Compressed sensing based cyclic feature spectrum sensing for cognitive radios

Spectrum sensing is currently one of the most challenging design problems in cognitive radio. A robust spectrum sensing technique is important in allowing implementation of a practical dynamic spectrum access in noisy and interference uncertain environments. In addition, it is desired to minimize the sensing time, while meeting the stringent cognitive radio application requirements. To cope with this challenge, cyclic spectrum sensing techniques have been proposed. However, such techniques require very high sampling rates in the wideband regime and thus are costly in hardware implementation and power consumption. In this thesis the concept of compressed sensing is applied to circumvent this problem by utilizing the sparsity of the two-dimensional cyclic spectrum. Compressive sampling is used to reduce the sampling rate and a recovery method is developed for re- constructing the sparse cyclic spectrum from the compressed samples. The reconstruction solution used, exploits the sparsity structure in the two-dimensional cyclic spectrum do-main which is different from conventional compressed sensing techniques for vector-form sparse signals. The entire wideband cyclic spectrum is reconstructed from sub-Nyquist-rate samples for simultaneous detection of multiple signal sources. After the cyclic spectrum recovery two methods are proposed to make spectral occupancy decisions from the recovered cyclic spectrum: a band-by-band multi-cycle detector which works for all modulation schemes, and a fast and simple thresholding method that works for Binary Phase Shift Keying (BPSK) signals only. In addition a method for recovering the power spectrum of stationary signals is developed as a special case. Simulation results demonstrate that the proposed spectrum sensing algorithms can significantly reduce sampling rate without sacrifcing performance. The robustness of the algorithms to the noise uncertainty of the wireless channel is also shown.

Altered perception of apparent motion in schizophrenia spectrum disorder

Apparent motion (AM), the Gestalt perception of motion in the absence of physical motion, was used to study perceptual organization and neurocognitive binding in schizophrenia. Associations between AM perception and psychopathology as well as meaningful subgroups were sought. Circular and stroboscopic AM stimuli were presented to 68 schizophrenia spectrum patients and healthy participants. Psychopathology was measured using the Positive and Negative Syndrome Scale (PANSS). Psychopathology was related to AM perception differentially: Positive and disorganization symptoms were linked to reduced gestalt stability; negative symptoms, excitement and depression had opposite regression weights. Dimensions of psychopathology thus have opposing effects on gestalt perception. It was generally found that AM perception was closely associated with psychopathology. No difference existed between patients and controls, but two latent classes were found. Class A members who had low levels of AM stability made up the majority of inpatients and control subjects; such participants were generally young and male, with short reaction times. Class B typically contained outpatients and some control subjects; participants in class B were older and showed longer reaction times. Hence AM perceptual dysfunctions are not specific for schizophrenia, yet AM may be a promising stage marker.

Method of Detecting System Function by Measuring Frequency Response

Real-time battery impedance spectrum is acquired using a one-time record. Fast Summation Transformation (FST) is a parallel method of acquiring a real-time battery impedance spectrum using a one-time record that enables battery diagnostics. An excitation current to a battery is a sum of equal amplitude sine waves of frequencies that are octave harmonics spread over a range of interest. A sample frequency is also octave and harmonically related to all frequencies in the sum. The time profile of this signal has a duration that is a few periods of the lowest frequency. The voltage response of the battery, average deleted, is the impedance of the battery in the time domain. Since the excitation frequencies are known and octave and harmonically related, a simple algorithm, FST, processes the time record by rectifying relative to the sine and cosine of each frequency. Another algorithm yields real and imaginary components for each frequency.

Method of Detecting System Function by Measuring Frequency Response

Methods of rapidly measuring an impedance spectrum of an energy storage device in-situ over a limited number of logarithmically distributed frequencies are described. An energy storage device is excited with a known input signal, and aresponse is measured to ascertain the impedance spectrum. An excitation signal is a limited time duration sum-of-sines consisting of a select number offrequencies. In one embodiment, magnitude and phase of each frequency ofinterest within the sum-of-sines is identified when the selected frequencies and sample rate are logarithmic integer steps greater than two. This technique requires a measurement with a duration of one period of the lowest frequency. In another embodiment, where selected frequencies are distributed in octave steps, the impedance spectrum can be determined using a captured time record that is reduced to a half-period of the lowest frequency.

