Data-driven model of the power-grid frequency dynamics

The energy system is rapidly changing to accommodate the increasing number of renewable generators and the general transition towards a more sustainable future. Simultaneously, business models and market designs evolve, affecting power-grid operation and power-grid frequency. Problems raised by this ongoing transition are increasingly addressed by transdisciplinary research approaches, ranging from purely mathematical modelling to applied case studies. These approaches require a stochastic description of consumer behaviour, fluctuations by renewables, market rules, and how they influence the stability of the power-grid frequency. Here, we introduce an easy-to-use, data-driven, stochastic model for the power-grid frequency and demonstrate how it reproduces key characteristics of the observed statistics of the Continental European and British power grids. Using data analysis tools and a Fokker–Planck approach, we estimate parameters of our deterministic and stochastic model. We offer executable code and guidelines on how to use the model on any power grid for various mathematical or engineering applications

Discovery of lead compounds targeting the bacterial sliding clamp using a fragment-based approach

The bacterial sliding clamp (SC), also known as the DNA polymerase III β subunit, is an emerging antibacterial target that plays a central role in DNA replication, serving as a protein-protein interaction hub with a common binding pocket to recognize linear motifs in the partner proteins. Here, fragment-based screening using X-ray crystallography produced four hits bound in the linear-motif-binding pocket of the Escherichia coli SC. Compounds structurally related to the hits were identified that inhibited the E. coli SC and SC-mediated DNA replication in vitro. A tetrahydrocarbazole derivative emerged as a promising lead whose methyl and ethyl ester prodrug forms showed minimum inhibitory concentrations in the range of 21-43 μg/mL against representative Gram-negative and Gram-positive bacteria species. The work demonstrates the utility of a fragment-based approach for identifying bacterial sliding clamp inhibitors as lead compounds with broad-spectrum antibacterial activity. © 2014 American Chemical Society

Comparison of Cross-Sectional and Daily Reports in Studying the Relationship Between Depression and Use of Alcohol in Response to Stress in College Students

Alcohol use in response to stress in college students may be affected by the presence of symptoms of depression. However, this is a challenging issue to study due to the various methodologies used as well as the possible effect of depressed mood on the accuracy of self-report. This study focused on methodological issues as possible sources of equivocal findings regarding the relationship between depressed mood and alcohol use in response to stress in a college student population. Findings may differ when these variables are examined cross-sectionally versus longitudinally. Methods : Depressed mood and alcohol coping were assessed both cross-sectionally and repeatedly over time in 125 college students. Participants were assessed at baseline using a diagnostic self-report measure of depression as well as a measure of typical coping style. In addition, daily measures of stress, symptoms of depression, and coping were completed for 45 consecutive days. Results : Different relationships between depressed mood and alcohol coping were found when depressed individuals were analyzed separately from those who were not depressed. Although a significant correlation between daily use of alcohol coping and daily depressed mood was found, there were no differences between depressed and nondepressed participants (as assessed at baseline) on daily alcohol coping. Conclusions : These findings have implications for research design as well as clinical assessment regarding the relationships between mood and use of alcohol for coping; the findings suggest that cross-sectional measures of mood and alcohol use may obscure differences as assessed repeatedly over time. In addition, these findings support the utility of frequent assessment of depressive symptoms when implementing or evaluating programs that target coping skills in college students.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65757/1/j.1530-0277.2000.tb04552.x.pd

Psychological Functioning, Nonadherence and Health Outcomes After Pediatric Liver Transplantation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74689/1/j.1600-6143.2007.01878.x.pd

Comprehensive Analysis of Market Conditions in the Foreign Exchange Market: Fluctuation Scaling and Variance-Covariance Matrix

We investigate quotation and transaction activities in the foreign exchange market for every week during the period of June 2007 to December 2010. A scaling relationship between the mean values of number of quotations (or number of transactions) for various currency pairs and the corresponding standard deviations holds for a majority of the weeks. However, the scaling breaks in some time intervals, which is related to the emergence of market shocks. There is a monotonous relationship between values of scaling indices and global averages of currency pair cross-correlations when both quantities are observed for various window lengths $\Delta t$.Comment: 13 pages, 10 figure

Patterns of analgesic use, pain and self-efficacy: a cross-sectional study of patients attending a hospital rheumatology clinic

