Relevant bibliographies by topics / Cluster count

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Cluster count'

Author: Grafiati
Published: 1 April 2023

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Journal articles on the topic "Cluster count"

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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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Dissertations / Theses on the topic "Cluster count"

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Gao, Dexiang. "Analysis of clustered longitudinal count data /." Connect to full text via ProQuest. Limited to UCD Anschutz Medical Campus, 2007.

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Thesis (Ph.D. in Analytic Health Sciences, Department of Preventive Medicine and Biometrics) -- University of Colorado Denver, 2007.
Typescript. Includes bibliographical references (leaves 75-77). Free to UCD affiliates. Online version available via ProQuest Digital Dissertations;
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Ekeh, Peter Nnamdi. "Survey on nail discoloration and association with CD4 count among untreated HIV patients at Apin Centre, Nigeria." Thesis, University of the Western Cape, 2010. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_4320_1362393499.

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Eligibility for antiretroviral therapy (ART) in HIV-infected patients is defined either by a cluster of differentiation antigen 4 (CD4) count of less than 200cells/mm3 or clinical diagnosis of WHO stage III and IV. Therefore, the decision to start ART becomes difficult when CD4 cell count is not available. With limited laboratory infrastructure, the decision to start ART is usually made based on clinical symptoms leading to late commencement of ART. This calls for alternative criteria to see if nail discoloration (ND) correlates with low CD4 count among untreated HIV infected patients. This will serve as a complementary screening tool for identifying asymptomatic ARV naive HIV patients with a CD4 cell count of less than 200cells/mm3 which signifies 
severe immunosuppression. Study Design and Setting: This was a quantitative cross-sectional descriptive and analytical study involving adult ART naï
ve HIV infected patients in WHO stage I and II. Systematic sampling was used to select the participants from all adult ART naï
ve HIV infected patients attending APIN clinic, located at the Jos University Teaching Hospital (JUTH), Jos, Nigeria. Data Collection: Face-to-face interviews, physical examination and relevant laboratory investigations with selected participants were conducted using a questionnaire guide. Questions on socio-demographic characteristics, clinical data, general physical examinations including finger nail examination and photographing with subsequent laboratory investigations including CD4 count and western blot were employed. Data Analysis: Variables were categorized and data analyzed using descriptive statistics including the frequency, percentage frequency
mean and standard deviation of continuous variables. Association between CD4 count of &le
200cells/mm3 and ND was tested using the chisquare test with an alpha level of 0.05. Prevalence of ND, sensitivity, specificity, positive predictive and negative predictive values and accuracy of the screening test of ND was calculated. Results: 394 patients had their fingernails photographed and assessed. It was shown that distal banded and grey nails were the common types of ND seen with a prevalence of 38%. There was an association between CD4 count &le
200cells/mm3 and ND (p<
0.0001). CD4 count &le
200cells/mm3 was a risk factor for developing ND (RR=2.3[1.8-3.6]). The association has a sensitivity of 78%, specificity of 55%, positive predictive value of 50%, and negative predictive value of 80% and accuracy of test 63%. Conclusion: With a significant association (p<
0.0001) and a sensitivity of 78%, ND can be a useful clinical indicator of immune dysfunction mediated by HIV among patients in WHO stage I or II. ND can either be a clinical sign or a symptom in HIV patients with a CD4 of &le
200cells/mm3 as seen in the study as the specificity and sensitivity of ND compared favourably with other WHO stage III diagnosis. Recommendations: Nail discoloration should complement CD4 count as an additional staging sign to help identify patients likely to benefit from ART especially in resource-limited settings. Finally, all patients with grey or distal banded should be on co-trimoxaxole prophylaxis in line with WHO /national guideline on the use of co-trimoxaxole for all HIV positive patients with a CD4 cell count of &le
350cells/mm3.

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WELLS, JODY M. "INITIATING COLLABORATION IN HAMILTON COUNTY THROUGH SUB-REGIONAL PLANNING: EVALUATING THE EFFECTIVENESS OF THE COMMUNITY CLUSTER PROJECT." University of Cincinnati / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1179266962.

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Seppi, Antony. "A Case for Avionics in Greene County and Southwestern Ohio." University of Cincinnati / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1277003167.

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Wells, Jody M. "Initiating collaboration in Hamilton County through sub-regional planning evaluating the effectiveness of the community cluster project /." Cincinnati, Ohio : University of Cincinnati, 2007. http://www.ohiolink.edu/etd/view.cgi?acc%5Fnum=ucin1179266962.

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Thesis (Master of Community Planning)--University of Cincinnati, 2007.
Title from electronic thesis title page (viewed July 17, 2007). Includes abstract. Keywords: regionalism, collaboration, sub-regionalism, Hamilton County, cluster Includes bibliographical references.
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Sandreth, Sherry. "Drinking Water and Autism: Using Spatial Cluster Detection to Explore Patterns of Autism Cases in Lane County, Oregon." ScholarWorks, 2016. https://scholarworks.waldenu.edu/dissertations/2335.

