets. Performance was evaluated on cluster efficiency for small and large data sets by varying the cluster count values. Similar results obtained from the three methods, the Elbow method, the Silhouette method and the clustering by Weka. It was also observed that the fast reduction in clustering efficiency for small changes in cluster count when the cluster count is small.
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Medury, Aditya, Julia B. Griswold, Louis Huang, and Offer Grembek. "Pedestrian Count Expansion Methods: Bridging the Gap between Land Use Groups and Empirical Clusters." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 5 (April 12, 2019): 720–30. http://dx.doi.org/10.1177/0361198119838266.
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Count expansion methods are a useful tool for creating long-term pedestrian or cyclist volume estimates from short-term counts for safety analysis or planning purposes. Expansion factors can be developed based on the trends from automated counters set up for long periods of time. Evidence has shown that the activity patterns can vary between sites so that there is potential to create more accurate estimates by grouping similar long-term count trends into factor groups. There are two common approaches to developing factor groups in pedestrian and cyclist count expansion studies. The land use classification approach has the advantage of being simple to apply to short-term count locations based on attributes of the surrounding area, but it requires assumptions by the researchers about which characteristics correlate with different activity patterns. Empirical clustering approaches can potentially create more distinct clusters by effectively matching locations with similar patterns, but they do not present an easy way to apply the resulting factor groups to appropriate short-term count sites. This study connects the two approaches and takes advantage of the benefits of both by using objective measures of the surrounding land use to model membership in the empirical cluster groups.
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Song, Hongshuo, Weidong Ou, Yi Feng, Junli Zhang, Fan Li, Jing Hu, Hong Peng, et al. "Disparate impact on CD4 T cell count by two distinct HIV-1 phylogenetic clusters from the same clade." Proceedings of the National Academy of Sciences 116, no. 1 (December 17, 2018): 239–44. http://dx.doi.org/10.1073/pnas.1814714116.
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HIV-1 evolved into various genetic subtypes and circulating recombinant forms (CRFs) in the global epidemic. The same subtype or CRF is usually considered to have similar phenotype. Being one of the world’s major CRFs, CRF01_AE infection was reported to associate with higher prevalence of CXCR4 (X4) viruses and faster CD4 decline. However, the underlying mechanisms remain unclear. We identified eight phylogenetic clusters of CRF01_AE in China and hypothesized that they may have different phenotypes. In the National HIV Molecular Epidemiology Survey, we discovered that people infected by CRF01_AE cluster 4 had significantly lower CD4 counts (391 vs. 470,P< 0.0001) and higher prevalence of X4-using viruses (17.1% vs. 4.4%,P< 0.0001) compared with those infected by cluster 5. In an MSM cohort, X4-using viruses were only isolated from seroconvertors in cluster 4, which was associated with low a CD4 count within the first year of infection (141 vs. 440,P= 0.003). Using a coreceptor binding model, we identified unique V3 signatures in cluster 4 that favor CXCR4 use. We demonstrate that the HIV-1 phenotype and pathogenicity can be determined at the phylogenetic cluster level in the same subtype. Since its initial spread to humans from chimpanzees, estimated to be the first half of the 20th century, HIV-1 continues to undergo rapid evolution in larger and more diverse populations. The divergent phenotype evolution of two major CRF01_AE clusters highlights the importance of monitoring the genetic evolution and phenotypic shift of HIV-1 to provide early warning of the appearance of more pathogenic strains.
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Bagherzadeh karimi, Nazli. "Survey on Multi Agent Energy Efficient Clustering Algorithms in Wireless Sensor Networks." Computer Engineering and Applications Journal 3, no. 3 (September 7, 2014): 172–84. http://dx.doi.org/10.18495/comengapp.v3i3.92.
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In the last few years, there are many applications for Wireless Sensor Networks (WSNs). One of the main drawbacks of these networks is the limited battery power of sensor nodes. There are many cases to reduce energy consumption in WSNs. One of them is clustering. Sensor nodes partitioned into the clusters so that one is chosen as Cluster Head (CH). Clustering and selection of the proper node as CH is very significant in reducing energy consumption and increasing network lifetime. In this paper, we have surveyed a multi agent clustering algorithms and compared on various parameters like cluster size, cluster count, clusters equality, parameters used in CHs selection, algorithm complexity, types of algorithm used in clustering, nodes location awareness, inter-cluster and intra-cluster topologies, nodes homogeneity and MAC layer communications.
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Kiremire, Enos Masheija Rwantale. "The Capping Theory of Chemical Elements and Clusters Based on 4N Series and Skeletal Numbers." International Journal of Chemistry 10, no. 4 (November 21, 2018): 94. http://dx.doi.org/10.5539/ijc.v10n4p94.
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The genesis of chemical clusters of the transition and main group elements has been established. The base-line cluster valence electrons has been demarcated with help of capping series. Using the base-line as a reference, the formulas of fragments and clusters were generated. Also a simple general formula for cleating cluster valence electrons for systems ranging from a single skeletal element to hundreds of them was identified. In so doing, the single elements of the periodic table were naturally placed into their respective periods. The concepts of the existence of nuclei in clusters and some having black-holes were deeply rooted. A tentative explanation of some clusters having an octahedral geometry but with low cluster valence electron count was put forward.
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Weigant, John. "Cluster computing: CPU count isn't the whole story." Leading Edge 23, no. 10 (October 2004): 964. http://dx.doi.org/10.1190/1.1813350.
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Hanfelt, John J., Ruosha Li, Yi Pan, and Pierre Payment. "Robust inference for sparse cluster-correlated count data." Journal of Multivariate Analysis 102, no. 1 (January 2011): 182–92. http://dx.doi.org/10.1016/j.jmva.2010.09.003.
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Anselin, Luc, and Xun Li. "Operational local join count statistics for cluster detection." Journal of Geographical Systems 21, no. 2 (May 2, 2019): 189–210. http://dx.doi.org/10.1007/s10109-019-00299-x.
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Michael, Popoola Omoniyi, and Olagunju Oluwatosin Olubunmi. "Morphological differentiation in African catfish (Clarias gariepinus) from three different populations in Nigeria." Nigerian Journal of Technological Research 16, no. 1 (March 9, 2021): 13–20. http://dx.doi.org/10.4314/njtr.v16i1.2.
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AbstractIntraspecific morphological variation in Clarias gariepinus was studied in three water bodies. Twenty-three morphometric characteristics and seven meristic were used. Principal component (PC) analysis showed that morphometric traits of River Osun and Ogbese were somewhat related while that of Aago showed no relatedness, there were no difference among the meristic counts of the populations. PC1, and PC2 accounted for 93% and 4% of the variation observed in the populations. High positive correlation was observed in Aago (r = 0.872, b = 2.10) and Ogbese population while low correlation and negative allometric growth (r = 0.425 and b= 1.38) was observed in Asejire population. Cluster analysis revealed that three studied populations are separated into two major clusters, with samples from Asejire and Ogbese population found within the same cluster but different sub- clusters, similarly some of samples from Aago were also within the same cluster while samples 10 were found on a separate and major cluster. The study confirms the variability among individual species within each population, indicates the presence of genetic diversity among the populations of C. gariepinus and the Pre-anal distance and dorsal fin ray count could be employed in the identification of populations of catfish.
