Comment on "Quality of paraxial electromagnetic beams"

We comment on a recent paper by Seshadri [Appl. Opt.45, 5335 (2006)]APOPAI0003-693510.1364/AO.45.005335. In the cited work the author utilized the so-named Felsen method in order to derive the full wave expression of a scalar Bessel-Gauss field, propagating in free space, originated from an assigned input distribution on the source plane z = 0. As we show, the author's obtained results do not correctly reproduce the aforesaid input field distribution, as, on the contrary, they have to do.     

Is normal bronchial responsiveness in asthmatics a reliable index for withdrawing inhaled corticosteroid treatment?

STUDY OBJECTIVE: Inhaled corticosteroid (ICS) treatment is first-line maintenance therapy in bronchial asthma. However, it is not clear whether and when ICS treatment can be withdrawn. The aim of this open study was to assess whether normalization of bronchial responsiveness could be used as a reliable index to assess the opportunity of ICS treatment withdrawal. DESIGN: Open study at two different points in time. SETTING: Outpatient pulmonary clinic. PATIENTS: Eighteen asthmatic subjects. MEASUREMENTS AND RESULTS: ICS therapy was withdrawn in subjects treated with beclomethasone dipropionate, at the maintenance dose of 889+/-246 microg/d for >3 months. Upon recruitment, all subjects were asymptomatic, had FEV1 >70% of predicted value, and were in treatment with beta2-agonists on an as-needed basis. Eight subjects (group 1) had normal bronchial responsiveness (methacholine provocative dose causing a 20% fall in FEV1 [PD20] >2,000 microg) and 10 subjects (group 2) had bronchial hyperresponsiveness (BHR) (PD20 < or = 2,000 microg). After withdrawal of ICS treatment, subjects were followed up for 3 weeks and were asked to record their asthma symptoms (cough, dyspnea, and wheezing) and their beta2-agonist use. At recruitment and at the end of follow-up, subjects underwent spirometry and a methacholine challenge test. Frequency of asthma exacerbation was similar in subjects with normal bronchial responsiveness (NBR) and in subjects with BHR (50% vs 60%), but subjects with NBR tended to remain asymptomatic for longer than those with BHR (mean+/-SD, 10.7+/-4.4 days vs 5.5+/-3.8 days) (p=0.08). None of the subjects reported any condition that could have triggered exacerbation. Asthma exacerbation was associated with a significant decrease in FEV1 (-105+/-107 mL; p<0.05) and in PD20 (-1,332+/-1,020 microg; p<0.001). CONCLUSIONS: Our study shows that the likelihood of asthma exacerbation is not reduced if ICS treatment is withdrawn when the subjects have NBR, but the exacerbation could be delayed. Further studies in larger populations of asthmatics are needed to confirm these findings.     

纳米压痕仪和激光超声技术检测薄膜弹性模量

在薄膜材料的力学性能测定中,弹性模量是衡量材料软硬程度的重要指标。为了测定弹性模量,本文选取不同种类和厚度的金属薄膜材料,采用纳米压痕技术(nanoindentation)和激光超声技术(laser-acoustics)两种测试方法相互比较,以确保测试的准确性。两种方法在膜厚较大的试样测试中得到了大致相符的试验结果,相对误差最小达到2%。     

Chemical modification of carbon fiber surfaces

Surface properties of a high modulus unsized carbon fiber modified by aqueous ammonia were studied. Basic groups were detected by potentiometric titration in addition to the pristine acid groups in untreated fiber. Surface composition of fiber modified with maleic anhydride or tetracyanoethylene was determined by XPS analysis. The modified fiber interaction with epoxide resin was studied by the Single Fiber Composite test. Ammonia treated fiber showed an improvement of the fiber/matrix stress transfer.     

Assessing cortical functional connectivity by partial directed coherence: simulations and application to real data

The aim of this paper is to test a technique called partial directed coherence (PDC) and its modification (squared PDC; sPDC) for the estimation of human cortical connectivity by means of simulation study, in which both PDC and sPDC were studied by analysis of variance. The statistical analysis performed returned that both PDC and sPDC are able to estimate correctly the imposed connectivity patterns when data exhibit a signal-to-noise ratio of at least 3 and a length of at least 27 s of nonconsecutive recordings at 250 Hz of sampling rate, equivalent, more generally, to 6750 data samples.     

Estimation of the cortical connectivity by high-resolution EEG and structural equation modeling: simulations and application to finger tapping data

Today, the concept of brain connectivity plays a central role in the neuroscience. While functional connectivity is defined as the temporal coherence between the activities of different brain areas, the effective connectivity is defined as the simplest brain circuit that would produce the same temporal relationship as observed experimentally between cortical sites. The most used method to estimate effective connectivity in neuroscience is the structural equation modeling (SEM), typically used on data related to the brain hemodynamic behavior. However, the use of hemodynamic measures limits the temporal resolution on which the brain process can be followed. The present research proposes the use of the SEM approach on the cortical waveforms estimated from the high-resolution EEG data, which exhibits a good spatial resolution and a higher temporal resolution than hemodynamic measures. We performed a simulation study, in which different main factors were systematically manipulated in the generation of test signals, and the errors in the estimated connectivity were evaluated by the analysis of variance (ANOVA). Such factors were the signal-to-noise ratio and the duration of the simulated cortical activity. Since SEM technique is based on the use of a model formulated on the basis of anatomical and physiological constraints, different experimental conditions were analyzed, in order to evaluate the effect of errors made in the a priori model formulation on its performances. The feasibility of the proposed approach has been shown in a human study using high-resolution EEG recordings related to finger tapping movements.     

The determination of tetraalkyl lead in air by a denuder diffusion technique

A diffusion method for the selective determination of tetraalkyl lead (TAL) in air is proposed. Separation from inorganic lead takes place on an ICl-coated annular denuder, where only TAL is removed during sampling. A differential technique making use of two denuders in series prevents any interference from particulate lead. Analysis of denuder acid extracts by flameless atomic absorption spectrometry provides a direct measure of organic lead thus avoiding a complex solvent extraction procedure.     

Hybrid soft computing algorithmic framework for smart home energy management

Energy management in Smart Home environments is undoubtedly one of the pressing issues in the Smart Grid research field. The aim typically consists in developing a suitable engineering solution able to maximally exploit the availability of renewable resources. Due to the presence of diverse cooperating devices, a complex model, involving the characterization of nonlinear phenomena, is indeed required on purpose. In this paper an Hybrid Soft Computing algorithmic framework, where genetic, neural networks and deterministic optimization algorithms jointly operate, is proposed to perform an efficient scheduling of the electrical tasks and of the activity of energy resources, by adequately handling the inherent nonlinear aspects of the energy management model. In particular, in order to address the end-user comfort constraints, the home thermal characterization is needed: this is accomplished by a nonlinear model relating the energy demand with the required temperature profile. A genetic algorithm, based on such model, is then used to optimally allocate the energy request to match the user thermal constraints, and therefore to allow the mixed-integer deterministic optimization algorithm to determine the remaining energy management actions. From this perspective, the ability to schedule the tasks and allocate the overall energy resources over a finite time horizon is assessed by means of diverse computer simulations in realistic conditions, allowing the authors to positively conclude about the effectiveness of the proposed approach. The degree of realism of the simulated scenario is confirmed by the usage of solar energy production forecasted data, obtained by means of a neural-network based algorithm which completes the framework.