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Autism Spectrum Disorders (ASD) are a complex array of neurological disorders with a diverse presentation, multiple etiologies, and long-term ramifications. Prevalence of ASD in the United States is about 1 in 50 children as of 2013, making it a significant public health problem. The etiology is not understood, and it is widely accepted that it is multicausal, with genetic and environmental influences. Prior research suggests an association between water source and ASD. Contaminants such as lead, arsenic, mercury, pharmaceuticals and pesticides found in water are associated with developmental disorders suggesting that a systematic review focused on water source was warranted. Following the integrative model of environmental health (IMEH), this study explored the relationship of water source and ASD prevalence among children in Lane County, Oregon. This cross-sectional study utilized retrospective data of 91 open cases in April 2014. The study used chi square and geographical information systems (GIS) aided by cluster analysis to generate risk maps. Investigation of sociodemographic variables allowed comparisons to national data by zip code. Findings indicated no significant relationships or clusters of ASD populations by zip code, and no significant relationships to comorbidities between private or municipal water supplies. The IMEH framework enabled an in-depth data characterization of ASD and underscored the need for additional environmental data and universally standardized comorbidity definitions. Implication for positive social change include recognizing the importance of using social services data in the search for ASD risk factors.
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Callander, Margarita. "Epidemiological and genetic studies of multiple sclerosis with focus on the Swedish county of Värmland /." Linköping : Linköpings universitet, 2006. http://www.bibl.liu.se/liupubl/disp/disp2006/med949s.pdf.

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Duan, Yuanyuan. "Statistical Predictions Based on Accelerated Degradation Data and Spatial Count Data." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/56616.

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This dissertation aims to develop methods for statistical predictions based on various types of data from different areas. We focus on applications from reliability and spatial epidemiology. Chapter 1 gives a general introduction of statistical predictions. Chapters 2 and 3 investigate the photodegradation of an organic coating, which is mainly caused by ultraviolet (UV) radiation but also affected by environmental factors, including temperature and humidity. In Chapter 2, we identify a physically motivated nonlinear mixed-effects model, including the effects of environmental variables, to describe the degradation path. Unit-to-unit variabilities are modeled as random effects. The maximum likelihood approach is used to estimate parameters based on the accelerated test data from laboratory. The developed model is then extended to allow for time-varying covariates and is used to predict outdoor degradation where the explanatory variables are time-varying. Chapter 3 introduces a class of models for analyzing degradation data with dynamic covariate information. We use a general path model with random effects to describe the degradation paths and a vector time series model to describe the covariate process. Shape restricted splines are used to estimate the effects of dynamic covariates on the degradation process. The unknown parameters of these models are estimated by using the maximum likelihood method. Algorithms for computing the estimated lifetime distribution are also described. The proposed methods are applied to predict the photodegradation path of an organic coating in a complicated dynamic environment. Chapter 4 investigates the Lyme disease emergency in Virginia at census tract level. Based on areal (census tract level) count data of Lyme disease cases in Virginia from 1998 to 2011, we analyze the spatial patterns of the disease using statistical smoothing techniques. We also use the space and space-time scan statistics to reveal the presence of clusters in the spatial and spatial/temporal distribution of Lyme disease. Chapter 5 builds a predictive model for Lyme disease based on historical data and environmental/demographical information of each census tract. We propose a Divide-Recombine method to take advantage of parallel computing. We compare prediction results through simulation studies, which show our method can provide comparable fitting and predicting accuracy but can achieve much more computational efficiency. We also apply the proposed method to analyze Virginia Lyme disease spatio-temporal data. Our method makes large-scale spatio-temporal predictions possible. Chapter 6 gives a general review on the contributions of this dissertation, and discusses directions for future research.
Ph. D.
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Madsen, Christopher. "Clustering of the Stockholm County housing market." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-252301.

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In this thesis a clustering of the Stockholm county housing market has been performed using different clustering methods. Data has been derived and different geographical constraints have been used. DeSO areas (Demographic statistical areas), developed by SCB, have been used to divide the housing market in to smaller regions for which the derived variables have been calculated. Hierarchical clustering methods, SKATER and Gaussian mixture models have been applied. Methods using different kinds of geographical constraints have also been applied in an attempt to create more geographically contiguous clusters. The different methods are then compared with respect to performance and stability. The best performing method is the Gaussian mixture model EII, also known as the K-means algorithm. The most stable method when applied to bootstrapped samples is the ClustGeo-method.
I denna uppsats har en klustring av Stockholms läns bostadsmarknad genomförts med olika klustringsmetoder. Data har bearbetats och olika geografiska begränsningar har använts. DeSO (Demografiska Statistiska Områden), som utvecklats av SCB, har använts för att dela in bostadsmarknaden i mindre regioner för vilka områdesattribut har beräknats. Hierarkiska klustringsmetoder, SKATER och Gaussian mixture models har tillämpats. Metoder som använder olika typer av geografiska begränsningar har också tillämpats i ett försök att skapa mer geografiskt sammanhängande kluster. De olika metoderna jämförs sedan med avseende på kvalitet och stabilitet. Den bästa metoden, med avseende på kvalitet, är en Gaussian mixture model kallad EII, även känd som K-means. Den mest stabila metoden är ClustGeo-metoden.
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Godke, Margaret Severinson. "Attitudes of county extension advisory committee members regarding the clustered staffing pattern in Ohio /." The Ohio State University, 1991. http://rave.ohiolink.edu/etdc/view?acc_num=osu148769438939494.

