Temperature-Robust Neural Function from Activity-Dependent Ion Channel Regulation

Many species of cold-blooded animals experience substantial and rapid fluctuations in body temperature. Because biological processes are differentially temperature dependent, it is difficult to understand how physiological processes in such animals can be temperature robust [1–8]. Experiments have shown that core neural circuits, such as the pyloric circuit of the crab stomatogastric ganglion (STG), exhibit robust neural activity in spite of large (20$^{\circ}$C) temperature fluctuations [3, 5, 7, 8]. This robustness is surprising because (1) each neuron has many different kinds of ion channels with different temperature dependencies (Q$_{10}$s) that interact in a highly nonlinear way to produce firing patterns and (2) across animals there is substantial variability in conductance densities that nonetheless produce almost identical firing properties. The high variability in conductance densities in these neurons [9, 10] appears to contradict the possibility that robustness is achieved through precise tuning of key temperature-dependent processes. In this paper, we develop a theoretical explanation for how temperature robustness can emerge from a simple regulatory control mechanism that is compatible with highly variable conductance densities [11–13]. The resulting model suggests a general mechanism for how nervous systems and excitable tissues can exploit degenerate relationships among temperature-sensitive processes to achieve robust function.Charles A. King Trust Fellowship, National Institutes of Health (Grant IDs: NS 081013, NIH 1P01NS079419

Building Disease Detection Algorithms with Very Small Numbers of Positive Samples

Although deep learning can provide promising results in medical image analysis, the lack of very large annotated datasets confines its full potential. Furthermore, limited positive samples also create unbalanced datasets which limit the true positive rates of trained models. As unbalanced datasets are mostly unavoidable, it is greatly beneficial if we can extract useful knowledge from negative samples to improve classification accuracy on limited positive samples. To this end, we propose a new strategy for building medical image analysis pipelines that target disease detection. We train a discriminative segmentation model only on normal images to provide a source of knowledge to be transferred to a disease detection classifier. We show that using the feature maps of a trained segmentation network, deviations from normal anatomy can be learned by a two-class classification network on an extremely unbalanced training dataset with as little as one positive for 17 negative samples. We demonstrate that even though the segmentation network is only trained on normal cardiac computed tomography images, the resulting feature maps can be used to detect pericardial effusion and cardiac septal defects with two-class convolutional classification networks

Bounds on R-parity violating supersymmetric couplings from leptonic and semi-leptonic meson decays

We present a comprehensive update of the bounds on R-Parity violating supersymmetric couplings from lepton-flavour- and lepton-number-violating decay processes. We consider tau and mu decays as well as leptonic and semi-leptonic decays of mesons. We present several new bounds resulting from tau, eta and Kaon decays and correct some results in the literature concerning B-meson decays.Comment: 30 pages; changed title, updated some bounds from the literature from different references, added reference

Dynamical Interactions and the Black Hole Merger Rate of the Universe

Binary black holes can form efficiently in dense young stellar clusters, such as the progenitors of globular clusters, via a combination of gravitational segregation and cluster evaporation. We use simple analytic arguments supported by detailed N-body simulations to determine how frequently black holes born in a single stellar cluster should form binaries, be ejected from the cluster, and merge through the emission of gravitational radiation. We then convolve this ``transfer function'' relating cluster formation to black hole mergers with (i) the distribution of observed cluster masses and (ii) the star formation history of the universe, assuming that a significant fraction gcl of star formation occurs in clusters and that a significant fraction gcand of clusters undergo this segregation and evaporation process. We predict future ground--based gravitational wave (GW) detectors could observe ~500 (gcl/0.5) (gcand/0.1) double black hole mergers per year, and the presently operating LIGO interferometer would have a chance (50%) at detecting a merger during its first full year of science data. More realistically, advanced LIGO and similar next-generation gravitational wave observatories provide unique opportunities to constrain otherwise inaccessible properties of clusters formed in the early universe.Comment: 4 pages, 2 figures. To appear in PRD Rapid Communication

