Lower Number Of Steps Research Articles

Estimating network parameters using random walks

Sampling from large graphs is an area of great interest, especially since the emergence of huge structures such as Online Social Networks and the World Wide Web (WWW). The large scale properties of a network can be summarized in terms of parameters of the underlying graph, such as the total number of vertices, edges and triangles. However, the large si ze of these networks makes it computationally expensive to obtain such structural properties of the underlying graph by exhaustive search. If we can estimate these properties by taking small but representative samples from the network, then size is no longer such a problem. In this paper we present a general framework to estimate network properties using random walks. These methods work under the assumption we are able to obtain local characteristics of a vertex during each step of the random walk, for example the number of its neighbours, and their labels. As examples of this approach, we present practical methods to estimate the total number of edges/links m, number of vertices/nodes n and number of connected triads of vertices (triangles) t in graphs. We also give a general method to count any type of small connected subgraph, of which vertices, edges and triangles are specific examples. Additionally we present experimental estimates for n, m, t we obtained using our methods on real or synthetic networks. The synthetic networks were random graphs with power-law degree distributions and designed to have a large number of triangles. We used these graphs as they tend to correspond to the structure of large online networks. The real networks were samples of the WWW and social networks obtained from the SNAP database. In order to test that the methods are indeed practical, the total number of steps made by the walk was limited to at most the size n of the network. In fact the estimates appear to converge to the correct value at a lower number of steps, indicating that our proposed methods are feasible in practice.

Comparison of Cardiopulmonary Responses During 2 Incremental Step Tests in Subjects With COPD

It is well established that the work rate increment size affects the duration of test and physiological responses to exercise during cycling in patients with COPD. However, this has never been tested for incremental step tests. To compare the exercise tolerance time, cardiopulmonary stress, and perception of effort between the Chester step test (CST) and a modified incremental step test (MIST). Thirty-two subjects with COPD (FEV(1) 50 ± 15% of predicted) were randomized to perform the CST and MIST on the same day, an hour apart, on a single step (20 cm high). During tests, pulmonary gas exchange was measured continuously by a portable metabolic system. CST had shorter duration and also lower number of steps, in comparison with MIST. However, similar cardiopulmonary responses were observed at exercise peak: oxygen uptake (V(.)(O(2))) 1.22 ± 0.59 L/min vs 1.24 ± 0.55 L/min, minute ventilation (V(.)(E)) 30.8 ± 12.7 L/min vs 30.0 ± 11.7 L/min, heart rate 86 ± 13 beats/min vs 85 ± 13 beats/min, and S(pO(2)) 87 ± 7% vs 87 ± 6%. Dyspnea and leg fatigue scores when correcting for exercise duration were higher for CST. The slower the work rate increment during step test, the higher the exercise tolerance. Regardless of the work rate increment, cardiopulmonary stress and exertion effort at peak exercise were equivalent between tests.

Accurate particle size distribution determination by nanoparticle tracking analysis based on 2-D Brownian dynamics simulation

A physical model is presented to simulate the average step length distribution during nanoparticle tracking analysis experiments as a function of the particle size distribution and the distribution of the number of steps within the tracks. Considering only tracks of at least five steps, numerical simulation could be replaced by a normal distribution approximation. Based on this model, simulation of a step length distribution allows obtaining a much more reliable estimation of the particle size distribution, thereby reducing the artificial broadening of the distribution, as is typically observed by direct conversion of step length to particle size data. As this fitting procedure also allowed including data from particles that were followed for a relatively low number of steps, the measurement time could be reduced for particles that are known to be monodisperse. Whereas the inversion is less sensitive towards the particle size distribution width, still similar values were obtained for both the average diameter and standard deviation of a polystyrene latex sample irrespective of the track length, provided that the latter included at least five steps.

Experimental design for optimization of microwave-assisted extraction of benzodiazepines in human plasma

A simple and fast microwave-assisted-extraction (MAE) method has been evaluated as an alternative to solid-phase extraction (SPE) for the determination of six benzodiazepines widely prescribed in European countries (alprazolam, bromazepam, diazepam, lorazepam, lormetazepam and tetrazepam) in human plasma. For MAE optimization a Doehlert experimental design was used with extraction time, temperature and solvent volume as influential parameters. A desirability function was employed in addition to the simultaneous optimization of the MAE conditions. The analysis of variance showed that the solvent volume had a positive influence on the extraction of all the analytes tested, achieving a statistically significant effect. Also, the extraction time had a statistically significant effect on the extraction of four benzodiazepines. The selected MAE conditions-89 degrees C, 13 min and 8 mL of chloroform/2-propanol (4:1, v/v)-led to recoveries between 89.8 +/- 0.3 and 102.1 +/- 5.2% for benzodiazepines using a high performance liquid chromatography method coupled with diode-array detection. The comparison of MAE and SPE shows better results for MAE, with a lower number of steps in handling the sample and greater efficiency. The applicability of MAE was successfully tested in 27 plasma samples from benzodiazepine users.