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Books on the topic "Cluster count"

1

Leonard, Peter J. T. Star counts in open clusters. Toronto: University of Toronto, Dept. of Astronomy, 1985.

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United States. Agency for Toxic Substances and Disease Registry. Pancreatic cancer cluster investigation of Livingston and Park County, Montana. Atlanta, Ga: [The Agency?, 1991.

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United States. Agency for Toxic Substances and Disease Registry. Division of Health Studies. Investigation of a cluster of pancreatic cancer deaths, Livingston and Park County, Montana. Atlanta, Ga: [The Agency, 1992.

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Liaoning Sheng xian yu chan ye ji qun zong he ping jia yan jiu: Study on the comprehensive evaluation of county industrial clusters in Liaoning Province. Beijing: Hua xue gong ye chu ban she, 2016.

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Inman, Rebecca J. 2006 report to the Legislature: Cluster residential development groundwater withdrawal exemption Whitman County pilot project. [Olympia, Wash.]: Washington State Dept. of Ecology, 2006.

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Inman, Rebecca J. Cluster residential development ground water withdrawal exemption Whitman County pilot project: 2004 report to the Legislature. Olympia, WA: Washington State Dept. of Ecology, 2004.

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Inman, Rebecca J. 2006 report to the Legislature: Cluster residential development ground water withdrawal exemption Whitman County pilot project. [Olympia, Wash.]: Washington State Dept. of Ecology, Water Resources Program, 2006.

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Leonard, Peter James Toivo. Star counts in open clusters. 1985.

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Henggeller, Michelle. Infections in the HIV Patient. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199976805.003.0055.

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The hallmark of the human immunodeficiency virus (HIV) patient with a cluster of differentiation 4 (CD4) T lymphocyte count below 200 is the development of opportunistic infections. Although the use of antiretroviral therapy (ART) has decreased the incidence of these infections, they continue to be a major case of morbidity and mortality in the patient with HIV. These infections can be respiratory in nature and present with cough or shortness of breath: Pneumocystis pneumonia (PCP), tuberculosis (TB), aspergillosis, and coccidioidomycosis. Neurological infections, which can present with change in mental status, include toxoplasmosis encephalitis (TE), meningoencephalitis, John Cunningham (JC) virus, and progressive multifocal leukoencephalopathy (PML). Gastrointestinal infections, such as Cryptosporidium, present with abdominal pain and diarrhea. Viral changes can result from cytomegalovirus retinitis. Fever or nonspecific symptoms can result from disseminated Mycobacterium Avium complex disease, histoplasmosis, bartonellosis, and cytomegalovirus.
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O'Hara, Alexander. Jonas of Bobbio and the Legacy of Columbanus. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190858001.001.0001.

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Jonas of Bobbio, writing in the mid-seventh century, was not only a major Latin monastic author but also a historic figure in his own right. Born in the ancient Roman town of Susa in the foothills of the Italian Alps, he became a monk of Bobbio, the monastery founded by the Irish abbot Columbanus, soon after the saint’s death. He became archivist and personal assistant to successive Bobbio abbots, traveled to Rome to obtain the first papal privilege of immunity, and served as a missionary on the northern borderlands of the Frankish kingdom, where he wrote his Vita Columbani, one of the most influential works of early medieval hagiography. As abbot of a community in the far north of the Frankish kingdom, Jonas was part of an extensive monastic network that stretched from the English Channel to the Italian Apennines. By the time of Jonas’s death toward the end of the seventh century, the monastic landscape of this region had been transformed. This was the result of a socioreligious revolution, initiated by Columbanus (d. 615) and continued by his Frankish disciples in the decades after his death. Columbanus established a cluster of monasteries in the Vosges forests of Burgundy in the last decade of the sixth century, chief among them Luxeuil. During the seventh century, Luxeuil, its abbots, and the Merovingian royal court in Paris spearheaded an unprecedented monastic movement in Merovingian Gaul that would transform the interrelationship between religious and secular authorities in the Early Middle Ages.
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Book chapters on the topic "Cluster count"

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Kumar, Vinay, Sadanand Yadav, D. N. Sandeep, Sanjay B. Dhok, Rabindra K. Barik, Akhilendra P. Singh, and Gaurav Srivastava. "Optimal Cluster Count and Coverage Analysis in a Gaussian Distributed WSNs Using TESM." In Frontiers in Intelligent Computing: Theory and Applications, 335–45. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9920-6_35.

