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The quantum Hall effect arises from the quantum behavior of two-dimensional, strongly-interacting electrons exposed to a strong, perpendicular magnetic field [1, 2]. Conventionally treated from a many-body perspective, we instead treat the system from the few-body perspective using collective coordinates and the hyperspherical adiabatic technique developed originally for atomic systems [3]. The grand angular momentum K from K-harmonic few-body theory, is shown to be an approximate good collective quantum number in this system, and is shown to correlate with known fractional quantum Hall (FQH) states at experimentally observed filling factors.

Bruce Peyser,1 Kathryn A Daily,2 Nicholas M Hudak,3 Kenyon Railey,3 Hayden B Bosworth1,41Department of Medicine, Division of General Internal Medicine, Duke University Medical Center, Durham, NC, USA; 2Duke University Medical Center, Durham, NC, USA; 3Department of Community and Family Medicine, Physician Assistant Program, Duke University, Durham, NC, USA; 4Center for Health Services Research in Primary Care, Durham Veterans Affairs Medical Center, Durham, NC, USAPurpose: To explore the barriers and incentives that affect primary care providers who precept students in outpatient clinics in the US.Method: In 2013, leadership of our large primary care group sent a 20-question survey via e-mail to all of the 180 providers within the network. The survey assessed provider demographics, precepting history, learner preferences, and other issues that might affect future decisions about teaching.Results: The response rate was 50% (90 providers). The top reasons for precepting in the past were enjoyment for teaching and personal interaction with learners. The most commonly cited reason for not precepting previously was a perceived lack of time followed by increased productivity demands. When questioned about the future, 65% (59 respondents) indicated that they were likely to precept within the next 6 months. A desired reduction in productivity expectations was the most commonly cited motivator, followed by anticipated monetary compensation and adjusted appointment times. A top barrier to future precepting was a belief that teaching decreases productivity and requires large amounts of time.Conclusion: This survey represents an opportunity to study a change in focus for a cohort of busy clinicians who were mostly new to teaching but not new to clinical practice. The survey provides further insight into clinician educators' perceptions regarding the education of a variety of different learners. The results align with data from previous studies in that time pressures and productivity demands transcend specific programs and learner backgrounds. This information is critical for future clerkship directors and hospital administrators in order to understand how to increase support for potential preceptors in medical education.Keywords: clinical teaching, medical education, preceptors, primary care

Abstract Background Quality improvement (QI) programs focused on mastery of content by individual staff members are the current standard to improve resident outcomes in nursing homes. However, complexity science suggests that learning is a social process that occurs within the context of relationships and interactions among individuals. Thus, QI programs will not result in optimal changes in staff behavior unless the context for social learning is present. Accordingly, we developed CONNECT, an intervention to foster systematic use of management practices, which we propose will enhance effectiveness of a nursing home Falls QI program by strengthening the staff-to-staff interactions necessary for clinical problem-solving about complex problems such as falls. The study aims are to compare the impact of the CONNECT intervention, plus a falls reduction QI intervention (CONNECT + FALLS), to the falls reduction QI intervention alone (FALLS), on fall-related process measures, fall rates, and staff interaction measures. Methods/design Sixteen nursing homes will be randomized to one of two study arms, CONNECT + FALLS or FALLS alone. Subjects (staff and residents) are clustered within nursing homes because the intervention addresses social processes and thus must be delivered within the social context, rather than to individuals. Nursing homes randomized to CONNECT + FALLS will receive three months of CONNECT first, followed by three months of FALLS. Nursing homes randomized to FALLS alone receive three months of FALLs QI and are offered CONNECT after data collection is completed. Complexity science measures, which reflect staff perceptions of communication, safety climate, and care quality, will be collected from staff at baseline, three months after, and six months after baseline to evaluate immediate and sustained impacts. FALLS measures including quality indicators (process measures) and fall rates will be collected for the six months prior to baseline and the six months after the end of the intervention. Analysis will use a three-level mixed model. Discussion By focusing on improving local interactions, CONNECT is expected to maximize staff's ability to implement content learned in a falls QI program and integrate it into knowledge and action. Our previous pilot work shows that CONNECT is feasible, acceptable and appropriate. Trial Registration ClinicalTrials.gov: NCT00636675

Abstract Background A central challenge of biology is to map and understand gene regulation on a genome-wide scale. For any given genome, only a small fraction of the regulatory elements embedded in the DNA sequence have been characterized, and there is great interest in developing computational methods to systematically map all these elements and understand their relationships. Such computational efforts, however, are significantly hindered by the overwhelming size of non-coding regions and the statistical variability and complex spatial organizations of regulatory elements and interactions. Genome-wide catalogs of regulatory elements for all model species simply do not yet exist. Results The MotifMap system uses databases of transcription factor binding motifs, refined genome alignments, and a comparative genomic statistical approach to provide comprehensive maps of candidate regulatory elements encoded in the genomes of model species. The system is used to derive new genome-wide maps for yeast, fly, worm, mouse, and human. The human map contains 519,108 sites for 570 matrices with a False Discovery Rate of 0.1 or less. The new maps are assessed in several ways, for instance using high-throughput experimental ChIP-seq data and AUC statistics, providing strong evidence for their accuracy and coverage. The maps can be usefully integrated with many other kinds of omic data and are available at http://motifmap.igb.uci.edu/. Conclusions MotifMap and its integration with other data provide a foundation for analyzing gene regulation on a genome-wide scale, and for automatically generating regulatory pathways and hypotheses. The power of this approach is demonstrated and discussed using the P53 apoptotic pathway and the Gli hedgehog pathways as examples.

Abstract Background High-throughput sequencing (HTS) technologies play important roles in the life sciences by allowing the rapid parallel sequencing of very large numbers of relatively short nucleotide sequences, in applications ranging from genome sequencing and resequencing to digital microarrays and ChIP-Seq experiments. As experiments scale up, HTS technologies create new bioinformatics challenges for the storage and sharing of HTS data. Results We develop data structures and compression algorithms for HTS data. A processing stage maps short sequences to a reference genome or a large table of sequences. Then the integers representing the short sequence absolute or relative addresses, their length, and the substitutions they may contain are compressed and stored using various entropy coding algorithms, including both old and new fixed codes (e.g Golomb, Elias Gamma, MOV) and variable codes (e.g. Huffman). The general methodology is illustrated and applied to several HTS data sets. Results show that the information contained in HTS files can be compressed by a factor of 10 or more, depending on the statistical properties of the data sets and various other choices and constraints. Our algorithms fair well against general purpose compression programs such as gzip, bzip2 and 7zip; timing results show that our algorithms are consistently faster than the best general purpose compression programs. Conclusions It is not likely that exactly one encoding strategy will be optimal for all types of HTS data. Different experimental conditions are going to generate various data distributions whereby one encoding strategy can be more effective than another. We have implemented some of our encoding algorithms into the software package GenCompress which is available upon request from the authors. With the advent of HTS technology and increasingly new experimental protocols for using the technology, sequence databases are expected to continue rising in size. The methodology we have proposed is general, and these advanced compression techniques should allow researchers to manage and share their HTS data in a more timely fashion.