Key words: morphometric traits, meristic characters, populations, allometric
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Kurtural, S. Kaan, Imed E. Dami, and Bradley H. Taylor. "Effects of Pruning and Cluster Thinning on Yield and Fruit Composition of `Chambourcin' Grapevines." HortTechnology 16, no. 2 (January 2006): 233–40. http://dx.doi.org/10.21273/horttech.16.2.0233.
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Response of yield components and fruit composition of `Chambourcin' (Vitis vinifera × V. rupestris) grapevines to three pruning levels of 15, 20, and 25 nodes retained for each pound of dormant prunings; and three cluster thinning levels of 1, 2, and 2+ clusters per shoot in 2002 and 1, 1.2, and 1.5 clusters per shoot in 2003 were measured at two vineyards in the lower midwestern United States. In both years of the study, there was very little interaction of pruning and cluster thinning. The proportion of non-count shoots increased within the canopy in response to increased pruning severity. Pruning weight means were lower in 2002 across all treatments compared to 2003. Pruning weights decreased with the increase in the number of clusters retained per vine. Pruning influenced yield only in 2003 when the proportion of count shoots decreased below 62% of the total, hence the relationship between number of shoots per vine and yield (R2 = 0.3452; P < 0.0003). In both years of the study, the increase in severity of cluster thinning resulted in yield reduction but an increase in the total soluble solids in juice. Yield compensation was achieved by an increase in cluster weight of 38%, and 25% in response to a reduction of 37%, and 23% in cluster numbers; which translated into a yield reduction of only 10% and 3%, at Vineyards 1 and 2, respectively. Balanced pruning to 15 to 20 nodes per 1 lb of prunings and cluster thinning to 1 to 1.2 clusters/shoot optimized yield (9.7 kg/vine, 13.4 t·ha-1) and fruit composition, and maintained vine size (≥0.3 kg·m-1 of row). These results provide valuable information for growers of `Chambourcin' grapevines in the lower midwestern U.S., as well as in other climates with long growing seasons.
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Koulouridis, E., N. Clerc, T. Sadibekova, M. Chira, E. Drigga, L. Faccioli, J. P. Le Fèvre, et al. "The X-CLASS survey: A catalogue of 1646 X-ray-selected galaxy clusters up to z ∼ 1.5." Astronomy & Astrophysics 652 (August 2021): A12. http://dx.doi.org/10.1051/0004-6361/202140566.
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Context. Cosmological probes based on galaxy clusters rely on cluster number counts and large-scale structure information. X-ray cluster surveys are well suited for this purpose because they are far less affected by projection effects than optical surveys, and cluster properties can be predicted with good accuracy. Aims. The XMM Cluster Archive Super Survey, X-CLASS, is a serendipitous search of X-ray-detected galaxy clusters in 4176 XMM-Newton archival observations until August 2015. All observations are clipped to exposure times of 10 and 20 ks to obtain uniformity, and they span ∼269 deg2 across the high-Galactic latitude sky (|b| > 20°). The main goal of the survey is the compilation of a well-selected cluster sample suitable for cosmological analyses. Methods. We describe the detection algorithm, the visual inspection, the verification process, and the redshift validation of the cluster sample, as well as the cluster selection function computed by simulations. We also present the various metadata that are released with the catalogue, along with two different count-rate measurements, an automatic one provided by the pipeline, and a more detailed and accurate interactive measurement. Furthermore, we provide the redshifts of 124 clusters obtained with a dedicated multi-object spectroscopic follow-up programme. Results. With this publication, we release the new X-CLASS catalogue of 1646 well-selected X-ray-detected clusters over a wide sky area, along with their selection function. The sample spans a wide redshift range, from the local Universe up to z ∼ 1.5, with 982 spectroscopically confirmed clusters, and over 70 clusters above z = 0.8. The redshift distribution peaks at z ∼ 0.1, while if we remove the pointed observations it peaks at z ∼ 0.3. Because of its homogeneous selection and thorough verification, the cluster sample can be used for cosmological analyses, but also as a test-bed for the upcoming eROSITA observations and other current and future large-area cluster surveys. It is the first time that such a catalogue is made available to the community via an interactive database which gives access to a wealth of supplementary information, images, and data.
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Venkateswarlu, K. Muni, A. Kandasamy, and K. Chandrasekaran. "An Energy-Efficient Hybrid Clustering Mechanism for Wireless Sensor Network." Unmanned Systems 03, no. 02 (April 2015): 109–25. http://dx.doi.org/10.1142/s2301385015500077.
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Valuable energy resources of sensor network should be utilized wisely to prolong network's lifetime. Clustering technique helps wireless sensor network (WSN) to enhance its lifetime by reducing energy consumption on every individual sensor node in the network. In multi-hop data forwarding model, difference in energy consumption among cluster heads (HS) causes hot-spot problem in the network. While data is being transferred, the CH close to base station are burdened with heavy relay traffic from several data routes and tend to die early. Unequal clustering avoids this hot-spot problem by establishing different sized clusters at various levels in the network. Since unequal clustering technique does not control number of CHs it creates, it forms huge number of clusters in the network. This increases hop count between source and destination, and leads to impose more over head on each data forwarding route in the network. Also, rapid variation in cluster size causes imbalance in energy dissipation among clustered nodes in the network. This uneven energy consumption influences network performance and lifetime. In this paper, we present an energy-efficient hybrid clustering mechanism for wireless sensor network using equal and unequal clustering techniques to create limited number of clusters in varied sizes at various level of the network. This avoids hot-spot problem with minimum hop count between the source and destination and achieves uniform energy dissipation between intra- and inter-cluster communication. Simulation results show that the proposed clustering mechanism balances the energy consumption among clusters with its hybrid cluster formation mechanism and elevates sensor network lifetime.
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Hao, Leijun, Greg J. Spivak, Jianliang Xiao, Jagadese J. Vittal, and Richard J. Puddephatt. "First Octahedral Platinum Cluster: Structure as a Function of Electron Count in Pt6 Clusters." Journal of the American Chemical Society 117, no. 26 (July 1995): 7011–12. http://dx.doi.org/10.1021/ja00131a028.
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Xie, Weiwei, Huixia Luo, Brendan F. Phelan, Tomasz Klimczuk, Francois Alexandre Cevallos, and Robert Joseph Cava. "Endohedral gallide cluster superconductors and superconductivity in ReGa5." Proceedings of the National Academy of Sciences 112, no. 51 (December 7, 2015): E7048—E7054. http://dx.doi.org/10.1073/pnas.1522191112.
