Impact of spatiotemporal heterogeneity in heat pump loads on generation and storage requirements

This paper investigates how spatiotemporal heterogeneity in inflexible residential heat pump loads affects the need for storage and generation in the electricity system under business-as-usual and low-carbon emissions budgets. Homogeneous and heterogeneous heat pump loads are generated using population-weighted average and local temperature, respectively, assuming complete residential heat pump penetration. The results of a storage and generation optimal expansion model with network effects for spatiotemporally homogeneous and heterogeneous load profiles are compared. A case study is performed using a 3-bus network of London, Manchester, and Glasgow in Britain for load and weather data for representative weeks. Using heterogeneous heating demand data changes storage sizing: under a business-as-usual budget, 26% more total storage is built on an energy and power basis, and this storage is distributed among all of the buses in the heterogeneous case. Under a low-carbon budget, total energy storage at all buses increases 2 times on an energy basis and 40% on a power basis. The energy to power ratio of storage at each bus also increases when accounting for heterogeneity; this change suggests that storage will be needed to provide energy support in addition to power support for electric heating in high-renewable power systems. Accounting for heterogeneity also increases modeled systems costs, particularly capital costs, because of the need for higher generation capacity in the largest load center and coincidence of local peak demand at different buses. These results show the importance of accounting for heat pump load heterogeneity in power system planning.Comment: 6 pages, 4 figures, to be published in the proceedings of the IEEE Power and Energy Society General Meeting 202

Data-based, high spatiotemporal resolution heat pump demand for power system planning

Decarbonizing the residential building sector by replacing gas boilers with electric heat pumps will dramatically increase electricity demand. Existing models of future heat pump demand either use daily heating demand profiles that do not capture heat pump use or do not represent sub-national heating demand variation. This work presents a novel method to generate high spatiotemporal resolution residential heat pump demand profiles based on heat pump field trial data. These spatially varied demand profiles are integrated into a generation, storage, and transmission expansion planning model to assess the impact of spatiotemporal variations in heat pump demand. This method is demonstrated and validated using the British power system in the United Kingdom (UK), and the results are compared with those obtained using spatially uniform demand profiles. The results show that while spatially uniform heating demand can be used to estimate peak and total annual heating demand and grid-wide systems cost, high spatiotemporal resolution heating demand data is crucial for spatial power system planning. Using spatially uniform heating demand profiles leads to 15.1 GW of misplaced generation and storage capacity for a 90% carbon emission reduction from 2019. For a 99% reduction in carbon emissions, the misallocated capacity increases to 16.9-23.9 GW. Meeting spatially varied heating load with the system planned for uniform national heating demand leads to 5% higher operational costs for a 90% carbon emission reduction. These results suggest that high spatiotemporal resolution heating demand data is especially important for planning bulk power systems with high shares of renewable generation

The limits of inter-religious dialogue and the form of football rituals: The case of Bosnia-Herzegovina

The difficulties with interfaith dialogue are linked, at least in part, to the lack of ritual forms (consisting of rules, ceremonial idioms, liturgy, and repertoires of action) designed to unite and integrate the "meta-group "formed by the various religious communities. By means of ethnographic research conducted in Bosnia-Herzegovina, the author studied the mechanisms with which, under particular conditions, some forms of collective ritual were able to create opportunities for the re-integration of the Bosnian population, which had been profoundly divided after the terrible war of 199295. Comparing the forms of religious rituals and those of sports ritualsin particular, of football ritualsthe author develops some considerations that can be applied to the general debate about inter-religious dialogue. The comparison brings to light some of the limits and difficulties that religious institutions encounter in giving life to an interfaith dialogue that directly and concretely involves the members of different communities. © 2007 Social Compass

Identification of baryon resonances in central heavy-ion collisions at energies between 1 and 2 AGeV

The mass distributions of baryon resonances populated in near-central collisions of Au on Au and Ni on Ni are deduced by defolding the $p_t$ spectra of charged pions by a method which does not depend on a specific resonance shape. In addition the mass distributions of resonances are obtained from the invariant masses of $(p, \pi^{\pm})$ pairs. With both methods the deduced mass distributions are shifted by an average value of -60 MeV/c$^2$ relative to the mass distribution of the free $\Delta(1232)$ resonance, the distributions descent almost exponentially towards mass values of 2000 MeV/c^2. The observed differences between $(p, \pi^-)$ and $(p, \pi^+)$ pairs indicate a contribution of isospin $I = 1/2$ resonances. The attempt to consistently describe the deduced mass distributions and the reconstructed kinetic energy spectra of the resonances leads to new insights about the freeze out conditions, i.e. to rather low temperatures and large expansion velocities.Comment: 30 pages, 13 figures, Latex using documentstyle[12pt,a4,epsfig], to appear in Eur. Phys. J.

