Different thermal analysis technique application in determination of fold surface-free energy

In this work, the crystallization rates and spherulitic growth rate of miscible blends of poly(vinylidene fluoride) (PVDF) and acrylic rubber (ACM) were determined using differential scanning calorimetry (DSC), real-time FTIR, and optical microscopy. FTIR results suggest that blending does not induce the creation of polymorphic crystalline forms of PVDF. SAXS data demonstrate the formation of interlamellar structure after blending. The fold surface-free energy (σ e) was analyzed and compared using different thermal analysis techniques. The isothermal crystallization curves obtained using real-time FTIR and DSC explored in two different methods: t 1/2 or Avrami equation. While the Avrami equation is more widespread and precise, both analytical methods gave similar free energy of folding values. However, it was found that the direct optical method of measuring spherulitic growth rate yields σ e values 30-50 % lower than those obtained from the overall crystallization rate data. Conversely, the σ e values were found to increase with increasing amorphous ACM phase content regardless of the analytical methods

Towards a Green and Self-Powered Internet of Things Using Piezoelectric Energy Harvesting

Internet of things (IoT) is a revolutionizing technology which aims to create an ecosystem of connected objects and embedded devices and provide ubiquitous connectivity between trillions of not only smart devices but also simple sensors and actuators. Although recent advancements in miniaturization of devices with higher computational capabilities and ultra-low power communication technologies have enabled the vast deployment of sensors and actuators everywhere, such an evolution calls for fundamental changes in hardware design, software, network architecture, data analytic, data storage and power sources. A large portion of IoT devices cannot be powered by batteries only anymore, as they will be installed in hard to reach areas and regular battery replacement and maintenance are infeasible. A viable solution is to scavenge and harvest energy from environment and then provide enough energy to the devices to perform their operations. This will significantly increase the device life time and eliminate the need for the battery as an energy source. This survey aims at providing a comprehensive study on energy harvesting techniques as alternative and promising solutions to power IoT devices. We present the main design challenges of IoT devices in terms of energy and power and provide design considerations for a successful implementations of self-powered IoT devices. We then specifically focus on piezoelectric energy harvesting and RF energy harvesting as most promising solutions to power IoT devices and present the main challenges and research directions. We also shed light on the security challenges of energy harvesting enabled IoT systems and green big data.Comment: The paper has been submitted to IEEE Acces

Differential Expression of Human Homeodomain TGIFLX in Brain Tumor Cell Lines

Glioblastoma is the most common and the most lethal primary brain cancer. This malignancy is highly locally invasive, rarely metastatic and resistant to current therapies. Little is known about the distinct molecular biology of glioblastoma multiforme (GBM) in terms of initiation and progression. So far, several molecular mechanisms have been suggested to implicate in GBM development. Homeodomain (HD) transcription factors play central roles in the expression of genomic information in all known eukaryotes. The TGIFX homeobox gene was originally discovered in human adult testes. Our previous study showed implications of TGIFLX in prostate cancer and azoospermia, although the molecular mechanism by which TGIFLX acts is unknown. Moreover, studies reported that HD proteins are involved in normal and abnormal brain developments. We examined the expression pattern of TGIFLX in different human brain tumor cell lines including U87MG, A172, Daoy and 1321N1. Interestingly, real time RT-PCR and western blot analysis revealed a high level of TGIFLX expression in A172 cells but not in the other cell lines. We subsequently cloned the entire coding sequence of TGIFLX gene into the pEGFP-N1 vector, eukaryotic expression vector encoding eGFP, and transfected into the U-87 MG cell line. The TGIFLX-GFP expression was confirmed by real time RT-PCR and UV-microscopic analysis. Upon transfection into U87 cells, fusion protein TGIFLX-GFP was found to locate mainly in the nucleus. This is the first report to determine the nuclear localization of TGIFLX and evaluation of its expression level between different brain tumor cell lines. Our data also suggest that TGIFLX gene dysregulation could be involved in the pathogenesis of some human brain tumors

Electrospun Poly Caprolactone-Carbon Nanotube Scaffold for Nerve Regeneration in Dental Tissue Engineering

Regeneration and engineering of functional new tissues containing the neural network have great importance. Progression of neural network into the dental tissue has a crucial role in dental tissue regeneration. In the present study polymer-ceramic blended scaffolds containing different weight percentages of carbon nanotube in poly caprolactone nanofiber matrix were fabricated. Morphological, mechanical and electrical properties of the prepared scaffolds have been characterized. Results showed that the sample containing 5 weight % of carbon nanotube had the smallest mean fiber diameter (50 - 300 nm) and the highest mechanical behavior. Also, its electrical conductivity was suitable to be used in nerve tissue scaffolds. The static culture of the Schwann cells on the prepared scaffolds indicated that increasing weight percentage of carbon nanotube into the polycaprolactone matrix up to the 5 wt. % enhanced cell viability