Cost-Effectiveness of Targeted Reemployment Bonuses

Targeting reemployment bonus offers to unemployment insurance (UI) claimants identified as most likely to exhaust benefits is estimated to reduce benefit payments. We show that targeting bonus offers with profiling models similar to those in state Worker Profiling and Reemployment Services systems can improve cost effectiveness. Since estimated average benefit payments do not steadily decline as the eligibility screen is gradually tightened, we find that narrow targeting is not optimal. The best candidate is a low bonus amount with a long qualification period, targeted to the half of profiled claimants most likely to exhaust their UI benefit entitlement. I

A Lanczos Method for Approximating Composite Functions

We seek to approximate a composite function h(x) = g(f(x)) with a global polynomial. The standard approach chooses points x in the domain of f and computes h(x) at each point, which requires an evaluation of f and an evaluation of g. We present a Lanczos-based procedure that implicitly approximates g with a polynomial of f. By constructing a quadrature rule for the density function of f, we can approximate h(x) using many fewer evaluations of g. The savings is particularly dramatic when g is much more expensive than f or the dimension of x is large. We demonstrate this procedure with two numerical examples: (i) an exponential function composed with a rational function and (ii) a Navier-Stokes model of fluid flow with a scalar input parameter that depends on multiple physical quantities

Grazing Cow Behavior’s Association with Mild and Moderate Lameness

peer-reviewedAccelerometer-based mobility scoring has focused on cow behaviors such as lying and walking. Accuracy levels as high as 91% have been previously reported. However, there has been limited replication of results. Here, measures previously identified as indicative of mobility, such as lying bouts and walking time, were examined. On a research farm and a commercial farm, 63 grazing cows’ behavior was monitored in four trials (16, 16, 16, and 15 cows) using leg-worn accelerometers. Seventeen good mobility (score 0), 23 imperfect mobility (score 1), and 22 mildly impaired mobility (score 2) cows were monitored. Only modest associations with activity, standing, and lying events were found. Thus, behavior monitoring appears to be insufficient to discern mildly and moderately impaired mobility of grazing cows

Understanding leadership in a world of shared problems: advancing network governance in large landscape conservation

Conservation of large landscapes requires three interconnected types of leadership: collaborative leadership, in which network members share leadership functions at different points in time; distributive leadership, in which network processes provide local opportunities for members to act proactively for the benefit of the network; and architectural leadership, in which the structure of the network is intentionally designed to allow network processes to occur. In network governance, each leadership approach is necessary to achieve sustained, successful outcomes. We discuss each of these approaches to leadership and offer specific practices for leaders of networks, including: shaping the network's identity and vision, attracting members, instilling leadership skills in members, and advancing common interests. These practices are then illustrated in case studies

The impact of workplace ergonomics and neck-specific exercise versus ergonomics and health promotion interventions on office worker productivity: A cluster-randomized trial

Objectives: Using an employer’s perspective, this study aimed to compare the immediate and longer-term impact of workplace ergonomics and neck-specific exercise versus ergonomics and health promotion information on health-related productivity among a general population of office workers and those with neck pain. Methods: A prospective one-year cluster randomized trial was conducted. Participants received an individualized workstation ergonomics intervention, combined with 12 weeks of either workplace neck-specific exercises or health promotion information. Health-related productivity at baseline, post-intervention and 12-months was measured with the Health and Work Performance Questionnaire. Intention-to-treat analysis was performed using multilevel mixed models. Results: We recruited 763 office workers from 14 organizations and allocated them to 100 clusters. For the general population of office workers, monetized productivity loss at 12 months [AU$1464 (standard deviation [SD] 1318) versus AU$1563 (SD=1039); P=0.023]; and presenteeism at 12 months [2.0 (SD 1.2) versus 2.4 (SD 1.4); P=0.007] was lower in the exercise group compared to those in the health promotion information group. For office workers with neck pain, exercise participants had lower sickness absenteeism at 12 months compared to health promotion information participants [0.7 days (SD 1.0) versus 1.4 days (SD 3.1); P=0.012], despite a short-term increase in sickness absenteeism post-intervention compared to baseline for the exercise group [1.2 days (SD 2.2) versus 0.6 days (SD 0.9); P<0.001]. Conclusion: A workplace intervention combining ergonomics and neck-specific exercise offers possible benefits for sickness presenteeism and health-related productivity loss among a general population of office workers and sickness absenteeism for office workers with neck pain in the longer-term