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We present transition metal-embedded (T@Gan) endohedral Ga-clusters as a favorable structural motif for superconductivity and develop empirical, molecule-based, electron counting rules that govern the hierarchical architectures that the clusters assume in binary phases. Among the binary T@Gan endohedral cluster systems, Mo8Ga41, Mo6Ga31, Rh2Ga9, and Ir2Ga9 are all previously known superconductors. The well-known exotic superconductor PuCoGa5 and related phases are also members of this endohedral gallide cluster family. We show that electron-deficient compounds like Mo8Ga41 prefer architectures with vertex-sharing gallium clusters, whereas electron-rich compounds, like PdGa5, prefer edge-sharing cluster architectures. The superconducting transition temperatures are highest for the electron-poor, corner-sharing architectures. Based on this analysis, the previously unknown endohedral cluster compound ReGa5 is postulated to exist at an intermediate electron count and a mix of corner sharing and edge sharing cluster architectures. The empirical prediction is shown to be correct and leads to the discovery of superconductivity in ReGa5. The Fermi levels for endohedral gallide cluster compounds are located in deep pseudogaps in the electronic densities of states, an important factor in determining their chemical stability, while at the same time limiting their superconducting transition temperatures.
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Deng, Min, Gerald G. Mace, and Zhien Wang. "Anvil Productivities of Tropical Deep Convective Clusters and Their Regional Differences." Journal of the Atmospheric Sciences 73, no. 9 (September 2016): 3467–87. http://dx.doi.org/10.1175/jas-d-15-0239.1.
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The anvil productivities of tropical deep convection are investigated and compared among eight climatological regions using 4 yr of collocated and combined CloudSat and CALIPSO data. For all regions, the convective clusters become deeper while they become wider and tend to be composed of multiple rainy cores. Two strong detrainment layers from deep convection are observed at 6–8 km and above 10 km, which is consistent with the trimodal characteristics of tropical convection that are associated with different divergence, cloud detrainment, and fractional cloudiness. The anvil productivity of tropical deep convection depends on the convection scale, convective life stage or intensity, and large-scale environment. Anvil ice mass ratio related to the whole cluster starts to level off or decrease when the cluster effective scales Weff (the dimension of an equivalent rectangular with the same volume and height as the original cluster) increase to about 200 km wide, while the ratios of anvil scale and volume keep increasing from 0.4 to 0.6 and 0.15 to 0.4, respectively. The anvil clouds above 12 km can count for more than 20% of cluster volume, or more than 50% of total anvil volume, but they only count less than about 2% of total ice mass in the cluster. Anvil production of younger convection of the same Weff is higher than that of the decaying convection. The regional difference in the composite anvil productivities of tropical convective clusters sorted by Weff is subtle, while the occurrence frequencies of different scales of convection vary substantially.
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Wang, Jijia, Song Zhang, and Chul Ahn. "Sample size calculation for count outcomes in cluster randomization trials with varying cluster sizes." Communications in Statistics - Theory and Methods 49, no. 1 (December 21, 2018): 116–24. http://dx.doi.org/10.1080/03610926.2018.1532004.
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Jeff, Janina M., Kristin Brown-Gentry, and Dana C. Crawford. "Replication and characterisation of genetic variants in the fibrinogen gene cluster with plasma fibrinogen levels and haematological traits in the Third National Health and Nutrition Examination Survey." Thrombosis and Haemostasis 107, no. 03 (2012): 458–67. http://dx.doi.org/10.1160/th11-07-0497.
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SummaryPrevious genetic association studies of the fibrinogen gene cluster have identified associations with plasma fibrinogen levels. These studies are typically limited to plasma fibrinogen measured among European-descent populations. We sought to replicate previous well-known associations with fibrinogen variants and plasma fibrinogen. We then sought to identify and characterise novel associations with fibrinogen variants with plasma fibrinogen and several haematological traits in three racial/ethnic populations. We genotyped 25 single nucleotide polymorphisms (SNPs) in the fibrinogen gene cluster in 2,631 non-Hispanic whites, 2,108 non-Hispanic blacks, and 2,073 Mexican-Americans from the Third National Health and Nutrition Examination Survey (NHANES). We performed single SNP tests of association for plasma fibrinogen, mean platelet volume, platelet distribution width, platelet count, white blood cell count, and serum triglycerides. Five previously identified associations with plasma fibrinogen replicated in our study in non-Hispanic whites and blacks. We identified two novel associations between genetic variants and decreased plasma fibrinogen: rs2227395 (p=0.0007; non-Hispanic whites) and rs2070022 (p=0.001; Mexican-Americans). Several fibrinogen SNPs were also associated with haema-tological traits: rs6050 with decreased platelet distribution width in non-Hispanic whites; rs6050 and rs2066879 with decreased and increased platelet distribution width, respectively, in non-Hispanic whites; rs2227409 with increased mean platelet volume, rs2070017 with decreased platelet count, and rs6063 with increased platelet distribution width in non-Hispanic blacks; and rs4220 and rs2227395 with decreased white blood cell count, rs2227409 with increased platelet distribution width, rs2066860 and rs1800792 with increased and decreased triclyceride levels, respectively, and rs1800792 with decreased platelet counts in Mexican-Americans. We successfully replicated and identified novel associations with fibrinogen variants and plasma fibrinogen. These data confirm the importance of the fibrinogen gene cluster for plasma fibrinogen levels as well as suggest this gene cluster may have pleiotropic effects on haematological traits.
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Nomura, Masaki, Yoshio Sakurai, and Toshio Aoyagi. "Analysis of Multineuron Activity Using the Kernel Method." Journal of Robotics and Mechatronics 19, no. 4 (August 20, 2007): 364–68. http://dx.doi.org/10.20965/jrm.2007.p0364.
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We recorded multineuron spike time-series data from rat hippocampus region CA1 during a conditional discrimination task. We separated out individual single-neuron activity from multineuron activity data and prepared spike count data and calculated a kernel matrix using a Spikernel function, then applied k-means clustering and principal component analysis (PCA). Comparing spike count data to an appropriate time, we divided data into clusters and found the correspondence between the obtained cluster and rat activity. We discuss information expression in nervous-system activity expected from the kernel function.
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Agárdi, Anita, and László Kovács. "Clustering algorithms with prediction the optimal number of clusters." Journal of Applied Research and Technology 20, no. 6 (December 23, 2022): 638–51. http://dx.doi.org/10.22201/icat.24486736e.2022.20.6.1077.