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Roul, Rajendra Kumar, and Sanjay Kumar Sahay. "Combining Apriori Approach with Support-Based Count Technique to Cluster the Web Documents." In Advances in Intelligent Systems and Computing, 119–32. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-3874-7_12.

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Uglickich, Evženie, and Ivan Nagy. "Prediction of Overdispersed Count Data Using Real-Time Cluster-Based Discretization of Explanatory Variables." In Informatics in Control, Automation and Robotics, 163–84. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-26474-0_9.

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Shoukri, Mohamed M. "Analysis of Clustered Count Data." In Analysis of Correlated Data with SAS and R, 197–228. Fourth edition. | Boca Raton : CRC Press, 2018. | Previous edition: Analysis of correlated data with SAS and R / Mohamed M. Shoukri (Boca Raton : Chapman & Hall/CRC, 2007).: Chapman and Hall/CRC, 2018. http://dx.doi.org/10.1201/9781315277738-6.

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Tang, Wan, Hua He, and Xin M. Tu. "Longitudinal and Clustered Data Analysis." In Applied Categorical and Count Data Analysis, 259–306. 2nd ed. Boca Raton: Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003109815-9.

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Lilje, Per B., and G. Efstathiou. "The Cross-Correlation of Abell Clusters with the Lick Galaxy Counts." In Large Scale Structures of the Universe, 550. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-2995-1_104.

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Hanami, Hitoshi. "Evolution and Statistics from the Number Counts of X-Ray Cluster and Intergalactic Medium." In Primordial Nucleosynthesis and Evolution of Early Universe, 569–70. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3410-1_87.

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Sharygin, Ethan. "Estimating Migration Impacts of Wildfire: California’s 2017 North Bay Fires." In The Demography of Disasters, 49–70. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49920-4_3.

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Abstract This chapter examines a cluster of wildfire conflagrations that hit northern California during October 2017, which resulted in significant loss of housing units (6874 residential structures destroyed or damaged). To assess the magnitude of the migration response and network of destinations, a method to estimate migration drawing from a proxy universe of households with students enrolled in public schools was proposed, using data on school exits and re-enrollments from a longitudinal student database. The analysis finds that a small minority of households affected by the fires moved out of the area. Out of nearly 7800 persons displaced by the central fire complex in one city, this study estimated fewer than 1000 changed neighborhoods; of those, fewer than 500 moved out of Sonoma County. These findings are applicable to other wildfires and localized disasters where a substantial portion of housing is lost but public infrastructure in the region remains intact.
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Wikle, C. "Spatial Modelling of Count Data." In Spatial Cluster Modelling. Chapman and Hall/CRC, 2002. http://dx.doi.org/10.1201/9781420035414.ch11.

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Elsner, James B., and Thomas H. Jagger. "Cluster Models." In Hurricane Climatology. Oxford University Press, 2013. http://dx.doi.org/10.1093/oso/9780199827633.003.0015.

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A cluster is a group of the same or similar events close together. Clusters arise in hurricane origin locations, tracks, and landfalls. In this chapter, we look at how to analyze and model clusters. We divide the chapter into methods for time, space, and feature clustering. Of the three feature clustering is best known to climatologists. We begin by showing you how to detect and model time clusters. Consecutive hurricanes originating in the same area often take similar paths. This grouping, or clustering, increases the potential for multiple landfalls above what you expect from random events. A statistical model for landfall probability captures clustering through covariates like the North Atlantic Oscillation (NAO), which relates a steering mechanism (position and strength of the subtropical high pressure) to coastal hurricane activity. But there could be additional time correlation not related to the covariates. A model that does not account for this extra variation will underestimate the potential for multiple hits in a season. Following Jagger and Elsner (2006), you consider three coastal regions including the Gulf Coast, Florida, and the East Coast (Fig. 6.2). Regions are large enough to capture enough hurricanes, but not too large as to include many non-coastal strikes. Here you use hourly position and intensity data described in Chapter 6. For each hurricane, you note its wind speed maximum within each region. If the maximum wind exceeds 33 m s−1, then you count it as a hurricane for the region. A tropical cyclone that affects more than one region at hurricane intensity is counted in each region. Because of this, the sum of the regional counts is larger than the total count. Begin by loading annual.RData. These data were assembled in Chapter 6. Subset the data for years starting with 1866. . . . > load("annual.RData") > dat = subset(annual, Year >= 1866) . . . The covariate Southern Oscillation Index (SOI) data begins in 1866 . Next, extract all hurricane counts for the Gulf coast, Florida, and East coast regions. . . . > cts = dat[, c("G.1", "F.1", "E.1")] . . .
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Conference papers on the topic "Cluster count"

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Sledge, Isaac J., Jacalyn M. Huband, and James C. Bezdek. "(Automatic) Cluster Count Extraction from Unlabeled Data Sets." In 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD). IEEE, 2008. http://dx.doi.org/10.1109/fskd.2008.552.

