USE OF HIGH PERFORMANCE CONCRETE IN OKLAHOMA BRIDGE DECKS

An investigation was performed to develop four different high performance concrete (HPC) mixtures for the Oklahoma Department of Transportation’s (ODOT’s) 2004 Innovative Bridge Research and Construction (IBRC) project funded by the Federal Highway Administration. These HPC mixtures are designed to achieve a greater durability than normal concretes with an emphasis on the shrinkage developed. These mixtures were developed by studying the affects of air entrainment, cementitious materials content, water to cementitious materials (w/cm) ratio, supplemental cementitious materials, fiber reinforcement, and a shrinkage-reducing admixture. Additionally, a large focus of this investigation was developed in the aggregate blend used in the concretes. This study was performed by conducting a separate study of the validity of the Shilstone method of blending aggregates. The research consisted of two parts: a laboratory and a field investigation. The laboratory investigation consisted of an initial system of batching matrices and a succeeding empirical study to develop the four mixtures required. The field investigation consisted of test slabs for the HPC mixtures and actual bridge construction where the University of Oklahoma investigators served as consultants and additional tests were taken to further characterize the mixtures. Based on the results found in these investigations, conclusions and recommendations were made on the local materials and practices used in the HPC mixture.Final Report, May 2005-July 2006N

Reward-Sensitive Basal Ganglia Stabilize the Maintenance of Goal-Relevant Neural Patterns in Adolescents

Maturation of basal ganglia (BG) and frontoparietal circuitry parallels developmental gains in working memory (WM). Neurobiological models posit that adult WM performance is enhanced by communication between reward-sensitive BG and frontoparietal regions, via increased stability in the maintenance of goal-relevant neural patterns. It is not known whether this reward-driven pattern stability mechanism may have a role in WM development. In 34 young adolescents (12.16–14.72 years old) undergoing fMRI, reward-sensitive BG regions were localized using an incentive processing task. WM-sensitive regions were localized using a delayed-response WM task. Functional connectivity analyses were used to examine the stability of goal-relevant functional connectivity patterns during WM delay periods between and within reward-sensitive BG and WM-sensitive frontoparietal regions. Analyses revealed that more stable goal-relevant connectivity patterns between reward-sensitive BG and WM-sensitive frontoparietal regions were associated with both greater adolescent age and WM ability. Computational lesion models also revealed that functional connections to WM-sensitive frontoparietal regions from reward-sensitive BG uniquely increased the stability of goal-relevant functional connectivity patterns within frontoparietal regions. Findings suggested (1) the extent to which goal-relevant communication patterns within reward-frontoparietal circuitry are maintained increases with adolescent development and WM ability and (2) communication from reward-sensitive BG to frontoparietal regions enhances the maintenance of goal-relevant neural patterns in adolescents’ WM. The maturation of reward-driven stability of goal-relevant neural patterns may provide a putative mechanism for understanding the developmental enhancement of WM

Integrated Commissioning for a Large Medical Facility

The energy costs of heating, ventilating and air conditioning usually represents a large portion of the utility bills for a medical facility. One large, modem medical center located in the hot and humid region of southern Texas includes clinic areas, inpatient areas, critical areas, diagnostic areas, and pharmacy and a research center. An integrated commissioning of the HVAC system was performed for this building. The commissioning activities improved the building comfort conditions and reduced the utility costs by $225,000 for seven months during the commissioning periods and four months following the major commissioning completion. Some unique optimized control strategies were developed and implemented in the control system. This paper describes the commissioning activities and the results

Judicial decision-making within political parties: A political approach

How do German intra-party tribunals manage internal conflicts? More specifically, why do they accept some cases for trial but reject others? Required by law to strictly adhere to implement rule of law standards, German intra-party tribunals are designed to insulate conflict regulation from politics. Meanwhile, research on judicial politics highlights the role of political and strategic considerations in accepting cases for trial. Building on the latter, we develop a theory that emphasizes tribunals’ political concerns such as winning elections. We test our hypotheses with a mixed-effects logit model on a novel data set covering 1088 tribunal decisions in six German parties from 1967 until 2015. Our findings indicate that political factors exert a strong effect on tribunal case acceptance. Tribunals are more likely to accept cases when suffering electoral loss and after losing government office. Moreover, tribunals dismiss cases more easily when their parties display relatively high levels of policy agreement

Where less may be more: how the rare biosphere pulls ecosystems strings

Rare species are increasingly recognized as crucial, yet vulnerable components of Earth’s ecosystems. This is also true for microbial communities, which are typically composed of a high number of relatively rare species. Recent studies have demonstrated that rare species can have an over-proportional role in biogeochemical cycles and may be a hidden driver of microbiome function. In this review, we provide an ecological overview of the rare microbial biosphere, including causes of rarity and the impacts of rare species on ecosystem functioning. We discuss how rare species can have a preponderant role for local biodiversity and species turnover with rarity potentially bound to phylogenetically conserved features. Rare microbes may therefore be overlooked keystone species regulating the functioning of host-associated, terrestrial and aquatic environments. We conclude this review with recommendations to guide scientists interested in investigating this rapidly emerging research area