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The clustering is a widely used technique for grouping of objects. The objects, which are similar to each other should be in the same cluster. One disadvantage of general clustering algorithms is that the user must specify the number of clusters in advance, as input parameter. This is a major drawback since it is possible that the user cannot specify the number of clusters correctly, and the algorithm thus creates a clustering that puts very different elements into the same cluster. The aim of this paper is to present our representation and evaluation technique to determine the optimal cluster count automatically. With this technique, the algorithms itself determine the number of clusters. In this paper first, the classical clustering algorithms are introduced, then the construction and improvement algorithms and then our representation and evaluation method are presented. Then the performance of the algorithms with test results are compared.
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Gwon, Hyeok-Jun, Sun-Boong Hwang, Sangrok Kim, and Kum-Bae Kim. "Evaluation of Parallel Computing on MPI Version PHITS Code." Applied Sciences 13, no. 6 (March 16, 2023): 3782. http://dx.doi.org/10.3390/app13063782.
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The Message Passing Interface (MPI) technique is an old solution and an improvement on the Monte Carlo N-Particle Transport (MCNP) method’s enormous computational time, which has not been evaluated based on PHITS code—a recently developed Monte Carlo simulation code. We conducted simulations on Varian Clinac iX 6MV phase space data from the IAEA. Venselaar et al.’s method and criteria were used to validate the Monte Carlo simulation. The PC cluster has also been tested in terms of processor count and bch, which stands for unit calculation count per operation. The MPI version PHITS code’s speedup factor and the K-factor, which represent the serial portion of the cluster, were both evaluated. All calculated data met the criteria except δ2, high dose, and high gradient of the beam profile data set. It was very clear that PC clusters with MPI were better than simple nodes up to 70.6%. Additionally, the speedup factor shows a tendency to follow Amdahl’s law. At the same time, the K-factor was saturated by a certain measure. The study concludes by arguing that the cluster has limitations that come from its serial composition. If we consider how improvements in specifications affect simulation time, this cluster system could be more effective.
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Montes-Mojarro, Ivonne A., Saki Hassas, Sina Staehle, Philip Sander, Niklas Harland, Lina Maria Serna-Higuita, Irina Bonzheim, Hans Bösmüller, Arnulf Stenzl, and Falko Fend. "Multiparametric Classification of Non-Muscle Invasive Papillary Urothelial Neoplasms: Combining Morphological, Phenotypical, and Molecular Features for Improved Risk Stratification." International Journal of Molecular Sciences 23, no. 15 (July 23, 2022): 8133. http://dx.doi.org/10.3390/ijms23158133.
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Diagnosis and grading of non-invasive papillary urothelial tumors according to the current WHO classification poses some challenges for pathologists. The diagnostic reproducibility of separating low-grade and high-grade lesions is low, which impacts their clinical management. Whereas papillary urothelial neoplasms with low malignant potential (PUN-LMP) and low-grade papillary non-invasive carcinoma (LG-PUC) are comparable and show frequent local recurrence but rarely metastasize, high-grade papillary non-invasive carcinoma (HG-PUC) has a poor prognosis. The main objective of this work is to develop a multiparametric classification to unambiguously distinguish low-grade and high-grade tumors, considering immunohistochemical stains for p53, FGFR3, CK20, MIB-1, p16, p21 and p-HH3, and pathogenic mutations in TP53, FGFR3, TP53, ERCC2, PIK3CA, PTEN and STAG2. We reviewed and analyzed the clinical and histological data of 45 patients with a consensus diagnosis of PUN-LMP (n = 8), non-invasive LG-PUC (n = 23), and HG-PUC (n = 14). The proliferation index and mitotic count assessed with MIB-1 and P-HH3 staining, respectively correlated with grading and clinical behavior. Targeted sequencing confirmed frequent FGFR3 mutations in non-invasive papillary tumors and identified mutations in TP53 as high-risk. Cluster analysis of the different immunohistochemical and molecular parameters allowed a clear separation in two different clusters: cluster 1 corresponding to PUN-LMP and LG-PUC (low MIB-1 and mitotic count/FGFR3 and STAG2 mutations) and cluster 2, HG-PUC (high MIB-1 and mitosis count/CK20 +++ expression, FGFR3 WT and TP53 mutation). Further analysis is required to validate and analyze the reproducibility of these clusters and their biological and clinical implication.
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Palmer, Richard. "Atomic Structure and Mass-Production of Supported Size-Selected Nanoclusters." Acta Crystallographica Section A Foundations and Advances 70, a1 (August 5, 2014): C733. http://dx.doi.org/10.1107/s2053273314092663.
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Deposition of size-selected nanoclusters assembled from atoms in the gas phase is a novel route to the fabrication of <10nm surface features. I will focus on the creation and atomic structure of monodispersed metal cluster arrays which enable new model catalysts and protein biochips. The atomic structure of the clusters – previously the province of theory - is revealed experimentally [1] by aberration-corrected scanning transmission electron microscopy (STEM) in the HAADF imaging regime; we can "count" atoms and obtain 3D information not just 2D projections. Results include mass spectrometry of thiolated Au clusters, adatom dynamics on Au923 magic-number nanoclusters [2], first atomic imaging results for Au55 and Au20 and a method to explore the potential energy landscape of (Au923) clusters via cluster transformations [3], presenting a reference system for theory. A new kind of cluster beam source, to allow super-abundant generation of size-selected nanoclusters, will also be demonstrated.
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Przysucha, Natalia, Katarzyna Górska, Marta Maskey-Warzęchowska, Małgorzata Proboszcz, Patrycja Nejman-Gryz, Magdalena Paplińska-Goryca, Barbara Dymek, Agnieszka Zagozdzon, and Rafał Krenke. "The Role of Chitinases in Chronic Airway Inflammation Associated with Tobacco Smoke Exposure." Cells 11, no. 23 (November 25, 2022): 3765. http://dx.doi.org/10.3390/cells11233765.
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Chitinases and chitinase-like proteins are thought to play a role in innate inflammatory responses. Our study aimed to assess whether chitinase concentration and activity in induced sputum (IS) of patients exposed to tobacco smoke are related to the level of airway inflammation including the level and activity of chitinases and chitinase-like proteins. The study included 22 patients with chronic obstructive pulmonary disease (COPD), 12 non-COPD smokers, and nine nonsmoking subjects. Sputum CHIT1 and YKL-40 levels and chitinolytic activity were compared with sputum IL-6, IL-8, IL-18, and MMP-9 levels. A hierarchical cluster analysis was also performed. Sputum YKL-40 was higher in COPD patients than in the control groups. Sputum CHIT1 and YKL-40 levels correlated with IS inflammatory cell count as well as with MMP-9 and IL-8 levels. Two main clusters were revealed: Cluster 1 had lower chitinase levels and activity, lower IS macrophage and neutrophil count, and lower IS IL-8, IL-18, and MMP-9 than Cluster 2. Comparison of COPD patients from both clusters revealed significant differences in the IS inflammatory profile despite comparable clinical and functional data. Our findings seem to confirm the involvement of chitinases in smoking-associated chronic airway inflammation and show that airway chitinases may be a potential novel marker in COPD phenotyping.
