Short- and Long-Term Effects of Prenatal Exposure to Iron Oxide Nanoparticles: Influence of Surface Charge and Dose on Developmental and Reproductive Toxicity

Iron oxide nanoparticles (NPs) are commonly utilized for biomedical, industrial, and commercial applications due to their unique properties and potential biocompatibility. However, little is known about how exposure to iron oxide NPs may affect susceptible populations such as pregnant women and developing fetuses. To examine the influence of NP surface-charge and dose on the developmental toxicity of iron oxide NPs, Crl:CD1(ICR) (CD-1) mice were exposed to a single, low (10 mg/kg) or high (100 mg/kg) dose of positively-charged polyethyleneimine-Fe₂O₃-NPs (PEI-NPs), or negatively-charged poly(acrylic acid)-Fe₂O₃-NPs (PAA-NPs) during critical windows of organogenesis (gestation day (GD) 8, 9, or 10). A low dose of NPs, regardless of charge, did not induce toxicity. However, a high exposure led to charge-dependent fetal loss as well as morphological alterations of the uteri (both charges) and testes (positive only) of surviving offspring. Positively-charged PEI-NPs given later in organogenesis resulted in a combination of short-term fetal loss (42%) and long-term alterations in reproduction, including increased fetal loss for second generation matings (mice exposed in utero). Alternatively, negatively-charged PAA-NPs induced fetal loss (22%) earlier in organogenesis to a lesser degree than PEI-NPs with only mild alterations in offspring uterine histology observed in the long-term.     

Cooperative adaptive neural partial tracking errors constrained control for nonlinear multi‐agent systems

This paper considers the problem of partial tracking errors constrained for high‐order nonlinear multi‐agent systems in strict‐feedback form. In the control design, radial‐based function neural networks are utilized to identify uncertain nonlinear functions, and a cooperative adaptive dynamic surface control is proposed to avoid the explosion of complexity in the backstepping technique. Based on the minimal learning parameter technique and the predefined performance approach, a novel cooperative adaptive neural network control method is developed. The proposed controller is able to guarantee that all the closed‐loop network signals are cooperative semi‐globally uniformly ultimately bounded, and partial tracking errors confine all times within the predefined bounds. Finally, simulation example and comparative example with previous methods are given to verify and clarify the effectiveness of the new design procedure. Copyright © 2016 John Wiley & Sons, Ltd.     

Synthesis and characterization of ethylene-xylene-based polysulfide block-copolymers using the interfacial polymerization method

Copolymers of linear and aromatic polysulfide blocks are synthesized using interfacial polymerization of dichloro-xylene-based aromatic and ethylene-dichloride-based non-aromatic organic monomers. Synthesized copolymers consist of poly(ethylene sulfide) as well as ploy (xylene sulfide) blocks. Fascinating properties of linear and aromatic polysulfide species are gathered in the structure of synthesized polysulfide copolymers. Ethylene dichloride and α,α′-dichloro-p-xylene are used as the non-aromatic and aromatic organic monomers, respectively. To investigate the influences of sulfur contents in the backbone of the polymer on the thermal stability of synthesized copolymers, poly(ethylene-xylene disulfide) (PEXDS), poly(ethylene-xylene trisulfide) (PEXTRS) and poly(ethylene-xylene tetrasulfide) (PEXTS) copolymers are synthesized using, respectively, sodium disulfide, sodium trisulfide and sodium tetrasulfide, as aqueous monomers. Compared to both linear and nonlinear homopolymers, synthesized copolymers exhibit improved thermal stability. Moreover, the thermal degradation temperatures of synthesized copolymers improve by decreasing the number of sulfur atoms in the backbone of copolymers. These results reveal that thermal degradation of polysulfide copolymers can be tailored by controlling the polysulfide chain’s sulfur contents. Structural characteristics of synthesized polysulfide copolymers are also investigated using Fourier transform infrared spectroscopy, proton nuclear magnetic resonance spectroscopy and X-ray diffraction analysis.     

Synthetic and physical characterization of phase change materials microencapsulated by complex coacervation for thermal energy storage applications

This paper presents a comprehensive study of encapsulated phase change materials (PCMs). In order to investigate some synthesis parameters, microencapsulated paraffin with gelatin/gum Arabic wall system was prepared by the complex coacervation method and the performance of these microcapsules was evaluated by optical microscopy and differential scanning calorimetry. Further investigations were carried out on the impact of physical parameters on the melting time by studying the constrained melting transformation of an encapsulated PCM in a spherical shell subjected to a constant temperature media. Results indicate successful production of PCM microcapsules with high melting enthalpy (116 kJ/kg), and the effects of diameter and thermal conductivity on melting time of PCMs were demonstrated. Copyright © 2014 John Wiley & Sons, Ltd.     

Stream processing coalgebraically

We study various operations for splitting, partitioning, projecting and merging streams of data. These operations are motivated by their use in dataflow programming and stream processing languages. We use the framework of stream calculus and stream circuits for defining and proving properties of such operations using behavioural differential equations and coinduction proof principles. As a featured example we give proofs of results, observed by Moessner, from elementary number theory using our framework. We study the invariance of certain well patterned classes of streams, namely rational and algebraic streams, under splitting and merging. Finally we show that stream circuits extended with gates for dyadic split and merge are expressive enough to realise some non-rational algebraic streams, thereby going beyond ordinary stream circuits.     

Genetic-based modeling of uplift capacity of suction caissons

In this study, classical tree-based genetic programming (TGP) and its recent variants, namely linear genetic programming (LGP) and gene expression programming (GEP) are utilized to develop new prediction equations for the uplift capacity of suction caissons. The uplift capacity is formulated in terms of several inflecting variables. An experimental database obtained from the literature is employed to develop the models. Further, a conventional statistical analysis is performed to benchmark the proposed models. Sensitivity and parametric analyses are conducted to verify the results. TGP, LGP and GEP are found to be effective methods for evaluating the horizontal, vertical and inclined uplift capacity of suction caissons. The TGP, LGP and GEP models reach a prediction performance better than or comparable with the models found in the literature.