Towards Designing Conceptual Data Models for Big Data Warehouses: The Genomics Case

[EN] Data Warehousing applied in Big Data contexts has been an emergent topic of research, as traditional Data Warehousing technologies are unable to deal with Big Data characteristics and challenges. The methods used in this field are already well systematized and adopted by practitioners, while research in Big Data Warehousing is only starting to provide some guidance on how to model such complex systems. This work contributes to the process of designing conceptual data models for Big Data Warehouses proposing a method based on rules and design patterns, which aims to gather the information of a certain application domain mapped in a relational conceptual model. A complex domain that can benefit from this work is Genomics, characterized by an increasing heterogeneity, both in terms of content and data structure. Moreover, the challenges for collecting and analyzing genome data under a unified perspective have become a bottleneck for the scientific community, reason why standardized analytical repositories such as a Big Genome Warehouse can be of high value to the community. In the demonstration case presented here, a genomics relational model is merged with the proposed Big Data Warehouse Conceptual Metamodel to obtain the Big Genome Warehouse Conceptual Model, showing that the design rules and patterns can be applied having a relational conceptual model as starting point.This work has been supported by FCT - Fundação para a Ciên-cia e Tecnologia within the Project Scope: UID/CEC/00319/2019, the Doctoral scholarship PD/BDE/135100/2017 and European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Programme (COMPETE 2020) [Project nº 039479; Funding Reference: POCI-01-0247-FEDER-039479]. We also thank both the Spanish State Research Agency and the Generalitat Valenciana under the projects DataME TIN2016-80811-P, ACIF/2018/171, and PROMETEO/2018/176. Icons made by Freepik, from www.flaticon.com.Galvão, J.; León-Palacio, A.; Costa, C.; Santos, MY.; Pastor López, O. (2020). Towards Designing Conceptual Data Models for Big Data Warehouses: The Genomics Case. Springer Nature. 3-19. https://doi.org/10.1007/978-3-030-63396-7_1S319Krishnan, K.: Data Warehousing in the Age of Big Data. Morgan Kaufmann is an imprint of Elsevier, Amsterdam (2013)Santos, M.Y., Costa, C.: Big Data: Concepts, Warehousing and Analytics. River Publishers, Aalborg (2020)Cuzzocrea, A., Moussa, R.: Multidimensional database modeling: literature survey and research agenda in the big data era. In: 2017 International Symposium on Networks, Computers and Communications (ISNCC), pp. 1–6 (2017)Di Tria, F., Lefons, E., Tangorra, F.: Design process for big data warehouses. 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Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-41924-9_1Giebler, C., Gröger, C., Hoos, E., Schwarz, H., Mitschang, B.: Modeling data lakes with data vault: practical experiences, assessment, and lessons learned. In: Laender, A.H.F., Pernici, B., Lim, E.-P., de Oliveira, J.P.M. (eds.) ER 2019. LNCS, vol. 11788, pp. 63–77. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-33223-5_7Gil, D., Song, I.-Y.: Modeling and management of big data: challenges and opportunities. Future Gener. Comput. Syst. 63, 96–99 (2016)Di Tria, F., Lefons, E., Tangorra, F.: GrHyMM: a graph-oriented hybrid multidimensional model. In: De Troyer, O., Bauzer Medeiros, C., Billen, R., Hallot, P., Simitsis, A., Van Mingroot, H. (eds.) ER 2011. LNCS, vol. 6999, pp. 86–97. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-24574-9_12Santos, M.Y., Costa, C.: Data warehousing in big data: from multidimensional to tabular data models. In: Proceedings of the Ninth International C* Conference on Computer Science & Software Engineering, pp. 51–60. ACM, New York (2016)Kimball, R., Ross, M.: The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling. Wiley, Hoboken (2013)Costa, C., Santos, M.Y.: Evaluating several design patterns and trends in big data warehousing systems. In: Krogstie, J., Reijers, H.A. (eds.) CAiSE 2018. LNCS, vol. 10816, pp. 459–473. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-91563-0_28Santos, M.Y., Costa, C., Galvão, J., Andrade, C., Pastor, O., Marcén, A.C.: Big data warehousing for efficient, integrated and advanced analytics - visionary paper. In: Cappiello, C., Ruiz, M. (eds.) CAiSE 2019. LNBIP, vol. 350, pp. 215–226. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-21297-1_1