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Venkataraman, P. "Data Clustering Using the Natural Bézier Functions." In ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/detc2018-85103.

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An unorthodox and effective non-iterative procedure for spherical clusters is demonstrated in this paper. It uses natural Bézier functions to determine initial cluster locations using the content of the data. The natural Bernstein-Bézier functions are very robust in representing data through continuous functions in the application of functional data analysis. This paper demonstrates that they are equally robust at resolving data clusters in classification problems. The original data is scaled and segmented. A natural Bézier function is fitted for each segment and the initial clusters are centered at the function extremums that are distinctly located. A self-selection process based on least distance is used to assign the data to these initial cluster centers. A minimum membership count is imposed and nearby clusters are combined to reduce these initial cluster centers based on visual clues. Centroid recalculation and data reassignment can be used for centroid convergence. The method is demonstrated for two dimensional spherical clusters. This approach requires no iteration. Four examples from clustering benchmark datasets are used to showcase the method. The data include different numbers of clusters, different data density for the clusters, as well as different levels of overlap. This method is new and different from other data clustering methods available in the literature. It is better than the standard k-means clustering method since it does not require information on the number of clusters or cluster membership count. The method is non-iterative and does not require random initialization or distance optimization.
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Eckdahl, Rick, Adam Vigrass, Amit Singh, Xinghui Liu, and Larry Chrusch. "Assessment of Limited Entry Cluster Distribution Effectiveness and Impactful Variables using Perforation Erosion Measurements." In SPE Hydraulic Fracturing Technology Conference and Exhibition. SPE, 2022. http://dx.doi.org/10.2118/209122-ms.

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Abstract Limited entry perforating is the most common method of diversion used in unconventional hydraulic fracturing. Still it is not immediately apparent how even the stimulation treatments are distributed between the clusters, and the impact of different perforating variables. This paper presents the finding of two well perforation erosion measurement in the Duvernay formation of Western Canada using two logging techniques, optical imaging and ultrasonic measurements. In two wells multiple perforating variables were tested including shot diameter, shot orientation, perforation pressure drop, variable vs constant cluster shot count, and cluster count per stage. Unstimulated perforations were measured for each perforating charge type and orientation to validate baseline perforation dimensions prior to erosion and use to calibration data for incremental erosion calculation. Each of the two wells were logged with an ultrasonic measurement device while one of the two was also logged with an optical imaging tool separately. Perforation area increase for each perforation and the total area increase for each perforation cluster were analyzed to assess the impact of perforating variables on erosion of individual perforation and effectiveness of different perforating designs with respect to equal distribution. The erosion measurement using both logging techniques provided unique opportunity to compare their measurement capability (optical imaging measured 90% of fracture stages as compared to ultrasonic, but both techniques missed ~10% of total measured perforations to quantify perforation size) and range of uncertainties of measurement erosion (general variability in eroded perf diameter measurement of individual perforation by each technique, but statistically R2 of 0.95 correlation excluding 3 outliers of total 873 perforations measured). Of the variables tested a few stood out as providing more even perforation distribution than others. Not surprisingly, reducing total shot count and subsequent flow area, creating a larger pressure drop at the perforations, resulted in a more even distribution of erosion. Smaller initial hole size with an increased shot count, to provide a similar expected pressure differential, also resulted in improved cluster distribution. Variable shot count perforating achieved a more even distribution and counteracted a nature tendency for heel bias. In general perforations on the lower side of the casing showed increase erosion compared to perforations in the upper part of the casing, providing credence to the notion that sand densities are higher in the bottom of the casing even with very high sand transport velocities. This paper shares a case history with results comparison of two major erosion measurement techniques, erosion variability of each perforation as per its azimuth, and highlights some of the variables that have a large impact on cluster distribution and is of benefit to anyone optimizing a perforating design or developing a similar trial to test cluster distribution in other basins.
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Anbalagan, Ranjith, and Anitha Julian. "Handover Count Based Location Aided Routing for Cluster Networks (HCBLR)." In 2014 International Conference on Advanced Communication, Control and Computing Technologies (ICACCCT). IEEE, 2014. http://dx.doi.org/10.1109/icaccct.2014.7019409.

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Olson, Karen, Joshua Merritt, Rair Barraez, Garrett Fowler, Jackson Haffener, and Kyle Haustveit. "Sealed Wellbore Pressure Monitoring (SWPM) and Calibrated Fracture Modeling: The Next Step in Unconventional Completions Optimization." In SPE Hydraulic Fracturing Technology Conference and Exhibition. SPE, 2023. http://dx.doi.org/10.2118/212367-ms.