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Jiménez Muñoz, A., J. F. Macías-Pérez, W. Cui, M. De Petris, A. Ferragamo, and G. Yepes. "The Three Hundred project: Contrasting clusters galaxy density in hydrodynamical and dark matter only simulations." EPJ Web of Conferences 257 (2022): 00022. http://dx.doi.org/10.1051/epjconf/202225700022.
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Cluster number count is a major cosmological probe for the next generation of cosmological large scale-structure surveys like the one expected from the Euclid satellite mission. Cosmological constraints will be mainly limited by the understanding of the selection function (SF), which characterize the probability of detecting a cluster of a given mass and redshift. The SF can be estimated by injecting realistic simulated clusters into the survey and re-applying the detection procedure. For this purpose we intend to use The Three Hundreds project, a 324 cluster sample simulated with full-physics hydrodynamical re-simulations. In this paper we concentrate on the study of the distribution of member galaxies in the cluster sample. First, we study possible resolution effects by comparing low and high resolution simulations. Finally, accounting for the latter we derive the density profiles of the member galaxies and discuss their evolution with cluster mass and redshift.
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Song, Yuli, Chengxu Liu, and Sydney M. Finegold. "Real-Time PCR Quantitation of Clostridia in Feces of Autistic Children." Applied and Environmental Microbiology 70, no. 11 (November 2004): 6459–65. http://dx.doi.org/10.1128/aem.70.11.6459-6465.2004.
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ABSTRACT Based on the hypothesis that intestinal clostridia play a role in late-onset autism, we have been characterizing clostridia from stools of autistic and control children. We applied the TaqMan real-time PCR procedure to detect and quantitate three Clostridium clusters and one Clostridium species, C. bolteae, in stool specimens. Group- and species-specific primers targeting the 16S rRNA genes were designed, and specificity of the primers was confirmed with DNA from related bacterial strains. In this procedure, a linear relationship exists between the threshold cycle (CT ) fluorescence value and the number of bacterial cells (CFU). The assay showed high sensitivity: as few as 2 cells of members of cluster I, 6 cells of cluster XI, 4 cells of cluster XIVab, and 0.6 cell of C. bolteae could be detected per PCR. Analysis of the real-time PCR data indicated that the cell count differences between autistic and control children for C. bolteae and the following Clostridium groups were statistically significant: mean counts of C. bolteae and clusters I and XI in autistic children were 46-fold (P = 0.01), 9.0-fold (P = 0.014), and 3.5-fold (P = 0.004) greater than those in control children, respectively, but not for cluster XIVab (2.6 � 108 CFU/g in autistic children and 4.8 � 108 CFU/g in controls; respectively). More subjects need to be studied. The assay is a rapid and reliable method, and it should have great potential for quantitation of other bacteria in the intestinal tract.
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Dr. Mukesh Kalla, Asha Rawat,. "Clustering Algorithm for Energy- Efficient Wireless Sensor Network." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 5 (April 11, 2021): 877–84. http://dx.doi.org/10.17762/turcomat.v12i5.1500.
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Wireless networks data aggregation allows in-network processing, reduces packet transmission and data redundancy, and thus helps extend wireless sensor systems to the full duration of their lives. There have been many ways of dividing the network into clusters, collecting information from nodes and adding it to the base station, to extend wireless sensor network life. Certain cluster algorithms consider the residual energy of the nodes when selecting clusterheads and others regularly rotate the selection head of the cluster. However, we seldom investigate the network density or local distance. In this report we present an energy-efficient clustering algorithm that selects the best cluster heads of the system after dividing the network into clusters. The cluster head selection depends on the distance between the base station nodes and the remaining power of this approach.Each node's residual energy is compared to the node count. Our results show that the solution proposed more efficiently extends the life of the wireless sensor network. The algorithm prolongs the life and effectiveness of the Wireless Sensor Network.
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Michael-Tsabari, Nava, Rania Labaki, and Ramona Kay Zachary. "Toward the Cluster Model." Family Business Review 27, no. 2 (March 11, 2014): 161–85. http://dx.doi.org/10.1177/0894486514525803.
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Building on a longitudinal case study, this article describes the entrepreneurial behavior of a multinational family firm over generations. The study inductively raises the theoretic level to fill gaps in the literature about the family role in entrepreneurial behavior and addresses the singular count of the two- and three-circle models. The data analysis shows that entrepreneurial behavior emerges not only in response to business challenges but also and predominantly to family challenges. The cluster model is suggested as a necessary extension of the circle models, positing the family as the relevant level of analysis when considering entrepreneurial behavior and introducing the distinction between organic and portfolio, core and peripheral firms.
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Roukema, Boudewijn F. "Anti-clustering in the national SARS-CoV-2 daily infection counts." PeerJ 9 (August 27, 2021): e11856. http://dx.doi.org/10.7717/peerj.11856.
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The noise in daily infection counts of an epidemic should be super-Poissonian due to intrinsic epidemiological and administrative clustering. Here, we use this clustering to classify the official national SARS-CoV-2 daily infection counts and check for infection counts that are unusually anti-clustered. We adopt a one-parameter model of $\phi _i^{\prime}$ infections per cluster, dividing any daily count ni into $n_i/ _i^{\prime}$ ‘clusters’, for ‘country’ i. We assume that ${n_i}/\phi _i^{\prime}$ on a given day j is drawn from a Poisson distribution whose mean is robustly estimated from the four neighbouring days, and calculate the inferred Poisson probability $P_{ij}^{\prime}$ of the observation. The $P_{ij}^{\prime}$ values should be uniformly distributed. We find the value $\phi_i$ that minimises the Kolmogorov–Smirnov distance from a uniform distribution. We investigate the (ϕi, Ni) distribution, for total infection count Ni. We consider consecutive count sequences above a threshold of 50 daily infections. We find that most of the daily infection count sequences are inconsistent with a Poissonian model. Most are found to be consistent with the ϕi model. The 28-, 14- and 7-day least noisy sequences for several countries are best modelled as sub-Poissonian, suggesting a distinct epidemiological family. The 28-day least noisy sequence of Algeria has a preferred model that is strongly sub-Poissonian, with $\phi _i^{28} < 0.1$. Tajikistan, Turkey, Russia, Belarus, Albania, United Arab Emirates and Nicaragua have preferred models that are also sub-Poissonian, with $\phi _i^{28} < 0.5$. A statistically significant (Pτ < 0.05) correlation was found between the lack of media freedom in a country, as represented by a high Reporters sans frontieres Press Freedom Index (PFI2020), and the lack of statistical noise in the country’s daily counts. The ϕi model appears to be an effective detector of suspiciously low statistical noise in the national SARS-CoV-2 daily infection counts.
