Transient scaling and resurgence of chimera states in networks of Boolean phase oscillators

We study networks of non-locally coupled electronic oscillators that can be described approximately by a Kuramoto-like model. The experimental networks show long complex transients from random initial conditions on the route to network synchronization. The transients display complex behaviors, including resurgence of chimera states, which are network dynamics where order and disorder coexists. The spatial domain of the chimera state moves around the network and alternates with desynchronized dynamics. The fast timescale of our oscillators (on the order of $100\;\mathrm{ns}$) allows us to study the scaling of the transient time of large networks of more than a hundred nodes, which has not yet been confirmed previously in an experiment and could potentially be important in many natural networks. We find that the average transient time increases exponentially with the network size and can be modeled as a Poisson process in experiment and simulation. This exponential scaling is a result of a synchronization rate that follows a power law of the phase-space volume.Comment: http://journals.aps.org/pre/abstract/10.1103/PhysRevE.90.03090

Reservoir computing with a single time-delay autonomous Boolean node

We demonstrate reservoir computing with a physical system using a single autonomous Boolean logic element with time-delay feedback. The system generates a chaotic transient with a window of consistency lasting between 30 and 300 ns, which we show is sufficient for reservoir computing. We then characterize the dependence of computational performance on system parameters to find the best operating point of the reservoir. When the best parameters are chosen, the reservoir is able to classify short input patterns with performance that decreases over time. In particular, we show that four distinct input patterns can be classified for 70 ns, even though the inputs are only provided to the reservoir for 7.5 ns.Comment: 5 pages, 5 figure

Transient dynamics and their control in time-delay autonomous Boolean ring networks

Biochemical systems with switch-like interactions, such as gene regulatory networks, are well modeled by autonomous Boolean networks. Specifically, the topology and logic of gene interactions can be described by systems of continuous piecewise-linear differential equations, enabling analytical predictions of the dynamics of specific networks. However, most models do not account for time delays along links associated with spatial transport, mRNA transcription, and translation. To address this issue, we have developed an experimental test bed to realize a time-delay autonomous Boolean network with three inhibitory nodes, known as a repressilator, and use it to study the dynamics that arise as time delays along the links vary. We observe various nearly periodic oscillatory transient patterns with extremely long lifetime, which emerge in small network motifs due to the delay, and which are distinct from the eventual asymptotically stable periodic attractors. For repeated experiments with a given network, we find that stochastic processes give rise to a broad distribution of transient times with an exponential tail. In some cases, the transients are so long that it is doubtful the attractors will ever be approached in a biological system that has a finite lifetime. To counteract the long transients, we show experimentally that small, occasional perturbations applied to the time delays can force the trajectories to rapidly approach the attractors

Healthy Firms: Constraints to Growth among Private Health Sector Facilities in Ghana and Kenya

Background: Health outcomes in developing countries continue to lag the developed world, and many countries are not on target to meet the Millennium Development Goals. The private health sector provides much of the care in many developing countries (e.g., approximately 50 percent in Sub-Saharan Africa), but private providers are often poorly integrated into the health system. Efforts to improve health systems performance will need to include the private sector and increase its contributions to national health goals. However, the literature on constraints private health care providers face is limited. Methodology/Principal Findings: We analyze data from a survey of private health facilities in Kenya and Ghana to evaluate growth constraints facing private providers. A significant portion of facilities (Ghana: 62 percent; Kenya: 40 percent) report limited access to finance as the most significant barrier they face; only a small minority of facilities report using formal credit institutions to finance day to day operations (Ghana: 6 percent; Kenya: 11 percent). Other important barriers include corruption, crime, limited demand for goods and services, and poor public infrastructure. Most facilities have paper-based rather than electronic systems for patient records (Ghana: 30 percent; Kenya: 22 percent), accounting (Ghana: 45 percent; Kenya: 27 percent), and inventory control (Ghana: 41 percent; Kenya: 24 percent). A majority of clinics in both countries report undertaking activities to improve provider skills and to monitor the level and quality of care they provide. However, only a minority of pharmacies report undertaking such activities

Making Projects Real in a Higher Education Context

Challenging educators to rethink projects and see them as a practice rather than as a model of management the authors explore the possibilities for using live projects to enhance real world learning in higher education. Drawing on the work of the ‘critical projects movement’ the chapter outlines a theoretical underpinning for reconceptualising projects as a practice and proposes a new pedagogic model that of ‘agile learning’. Framing the use of live projects is a mode of real world learning that generates encounters with industry professionals and provides real-value outputs for clients. The chapter explores the challenges that face educators who wish to foreground ‘social learning’ and engagement with communities of practice as a means of easing the transition for students from education to the world of work

The influence of 'significant others' on persistent back pain and work participation: a qualitative exploration of illness perceptions

Background Individual illness perceptions have been highlighted as important influences on clinical outcomes for back pain. However, the illness perceptions of 'significant others' (spouse/partner/close family member) are rarely explored, particularly in relation to persistent back pain and work participation. The aim of this study was to initiate qualitative research in this area in order to further understand these wider influences on outcome. Methods Semi-structured interviews based on the chronic pain version of the Illness Perceptions Questionnaire-Revised were conducted with a convenience sample of UK disability benefit claimants, along with their significant others (n=5 dyads). Data were analysed using template analysis. Results Significant others shared, and perhaps further reinforced, claimants' unhelpful illness beliefs including fear of pain/re-injury associated with certain types of work and activity, and pessimism about the likelihood of return to work. In some cases, significant others appeared more resigned to the permanence and negative inevitable consequences of the claimant's back pain condition on work participation, and were more sceptical about the availability of suitable work and sympathy from employers. In their pursuit of authenticity, claimants were keen to stress their desire to work whilst emphasising how the severity and physical limitations of their condition prevented them from doing so. In this vein, and seemingly based on their perceptions of what makes a 'good' significant other, significant others acted as a 'witness to pain', supporting claimants' self-limiting behaviour and statements of incapacity, often responding with empathy and assistance. The beliefs and responses of significant others may also have been influenced by their own experience of chronic illness, thus participants lives were often intertwined and defined by illness. Conclusions The findings from this exploratory study reveal how others and wider social circumstances might contribute both to the propensity of persistent back pain and to its consequences. This is an area that has received little attention to date, and wider support of these findings may usefully inform the design of future intervention programmes aimed at restoring work participation