Prediction of Preterm Deliveries from EHG Signals Using Machine Learning

There has been some improvement in the treatment of preterm infants, which has helped to increase their chance of survival. However, the rate of premature births is still globally increasing. As a result, this group of infants are most at risk of developing severe medical conditions that can affect the respiratory, gastrointestinal, immune, central nervous, auditory and visual systems. In extreme cases, this can also lead to long-term conditions, such as cerebral palsy, mental retardation, learning difficulties, including poor health and growth. In the US alone, the societal and economic cost of preterm births, in 2005, was estimated to be $26.2 billion, per annum. In the UK, this value was close to £2.95 billion, in 2009. Many believe that a better understanding of why preterm births occur, and a strategic focus on prevention, will help to improve the health of children and reduce healthcare costs. At present, most methods of preterm birth prediction are subjective. However, a strong body of evidence suggests the analysis of uterine electrical signals (Electrohysterography), could provide a viable way of diagnosing true labour and predict preterm deliveries. Most Electrohysterography studies focus on true labour detection during the final seven days, before labour. The challenge is to utilise Electrohysterography techniques to predict preterm delivery earlier in the pregnancy. This paper explores this idea further and presents a supervised machine learning approach that classifies term and preterm records, using an open source dataset containing 300 records (38 preterm and 262 term). The synthetic minority oversampling technique is used to oversample the minority preterm class, and cross validation techniques, are used to evaluate the dataset against other similar studies. Our approach shows an improvement on existing studies with 96% sensitivity, 90% specificity, and a 95% area under the curve value with 8% global error using the polynomial classifier

Uterine electromyography for discrimination of labor imminence in women with threatened preterm labor under tocolytic treatment