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Hayashi, Keigo, Keiji Ohashi, Haruki Watanabe, Ken-Ei Sada, Kenta Shidahara, Yosuke Asano, Sumie Hiramatsu Asano, et al. "Thrombocytosis as a prognostic factor in polymyalgia rheumatica: characteristics determined from cluster analysis." Therapeutic Advances in Musculoskeletal Disease 11 (January 2019): 1759720X1986482. http://dx.doi.org/10.1177/1759720x19864822.
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Background: This study aimed to identify the clinical subgroups of polymyalgia rheumatica (PMR) using cluster analysis and compare the outcomes among the identified subgroups. Methods: We enrolled patients with PMR who were diagnosed at Okayama University Hospital, Japan between 2006 and 2017, met the 2012 European League Against Rheumatism/American College of Rheumatology provisional classification criteria for PMR, and were treated with glucocorticoids. Hierarchical cluster analysis using variables selected by principal component analysis was performed to identify the clusters. Subsequently, the outcomes among the identified clusters were compared in the study. The primary outcome was treatment response at 1 month after commencement of treatment. The secondary outcome was refractory clinical course, which was defined as the requirement of additional treatments or relapse during a 2-year observational period. Results: A total of 61 consecutive patients with PMR were enrolled in the study. Their mean age was 71 years, and 67% were female. Hierarchical cluster analysis revealed three distinct subgroups: cluster 1 ( n = 14) was characterized by patients with thrombocytosis (all patients showed a platelet count of >45 × 10⁴/µl), cluster 2 ( n = 38), by patients without peripheral arthritis, and cluster 3 ( n = 9), by patients with peripheral arthritis. The patients in cluster 1 achieved treatment response less frequently than those in cluster 2 (14% versus 47%, p = 0.030). Refractory cases were more frequent in cluster 1 than in cluster 2; however, no significant difference was noted (71% versus 42%, p = 0.06). Conclusions: Thrombocytosis could predict the clinical course in patients with PMR.
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Youroukova, Vania M., Denitsa G. Dimitrova, Anna D. Valerieva, Spaska S. Lesichkova, Tsvetelina V. Velikova, Ekaterina I. Ivanova-Todorova, and Kalina D. Tumangelova-Yuzeir. "Phenotypes Determined by Cluster Analysis in Moderate to Severe Bronchial Asthma." Folia Medica 59, no. 2 (June 1, 2017): 165–73. http://dx.doi.org/10.1515/folmed-2017-0031.
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AbstractBackground:Bronchial asthma is a heterogeneous disease that includes various subtypes. They may share similar clinical characteristics, but probably have different pathological mechanisms.Aim:To identify phenotypes using cluster analysis in moderate to severe bronchial asthma and to compare differences in clinical, physiological, immunological and inflammatory data between the clusters.Patients and methods:Forty adult patients with moderate to severe bronchial asthma out of exacerbation were included. All underwent clinical assessment, anthropometric measurements, skin prick testing, standard spirometry and measurement fraction of exhaled nitric oxide. Blood eosinophilic count, serum total IgE and periostin levels were determined. Two-step cluster approach, hierarchical clustering method and k-mean analysis were used for identification of the clusters.Results:We have identified four clusters. Cluster 1 (n=14) - late-onset, non-atopic asthma with impaired lung function, Cluster 2 (n=13) - late-onset, atopic asthma, Cluster 3 (n=6) - late-onset, aspirin sensitivity, eosinophilic asthma, and Cluster 4 (n=7) - early-onset, atopic asthma.Conclusions:Our study is the first in Bulgaria in which cluster analysis is applied to asthmatic patients. We identified four clusters. The variables with greatest force for differentiation in our study were: age of asthma onset, duration of diseases, atopy, smoking, blood eosinophils, nonsteroidal anti-inflammatory drugs hypersensitivity, baseline FEV1/FVC and symptoms severity. Our results support the concept of heterogeneity of bronchial asthma and demonstrate that cluster analysis can be an useful tool for phenotyping of disease and personalized approach to the treatment of patients.
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Sun, Yeran, Yu Wang, Ke Yuan, Ting On Chan, and Ying Huang. "Discovering Spatio-Temporal Clusters of Road Collisions Using the Method of Fast Bayesian Model-Based Cluster Detection." Sustainability 12, no. 20 (October 20, 2020): 8681. http://dx.doi.org/10.3390/su12208681.
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Public availability of geo-coded or geo-referenced road collisions (crashes) makes it possible to perform geovisualisation and spatio-temporal analysis of road collisions across a city. This study aims to detect spatio-temporal clusters of road collisions across Greater London between 2010 and 2014. We implemented a fast Bayesian model-based cluster detection method with no covariates and after adjusting for potential covariates respectively. As empirical evidence on the association of street connectivity measures and the occurrence of road collisions had been found, we selected street connectivity measures as the potential covariates in our cluster detection. Results of the most significant cluster and the second most significant cluster during five consecutive years are located around the central areas. Moreover, after adjusting the covariates, the most significant cluster moves from the central areas of London to its peripheral areas, while the second most significant cluster remains unchanged. Additionally, one potential covariate used in this study, length-based road density, exhibits a positive association with the number of road collisions; meanwhile count-based intersection density displays a negative association. Although the covariates (i.e., road density and intersection density) exhibit potential impact on the clusters of road collisions, they are unlikely to contribute to the majority of clusters. Furthermore, the method of fast Bayesian model-based cluster detection is developed to discover spatio-temporal clusters of serious injury collisions. Most of the areas at risk of serious injury collisions overlay those at risk of road collisions. Although not being identified as areas at risk of road collisions, some districts, e.g., City of London, are regarded as areas at risk of serious injury collisions.
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King, R. B., and I. Silaghi-Dumitrescu. "Density Functional Theory Study of Nine-Atom Germanium Clusters: Effect of Electron Count on Cluster Geometry." Inorganic Chemistry 42, no. 21 (October 2003): 6701–8. http://dx.doi.org/10.1021/ic030107y.
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King, R. B., I. Silaghi-Dumitrescu, and M. M. Uţǎ. "Density Functional Theory Study of 10-Atom Germanium Clusters: Effect of Electron Count on Cluster Geometry." Inorganic Chemistry 45, no. 13 (June 2006): 4974–81. http://dx.doi.org/10.1021/ic051905m.
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King, R. B., I. Silaghi-Dumitrescu, and A. Lupan. "Density Functional Theory Study of 11-Atom Germanium Clusters: Effect of Electron Count on Cluster Geometry." Inorganic Chemistry 44, no. 10 (May 2005): 3579–88. http://dx.doi.org/10.1021/ic040110x.
