49 research outputs found
Scaling Laws in Human Language
Zipf's law on word frequency is observed in English, French, Spanish,
Italian, and so on, yet it does not hold for Chinese, Japanese or Korean
characters. A model for writing process is proposed to explain the above
difference, which takes into account the effects of finite vocabulary size.
Experiments, simulations and analytical solution agree well with each other.
The results show that the frequency distribution follows a power law with
exponent being equal to 1, at which the corresponding Zipf's exponent diverges.
Actually, the distribution obeys exponential form in the Zipf's plot. Deviating
from the Heaps' law, the number of distinct words grows with the text length in
three stages: It grows linearly in the beginning, then turns to a logarithmical
form, and eventually saturates. This work refines previous understanding about
Zipf's law and Heaps' law in language systems.Comment: 6 pages, 4 figure
Reliability and tolerance comparison in water supply networks
The final publication is available at Springer via http://dx.doi.org/10.1007/s11269-010-9753-2Urban water supply is a high priority service and so looped networks are extensively used in order to considerably reduce the number of consumers affected by a failure. Looped networks may be redundant in connectivity and capacity. The concept of reliability has been introduced in an attempt to quantitatively measure the possibility of maintaining an adequate service for a given period. Numerous researchers have considered reliability as a measure of redundancy. This concept is usually implicit, but some researchers have even stated it explicitly. This paper shows why reliability cannot be considered a measure of redundancy given that branched networks can achieve high values of reliability and this would deny the fact that a looped network is more reliable than a branched network with a similar layout and size. To this end the paper discusses two quantitative indices for measuring expected network behavior: reliability and tolerance. These indices are calculated and a comparison is made between looped, branched, and mixed networks. © 2011 Springer Science+Business Media B.V.The authors wish to acknowledge the support received from project IDAWAS, DPI2009-11591, of the Directorate-General of Research at the Spanish Ministry of Education, the grant PAID-02-09 for a stay at the Universidad Politecnica de Valencia by the first author, and a grant MAEC-AECI 0000202066 awarded to the second author by the Ministerio de Asuntos Exteriores y Cooperacion of Spain. The use of English in this paper was revised by John Rawlins; and the revision was funded by the Universidad Politecnica de Valencia, Spain.MartÃnez-RodrÃguez, JB.; Montalvo Arango, I.; Izquierdo Sebastián, J.; Pérez GarcÃa, R. (2011). Reliability and tolerance comparison in water supply networks. Water Resources Management. 25(5):1437-1448. https://doi.org/10.1007/s11269-010-9753-2S14371448255Bao Y, Mays LW (1990) Model for water distribution system reliability. J Hydraul Eng ASCE 116(9):1119–1137Bouchart F, Goulter I (1991) Reliability improvements in design of water distribution networks recognizing valve location. Water Resour Res 27(12):3029–3040Carrión A, Solano H, Gamiz ML, Debón A (2010) Evaluation of the reliability of a water supply network from right-censored and left-truncated break data. Water Resour Manag, Springer Sci 24:2917–2935. Published online: 28 January 2010Chiong C (1985) Optimización de redes cerradas, Doctoral Thesis, CIH-CUJAE, Havana (in Spanish)Christodoulou SE (2010) Water network assessment and reliability analysis by use of survival analysis. Water Resour Manag, Springer Sci, Published online: 19 June 2010Cullinane MJ, Lansey KE, Mays LW (1992) Optimization-availability-based design of water distribution networks. J Hydraul Eng ASCE 118(3):420–441Duan N, Mays LW, Lansey KE (1990) Optimal reliability-based design of pumping and distribution systems. J Hydraul Eng ASCE 116(2):249–268Goulter I (1992) Systems analysis in water distribution network design: from theory to practice. J Water Resour Plan Manage ASCE 118(3):238–248Goulter I (1993) Modern concepts of a water distribution system. Policies for improvement of networks with shortcomings. In: Cabrera E, MartÃnez F (eds) Water supply systems: state of the art and future trends, Valencia (Spain). Comput Mech Publ, Southampton, pp 121–138Goulter I, Bouchart F (1990) Reliability-constrained pipe network model. J Hydraul Eng ASCE 116(2):211–229Gupta R, Bhave R (1994) Reliability analysis of water distribution systems. J Environ Eng ASCE 120(2):447–460Jacobs P, Goulter I (1991) Estimation of maximum cut-set size for water network failure. J Water Resour Plan Manage ASCE 117(5):588–605Jowitt P, Xu C (1993) Predicting pipe failure effects in water distribution networks. J Water Resour Plan Manage ASCE 119(l):18–31Kalungi P, Tanyimboh TT (2003) Redundancy model for water distribution systems. Rel Eng Syst Safety 82(3):275–286Khomsi D, Walters GA, Thorley ARD, Ouazar D (1996) Reliability tester for water-distribution networks. J Comput Civ Eng ASCE 10(l):10–9Lansey K, Duan N, Mays LW, Tung YK (1989) Water distribution system design under uncertainty. J Water Resour Plan Manage ASCE 115(5):630–645Loganathan GV, Shah MP, Sherali HP (1990) A two-phase network design heuristic for minimum cost water distribution systems under a reliability constraint. Eng Optim 15(4):311–336MartÃnez JB (2007) Quantifying the economy of water supply looped networks. J Hydraul Eng ASCE 133(1):88–97MartÃnez JB (2010) Cost and reliability comparison between branched and looped water supply networks. J Hydroinform IWA 12(2):150–160Morgan DR, Goulter IC (1985) Optimal urban water distribution design. Water Resour Res 21(5):642–652Park H, Leibman J (1993) Redundancy-constrained minimum-cost design of water distribution networks. J Water Resour Plan Manage ASCE 119(l):83–98Pinto J, Varum H, Bentes I, Agarwal J (2010) A theory of vulnerability of water pipe network. Water Resour Manag 24:4237–4254. Springer Science, Published online: 6 May 2010Quimpo R, Shamsi U (1991) Reliability-based distribution system maintenance. J Water Resour Plan Manage ASCE 117(3):321–339Su Y, Mays LW, Duan N, Lansey K (1987) Reliability based optimization model for water distribution systems. J Hydraul Eng ASCE 113(12):1539–1556Tanyimboh TT, Tabesh M, Burrows R (2001) Appraisal of source head methods for calculating reliability of water distribution networks. J Water Resour Plan Manage ASCE 127(4):206–213Walski TM, Weiler JS, Culver T (2006) Using criticality analysis to identify impact of valve location. In: Proc 8th annual water distrib systems analysis symposium, August 27–30, Cincinnati, Ohio, USA,Walters GA, Knezevic J (1989) Discussion of ‘Reliability based optimization model for water distribution systems’ by Su, Y., Mays, L. W. , Duan, N., and Lansey, K. J Hydraul Eng ASCE 115(8):1157–1158Xu C, Goulter I (1997) Simulation-based optimal design of reliable water distribution networks. In: Zayegh A (ed) Proc 3rd int conf on modeling and simulation. Victoria University of Technology, Melbourne, pp 107–112Xu C, Goulter I (1998) Probabilistic model for water distribution reliability. J Water Resour Plan Manage ASCE 124(4):218–228Xu C, Goulter I (1999) Reliability based optimal design of water distribution networks. J Water Resour Plan Manage ASCE 125(6):352–362Xu C, Goulter I (2000) A model for optimal design of reliable water distribution networks. In: Blain WR, Brebbia CA (eds) Hydraulic engineering software VIII. WIT, Southampton, pp 71–8
A <i>Tbc1d1</i><sup>Ser231Ala</sup>-knockin mutation partially impairs AICAR- but not exercise-induced muscle glucose uptake in mice
Quantitative Approach to Select Energy Benchmarking Parameters for Drinking Water Utilities
Determining pipe groupings for water distribution networks
Mathematical modeling of a water distribution system allows comparisons between design and operation alternatives. However, to make meaningful comparisons, the true field system must be represented within the model. Water distribution systems contain a large number of pipes with unknown roughness coefficients. Even with an extensive data collection effort, pipe roughnesses for all links cannot be determined exactly. Therefore, the system is simplified by assuming sets of pipes have the same roughness coefficient. The impacts of such simplification have not been examined in quantitative manner. This work develops a methodology to quantify impacts introduced by system simplification and identify the best number of pipe groupings for a network
Development and Testing of a Mobile App to Collect Social Determinants of Health Data in Cancer Settings: Interview Study
BackgroundSocial determinants of health (SDOH) such as lack of basic resources, housing, transportation, and social isolation play an important role for patients on the cancer care continuum. Health systems’ current technological solutions for identifying and managing patients’ SDOH data largely focus on information recorded in the electronic health record by providers, which is often inaccessible to patients to contribute to or modify.
ObjectiveWe developed and tested a patient-centric SDOH screening tool designed for use on patients’ personal mobile phone that preserves patient privacy and confidentiality, collects information about the unmet social needs of patients with cancer, and communicates them to the provider.
MethodsWe interviewed 22 patients with cancer, oncologists, and social workers associated with a US-based comprehensive cancer center to better understand how patients’ SDOH information is collected and reported. After triangulating data obtained from thematic analysis of interviews, an environmental scan, and a literature search of validated tools to collect SDOH data, we developed an SDOH screening tool mobile app and conducted a pilot study of 16 dyadic pairs of patients and cancer care team members at the same cancer center. We collected patient SDOH data using 36 survey items covering 7 SDOH domains and used validated scales and follow-up interviews to assess the app’s usability and acceptability among patients and cancer care team members.
ResultsFormative interviews with patients and care team members revealed that transportation, financial challenges, food insecurity, and low health literacy were common SDOH challenges and that a mobile app that collected those data, shared those data with care team members, and offered supportive resources could be useful and valuable. In the pilot study, 25% (4/16) of app-using patients reported having at least one of the abovementioned social needs; the most common social need was social isolation (7/16, 44%). Patients rated the mobile app as easy to use, accurately capturing their SDOH, and preserving their privacy but suggested that the app could be more helpful by connecting patients to actual resources. Providers reported high acceptability and usability of the app.
ConclusionsUse of a brief, patient-centric, mobile app–based SDOH screening tool can effectively capture SDOH of patients with cancer for care team members in a way that preserves patient privacy and that is acceptable and usable for patients and care team members. However, only collecting SDOH information is not sufficient; usefulness can be increased by connecting patients directly to resources to address their unmet social needs
Recommended from our members
New Methodologies for the Reliability-Based Analysis and Design of Water Distribution Systems
National Science Foundation Grant No. ECE-8511399Center for Water and the Environmen