Bio-Cyber Interface Parameter Estimation with Neural Network for the Internet of Bio-Nano Things

Wireless Personal Communications - Recently, there is growing interest in the Internet of Bio-Nano Things (IoBNT) based on biological communication with the advent of communication engineering and...     

Phenotypic,genetic, and single nucleotide polymorphism marker associations between calf diseases and subsequent performance and disease occurrences of first-lactation German Holstein cows

A total of 31,396 females born from 2010 to 2013 in 43 large-scale Holstein-Friesian herds were phenotyped for calf and cow disease traits using a veterinarian diagnosis key. Calf diseases were general disease status (cGDS), calf diarrhea (cDIA), and calf respiratory disease (cRD) recorded from birth to 2 mo of age. Incidences were 0.48 for cGDS, 0.28 for cRD, and 0.21 for cDIA. Cow disease trait recording focused on the early period directly after calving in first parity, including the interval from 10 d before calving to 200 d in lactation. For cows, at least one entry for the respective disease implied a score = 1 (sick); otherwise, score = 0 (healthy). Corresponding cow diseases were first-lactation general disease status (flGDS), first-lactation diarrhea (flDIA), and first-lactation respiratory disease (flRD). Additional cow disease categories included mastitis (flMAST), claw disorders (flCLAW), female fertility disorders (flFF), and metabolic disorders (flMET). A further cow trait category considered first-lactation test-day production traits from official test-days 1 and 2 after calving. The genotype data set included 41,256 single nucleotide polymorphisms (SNP) from 9,388 females with phenotypes. Linear and generalized linear mixed models with a logit link-function were applied to Gaussian and categorical cow traits, respectively, considering the calf disease as a fixed effect. Most of the calf diseases were not significantly associated with the occurrence of any cow disease. By trend, increasing risks for the occurrence of cow diseases were observed for healthy calves, indicating mechanisms of disease resistance with aging. Also by trend, occurrence of calf diseases was associated with decreasing milk, protein, and fat yields. Univariate linear and threshold animal models were used to estimate heritabilities and breeding values (EBV) for all calf and cow traits. Heritabilities for cGDS and cRD were 0.06 and 0.07 for cDIA. Genetic correlations among all traits were estimated using linear-linear animal models in a series of bivariate runs. The genetic correlation between cDIA and cRD was 0.29. Apart from the genetic correlation between flRD with cGDS (?0.38), EBV correlations and genetic correlations between calf diseases with all cow traits were close to zero. Genome-wide association studies were applied to estimate SNP effects for cRD and cDIA, and for the corresponding traits observed in cows (flRD and flDIA). Different significant SNP markers contributed to cDIA and flDIA, or to cRD and flRD. The average correlation coefficient between cRD and flRD considering SNP effects from all chromosomes was 0.01, and between cDIA and flDIA was ?0.04. In conclusion, calf diseases are not appropriate early predictors for cow traits during the early lactation stage in parity 1.     

Synthesis and characterization of partially crystalline nanosized ZSM-5 zeolites

Partially crystalline nanosize ZSM-5 with high surface area (678 m²/g) was synthesized successfully without using organic template by a two-step temperature process. Aluminum nitrate was used as aluminum source for the first time to synthesize ZSM-5 materials. The presence of MFI structure of the materials was analyzed by XRD, FTIR, Raman spectroscopy and TEM techniques. Addition of commercial HZSM-5 as a seeding agent to the reactants resulted an increase in crystallinity of the ZSM-5 sample and subsequent decrease in specific surface area. The partially crystalline samples exhibited low microporosity and remarkably high meso/macropore volume with pore diameters around 30 nm.     

Modeling and optimization of a bioethanol production facility

The overall objective of this study is to identify the optimal bioethanol production plant capacity, configuration, and operating conditions, based on currently available technology for all the processing sections involved. To effect this study, a systematic method is utilized which involves the development of a process flow-sheet and superstructure for the overall technology selection. It also includes simulation as well as mathematical model development for each processing step. The optimality of each process pathway is determined via economic analysis. The developed optimization model also incorporates various biomass feedstocks as well as realistic upper and lower limit equipment sizes thereby ensuring pragmatism of the work. For this study, the criterion for optimization is minimum ethanol price. The secondary objective of this study attempts to mathematically model the seasonal variation in availability of biomass feedstock. This sub-model is incorporated into the overall model and economic evaluations done to determine the minimum ethanol selling price and optimal plant capacity.     

99M o/99m Tc chromatographic column generator based on cerium(IV) molybdate gel

Cerium(IV) molybdate was prepared and characterized by IR spectroscopy, thermal analysis, and XRD. The highest precipitation yield of ^99m o within the formed gel was found to be 63% with the Mo: Ce molar ratio of 2: 1. ^99m o/^99m Tc chromatographic column generator based on Ce(IV) molybdate was prepared and eluted with 10 ml of 0.9% NaCl solution. The elution yield of ^99m Tc was 75.4 ± 2.2% with the radiochemical purity of 97.3 ± 0.8%. The activity contribution of ^99m o in the ^99m Tc eluate did not exceed (2.0 ± 0.5) × 10^?3%. The Mo and Ce concentrations in the ^99m Tc eluates did not exceed 2 and 0.5 ppm, respectively.