Synergistic Effects of Polybenzimidazole and Aramide on Enhancing Flame-Retardancy and Solubility

Aromatic and functional polymers with processibility derived from biobased starting materials are prerequisite considering sustainable society. Poly(2,5-benzimidazole)s are rigid-rod polymers to show ultrahigh thermal stability such as flame retardance, while usually suffer from poor solubility. Here, poly(benzimidazole-co-amide)s are synthesized from two biobased monomers, 3,4-diaminobenzoic acid and a semirigid comonomer, 4-aminohydrocinnamic acid. The copolymers with an amide composition of 80 mol% and higher are soluble in widely used polar solvents to fabricate the films keeping high flame retardance, which is comparable with popular high-performance polymers such as aromatic polyimides, polyetheretherketone, polyphenylene sulfide, etc.     

An efficient verifiable (t,n)-threshold secret image sharing scheme with ultralight shares

Multimedia Tools and Applications - A secret sharing scheme partitions a secret into a set of shares and distributes them among the eligible participants, with each participant receiving one share...     

CMV colitis masquerading as colon cancer--an unusual presentation of acquired immunodeficiency syndrome

To determine whether there is any correlation between sudden decrease in barometric pressure and onset of labor, a non-experimental, retrospective study at a 948-bed tertiary care hospital was done. Pregnant patients of 36 weeks gestation or more who presented with spontaneous onset of labor during the 48 hours surrounding the 12 occurrences of significant drop in barometric pressure in 1992 were included in the study. Significantly more occurrences of onset of labor were identified in the 24 hours after a drop in barometric pressure than were identified in the 24 hours prior to the drop in barometric pressure (P < 0.05). Therefore, the overall number of labor onsets increased in the 24 hours following a significant drop in barometric pressure.     

A new method to estimate parameters of linear compartmental models using artificial neural networks

At present, the preferred tool for parameter estimation in compartmental analysis is an iterative procedure; weighted nonlinear regression. For a large number of applications, observed data can be fitted to sums of exponentials whose parameters are directly related to the rate constants/coefficients of the compartmental models. Since weighted nonlinear regression often has to be repeated for many different data sets, the process of fitting data from compartmental systems can be very time consuming. Furthermore the minimization routine often converges to a local (as opposed to global) minimum. In this paper, we examine the possibility of using artificial neural networks instead of weighted nonlinear regression in order to estimate model parameters. We train simple feed-forward neural networks to produce as outputs the parameter values of a given model when kinetic data are fed to the networks' input layer. The artificial neural networks produce unbiased estimates and are orders of magnitude faster than regression algorithms. At noise levels typical of many real applications, the neural networks are found to produce lower variance estimates than weighted nonlinear regression in the estimation of parameters from mono- and biexponential models. These results are primarily due to the inability of weighted nonlinear regression to converge. These results establish that artificial neural networks are powerful tools for estimating parameters for simple compartmental models.     

A behavioral medicine intervention in persons with HIV

This study used a pretest-posttest preexperimental design to examine the effect of a 10-week behavioral medicine support group intervention in a sample of persons with HIV. Using Solomon's psychoneuroimmunologic framework, the 10-week behavioral medicine program focused on the mind/body interaction, the relaxation response, coping with illness, hardiness, and nutrition. Pearson correlation coefficients and t tests were performed on the pre- and postintervention measures of hardiness, social support, immune function, and perceived health status. Results of the study indicated that hardiness (preintervention) and CD4 counts (pre- and postintervention) were significantly correlated with health status; however, CD4 counts decreased over the course of the behavioral medicine program. Implications for nursing and recommendations for further research are discussed.     

Fetus-in-fetu with malignant recurrence

Fetus-in-fetu is an unusual condition in which a vertebrate fetus is enclosed within the abdomen of another fetus. These occurrences are usually benign. This report describes an instance of malignant recurrence after resection of a fetus-in-fetu.