Development of Composite Textile Structures for Wound Dressing Applications

The main objective of this research work was the development of novel and responsive nonwoven composite structures containing gelling materials for wound management. The development of novel all inclusive collagen booster(CB) therapeutic nonwoven wound dressings was mainly focused on. It provides essential functional properties such as high absorption,vertical and lateral wicking,and antibacterial and acidic pH properties. The developed composite wound dressing consisted of carboxymethylcellulose(CMC) fibre and also it was reinforced with polylactic acid( PLA) fibre. The produced composite wound dressings were treated with two different CBs at 4% by using the spray method. The details of the CBs have not been disclosed in this paper due to the Intellectual Property Rights( IPR) issues. The important benefit of using CB treatment is that it allows the maintenance of an acidic pH environment at the wound area. It is well known that acidic pH reduces the wound healing time and enhances the wound healing process. Furthermore,one of the CBs not only promotes the proliferation of the epithelial cells in wounds but also can provide antibacterial action. The PLA fibre reinforced CMC composite dressing has enhanced wicking properties which help to minimise the pooling of exudate on the wound bed and as a result maceration is prevented. The CBs treated dressings maintain the wound bed in an acidic pH condition which also improves the wound healing process. In addition to the above-mentioned properties,the CB treatment imparts antimicrobial activity against Gram-positive and Gram-negative bacteria,thus resulting in the reduction in the propensity for wound infection. Ultimately,the research has proved that the 4% CB treatment enhances the antimicrobial activity and the acidic pH characteristics of the developed CMC /PLA composite wound dressings.     

A BVAR model for the connecticut economy

A Bayesian vector autoregressive (BVAR) model is developed for the Connecticut economy to forecast the unemployment rate, nonagricultural employment, real personal income, and housing permits authorized. The model includes both national and state variables. The Bayesian prior is selected on the basis of the accuracy of the out-of-sample forecasts. We find that a loose prior generally produces more accurate forecasts. The out-of-sample accuracy of the BVAR forecasts is also compared with that of forecasts from an unrestricted VAR model and of benchmark forecasts generated from univariate ARIMA models. The BVAR model generally produces the most accurate short- and long-term out-of-sample forecasts for 1988 through 1992. It also correctly predicts the direction of change.     

BubR1 insufficiency causes early onset of aging-associated phenotypes and infertility in mice

Faithful segregation of replicated chromosomes is essential for maintenance of genetic stability and seems to be monitored by several mitotic checkpoints. Various components of these checkpoints have been identified in mammals, but their physiological relevance is largely unknown. Here we show that mutant mice with low levels of the spindle assembly checkpoint protein BubR1 develop progressive aneuploidy along with a variety of progeroid features, including short lifespan, cachectic dwarfism, lordokyphosis, cataracts, loss of subcutaneous fat and impaired wound healing. Graded reduction of BubR1 expression in mouse embryonic fibroblasts causes increased aneuploidy and senescence. Male and female mutant mice have defects in meiotic chromosome segregation and are infertile. Natural aging of wild-type mice is marked by decreased expression of BubR1 in multiple tissues, including testis and ovary. These results suggest a role for BubR1 in regulating aging and infertility.     

ARIMA models of the price level: An assessment of the multilevel adaptive learning process in the USA

This paper estimates the ARIMA processes for the observed and expected price level corresponding to the three-level adaptive expectations model proposed by Jacobs and Jones (1980). These univariate processes are then compared with the best-fit ARIMA model. The results indicate that the best-fit model for the observed price level is a restricted version of the two-level adaptive learning process specified in terms of prices, suggesting a simple adaptive rule in the inflation rate. A comparison of the time-series forecasts from the best-fit model with the mean responses to the ASA-NBER survey shows no significant difference in their accuracy. The time-series forecasts are, however, conditionally efficient. The best-fit ARIMA model for expected prices measured by the ASA-NBER consensus forecasts does not correspond to any version of the Jacobs and Jones model.     

A genome scan for quantitative trait loci affecting grain yield and its components of maize both in single-and two-locus levels

Maize is one of the most important cereal crops in the world. The hybrid yield advantage is responsible for about 10 percent of the total global maize production of 550 Mt[1]. It is exigent to study the yield traits so as to improve the hybrids per se in …