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King, R. B., I. Silaghi-Dumitrescu, and A. Lupan. "Density functional theory study of eight-atom germanium clusters: effect of electron count on cluster geometry." Dalton Transactions, no. 10 (2005): 1858. http://dx.doi.org/10.1039/b501855b.
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C, Hema, Sharmila Sankar, and Sandhya M. "Tag count based priority scheduling algorithm for mitigating the RFID collisions." Indonesian Journal of Electrical Engineering and Computer Science 18, no. 1 (April 1, 2020): 434. http://dx.doi.org/10.11591/ijeecs.v18.i1.pp434-442.
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<p><span>RFID (Radio Frequency IDentification) is a developing technology that employs electromagnetic signals to send the data among reader and tags to identify categorize and track the moveable items. The objective of this paper is to mitigate the reader collision problem by scheduling the readers in RFID system. Mobile readers in the RFID network send the same frequency signal to the air to read the data from the tags. While these two signals interfere each other and Tags are unable to backscatter signal to the reader. This causes a reader collision problem. The Reader collision problem reduces the lifetime of the RFID network and generates redundant data in the RFID Network. Tag Count based Priority Scheduling algorithm is proposed, that enhances the throughput of the readers and mitigates the reader collision problem. In the cluster based RFID network, The Dragonfly algorithm performed the Cluster Head reader election and cluster construction process and then allotting the mobile readers in the cluster. This algorithm improves the energy efficiency and diminishes the reader collision problem, thereby alleviating the tag information loss and expanding the mobile RFID network life time, while compared with Priority Clustering Protocol and the Graph Coloring based TDMA algorithm.</span></p>
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Collerton, Joanna, Carol Jagger, Mohammad E. Yadegarfar, Karen Davies, Stuart G. Parker, Louise Robinson, and Thomas B. L. Kirkwood. "Deconstructing Complex Multimorbidity in the Very Old: Findings from the Newcastle 85+ Study." BioMed Research International 2016 (2016): 1–15. http://dx.doi.org/10.1155/2016/8745670.
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Objectives. To examine the extent and complexity of the morbidity burden in 85-year-olds; identify patterns within multimorbidity; and explore associations with medication and healthcare use.Participants. 710 men and women; mean (SD) age 85.5 (0.4) years.Methods. Data on 20 chronic conditions (diseases and geriatric conditions) ascertained from general practice records and participant assessment. Cluster analysis within the multimorbid sample identified subgroups sharing morbidity profiles. Clusters were compared on medication and healthcare use.Results. 92.7% (658/710) of participants had multimorbidity; median number of conditions: 4 (IQR 3–6). Cluster analysis (multimorbid sample) identified five subgroups sharing similar morbidity profiles; 60.0% (395/658) of participants belonged to one of two high morbidity clusters, with only 4.9% (32/658) in the healthiest cluster. Healthcare use was high, with polypharmacy (≥5 medications) in 69.8% (459/658). Between-cluster differences were found in medication count (p=0.0001); hospital admissions (p=0.022); and general practitioner (p=0.034) and practice nurse consultations (p=0.011). Morbidity load was related to medication burden and use of some, but not all, healthcare services.Conclusions. The majority of 85-year-olds had extensive and complex morbidity. Elaborating participant clusters sharing similar morbidity profiles will help inform future healthcare provision and the identification of common underlying biological mechanisms.
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Gokuldev, S., and Jathin R. "Range smart cluster monitor based guesstimate approach for resource scheduling in small size clusters." International Journal of Engineering & Technology 7, no. 2 (June 1, 2018): 837. http://dx.doi.org/10.14419/ijet.v7i2.9531.
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Performing scheduling of tasks with low energy consumption with high performance is one of the major concerns in distributed computing. Most of the existing systems have achieved improved energy efficiency but compromised with QoS metrics such as makespan and resource utilization. A resource scheduling strategy for wireless clusters is proposed by making careful considerations on decisions that would im-prove the battery life of nodes. The proposed strategy also incorporates monitoring system with in the clusters for optimizing the system performance as well as energy consumption. The system ensures “Any case zero loss" performance wherein each cluster will be monitored by at least one cluster monitor. This is implemented by using predictive calculation at each cluster monitor to communicate only if absolutely essential, during assigning jobs to resources, selecting optimal resources by assigning the jobs to the most power efficient resource among the available idle resources within the cluster. The experimental result ensures improved system performance with low power consumption in homogeneous computing environment. The resource sharing strategy is experimentally analyzed, considering the important performance metrics such as starvation deadline, turnaround time, miss hit count through simulations. Significant results were observed with improved efficiency.
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Barroso, Isaac, João Tiago Guimarães, Milton Severo, Vanda Craveiro, and Elisabete Ramos. "Immunological Trajectories of White Blood Cells from Adolescence to Adulthood: Description and Determinants." Diagnostics 11, no. 11 (November 8, 2021): 2063. http://dx.doi.org/10.3390/diagnostics11112063.
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Background: The immune system gradually matures early in life in the face of internal and external stimuli. Whether the immune responses are lasting and stable during the course of life is still unclear. Methods: As part of the EPITeen cohort, 1183 adolescents were prospectively evaluated at the ages of 13, 17, 21, 24 and 27. Sociodemographic, behavioral and clinical data were collected by self- and face-to-face-administered questionnaires, along with a physical examination comprising anthropometric measurements and blood sample collections. Mixed-effects models were used to identify individual trajectories of white blood cells (WBC) and finite Gaussian mixture models were used to identify the clusters of individual trajectories. Results: Participants were allocated into six clusters based on the individual trajectories of WBC distribution. Higher Inflammatory Activation Cluster (11.4%) had the highest total WBC count and neutrophils percentage, as well as the lowest percentage of lymphocytes. These participants had significantly higher odds of being overweight [OR = 2.44, 95%CI:1.51–3.92]. Lowest Levels of WBC Cluster (24.1%) had the lowest total WBC count, being characterized by a higher participation on sports [OR = 1.54, 95%CI:1.12–2.13]. Highest Proportion of Eosinophils Cluster (20.1%) had the highest eosinophils percentage and the highest likelihood of having been diagnosed with a chronic disease [OR = 2.11, 95%CI:1.43–3.13], namely “asthma or allergies” [OR = 14.0 (1.73, 112.2]. Lowest Proportion of Eosinophils Cluster (29.1%) had the lowest percentage of eosinophils and basophils, as well as the highest lymphocyte proportion. Participants in the Undefined Cluster (13.8%) showed the highest percentage of monocytes and basophils and were also characterized by significant lower odds of having parents with 7–9 years of schooling [OR = 0.56, (0.32, 0.99]. Conclusions: In this study we identified distinct immunological trajectories of WBC from adolescence to adulthood that were associated with social, clinical and behavioral determinants. These results suggest that these immunological trajectories are defined early in life, being dependent on the exposures.