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Abstract Sealed Wellbore Pressure Monitoring (SWPM) has been utilized across North and South America Basins with over 16,000 stages monitored as of June 2022. Since May 2020, the analysis procedure has been automated using a cloud-based software platform designed to ingest, process, and analyze high-frequency hydraulic fracturing data (Iriarte et al., 2021). A real time option of SWPM was also developed to aid in real time fracturing decisions (Ramirez et al., 2022). The latest development is the added capability of a fracture model that can automatically history match the volume to first responses (VFRs) determined from SWPM. This next level allows for the matching of the VFRs and the visualization of the resulting fracture geometries from a fully-coupled fracture propagation, reservoir, and geomechanics simulator. The simulator is capable of accounting for complex processes such as poroelastic stress changes from depletion, allowing for evaluation of complex interactions of fracture propagation and depletion. Insights gained from this process allows the operator to optimize their completion design faster and with fewer field trials. This paper’s focus is a case study of the DOE Eagle Ford refracturing project where a range of completion designs were trialed while monitoring offset SWPM and fiber optic strain. The resulting VFRs of the SWPM project were compared to the fiber data and then used to calibrate the fracture model. Fracture model calibration was first performed assuming that restimulation fractures propagated independently of the previously created fractures. The VFR of each stage design was calculated and summarized. The model is constructed with three stage designs primarily identified by cluster count: 7-clusters, 12-clusters, and 22-clusters. The VFR for the 7-cluster stage design was then used as an objective in an automated history matching algorithm employing the fracture model. The resulting best fit model was then evaluated on VFRs for the 12 and 22-cluster stage designs. The results demonstrate the model calibrated to the VFR of the 7-cluster stage design was able to predict VFRs in the far field for 12 and 22-cluster stage designs. Further, it is shown that including the original fractures in the model and allowing crossflow between the original and newly created fractures can match the rapid VFRs observed on a minority of stages. These same results were confirmed by the fiber data (not shared with modelers prior to calibration). Conclusions of the DOE project will show the optimum cluster spacing, cluster count and stage spacing as confirmed by the SWPM analysis and the fracture modeling.
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Kim, Eun Hwa. "Cluster Head Selection Based On Hop Count in a Wireless Sensor Networks." In Circuits, Control, Communication, Electricity, Electronics, Energy, System, Signal and Simulation 2014. Science & Engineering Research Support soCiety, 2014. http://dx.doi.org/10.14257/astl.2014.51.29.

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Ooi, Melanie P.-L., Ye Chow Kang, Wei Jean Tee, Ajay Achath MOhanan, and Chris Chan. "Accurate defect cluster detection and localisation on fabricated semiconductor wafters using joint count statistics." In 2009 1st Asia Symposium on Quality Electronic Design (ASQED 2009). IEEE, 2009. http://dx.doi.org/10.1109/asqed.2009.5206264.

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Griffin, J., D. J. Rojas, A. Al Shmakhy, and P. Scranton. "Application of Interventionless Single Point Entry Technology to Improve Proppant Placement Control and Well Production." In SPE Annual Technical Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/205865-ms.

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Abstract The hydraulic fracture treatment (HFT) and its effectiveness to enhance wellbore drainage directly correlate with each well’s overall production performance and underlining economics. This paper will discuss the potential of ultra high stage count Single Point Entry (SPE) sleeves and their ability to increase control over proppant placement and isolation during the HFT as a method for optimizing well performance, economics, and reduce non-uniformity between treatments and wells. To address the limitations of current completion methods, full ID single point entry systems have been developed for open hole and cemented applications. These systems provide unlimited frac stage count with lower frac tortuosity, provide increased control over proppant placement and well production, reduce or eliminate over- flush and formation damage, and achieve higher efficiency during and after frac stimulation than previous conventional plug-and-perf (PnP) and sleeve systems, thereby reducing costs. While the ball-and-seat completion technique revolutionized the efficiency of multi-stage single point entry fracturing, its vast array of limitations (primarily ID restrictions), limited stage count, and compatibility with cemented liners quickly sidelined it in place of PnP. PnP offers increased surface area contact through additional entry points compared to sleeve systems of the past and remains the accepted method for achieving zonal isolation and initiation during stimulation. However, the time intensive operations of PnP present challenges in maintaining efficiencies due to variability in wireline during deployment and coiled tubing during millouts. The increase in number of clusters per stage and number of stages per well achieved with PnP often results in higher stimulated rock volumes (SRV) however, due to the number of multiple clusters open simultaneously, this method gained a "pump-n-pray" reputation due to the uncertainty of cluster efficiency and its unpredictability. The lack of cluster control over the years has created a series of challenges in terms of parent-child well relationships and spacing, economical asset development, and loss of potential production. With over 4,000 stages fracture stimulated across US, Canada, and Asia, some wells containing 220 individual stages, this paper will address the differences in production in terms of bbl of oil equivalent (BOE) for direct and indirect offsets in trials, compare capital efficiency with spud to put on production (POP) timelines, demonstrate economical completion optimization for lower commodity pricing of oil, and carbon intensity reduction measures to lower greenhouse gas emissions.
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Liu, Xinghui, Jiehao Wang, Amit Singh, Margaretha Rijken, Larry Chrusch, Dean Wehunt, Faraj Ahmad, and Jennifer Miskimins. "Achieving Perfect Fluid and Proppant Placement in Multi-Stage Fractured Horizontal Wells: A CFD Modeling Approach." In SPE Hydraulic Fracturing Technology Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/204182-ms.