[EN] As one of the main aims of obstetrics is to be able to detect imminent delivery in patients with threatened preterm labor, the techniques currently used in clinical practice have serious limitations in this respect. The electrohysterogram (EHG) has now emerged as an alternative technique, providing relevant information about labor onset when recorded in controlled checkups without administration of tocolytic drugs. The studies published to date mainly focus on EHG-burst analysis and, to a lesser extent, on whole EHG window analysis. The study described here assessed the ability of EHG signals to discriminate imminent labor (The ability of EHG recordings to predict imminent labor (<7days) was analyzed in preterm threatened patients undergoing tocolytic therapies by means of EHG-burst and whole EHG window analysis. The non-linear features were found to have better performance than the temporal and spectral parameters in separating women who delivered in less than 7days from those who did not.Mas-Cabo, J.; Prats-Boluda, G.; Perales Marín, AJ.; Garcia-Casado, J.; Alberola Rubio, J.; Ye Lin, Y. (2019). Uterine electromyography for discrimination of labor imminence in women with threatened preterm labor under tocolytic treatment. Medical & Biological Engineering & Computing. 57:401-411. https://doi.org/10.1007/s11517-018-1888-yS40141157Aboy M, Cuesta-Frau D, Austin D, Micó-Tormos P (2007) Characterization of sample entropy in the context of biomedical signal analysis. Conf Proc IEEE Eng Med Biol Soc:5942–5945. https://doi.org/10.1109/IEMBS.2007.4353701Aboy M, Hornero R, Abásolo D, Álvarez D (2006) Interpretation of the Lempel-Ziv complexity measure in the context of biomedical signal analysis. IEEE Trans Biomed Eng 53:2282–2288. https://doi.org/10.1109/TBME.2006.883696Chkeir A, Fleury MJ, Karlsson B, Hassan M, Marque C (2013) Patterns of electrical activity synchronization in the pregnant rat uterus. Biomed 3:140–144. https://doi.org/10.1016/j.biomed.2013.04.007Crandon AJ (1979) Maternal anxiety and neonatal wellbeing. J Psychosom Res 23:113–115. https://doi.org/10.1016/0022-3999(79)90015-1Devedeux D, Marque C, Mansour S, Germain G, Duchêne J (1993) Uterine electromyography: a critical review. Am J Obstet Gynecol 169:1636–1653. https://doi.org/10.1016/0002-9378(93)90456-SFele-Žorž G, Kavšek G, Novak-Antolič Ž, Jager F (2008) A comparison of various linear and non-linear signal processing techniques to separate uterine EMG records of term and pre-term delivery groups. Med Biol Eng Comput 46:911–922. https://doi.org/10.1007/s11517-008-0350-yFergus P, Cheung P, Hussain A, al-Jumeily D, Dobbins C, Iram S (2013) Prediction of preterm deliveries from EHG signals using machine learning. PLoS One 8:e77154. https://doi.org/10.1371/journal.pone.0077154Garfield RE, Maner WL (2006) Biophysical methods of prediction and prevention of preterm labor: uterine electromyography and cervical light-induced fluorescence—new obstetrical diagnostic techniques. In: Preterm Birth pp 131–144Garfield RE, Maner WL (2007) Physiology and electrical activity of uterine contractions. Semin Cell Dev Biol 18:289–295. https://doi.org/10.1016/j.semcdb.2007.05.004Garfield RE, Maner WL, MacKay LB et al (2005) Comparing uterine electromyography activity of antepartum patients versus term labor patients. Am J Obstet Gynecol 193:23–29. https://doi.org/10.1016/j.ajog.2005.01.050Goldenberg RL, Culhane JF, Iams JD, Romero R (2008) Epidemiology and causes of preterm birth. Lancet 371:75–84. https://doi.org/10.1016/S0140-6736(08)60074-4American College of Obstetricians and Gynecologists and Committee on Practice Bulletins— Obstetrics (2012) Practice bulletin no. 127. Obstet Gynecol 119(6):1308–1317.Hadar E, Biron-Shental T, Gavish O, Raban O, Yogev Y (2015) A comparison between electrical uterine monitor, tocodynamometer and intra uterine pressure catheter for uterine activity in labor. J Matern Neonatal Med 28:1367–1374. https://doi.org/10.3109/14767058.2014.954539Hans P, Dewandre P, Brichant JF, Bonhomme V (2005) Comparative effects of ketamine on Bispectral Index and spectral entropy of the electroencephalogram under sevoflurane anaesthesia. Br J Anaesth 94:336–340. https://doi.org/10.1093/bja/aei047Hassan M, Terrien J, Marque C, Karlsson B (2011) Comparison between approximate entropy, correntropy and time reversibility: application to uterine electromyogram signals. Med Eng Phys 33:980–986. https://doi.org/10.1016/j.medengphy.2011.03.010Hassan M, Terrien J, Muszynski C et al (2013) Better pregnancy monitoring using nonlinear correlation analysis of external uterine electromyography. IEEE Trans Biomed Eng 60:1160–1166. https://doi.org/10.1109/TBME.2012.2229279Horoba K, Jezewski J, Matonia A, Wrobel J, Czabanski R, Jezewski M (2016) Early predicting a risk of preterm labour by analysis of antepartum electrohysterograhic signals. Biocybern Biomed Eng 36:574–583. https://doi.org/10.1016/j.bbe.2016.06.004Lawn JE, Wilczynska-Ketende K, Cousens SN (2006) Estimating the causes of 4 million neonatal deaths in the year 2000. Int J Epidemiol 35:706–718. https://doi.org/10.1093/ije/dyl043Lemancewicz A, Borowska M, Kuć P, Jasińska E, Laudański P, Laudański T, Oczeretko E (2016) Early