Method of Detecting System Function by Measuring Frequency Response

Real time battery impedance spectrum is acquired using one time record, Compensated Synchronous Detection (CSD). This parallel method enables battery diagnostics. The excitation current to a test battery is a sum of equal amplitude sin waves of a few frequencies spread over range of interest. The time profile of this signal has duration that is a few periods of the lowest frequency. The voltage response of the battery, average deleted, is the impedance of the battery in the time domain. Since the excitation frequencies are known, synchronous detection processes the time record and each component, both magnitude and phase, is obtained. For compensation, the components, except the one of interest, are reassembled in the time domain. The resulting signal is subtracted from the original signal and the component of interest is synchronously detected. This process is repeated for each component.

Multivariable adjustments counteract spectrum and test review bias in accuracy studies

OBJECTIVES: The STAndards for Reporting studies of Diagnostic accuracy (STARD) for investigators and editors and the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) for reviewers and readers offer guidelines for the quality and reporting of test accuracy studies. These guidelines address and propose some solutions to two major threats to validity: spectrum bias and test review bias. STUDY DESIGN AND SETTING: Using a clinical example, we demonstrate that these solutions fail and propose an alternative solution that concomitantly addresses both sources of bias. We also derive formulas that prove the generality of our arguments. RESULTS: A logical extension of our ideas is to extend STARD item 23 by adding a requirement for multivariable statistical adjustment using information collected in QUADAS items 1, 2, and 12 and STARD items 3-5, 11, 15, and 18. CONCLUSION: We recommend reporting not only variation of diagnostic accuracy across subgroups (STARD item 23) but also the effects of the multivariable adjustments on test performance. We also suggest that the QUADAS be supplemented by an item addressing the appropriateness of statistical methods, in particular whether multivariable adjustments have been included in the analysis.

Potent and broad-spectrum antimicrobial activity of CXCL14 suggests an immediate role in skin infections

The skin is constantly exposed to commensal microflora and pathogenic microbes. The stratum corneum of the outermost skin layer employs distinct tools such as harsh growth conditions and numerous antimicrobial peptides (AMPs) to discriminate between beneficial cutaneous microflora and harmful bacteria. How the skin deals with microbes that have gained access to the live part of the skin as a result of microinjuries is ill defined. In this study, we report that the chemokine CXCL14 is a broad-spectrum AMP with killing activity for cutaneous gram-positive bacteria and Candida albicans as well as the gram-negative enterobacterium Escherichia coli. Based on two separate bacteria-killing assays, CXCL14 compares favorably with other tested AMPs, including human beta-defensin and the chemokine CCL20. Increased salt concentrations and skin-typical pH conditions did not abrogate its AMP function. This novel AMP is highly abundant in the epidermis and dermis of healthy human skin but is down-modulated under conditions of inflammation and disease. We propose that CXCL14 fights bacteria at the earliest stage of infection, well before the establishment of inflammation, and thus fulfills a unique role in antimicrobial immunity.

Expanding the spectrum of mutations in GH1 and GHRHR: genetic screening in a large cohort of patients with congenital isolated growth hormone deficiency

CONTEXT: It is estimated that 3-30% of cases with isolated GH deficiency (IGHD) have a genetic etiology, with a number of mutations being reported in GH1 and GHRHR. The aim of our study was to genetically characterize a cohort of patients with congenital IGHD and analyze their characteristics. PATIENTS AND METHODS: A total of 224 patients (190 pedigrees) with IGHD and a eutopic posterior pituitary were screened for mutations in GH1 and GHRHR. To explore the possibility of an association of GH1 abnormalities with multiple pituitary hormone deficiencies, we have screened 62 patients with either multiple pituitary hormone deficiencies (42 pedigrees), or IGHD with an ectopic posterior pituitary (21 pedigrees). RESULTS: Mutations in GH1 and GHRHR were identified in 41 patients from 21 pedigrees (11.1%), with a higher prevalence in familial cases (38.6%). These included previously described and novel mutations in GH1 (C182X, G120V, R178H, IVS3+4nt, a>t) and GHRHR (W273S, R94L, R162W). Autosomal dominant, type II IGHD was the commonest form (52.4%), followed by type IB (42.8%) and type IA (4.8%). Patients with type II IGHD had highly variable phenotypes. There was no difference in the endocrinology or magnetic resonance imaging appearance between patients with and without mutations, although those with mutations presented with more significant growth failure (height, -4.7 +/- 1.6 SDS vs. -3.4 +/- 1.7 SDS) (P = 0.001). There was no apparent difference between patients with mutations in GH1 and GHRHR. CONCLUSIONS: IGHD patients with severe growth failure and a positive family history should be screened for genetic mutations; the evolving endocrinopathy observed in some of these patients suggests the need for long-term follow-up.