Improving Visual Field Examination of the Macula Using Structural Information

Purpose: To investigate a novel approach for structure-function modeling in glaucoma to improve visual field testing in the macula. Methods: We acquired data from the macular region in 20 healthy eyes and 31 with central glaucomatous damage. Optical coherence tomography (OCT) scans were used to estimate the local macular ganglion cell density. Perimetry was performed with a fundus-tracking device using a 10-2 grid. OCT scans were matched to the retinal image from the fundus perimeter to accurately map the tested locations onto the structural damage. Binary responses from the subjects to all presented stimuli were used to calculate the structure-function model used to generate prior distributions for a ZEST (Zippy Estimation by Sequential Testing) Bayesian strategy. We used simulations based on structural and functional data acquired from an independent dataset of 20 glaucoma patients to compare the performance of this new strategy, structural macular ZEST (MacS-ZEST), with a standard ZEST. Results: Compared to the standard ZEST, MacS-ZEST reduced the number of presentations by 13% in reliable simulated subjects and 14% with higher rates (≥20%) of false positive or false negative errors. Reduction in mean absolute error was not present for reliable subjects but was gradually more important with unreliable responses (≥10% at 30% error rate). Conclusions: Binary responses can be modeled to incorporate detailed structural information from macular OCT into visual field testing, improving overall speed and accuracy in poor responders. Translational Relevance: Structural information can improve speed and reliability for macular testing in glaucoma practice

Facing Non-Stationary Conditions with a New Indicator of Entropy Increase: The Cassandra Algorithm

We address the problem of detecting non-stationary effects in time series (in particular fractal time series) by means of the Diffusion Entropy Method (DEM). This means that the experimental sequence under study, of size $N$, is explored with a window of size $L << N$. The DEM makes a wise use of the statistical information available and, consequently, in spite of the modest size of the window used, does succeed in revealing local statistical properties, and it shows how they change upon moving the windows along the experimental sequence. The method is expected to work also to predict catastrophic events before their occurrence.Comment: FRACTAL 2002 (Spain

Activity autocorrelation in financial markets. A comparative study between several models

We study the activity, i.e., the number of transactions per unit time, of financial markets. Using the diffusion entropy technique we show that the autocorrelation of the activity is caused by the presence of peaks whose time distances are distributed following an asymptotic power law which ultimately recovers the Poissonian behavior. We discuss these results in comparison with ARCH models, stochastic volatility models and multi-agent models showing that ARCH and stochastic volatility models better describe the observed experimental evidences.Comment: 15 pages, 4 figure

Survey of hyperfine structure measurements in alkali atoms

The spectroscopic hyperfine constants for all the alkali atoms are reported. For atoms from lithium to cesium, only the long lived atomic isotopes are examined. For francium, the measured data for nuclear ground states of all available isotopes are listed. All results obtained since the beginning of laser investigations are presented, while for previous works the data of Arimondo {\it et. al.} Rev. Mod. Phys. 49, 31 (1977) are recalled. Global analyses based on the scaling laws and on the hyperfine anomalies are performed.Comment: 41 pages, 5 figure

Memory beyond memory in heart beating: an efficient way to detect pathological conditions

We study the long-range correlations of heartbeat fluctuations with the method of diffusion entropy. We show that this method of analysis yields a scaling parameter $\delta$ that apparently conflicts with the direct evaluation of the distribution of times of sojourn in states with a given heartbeat frequency. The strength of the memory responsible for this discrepancy is given by a parameter $\epsilon^{2}$, which is derived from real data. The distribution of patients in the ($\delta$, $\epsilon^{2}$)-plane yields a neat separation of the healthy from the congestive heart failure subjects.Comment: submitted to Physical Review Letters, 5 figure

Polarization-modulation near-field optical microscope for quantitative local dichroism mapping

A couple of experimental techniques have been implemented to an aperture near-field scanning optical microscopy (NSOM) to obtain reliable measurement of sample dichroism on the local scale. First, a method to test NSOM tapered fiber probes toward polarization conservation into the near optical field is reported. The probes are characterized in terms of the in-plane polarization of the near field emerging from their aperture, by using a thin dichroic layer of chromophore molecules, structured along stretched polymeric chains, to probe such polarization when approached in the near-field region of the probe. Second, to assure that the light intensity coupled in the fiber is polarization independent, an active system operating in real time has been realized. Such combination of techniques allowed quantitative imaging of local dichroism degree and average orientation by means of dual-phase lock-in demodulation of the optical signal. Translation of the coupled light polarization state in the near field has been observed for one-half of the tested probes. For the others, the tip acts as a polarizer, and therefore showed it was not suitable for polarization modulation NSOM measurements