Investigation of conduction band structure, electron scattering mechanisms and phase transitions in indium selenide by means of transport measurements under pressure

In this work we report on Hall effect, resistivity and thermopower measurements in n-type indium selenide at room temperature under either hydrostatic and quasi-hydrostatic pressure. Up to 40 kbar (= 4 GPa), the decrease of carrier concentration as the pressure increases is explained through the existence of a subsidiary minimum in the conduction band. This minimum shifts towards lower energies under pressure, with a pressure coefficient of about -105 meV/GPa, and its related impurity level traps electrons as it reaches the band gap and approaches the Fermi level. The pressure value at which the electron trapping starts is shown to depend on the electron concentration at ambient pressure and the dimensionality of the electron gas. At low pressures the electron mobility increases under pressure for both 3D and 2D electrons, the increase rate being higher for 2D electrons, which is shown to be coherent with previous scattering mechanisms models. The phase transition from the semiconductor layered phase to the metallic sodium cloride phase is observed as a drop in resistivity around 105 kbar, but above 40 kbar a sharp nonreversible increase of the carrier concentration is observed, which is attributed to the formation of donor defects as precursors of the phase transition.Comment: 18 pages, Latex, 10 postscript figure

Perturbation biology: inferring signaling networks in cellular systems.

We present a powerful experimental-computational technology for inferring network models that predict the response of cells to perturbations, and that may be useful in the design of combinatorial therapy against cancer. The experiments are systematic series of perturbations of cancer cell lines by targeted drugs, singly or in combination. The response to perturbation is quantified in terms of relative changes in the measured levels of proteins, phospho-proteins and cellular phenotypes such as viability. Computational network models are derived de novo, i.e., without prior knowledge of signaling pathways, and are based on simple non-linear differential equations. The prohibitively large solution space of all possible network models is explored efficiently using a probabilistic algorithm, Belief Propagation (BP), which is three orders of magnitude faster than standard Monte Carlo methods. Explicit executable models are derived for a set of perturbation experiments in SKMEL-133 melanoma cell lines, which are resistant to the therapeutically important inhibitor of RAF kinase. The resulting network models reproduce and extend known pathway biology. They empower potential discoveries of new molecular interactions and predict efficacious novel drug perturbations, such as the inhibition of PLK1, which is verified experimentally. This technology is suitable for application to larger systems in diverse areas of molecular biology

Classification and risk stratification of invasive breast carcinomas using a real-time quantitative RT-PCR assay

INTRODUCTION: Predicting the clinical course of breast cancer is often difficult because it is a diverse disease comprised of many biological subtypes. Gene expression profiling by microarray analysis has identified breast cancer signatures that are important for prognosis and treatment. In the current article, we use microarray analysis and a real-time quantitative reverse-transcription (qRT)-PCR assay to risk-stratify breast cancers based on biological 'intrinsic' subtypes and proliferation. METHODS: Gene sets were selected from microarray data to assess proliferation and to classify breast cancers into four different molecular subtypes, designated Luminal, Normal-like, HER2+/ER-, and Basal-like. One-hundred and twenty-three breast samples (117 invasive carcinomas, one fibroadenoma and five normal tissues) and three breast cancer cell lines were prospectively analyzed using a microarray (Agilent) and a qRT-PCR assay comprised of 53 genes. Biological subtypes were assigned from the microarray and qRT-PCR data by hierarchical clustering. A proliferation signature was used as a single meta-gene (log(2 )average of 14 genes) to predict outcome within the context of estrogen receptor status and biological 'intrinsic' subtype. RESULTS: We found that the qRT-PCR assay could determine the intrinsic subtype (93% concordance with microarray-based assignments) and that the intrinsic subtypes were predictive of outcome. The proliferation meta-gene provided additional prognostic information for patients with the Luminal subtype (P = 0.0012), and for patients with estrogen receptor-positive tumors (P = 3.4 × 10(-6)). High proliferation in the Luminal subtype conferred a 19-fold relative risk of relapse (confidence interval = 95%) compared with Luminal tumors with low proliferation. CONCLUSION: A real-time qRT-PCR assay can recapitulate microarray classifications of breast cancer and can risk-stratify patients using the intrinsic subtype and proliferation. The proliferation meta-gene offers an objective and quantitative measurement for grade and adds significant prognostic information to the biological subtypes

Cell-selective labeling using amino acid precursors for proteomic studies of multicellular environments.

We report a technique to selectively and continuously label the proteomes of individual cell types in coculture, named cell type-specific labeling using amino acid precursors (CTAP). Through transgenic expression of exogenous amino acid biosynthesis enzymes, vertebrate cells overcome their dependence on supplemented essential amino acids and can be selectively labeled through metabolic incorporation of amino acids produced from heavy isotope-labeled precursors. When testing CTAP in several human and mouse cell lines, we could differentially label the proteomes of distinct cell populations in coculture and determine the relative expression of proteins by quantitative mass spectrometry. In addition, using CTAP we identified the cell of origin of extracellular proteins secreted from cells in coculture. We believe that this method, which allows linking of proteins to their cell source, will be useful in studies of cell-cell communication and potentially for discovery of biomarkers