Background: Many people attending rheumatology clinics use analgesics and non-steroidal anti-inflammatories for persistent musculoskeletal pain. Guidelines for pain management recommend regular and pre-emptive use of analgesics to reduce the impact of pain. Clinical experience indicates that analgesics are often not used in this way. Studies exploring use of analgesics in arthritis have historically measured adherence to such medication. Here we examine patterns of analgesic use and their relationships to pain, self-efficacy and demographic factors. Methods: Consecutive patients were approached in a hospital rheumatology out-patient clinic. Pattern of analgesic use was assessed by response to statements such as 'I always take my tablets every day.' Pain and self-efficacy (SE) were measured using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and Arthritis Self-Efficacy Scale (ASES). Influence of factors on pain level and regularity of analgesic use were investigated using linear regression. Differences in pain between those agreeing and disagreeing with statements regarding analgesic use were assessed using t-tests. Results: 218 patients (85% of attendees) completed the study. Six (2.8%) patients reported no current pain, 26 (12.3%) slight, 100 (47.4%) moderate, 62 (29.4%) severe and 17 (8.1%) extreme pain. In multiple linear regression self efficacy and regularity of analgesic use were significant (p < 0.01) with lower self efficacy and more regular use of analgesics associated with more pain. Low SE was associated with greater pain: 40 (41.7%) people with low SE reported severe pain versus 22 (18.3%) people with high SE, p < 0.001. Patients in greater pain were significantly more likely to take analgesics regularly; 13 (77%) of those in extreme pain reported always taking their analgesics every day, versus 9 (35%) in slight pain. Many patients, including 46% of those in severe pain, adjusted analgesic use to current pain level. In simple linear regression, pain was the only variable significantly associated with regularity of analgesic use: higher levels of pain corresponded to more regular analgesic use (p = 0.003). Conclusion: Our study confirms that there is a strong inverse relationship between self-efficacy and pain severity. Analgesics are often used irregularly by people with arthritis, including some reporting severe pain

Complexity and Persistence of Price Time Series of the European Electricity Spot Market

The large variability of renewable power sources is a central challenge in the transition to a sustainable energy system. Electricity markets are central for the coordination of electric power generation. These markets rely evermore on short-term trading to facilitate the balancing of power generation and demand and to enable systems integration of small producers. Electricity prices in these spot markets show pronounced fluctuations, featuring extreme peaks as well as occasional negative prices. In this article, we analyze electricity price time series from the European Power Exchange market, in particular the hourly day-ahead, hourly intraday, and 15-min intraday market prices. We quantify the fluctuations, correlations, and extreme events and reveal different time scales in the dynamics of the market. The short-term fluctuations show remarkably different characteristics for time scales below and above 12 h. Fluctuations are strongly correlated and persistent below 12 h, which contributes to extreme price events and a strong multifractal behavior. On longer time scales, they get anticorrelated and price time series revert to their mean, witnessed by a stark decrease of the Hurst coefficient after 12 h. The long-term behavior is strongly influenced by the evolution of a large-scale weather pattern with a typical time scale of four days. We elucidate this dependence in detail using a classification into circulation weather types. The separation in time scales enables a superstatistical treatment, which confirms the characteristic time scale of four days, and motivates the use of q-Gaussian distributions as the best fit to the empiric distribution of electricity prices

Theoretical Models of Sunspot Structure and Dynamics

Recent progress in theoretical modeling of a sunspot is reviewed. The observed properties of umbral dots are well reproduced by realistic simulations of magnetoconvection in a vertical, monolithic magnetic field. To understand the penumbra, it is useful to distinguish between the inner penumbra, dominated by bright filaments containing slender dark cores, and the outer penumbra, made up of dark and bright filaments of comparable width with corresponding magnetic fields differing in inclination by some 30 degrees and strong Evershed flows in the dark filaments along nearly horizontal or downward-plunging magnetic fields. The role of magnetic flux pumping in submerging magnetic flux in the outer penumbra is examined through numerical experiments, and different geometric models of the penumbral magnetic field are discussed in the light of high-resolution observations. Recent, realistic numerical MHD simulations of an entire sunspot have succeeded in reproducing the salient features of the convective pattern in the umbra and the inner penumbra. The siphon-flow mechanism still provides the best explanation of the Evershed flow, particularly in the outer penumbra where it often consists of cool, supersonic downflows.Comment: To appear in "Magnetic Coupling between the Interior and the Atmosphere of the Sun", eds. S.S. Hasan and R.J. Rutten, Astrophysics and Space Science Proceedings, Springer-Verlag, Heidelberg, Berlin, 200

The Evershed Flow and the Brightness of the Penumbra

The Evershed flow is a systematic motion of gas that occurs in the penumbra of all sunspots. Discovered in 1909, it still lacks a satisfactory explanation. We know that the flow is magnetized, often supersonic, and that it shows conspicuous fine structure on spatial scales of 0.2"-0.3", but its origin remains unclear. The hope is that a good observational understanding of the relation between the flow and the penumbral magnetic field will help us determine its nature. Here I review advances in the characterization of the Evershed flow and sunspot magnetic fields from high-resolution spectroscopic and spectropolarimetric measurements. Using this information as input for 2D heat transfer simulations, it has been demonstrated that hot Evershed upflows along nearly horizontal field lines are capable of explaining one of the most intriguing aspects of sunspots: the surplus brightness of the penumbra relative to the umbra. They also explain the existence of penumbral filaments with dark cores. These results support the idea that the Evershed flow is largely responsible for the transport of energy in the penumbra.Comment: 18 pages, to appear in "Magnetic Coupling between the Interior and the Atmosphere of the Sun", eds. S.S. Hasan and R.J. Rutten, Astrophysics and Space Science Proceedings, Springer, Heidelberg, 200

Individualization as driving force of clustering phenomena in humans

One of the most intriguing dynamics in biological systems is the emergence of clustering, the self-organization into separated agglomerations of individuals. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is clustering of opinions in human populations. The puzzle is particularly pressing if opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing opinion formation models suggest that "monoculture" is unavoidable in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness did not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution of the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct simulation experiments to demonstrate that with this kind of noise, a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting.Comment: 12 pages, 4 figure