Calf massager: Intervention for body muscle discomfort during prolonged standing

Many occupations require workers to stand for long periods of time without proper interventions, which causes discomfort in the back and lower limbs. Therefore, this study aims to assess the effectiveness in alleviating body muscle discomfort during prolonged standing through the use of a calf massager. This study was conducted among male workers at a manufacturer with production line workers and the list was obtained from the HR Department and simple random sampling was done by number categorization. A total of 100 respondents (50 respondents for both the control and the experimental groups) participated in this study. The experiment took place in a room with a similar setup for the production line. Each respondent was requested to perform the simulated task for 2 hr. For the experimental group, the calf massager was turned on every 15 min. At every 15‐min interval after turning on the calf massager, respondents from both groups were required to evaluate their discomfort level on a Borg's scale CR‐10 questionnaire. The results showed that the level of body discomfort among respondents in the experimental group reduced (20–30%) compared with that of the control group. Multivariate analysis results revealed that the discomfort rating for the lower back, knees, thighs, calves, and feet was significantly lower (p < .05) among the experimental group compared with the control group. For lower body parts, the lower back region was statistically significant (p < .05) at the 90th, 105th, and 120th min; the thigh region was statistically significant (p < .05) at the 120th min; the knee region was statistically significant (p < .05) at the 105th and 120th min; the calf region was statistically significant (p < .05) at all minute intervals except the 15th and 45th min, while the feet region, was statistically significant at the 105th and 120th min. Therefore, this study indicates that calf massage treatment is capable of reducing body muscle discomfort during prolonged standing and highlights the significance of calf massage.     

Universal Portfolios With and Without Transaction Costs

A constant rebalanced portfolio is an investment strategy which keeps the same distribution of wealth among a set of stocks from period to period. Recently there has been work on on-line investment strategies that are competitive with the best constant rebalanced portfolio determined in hindsight (Cover, 1991, 1996; Helmbold et al., 1996; Cover & Ordentlich, 1996a, 1996b; Ordentlich & Cover, 1996). For the universal algorithm of Cover (Cover, 1991),we provide a simple analysis which naturallyextends to the case of a fixed percentage transaction cost (commission ), answering a question raised in (Cover, 1991; Helmbold et al., 1996; Cover & Ordentlich, 1996a, 1996b; Ordentlich & Cover, 1996; Cover, 1996). In addition, we present a simple randomized implementation that is significantly faster in practice. We conclude by explaining how these algorithms can be applied to other problems, such as combining the predictions of statistical language models, where the resulting guarantees are more striking.     

Particle size effect on the magnetic properties of NiO nanoparticles prepared by a precipitation method

Nickel oxide (NiO) nanoparticles of nominal size range 16 nm and 25 nm were obtained by controlling the calcination temperature. These particles were prepared by the precipitation method. Structural, optical and morphological characterizations were done by X-ray powder diffraction, UV-vis diffuse reflectance spectroscopy and scanning electron microscopy. Studies of magnetic measurements (up to 60 kOe) and temperature variations from 2 K to 300 K of the NiO nanoparticles were investigated. Particles of 16 nm exhibited a weak ferromagnetic component and hysteresis loop. There is a increase in coercivity H_c and the remanence M_r at 8 K accompanied by an exchange bias H_E. H_E monotonically tends to zero as the particles size varied from 16 nm to 25 nm. The hysteresis loop and the size dependent χ are interpreted with the uncompensated surface spins, whereas the transition at 30 K is suggested to be Néel temperature T_N of the spins in the core of the 16 nm particles. In addition, the increasing temperature cannot showed an approach to saturation in the magnetization curve, it indicates the possibility of an asperomagnetism and/or spin glass behavior of the NiO nanoparticles.     

Combustion synthesis of CuFe2O4

Metallic ferrites are investigated as prospective materials for different applications especially as anodes in extractive metallurgy. CuFe₂O₄, one of the important ferrites, is envisaged for substituting the carbon anode in Hall-Heroult cells. A single step combustion process has been used for the synthesis of CuFe₂O₄ powder from cupric nitrate, ferric nitrate and urea. The experimental conditions for maximum conversion efficiency of the precursor powders have been optimized. X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) have confirmed the formation, structure and homogeneity of the as-prepared powders. The detailed physical, electrical and structural characterization of the materials have been carried out for the specimens obtained on sintering at different temperatures up to 1000 °C.     

Synthesis of MnWO4 nanorods and its electrical and electrochemical properties

The MnWO₄ nanorods were successfully synthesized by surfactant assisted ultrasonics method and characterized its structural (XRD), morphological (SEM) electrical (solid state impedance) and electrochemical (CV) properties. The X-ray diffraction patterns inferred the formation of highly crystalline monoclinic structure of MnWO₄. The formation of nanorods with the aspect ratios of 30–40?nm were reveals from SEM image. The maximum d.c. electrical conductivity was found to be 4.40?×?10^?5?S/cm at 570°C for MnWO₄ nanorods prepared by surfactant assisted ultrasonic method. The quasi-rectangular behavior of cyclic voltammogram inferred the supercapacitive behavior of the prepared MnWO₄ nanorods.     

2D graphene supported nickel oxide nano-composite for fiber optic ethanol gas sensing,removal of azo dye,and biological activity

Journal of Materials Science: Materials in Electronics - Green synthesis of multifunctional metal oxide nanoparticles and its composites are widely evaluated for their efficacy in environmental and...     

A Note on Learning from Multiple-Instance Examples

We describe a simple reduction from the problem of PAC-learning from multiple-instance examples to that of PAC-learning with one-sided random classification noise. Thus, all concept classes learnable with one-sided noise, which includes all concepts learnable in the usual 2-sided random noise model plus others such as the parity function, are learnable from multiple-instance examples. We also describe a more efficient (and somewhat technically more involved) reduction to the Statistical-Query model that results in a polynomial-time algorithm for learning axis-parallel rectangles with sample complexity Õ(d²r/²) , saving roughly a factor of r over the results of Auer et al. (1997).     

Reliable agnostic learning

It is well known that in many applications erroneous predictions of one type or another must be avoided. In some applications, like spam detection, false positive errors are serious problems. In other applications, like medical diagnosis, abstaining from making a prediction may be more desirable than making an incorrect prediction. In this paper we consider different types of reliable classifiers suited for such situations. We formalize the notion and study properties of reliable classifiers in the spirit of agnostic learning (Haussler, 1992; Kearns, Schapire, and Sellie, 1994), a PAC-like model where no assumption is made on the function being learned. We then give two algorithms for reliable agnostic learning under natural distributions. The first reliably learns DNFs with no false positives using membership queries. The second reliably learns halfspaces from random examples with no false positives or false negatives, but the classifier sometimes abstains from making predictions.