diagnosis of threatened premature labor by electrohysterographic recordings—the use of digital signal processing. Biocybern Biomed Eng 36:302–307. https://doi.org/10.1016/j.bbe.2015.11.005M L WLM, LR C (2012) Noninvasive uterine electromyography for prediction of preterm delivery. Am J Obstet Gynecol 204:1–20. https://doi.org/10.1016/j.ajog.2010.09.024.NoninvasiveManer WL, Garfield RE (2007) Identification of human term and preterm labor using artificial neural networks on uterine electromyography data. Ann Biomed Eng 35:465–473. https://doi.org/10.1007/s10439-006-9248-8Maner WL, Garfield RE, Maul H, Olson G, Saade G (2003) Predicting term and preterm delivery with transabdominal uterine electromyography. Obstet Gynecol 101:1254–1260. https://doi.org/10.1016/S0029-7844(03)00341-7Marque C, Gondry J (1999) Use of the electrohysterogram signal for characterization of contractions during pregnancy. IEEE Trans Biomed Eng 46:1222–1229Maul H, Maner WL, Olson G, Saade GR, Garfield RE (2004) Non-invasive transabdominal uterine electromyography correlates with the strength of intrauterine pressure and is predictive of labor and delivery. J Matern Fetal Neonatal Med 15:297–301Mischi M, Chen C, Ignatenko T, de Lau H, Ding B, Oei SGG, Rabotti C (2018) Dedicated entropy measures for early assessment of pregnancy progression from single-channel electrohysterography. IEEE Trans Biomed Eng 65:875–884. https://doi.org/10.1109/TBME.2017.2723933Most O, Langer O, Kerner R, Ben David G, Calderon I (2008) Can myometrial electrical activity identify patients in preterm labor? Am J Obstet Gynecol 199:378. https://doi.org/10.1016/j.ajog.2008.08.003Petrou S (2005) The economic consequences of preterm birth during the first 10 years of life. BJOG 112:10–15. https://doi.org/10.1111/j.1471-0528.2005.00577.xRabotti C, Sammali F, Kuijsters N, et al (2015) Analysis of uterine activity in nonpregnant women by electrohysterography: a feasibility study. In: Proc Annu Int Conf IEEE Eng Med Biol Soc EMBS pp 5916–5919Schlembach D, Maner WL, Garfield RE, Maul H (2009) Monitoring the progress of pregnancy and labor using electromyography. Eur J Obstet Gynecol Reprod Biol 144:2–8. https://doi.org/10.1016/j.ejogrb.2009.02.016Sikora J, Matonia A, Czabański R et al (2011) Recognition of premature threatening labour symptoms from bioelectrical uterine activity signals. Arch Perinat Med 17:97–103Vinken MPGC, Rabotti C, Mischi M, van Laar JOEH, Oei SG (2010) Nifedipine-induced changes in the electrohysterogram of preterm contractions: feasibility in clinical practice. Obstet Gynecol Int 2010:325635. https://doi.org/10.1155/2010/325635Vrhovec J, Lebar AM (2012) An uterine electromyographic activity as a measure of labor progression. Appl EMG Clin Sport Med 243–268. doi: https://doi.org/10.5772/25526Vrhovec J, Macek-Lebar A, Rudel D (2007) Evaluating uterine electrohysterogram with entropy. 11th Mediterr Conf Med Biomed Eng Comput 144–147. https://doi.org/10.1007/978-3-540-73044-6_36Ye-Lin Y, Bueno-Barrachina JM, Prats-boluda G, Rodriguez de Sanabria R, Garcia-Casado J (2017) Wireless sensor node for non-invasive high precision electrocardiographic signal acquisition based on a multi-ring electrode. Measurement 97:195–202. https://doi.org/10.1016/J.MEASUREMENT.2016.11.009Ye-Lin Y, Garcia-Casado J, Prats-Boluda G, Alberola-Rubio J, Perales A (2014) Automatic identification of motion artifacts in EHG recording for robust analysis of uterine contractions. Comput Math Methods Med 2014:1–11. https://doi.org/10.1155/2014/470786Zhang XS, Roy RJ, Jensen EW (2001) EEG complexity as a measure of depth of anesthesia for patients. IEEE Trans Biomed Eng 48:1424–1433. https://doi.org/10.1109/10.96660

Public understanding of food risks in four European countries: a qualitative study.

BACKGROUND: In the wake of the 'bovine spongiform encephalopathy (BSE) crisis' there was renewed interest in how those responsible for public health could take account of public views, both to 'democratize' policy making and to increase the likelihood of information about health risks resonating with public concerns. This study explored how members of the public in four European countries (Finland, Germany, Italy and the UK) understood food risks in general, and risks arising from BSE in particular. The aims were to identify the sources of knowledge used and trusted by the public and to explore how public views could be accessed for public health information policy. METHODS: Thirty-six focus group interviews were held using a common protocol across the four countries, including people from four life-cycle stages. RESULTS: The study demonstrated the utility of using focus groups as a relatively efficient method for accessing public views, and the feasibility of cross-national qualitative research on public views. We found that public views of food risks are neither irrational nor naïve, but that they do need to be interpreted in the context of everyday food purchasing decisions, in which particular food risks are unlikely to have the same salience as they do for experts. CONCLUSIONS: Focus groups are a feasible method for accessing public knowledge on public health risks to inform information strategies