Detection of enterotoxigenic Staphylococcus aureus isolates in raw milk cheese

To develop an easy, rapid and efficient DNA extraction procedure for Staphylococcus aureus detection with a low number of steps and removing completely the PCR inhibitors, applicable to raw milk cheese samples, and to compare phenotypical and genotypical method to detect Staph. aureus isolates and staphylococcal enterotoxins (SEs) production. A total of 33 bovine and caprine raw milk cheese samples were analysed by means of both classic microbiological and molecular techniques. All samples were positive for Staph. aureus contamination. The DNA extraction protocol optimized was found to achieve a detection limit of 100 CFU g(-1) for Staph. aureus. None of the samples tested with immunological assays contained SEs but in 14 of 33 samples a mixture of se positive (sea, sec, sed, seg, sel, sej) isolates were identified. Staphylococcus aureus is a food-borne pathogen mainly detected in finished dairy products. The rapid and efficient detection of Staph. aureus isolates from dairy products is essential for consumer safety. The direct detection of pathogens from food is possible with careful attention to sample preparation and nucleic acid amplification optimization. This study shows that raw milk cheese samples can be tested for Staph. aureus contamination with a rapid, simple and reproducible procedure.

Use of pedometers to measure physical activity in dogs

To determine whether pedometers can be used to measure physical activity in dogs. Cross-sectional study. 26 dogs. To determine pedometer accuracy, number of steps recorded with the pedometer as dogs walked, trotted, and ran for a distance of approximately 30 m (100 ft) at each gait was compared with actual number of steps. Dogs and owners then wore pedometers for 7 to 14 days, and dog pedometer output was compared with body condition score, owner-reported activity of the dog, and owner pedometer output. Most owners classified their dogs as active or quite active and indicated that their dogs exercised 3 to 7 days/wk. For all dogs, body condition score was 5, 6, or 7 on a scale from 1 to 9. At a walk, pedometers overestimated actual number of steps by approximately 17% in large and medium dogs and underestimated actual number of steps by approximately 7% in small dogs. No significant differences between pedometer-recorded and actual number of steps were detected when dogs trotted or ran. Number of steps per day for the dogs was significantly correlated with owner-reported activity of the dog (r = 0.305) and number of steps per day for the owners (r = 0.469) and was inversely correlated with body condition score (r = -0.554). Results suggest that pedometers can measure physical activity in dogs with reasonable accuracy. A lower number of steps per day was associated with a higher body condition score, and less active owners generally had less active dogs.

Development and real-time implementation of a rule-based auto-focus algorithm

This paper presents the development and real-time implementation of a rule-based approach to passive auto-focusing for digital still cameras. The implementation is performed on the processor DM310 which is specifically manufactured by Texas Instruments for digital still cameras. The squared-gradient sharpness function is considered to measure the amount of high-frequency content in an out-of-focus image. This sharpness function is then used within a rule-based search algorithm to obtain the focused lens position via moving the lens head step-motor. The developed rule-based approach is compared to the commonly used global search and binary search algorithms in terms of focusing speed and power consumption. It is shown that the introduced rule-based search algorithm achieves a lower number of focusing iterations or faster focusing speed, and a lower number of steps or lower power consumption.

Comparison of different methods for the determination of several quinolonic and cinolonic antibiotics in trout muscle tissue by HPLC with fluorescence detection

Quinolonic and cinolonic derivatives are mainly used as antibacterials in fish-farms. In this paper we describe a careful revision of the treatment procedures of samples and a prodedure for the determination of residues of these compounds. Because of the complexity and duration of these procedures, several studies have been carried out and these have lead to a simpler and shorter method. Three approaches have been examined: lyophilization followed by extraction with chloroform, solid-liquid extraction with chloroform and solid-liquid extraction with sodium hydroxide solution, followed by liquid-liquid partition in chloroform. Some previous studies into the partition equilibrium are also included. As a result of our studies we propose a procedure with a lower number of steps than those previously described in the literature. This method has been applied to the analysis of nalidixic, 7-hydroxymethylnalidixic and oxolinic acids and cinoxacin in trout muscle. These analysis have been carried out using an HPLC system equipped with a C18 column and fluorimetric detection. The mobile phase was acetonitrile:oxalic acid. The recoveries obtained were: 70–97% for 7-hydroxymethylnalidixic acid, 75–78% for nalidixic acid, 71–95% for oxolinic acid and 72–85% for cinoxacin.