Compression and diffusion: a joint approach to detect complexity

The adoption of the Kolmogorov-Sinai (KS) entropy is becoming a popular research tool among physicists, especially when applied to a dynamical system fitting the conditions of validity of the Pesin theorem. The study of time series that are a manifestation of system dynamics whose rules are either unknown or too complex for a mathematical treatment, is still a challenge since the KS entropy is not computable, in general, in that case. Here we present a plan of action based on the joint action of two procedures, both related to the KS entropy, but compatible with computer implementation through fast and efficient programs. The former procedure, called Compression Algorithm Sensitive To Regularity (CASToRe), establishes the amount of order by the numerical evaluation of algorithmic compressibility. The latter, called Complex Analysis of Sequences via Scaling AND Randomness Assessment (CASSANDRA), establishes the complexity degree through the numerical evaluation of the strength of an anomalous effect. This is the departure, of the diffusion process generated by the observed fluctuations, from ordinary Brownian motion. The CASSANDRA algorithm shares with CASToRe a connection with the Kolmogorov complexity. This makes both algorithms especially suitable to study the transition from dynamics to thermodynamics, and the case of non-stationary time series as well. The benefit of the joint action of these two methods is proven by the analysis of artificial sequences with the same main properties as the real time series to which the joint use of these two methods will be applied in future research work.Comment: 27 pages, 9 figure

L\'{e}vy scaling: the Diffusion Entropy Analysis applied to DNA sequences

We address the problem of the statistical analysis of a time series generated by complex dynamics with a new method: the Diffusion Entropy Analysis (DEA) (Fractals, {\bf 9}, 193 (2001)). This method is based on the evaluation of the Shannon entropy of the diffusion process generated by the time series imagined as a physical source of fluctuations, rather than on the measurement of the variance of this diffusion process, as done with the traditional methods. We compare the DEA to the traditional methods of scaling detection and we prove that the DEA is the only method that always yields the correct scaling value, if the scaling condition applies. Furthermore, DEA detects the real scaling of a time series without requiring any form of de-trending. We show that the joint use of DEA and variance method allows to assess whether a time series is characterized by L\'{e}vy or Gauss statistics. We apply the DEA to the study of DNA sequences, and we prove that their large-time scales are characterized by L\'{e}vy statistics, regardless of whether they are coding or non-coding sequences. We show that the DEA is a reliable technique and, at the same time, we use it to confirm the validity of the dynamic approach to the DNA sequences, proposed in earlier work.Comment: 24 pages, 9 figure

Cataract and optic disk drusen in a patient with glycogenosis and di George syndrome: clinical and molecular report

Background We report the ophthalmic findings of a patient with type Ia glycogen storage disease (GSD Ia), DiGeorge syndrome (DGS), cataract and optic nerve head drusen (ONHD). Case presentation A 26-year-old white woman, born at term by natural delivery presented with a post-natal diagnosis of GSD Ia. Genetic testing by array-comparative genomic hybridization (CGH) for DGS was required because of her low levels of serum calcium. The patient has been followed from birth, attending the day-hospital every six months at the San Paolo Hospital, Milan, outpatient clinic for metabolic diseases and previously at another eye center. During the last day-hospital visit, a complete eye examination showed ONHD and cataract in both eyes. Next Generation Sequencing (NGS) was subsequently done to check for any association between the eye problems and metabolic aspects. Conclusions This is the first description of ocular changes in a patient with GSD Ia and DGS. Mutations explaining GSD Ia and DGS were found but no specific causative mutation for cataract and ONHD. The metabolic etiology of her lens changes is known, whereas the pathogenesis of ONHD is not clear. Although the presence of cataract and ONHD could be a coincidence; the case reported could suggest that hypocalcemia due to DGS could be the common biochemical pathway

Follicular development, plasma Inhibin-A and Estradiol-17-beta concentrations in Buffalo cows during different treatment schedules for MOET programs

Buffalo cows were submitted to three superovulatory treatments. T1 (n = 7): PRID for 10 days (d0-d9) plus decreasing doses of 500 IU FSH/LH (12 h-intervals d7‑d10); T2 (n = 8): PRID for 11 d (d0-d10) plus 2000 IU PMSG at d7; T3 (n = 9): PRID for 11 d plus 2000 IU PMSG at d7 and decreasing doses of 175 IU FSH/LH (12 h-intervals d10‑ d11). Overall plasma inhibin‑A (In-A) concentrations correlated with large follicles (LF, diameter >6mm, R=0.83, P10 mm at d12- 13 (T1=5.0+/-1.4, T2=1.2+/-0.9, T3=8.3+/-2.3). In-A concentrations significantly rised at d11-13 of T1 and T3. In-A seems a good indicator of the follicular development during superovulation in buffalo cows, while E2 is not. Furthermore T3 was followed by better ovarian follicular responses