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Amazouz, Hélène, Nicolas Bougas, Michel Thibaudon, Guillaume Lezmi, Nicole Beydon, Mélisande Bourgoin-Heck, Jocelyne Just, Isabelle Momas, and Fanny Rancière. "Association between lung function of school age children and short-term exposure to air pollution and pollen: the PARIS cohort." Thorax 76, no. 9 (February 16, 2021): 887–94. http://dx.doi.org/10.1136/thoraxjnl-2020-215515.
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BackgroundDaily levels of ambient air pollution and pollen may affect lung function but have rarely been studied together. We investigated short-term exposure to pollen and air pollution in relation to lung function in school-age children from a French population-based birth cohort.MethodsThis study included 1063 children from the PARIS (Pollution and Asthma Risk: an Infant Study) cohort whose lung function and FeNO measurements were performed at age 8 years old. Exposure data were collected up to 4 days before testing. We estimated daily total pollen concentration, daily allergenic risk indices for nine pollen taxa, as well as daily concentrations of three air pollutants (particulate matter less than 10 µm (PM10), nitrogen dioxide (NO2), ozone (O3)). Children with similar pollen and air pollution exposure were grouped using multidimensional longitudinal cluster analysis. Associations between clusters of pollen and air pollution exposure and respiratory indices (FEV1, FVC, FeNO) were studied using multivariable linear and logistic regression models adjusted for potential confounders.ResultsFour clusters of exposure were identified: no pollen and low air pollution (Cluster 1), grass pollen (Cluster 2), PM10 (Cluster 3) and birch/plane-tree pollen with high total pollen count (Cluster 4). Compared with children in Cluster 1, children in Cluster 2 had significantly lower FEV1 and FVC levels, and children from Cluster 3 had higher FeNO levels. For FEV1 and FVC, the associations appeared stronger in children with current asthma. Additional analysis suggested a joint effect of grass pollen and air pollution on lung function.ConclusionDaily ambient chemical and biological air quality could adversely influence lung function in children.
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Tofan, Luiza, Monica Piqueras, Óscar Fuster, and Begoña Laíz. "Monocytopenia in hairy cell leukemia, a difficult feature to detect using sysmex XN series hematology analyzer." International Journal of Family & Community Medicine 6, no. 3 (May 17, 2022): 94–97. http://dx.doi.org/10.15406/ijfcm.2022.06.00271.
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Hairy cell leukemia (HCL) is a relatively rare chronic B-cell malignancy that involves the bone marrow, spleen and peripheral blood. Monocytopenia could represent a clue for the suspicion of HCL with complete blood counts (CBCs) and careful assessment of the cell morphology being the first steps in the identification of hairy cells. The purpose of our study is to describe our experience with cell count and flag performance provided by the XN-module in a continuous series of six HCL patients diagnosed in the last two years. The final diagnosis was made by immunophenotypic and genetic analysis. Five out of six patients presented relative monocytosis on automated differential count. Nevertheless, the relative monocyte count was overestimated by the analyzer regarding to the manual count in all cases. The smear revision showed that most cells classified as monocytes were primarily hairy cells which afterwards were confirmed by the immunophenotype. All patients showed potentially pathologic WDF scatergrams or flags and were selected for microscopic smear review. In five of the six patients the WDF channel displayed the “Blasts/Abn Lympho?” flag and triggered the reflex reanalysis using the WPC channel. All samples presented lack or abnormal position of the monocytes cluster in the WPC scattergram. As a conclusion the monocytopenia should be taken with caution for the initial screening of hairy cell leukemia. Instead, an abnormal appearance of WDF scattergram and the lack or an ectopic position of the monocyte cluster in WPC scattergram should be considered to initiate the review of the peripheral blood smear.
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PETROV, DMYTRO, and ANDRYY BOICHUK. "CLUSTERIZATION METHOD BASED ON BREADTH FIRST SEARCH OR BFS FOR A GRAPH." Herald of Khmelnytskyi National University. Technical sciences 307, no. 2 (May 2, 2022): 87–91. http://dx.doi.org/10.31891/2307-5732-2022-307-2-87-91.
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Clusterization is one of the types of algorithms of unsupervised learning. The idea behind it is that an algorithm learns patterns from untagged data. Such type of algorithm helps to find unseen dependencies in the untagged data itself. This paper presented algorithms based on Breadth-First Search or BFS for a Graph. The method was built based on the basic theory of clusterization. To the theory of clusterization, the calculated distance between the two farthest points in the cluster should be less than the distance between the closest two points from different clusters. By this rule, we defined that two parameters of the method should be the maximum distance between points by which these can be connected and assumed to be in one cluster. The second had to be the maximum distance in the cluster, aka the cluster’s diameter. A cluster’s diameter is the farthest distance between two points within a cluster. With these hyperparameters and the defined distance method, we can assume that every point is a vertex of a graph, two points within the threshold of the distance between pairs of ones are neighbours, and count the connection between counts as an edge of a graph. The group of connected vertexes or a particular vertex is a graph. The diameter hyperparameter ought to keep the data homogeneity in a cluster. We can define every graph as a cluster with defined rules based on previous assumptions. Later in this paper will be visualized the clusterization of three-dimensional data points. We took one of the most popular clusterization dataset – the iris dataset for visualizing purposes. The paper contains several examples of clusterization of the dataset with different hyperparameters. We took KMeans [3] as an example of the clusterization method. The method based on BFS is a flexible clusterization method that relies on meta-information about distancing between data points.
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Wuan, Adrianus Ola, Ayorince Herlinalt Gloria Banunu, and Norma Tiku Kambuno. "Total Lymfosit Count (TLC) with CD4 in HIV/AIDS Patients at Kupang." Jurnal Teknologi Laboratorium 8, no. 2 (September 30, 2019): 70–75. http://dx.doi.org/10.29238/teknolabjournal.v8i2.189.
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Human Immunodeficiency Virus (HIV) is a retrovirus originating from the retroviridae family of the genus lentivirus that infects and damages cells that have a molecule Cluster of Differentiation 4 (CD4), especially T lymphocytes that have receptors with high affinity for HIV. Total lymphocyte count / TLC has been proposed as an alternative guide to CD4 in limited health facilities. This study aims to determine the correlation between Total Lymphocyte Count (TLC) and CD4 in HIV/AIDS patients in the W.Z. Johannes Kupang hospital. The type of this research was observational analytic with a cross-sectional design. The study was conducted on 121 samples of patients who performed CD4 examination and Total Lymphocytic Count (TLC) in the laboratory of W.Z.Johannes Kupang Hospital. The Spearman correlation test shows a significance value of 0,000 with a Spearman correlation value of 0.799. Based on the results of this study it can be concluded that there is a significant correlation between Total Lymphocyte Count and CD4 and shows the direction of positive correlation with a very strong relationship, where the increase in the number of Total Lymphocyte Count is in line with the increase in CD4 counts.