Electromagnetics from a quasistatic perspective

Quasistatics is introduced so that it fits smoothly into the standard textbook presentation of electrodynamics. The usual path from statics to general electrodynamics is rather short and surprisingly simple. A closer look reveals however that it is not without confusing issues as has been illustrated by many contributions to this Journal. Quasistatic theory is conceptually useful by providing an intermediate level in between statics and the full set of Maxwell's equations. Quasistatics is easier than general electrodynamics and in some ways more similar to statics. It is however, in terms of interesting physics and important applications, far richer than statics. Quasistatics is much used in electromagnetic modeling, an activity that today is possible on a PC and which also has great pedagogical potential. The use of electromagnetic simulations in teaching gives additional support for the importance of quasistatics. This activity may also motivate some change of focus in the presentation of basic electrodynamics

Analytical reasoning task reveals limits of social learning in networks

Social learning -by observing and copying others- is a highly successful cultural mechanism for adaptation, outperforming individual information acquisition and experience. Here, we investigate social learning in the context of the uniquely human capacity for reflective, analytical reasoning. A hallmark of the human mind is our ability to engage analytical reasoning, and suppress false associative intuitions. Through a set of lab-based network experiments, we find that social learning fails to propagate this cognitive strategy. When people make false intuitive conclusions, and are exposed to the analytic output of their peers, they recognize and adopt this correct output. But they fail to engage analytical reasoning in similar subsequent tasks. Thus, humans exhibit an 'unreflective copying bias,' which limits their social learning to the output, rather than the process, of their peers' reasoning -even when doing so requires minimal effort and no technical skill. In contrast to much recent work on observation-based social learning, which emphasizes the propagation of successful behavior through copying, our findings identify a limit on the power of social networks in situations that require analytical reasoning

An efficient and principled method for detecting communities in networks

A fundamental problem in the analysis of network data is the detection of network communities, groups of densely interconnected nodes, which may be overlapping or disjoint. Here we describe a method for finding overlapping communities based on a principled statistical approach using generative network models. We show how the method can be implemented using a fast, closed-form expectation-maximization algorithm that allows us to analyze networks of millions of nodes in reasonable running times. We test the method both on real-world networks and on synthetic benchmarks and find that it gives results competitive with previous methods. We also show that the same approach can be used to extract nonoverlapping community divisions via a relaxation method, and demonstrate that the algorithm is competitively fast and accurate for the nonoverlapping problem.Comment: 14 pages, 5 figures, 1 tabl

Meta-Reinforcement Learning for the Tuning of PI Controllers: An Offline Approach

Meta-learning is a branch of machine learning which trains neural network models to synthesize a wide variety of data in order to rapidly solve new problems. In process control, many systems have similar and well-understood dynamics, which suggests it is feasible to create a generalizable controller through meta-learning. In this work, we formulate a meta reinforcement learning (meta-RL) control strategy that can be used to tune proportional--integral controllers. Our meta-RL agent has a recurrent structure that accumulates "context" to learn a system's dynamics through a hidden state variable in closed-loop. This architecture enables the agent to automatically adapt to changes in the process dynamics. In tests reported here, the meta-RL agent was trained entirely offline on first order plus time delay systems, and produced excellent results on novel systems drawn from the same distribution of process dynamics used for training. A key design element is the ability to leverage model-based information offline during training in simulated environments while maintaining a model-free policy structure for interacting with novel processes where there is uncertainty regarding the true process dynamics. Meta-learning is a promising approach for constructing sample-efficient intelligent controllers.Comment: 23 pages; postprin

Mesoscopic structure and social aspects of human mobility

The individual movements of large numbers of people are important in many contexts, from urban planning to disease spreading. Datasets that capture human mobility are now available and many interesting features have been discovered, including the ultra-slow spatial growth of individual mobility. However, the detailed substructures and spatiotemporal flows of mobility - the sets and sequences of visited locations - have not been well studied. We show that individual mobility is dominated by small groups of frequently visited, dynamically close locations, forming primary "habitats" capturing typical daily activity, along with subsidiary habitats representing additional travel. These habitats do not correspond to typical contexts such as home or work. The temporal evolution of mobility within habitats, which constitutes most motion, is universal across habitats and exhibits scaling patterns both distinct from all previous observations and unpredicted by current models. The delay to enter subsidiary habitats is a primary factor in the spatiotemporal growth of human travel. Interestingly, habitats correlate with non-mobility dynamics such as communication activity, implying that habitats may influence processes such as information spreading and revealing new connections between human mobility and social networks.Comment: 7 pages, 5 figures (main text); 11 pages, 9 figures, 1 table (supporting information

