Infinities of stable periodic orbits in systems of coupled oscillators

We consider the dynamical behavior of coupled oscillators with robust heteroclinic cycles between saddles that may be periodic or chaotic. We differentiate attracting cycles into types that we call phase resetting and free running depending on whether the cycle approaches a given saddle along one or many trajectories. At loss of stability of attracting cycling, we show in a phase-resetting example the existence of an infinite family of stable periodic orbits that accumulate on the cycling, whereas for a free-running example loss of stability of the cycling gives rise to a single quasiperiodic or chaotic attractor

Recursive Training of 2D-3D Convolutional Networks for Neuronal Boundary Detection

Efforts to automate the reconstruction of neural circuits from 3D electron microscopic (EM) brain images are critical for the field of connectomics. An important computation for reconstruction is the detection of neuronal boundaries. Images acquired by serial section EM, a leading 3D EM technique, are highly anisotropic, with inferior quality along the third dimension. For such images, the 2D max-pooling convolutional network has set the standard for performance at boundary detection. Here we achieve a substantial gain in accuracy through three innovations. Following the trend towards deeper networks for object recognition, we use a much deeper network than previously employed for boundary detection. Second, we incorporate 3D as well as 2D filters, to enable computations that use 3D context. Finally, we adopt a recursively trained architecture in which a first network generates a preliminary boundary map that is provided as input along with the original image to a second network that generates a final boundary map. Backpropagation training is accelerated by ZNN, a new implementation of 3D convolutional networks that uses multicore CPU parallelism for speed. Our hybrid 2D-3D architecture could be more generally applicable to other types of anisotropic 3D images, including video, and our recursive framework for any image labeling problem

Observing the Symmetry of Attractors

We show how the symmetry of attractors of equivariant dynamical systems can be observed by equivariant projections of the phase space. Equivariant projections have long been used, but they can give misleading results if used improperly and have been considered untrustworthy. We find conditions under which an equivariant projection generically shows the correct symmetry of the attractor.Comment: 28 page LaTeX document with 9 ps figures included. Supplementary color figures available at http://odin.math.nau.edu/~jws

A prospective study on results of bacterial culture from wound in type III compound fractures

Background: Open fractures still represent a major challenge for the treating surgeon. Sound knowledge of the bacteriological epidemiology and antimicrobial susceptibility helps to prevent complications. Our aim is to study about the common bacteria causing open fracture infection and their antibiotic sensitivity in patients who are admitted in the department of Orthopedics, Government medical college, Kottayam.Methods: A prospective study on 130 patients with type III open long bone fractures were studied for infection during study period of June 2016 to July 2017. After initial debridement and at third day during follow up wound inspection, swabs were taken from wound site. Swabs were send for microscopic examination, culture and antimicrobial susceptibility testing.Results: Out of 130 type III open long bone fractures, 7.7% were having day 0 infection and 25.4% were having day 3 infection. 19.2% of patients developed infection from day 3 onwards. Staphylococcus aureus (37.1%) was the most commonly isolated bacteria from wound. Other organisms isolated were Acinetobacter, Pseudomonas, Klebsiella, E coli, Enterococcus, Streptococcus and Enterobacter. 100% of diabetic patients developed infection on day 3. Gentamicin, amikacin doxycycline, ciprofloxacin, vancomycin, piperacillin + tazobactum and cefoperazone + sulbactum were found to be effective against isolated organisms.Conclusions: Gram positive Staphylococcus aureus was found to be the most common cause of wound infection in type III open fractures. An early adequate wound debridement, proper antibiotic therapy and aseptic post-operative wound care are essential for wound healing and fracture union in an open fracture

On the Development of Machine Learning Based Real-Time Stress Monitoring : A Pilot Study

During specific environmental changes, the human body regulates itself through emotional, physical or mental responses. One such response is stress. The psychological and physical stability of an individual may be affected by recurrent occurrences of acute stress. This often leads to anxiety disorder, other psychological illnesses, hypertension, and other physiological disorders. The work performance of the individual is also negatively affected due to long-term stress. Across various age groups, the global population is primarily influenced by anxiety, depression and psychological stress. The long-term adverse effects of stress can be mitigated by effectively monitoring and managing stress through a cost-efficient and reliable stress detection system.  This paper mainly focuses on stress detection using a machine-learning approach. Wearable sensor data from electroencephalogram (EEG) and electrocardiogram (ECG) are considered during exposure to stress and the level of stress undergone by the participant is further analyzed. This approach helps in stress detection, analysis and mitigation, which in turn improves the quality life of people. Machining Learning technique k-means clustering algorithm is used after removal of artifacts to obtain case-specific clusters that segregate features pointing to non-stress and stress periods.  The results of the proposed K-means clustering algorithm are compared to state-of-the-art techniques such as Artificial Neural Network (ANN), Decision Tree (DT), Random Forest (RF) and Support Vector Machine (SVM). From the results, it was concluded that the proposed algorithm outperformed the other with an accuracy of 96% in the overall analysis

Invariant sets for discontinuous parabolic area-preserving torus maps

We analyze a class of piecewise linear parabolic maps on the torus, namely those obtained by considering a linear map with double eigenvalue one and taking modulo one in each component. We show that within this two parameter family of maps, the set of noninvertible maps is open and dense. For cases where the entries in the matrix are rational we show that the maximal invariant set has positive Lebesgue measure and we give bounds on the measure. For several examples we find expressions for the measure of the invariant set but we leave open the question as to whether there are parameters for which this measure is zero.Comment: 19 pages in Latex (with epsfig,amssymb,graphics) with 5 figures in eps; revised version: section 2 rewritten, new example and picture adde

Relationship of serum prolactin with severity of drug use and treatment outcome in cocaine dependence.

RATIONALE: Alteration in serum prolactin (PRL) levels may reflect changes in central dopamine activity, which modulates the behavioral effects of cocaine. Therefore, serum PRL may have a potential role as a biological marker of drug severity and treatment outcome in cocaine dependence. OBJECTIVE: We investigated whether serum PRL levels differed between cocaine-dependent (CD) subjects and controls, and whether PRL levels were associated with severity of drug use and treatment outcome in CD subjects. METHODS: Basal PRL concentrations were assayed in 141 African-American (AA) CD patients attending an outpatient treatment program and 60 AA controls. Severity of drug use was assessed using the Addiction Severity Index (ASI). Measures of abstinence and retention during 12 weeks of treatment and at 6-month follow-up were employed as outcome variables. RESULTS: The basal PRL (ng/ml) in CD patients (9.28+/-4.13) was significantly higher than controls (7.33+/-2.94) (t=3.77, P\u3c0.01). At baseline, PRL was positively correlated with ASI-drug (r=0.38, P\u3c0.01), ASI-alcohol (r=0.19, P\u3c0.05), and ASI-psychological (r=0.25, P\u3c0.01) composite scores, and with the quantity of cocaine use (r=0.18, P\u3c0.05). However, PRL levels were not significantly associated with number of negative urine screens, days in treatment, number of sessions attended, dropout rate or changes in ASI scores during treatment and at follow-up. Also, basal PRL did not significantly contribute toward the variance in predicting any of the outcome measures. CONCLUSION: Although cocaine use seems to influence PRL levels, it does not appear that PRL is a predictor of treatment outcome in cocaine dependence