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Extensive research on functionalized graphene, graphene oxide, and carbon nanotube based cement composites has been carried out to strengthen and overcome the shortcomings of construction materials. However, less literature is available on the pure graphene based cement composite. In this review paper, an in-depth study on a graphene-based cement composite was performed. Various structural forms of graphene and classifications of graphene-based nanomaterial have been presented. The dispersion mechanism and techniques, which are important for effective utilization in the construction industry, are reviewed critically. Micro-scale characterization of carbon-based cement composite using thermogravimetric analysis (TGA), infrared (IR) spectroscopic analysis, x-ray diffractometric (XRD) analysis, and morphological analysis has also been reviewed. As per the authors’ knowledge, for the first time, a review of flow, energy harvesting, thermoelectrical, and self-sensing properties of graphene and its derivatives as the bases of cement composite are presented. The self-sensing properties of the composite material are reported by exploring physical applications by reinforcing graphene nanoplatelets (GNPs) into concrete beams.Growth hormone-releasing hormone (GHRH) is secreted primarily from the hypothalamus, but other tissues, including the lungs, produce it locally. GHRH stimulates the release and secretion of growth hormone (GH) by the pituitary and regulates the production of GH and hepatic insulin-like growth factor-1 (IGF-1). Pituitary-type GHRH-receptors (GHRH-R) are expressed in human lungs, indicating that GHRH or GH could participate in lung development, growth, and repair. GHRH-R antagonists (i.e., synthetic peptides), which we have tested in various models, exert growth-inhibitory effects in lung cancer cells in vitro and in vivo in addition to having anti-inflammatory, anti-oxidative, and pro-apoptotic effects. One antagonist of the GHRH-R used in recent studies reviewed here, MIA-602, lessens both inflammation and fibrosis in a mouse model of bleomycin lung injury. GHRH and its peptide agonists regulate the proliferation of fibroblasts through the modulation of extracellular signal-regulated kinase (ERK) and Akt pathways. In addition to downregulating GH and IGF-1, GHRH-R antagonist MIA-602 inhibits signaling pathways relevant to inflammation, including p21-activated kinase 1-signal transducer and activator of transcription 3/nuclear factor-kappa B (PAK1-STAT3/NF-κB and ERK). MIA-602 induces fibroblast apoptosis in a dose-dependent manner, which is an effect that is likely important in antifibrotic actions. Taken together, the novel data reviewed here show that GHRH is an important peptide that participates in lung homeostasis, inflammation, wound healing, and cancer; and GHRH-R antagonists may have therapeutic potential in lung diseases.Employing density functional theory calculations, we obtain the possibility of fine-tuning the bandgap in graphene deposited on the hexagonal boron nitride and graphitic carbon nitride substrates. We found that the graphene sheet located on these substrates possesses the semiconducting gap, and uniform biaxial mechanical deformation could provide its smooth fitting. Olitigaltin order Moreover, mechanical tension offers the ability to control the Dirac velocity in deposited graphene. We analyze the resonant scattering of charge carriers in states with zero total angular momentum using the effective two-dimensional radial Dirac equation. In particular, the dependence of the critical impurity charge on the uniform deformation of graphene on the boron nitride substrate is shown. It turned out that, under uniform stretching/compression, the critical charge decreases/increases monotonically. The elastic scattering phases of a hole by a supercritical impurity are calculated. It is found that the model of a uniform charge distribution over the small radius sphere gives sharper resonance when compared to the case of the ball of the same radius. Overall, resonant scattering by the impurity with the nearly critical charge is similar to the scattering by the potential with a low-permeable barrier in nonrelativistic quantum theory.A common metabolic condition for living organisms is starvation/fasting, a state that could play systemic-beneficial roles. Complex adaptive responses are activated during fasting to help the organism to maintain energy homeostasis and avoid nutrient stress. Metabolic rearrangements during fasting cause mild oxidative stress in skeletal muscle. The nuclear factor erythroid 2-related factor 2 (Nrf2) controls adaptive responses and remains the major regulator of quenching mechanisms underlying different types of stress. Here, we demonstrate a positive role of fasting as a protective mechanism against oxidative stress in skeletal muscle. In particular, by using in vivo and in vitro models of fasting, we found that typical Nrf2-dependent genes, including those controlling iron (e.g., Ho-1) and glutathione (GSH) metabolism (e.g., Gcl, Gsr) are induced along with increased levels of the glutathione peroxidase 4 (Gpx4), a GSH-dependent antioxidant enzyme. These events are associated with a significant reduction in malondialdehyde, a well-known by-product of lipid peroxidation. Our results suggest that fasting could be a valuable approach to boost the adaptive anti-oxidant responses in skeletal muscle.Network security is a crucial challenge facing Internet-of-Things (IoT) systems worldwide, which leads to serious safety alarms and great economic loss. This paper studies the problem of malicious interdicting network exploitation of IoT systems that are modeled as a bi-layer logical-physical network. In this problem, a virtual attack takes place at the logical layer (the layer of Things), while the physical layer (the layer of Internet) provides concrete support for the attack. In the interdiction problem, the attacker attempts to access a target node on the logical layer with minimal communication cost, but the defender can strategically interdict some key edges on the physical layer given a certain budget of interdiction resources. This setting generalizes the classic single-layer shortest-path network interdiction problem, but brings in nonlinear objective functions, which are notoriously challenging to optimize. We reformulate the model and apply Benders decomposition process to solve this problem. A layer-mapping module is introduced to improve the decomposition algorithm and a random-search process is proposed to accelerate the convergence.