The effects of continued azacitidine treatment cycles on response in higher risk patients with myelodysplastic syndromes: an update

The international, phase III, multi-centre AZA-001 trial demonstrated azacitidine (AZA) is the first treatment to significantly extend overall survival (OS) in higher risk myelodysplastic syndromes (MDS) patients (Fenaux (2007) Blood 110 817). The current treatment paradigm, which is based on a relationship between complete remission (CR) and survival, is increasingly being questioned (Cheson (2006) Blood 108 419). Results of AZA-001 show CR is sufficient but not necessary to prolong OS (List (2008) Clin Oncol 26 7006). Indeed, the AZA CR rate in AZA-001 was modest (17%), while partial remission (PR, 12%) and haematological improvement (HI, 49%) were also predictive of prolonged survival. This analysis was conducted to assess the median number of AZA treatment cycles associated with achievement of first response, as measured by IWG 2000-defined CR, PR or HI (major + minor). The number of treatment cycles from first response to best response was also measured

Azacitidine prolongs overall survival and reduces infections and hospitalizations in patients with WHO-defined acute myeloid leukaemia compared with conventional care regimens: an update

Azacitidine (AZA), as demonstrated in the phase III trial (AZA-001), is the first MDS treatment to significantly prolong overall survival (OS) in higher risk MDS pts ((2007) Blood 110 817). Approximately, one-third of the patients (pts) enrolled in AZA-001 were FAB RAEB-T (≥20–30% blasts) and now meet the WHO criteria for acute myeloid leukaemia (AML) ((1999) Blood 17 3835). Considering the poor prognosis (median survival <1 year) and the poor response to chemotherapy in these pts, this sub-group analysis evaluated the effects of AZA versus conventional care regimens (CCR) on OS and on response rates in pts with WHO AML

Circadian hormone secretory profiles in women with severe premenstrual tension syndrome.

The circadian secretory profiles of serum prolactin, growth hormone and cortisol were measured in two women suffering from severe premenstrual tension syndrome and in two asymptomatic control subjects. Subjects and controls were screened and included after a rigorous selection process. Blood samples were obtained every 30 min over a period of 24 h in each woman both on day 9 (follicular phase) and day 26 (luteal phase) of the menstrual cycle. There was no relationship between the hormonal secretory profiles and the premenstrual tension syndrome.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75119/1/j.1471-0528.1984.tb04785.x.pd

General lack of global dosage compensation in ZZ/ZW systems? Broadening the perspective with RNA-seq

Background Species with heteromorphic sex chromosomes face the challenge of large-scale imbalance in gene dose. Microarray-based studies in several independent male heterogametic XX/XY systems suggest that dosage compensation mechanisms are in place to mitigate the detrimental effects of gene dose differences. However, recent genomic research on female heterogametic ZZ/ZW systems has generated surprising results. In two bird species and one lepidopteran no evidence for a global dosage compensating mechanism has been found. The recent advent of massively parallel RNA sequencing now opens up the possibility to gauge the generality of this observation with a broader phylogenetic sampling. It further allows assessing the validity of microarray-based inference on dosage compensation with a novel technology. Results We here expemplify this approach using massively parallel sequencing on barcoded individuals of a bird species, the European crow (Corvus corone), where previously no genetic resources were available. Testing for Z-linkage with quantitative PCR (qPCR,) we first establish that orthology with distantly related species (chicken, zebra finch) can be used as a good predictor for chromosomal affiliation of a gene. We then use a digital measure of gene expression (RNA-seq) on brain transcriptome and confirm a global lack of dosage compensation on the Z chromosome. RNA-seq estimates of male-to-female (m:f) expression difference on the Z compare well to previous microarray-based estimates in birds and lepidopterans. The data further lends support that an up-regulation of female Z-linked genes conveys partial compensation and suggest a relationship between sex-bias and absolute expression level of a gene. Correlation of sex-biased gene expression on the Z chromosome across all three bird species further suggests that the degree of compensation has been partly conserved across 100 million years of avian evolution. Conclusions This work demonstrates that the study of dosage compensation has become amenable to species where previously no genetic resources were available. Massively parallele transcriptome sequencing allows re-assessing the degree of dosage compensation with a novel tool in well-studies species and, in addition, gain valuable insights into the generality of mechanisms across independent taxonomic group for both the XX/XY and ZZ/ZW system