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Abstract Multi-stage plug-n-perf fracturing of horizontal wells has proven to be an effective method to develop unconventional reservoirs. Various studies have shown uneven fluid and proppant distributions across all perforation clusters. It is commonly believed that both fracturing fluid and proppant contribute to unconventional well performance. Achieving uniform fluid and proppant placement is an important step toward optimal stimulation. This paper discusses how to achieve such uniform placement in each stage via a CFD (Computational Fluid Dynamics) modeling approach. CFD models in several lab scales were built and calibrated using experimental data of proppant transport through horizontal pipes in several laboratory configurations. A field-scale model was then built and validated using perforation erosion data from downhole camera observations and the same model parameters calibrated in the lab-scale model. With the field-scale model validated, CFD simulations were performed to evaluate the impact of key parameters on fluid and proppant placement in individual perforations and clusters. Some key parameters investigated in this study included perforation parameters (size, orientation, number), cluster spacing, cluster count per stage, fluid properties, proppant properties, pumping rates, casing sizes, and stress shadow effects, etc. Both lab and CFD results show that bottom-side perforations receive significantly more proppant than top-side perforations due to gravitational effects. Lab and CFD results also show that proppant distribution is increasingly toe-biased at higher rates. Proppant concentration along the wellbore from heel to toe generally varies significantly. Gravity, momentum, viscous drag, and turbulent dispersion are key factors affecting proppant transport in horizontal wellbores. This study demonstrates that near-uniform fluid and proppant placement across all clusters in each stage is achievable by optimizing perforation, cluster, and other treatment design factors. Validated CFD modeling plays an important role in this design optimization process.
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SNEDDON, G., M. T. HASAN, and R. MA. "A UNIFIED APPROACH BETWEEN POPULATION-AVERAGED AND CLUSTER-SPECIFIC ANALYSES FOR MULTILEVEL ZERO-INFLATED COUNT DATA." In Proceedings of Statistics 2011 Canada/IMST 2011-FIM XX. WORLD SCIENTIFIC, 2013. http://dx.doi.org/10.1142/9789814417983_0016.

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Reports on the topic "Cluster count"

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Iyer, Ananth V., Konstantina Gkritza, Steven R. Dunlop, Dutt J. Thakkar, Raul Candanedo, Srinath Jayan, Pooja Gupta, et al. Last Mile Delivery and Route Planning for Freight. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317315.

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This report analyzes anticipated list mile challenges in Indiana by using a scenario-based approach to develop forecasts of GDP growth and thus freight growth across industry clusters in Indiana counties; potential congestion implied by this growth; and a proactive plan to add capacity to alleviate the congestion. We use a quantitative approach to aggregate ramp level flows, industry cluster locations, county layout, and economic activity to develop our recommendations. We develop forecasts through the year 2050 based on long-term planning approaches used by other states (California, Ohio, and Utah). We use data from global databases that consider different possible geo-political scenarios and regulatory choices to scale it down to county-level impact. At the same time, we track industry cluster locations within each county, ramps from interstates, and distances to travel within the counties to reach freight destinations. The result is a report that combines macro trends with micro detail to develop potential capacity bottlenecks.
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Iyer, Ananth V., Konstantina Gkritza, Steven R. Dunlop, Dutt J. Thakkar, Raul Candanedo, Srinath Jayan, Pooja Gupta, et al. Last Mile Delivery and Route Planning for Freight. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317315.

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This report analyzes anticipated list mile challenges in Indiana by using a scenario-based approach to develop forecasts of GDP growth and thus freight growth across industry clusters in Indiana counties; potential congestion implied by this growth; and a proactive plan to add capacity to alleviate the congestion. We use a quantitative approach to aggregate ramp level flows, industry cluster locations, county layout, and economic activity to develop our recommendations. We develop forecasts through the year 2050 based on long-term planning approaches used by other states (California, Ohio, and Utah). We use data from global databases that consider different possible geo-political scenarios and regulatory choices to scale it down to county-level impact. At the same time, we track industry cluster locations within each county, ramps from interstates, and distances to travel within the counties to reach freight destinations. The result is a report that combines macro trends with micro detail to develop potential capacity bottlenecks.
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Smalley, Rebecca, Emmanuel Sulle, Ngala Chome, Ana Duarte, and Euclides Gonçalves. Agricultural Investment Corridors in Africa: Does Smallholder and Women's Participation Count? Institute of Development Studies (IDS), August 2021. http://dx.doi.org/10.19088/apra.2021.021.

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Agricultural development corridors and clusters are highly complex projects that have been driven in Africa by agribusiness and mining corporations, host governments, international donors and development finance institutions. There is interest in whether these projects can support inclusive agribusiness. Evidence shows that involvement of small-scale economic actors in such initiatives is often impeded by a failure to grant them participation or a voice. We therefore investigated if and how recent corridors and clusters in Africa have been able to achieve the meaningful engagement of small-scale economic actors, with a focus on smallholders, including pastoralists, and the women among them.
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Willis, C., F. Jorgensen, S. A. Cawthraw, H. Aird, S. Lai, M. Chattaway, I. Lock, E. Quill, and G. Raykova. A survey of Salmonella, Escherichia coli (E. coli) and antimicrobial resistance in frozen, part-cooked, breaded or battered poultry products on retail sale in the United Kingdom. Food Standards Agency, May 2022. http://dx.doi.org/10.46756/sci.fsa.xvu389.

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Frozen, breaded, ready-to-cook chicken products have been implicated in outbreaks of salmonellosis. Some of these outbreaks can be large. For example, one outbreak of Salmonella Enteritidis involved 193 people in nine countries between 2018 and 2020, of which 122 cases were in the UK. These ready-to-cook products have a browned, cooked external appearance, which may be perceived as ready-to-eat, leading to mishandling or undercooking by consumers. Continuing concerns about these products led FSA to initiate a short-term (four month), cross-sectional surveillance study undertaken in 2021 to determine the prevalence of Salmonella spp., Escherichia coli and antimicrobial resistance (AMR) in frozen, breaded or battered chicken products on retail sale in the UK. This study sought to obtain data on AMR levels in Salmonella and E. coli in these products, in line with a number of other FSA instigated studies of the incidence and nature of AMR in the UK food chain, for example, the systematic review (2016). Between the beginning of April and the end of July 2021, 310 samples of frozen, breaded or battered chicken products containing either raw or partly cooked chicken, were collected using representative sampling of retailers in England, Wales, Scotland and Northern Ireland based on market share data. Samples included domestically produced and imported chicken products and were tested for E. coli (including extended-spectrum beta-lactamase (ESBL)-producing, colistin-resistant and carbapenem-resistant E. coli) and Salmonella spp. One isolate of each bacterial type from each contaminated sample was randomly selected for additional AMR testing to determine the minimum inhibitory concentration (MIC) for a range of antimicrobials. More detailed analysis based on Whole Genome Sequencing (WGS) data was used to further characterise Salmonella spp. isolates and allow the identification of potential links with human isolates. Salmonella spp. were detected in 5 (1.6%) of the 310 samples and identified as Salmonella Infantis (in three samples) and S. Java (in two samples). One of the S. Infantis isolates fell into the same genetic cluster as S. Infantis isolates from three recent human cases of infection; the second fell into another cluster containing two recent cases of infection. Countries of origin recorded on the packaging of the five Salmonella contaminated samples were Hungary (n=1), Ireland (n=2) and the UK (n=2). One S. Infantis isolate was multi-drug resistant (i.e. resistant to three different classes of antimicrobials), while the other Salmonella isolates were each resistant to at least one of the classes of antimicrobials tested. E. coli was detected in 113 samples (36.4%), with counts ranging from <3 to >1100 MPN (Most Probable Number)/g. Almost half of the E. coli isolates (44.5%) were susceptible to all antimicrobials tested. Multi-drug resistance was detected in 20.0% of E. coli isolates. E. coli isolates demonstrating the ESBL (but not AmpC) phenotype were detected in 15 of the 310 samples (4.8%) and the AmpC phenotype alone was detected in two of the 310 samples (0.6%) of chicken samples. Polymerase Chain Reaction (PCR) testing showed that five of the 15 (33.3%) ESBL-producing E. coli carried blaCTX-M genes (CTX-M-1, CTX-M-55 or CTX-M-15), which confer resistance to third generation cephalosporin antimicrobials. One E. coli isolate demonstrated resistance to colistin and was found to possess the mcr-1 gene. The five Salmonella-positive samples recovered from this study, and 20 similar Salmonella-positive samples from a previous UKHSA (2020/2021) study (which had been stored frozen), were subjected to the cooking procedures described on the sample product packaging for fan assisted ovens. No Salmonella were detected in any of these 25 samples after cooking. The current survey provides evidence of the presence of Salmonella in frozen, breaded and battered chicken products in the UK food chain, although at a considerably lower incidence than reported in an earlier (2020/2021) study carried out by PHE/UKHSA as part of an outbreak investigation where Salmonella prevalence was found to be 8.8%. The current survey also provides data on the prevalence of specified AMR bacteria found in the tested chicken products on retail sale in the UK. It will contribute to monitoring trends in AMR prevalence over time within the UK, support comparisons with data from other countries, and provide a baseline against which to monitor the impact of future interventions. While AMR activity was observed in some of the E. coli and Salmonella spp. examined in this study, the risk of acquiring AMR bacteria from consumption of these processed chicken products is low if the products are cooked thoroughly and handled hygienically.
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