Structural study in Highly Compressed BiFeO3 Epitaxial Thin Films on YAlO3

We report a study on the thermodynamic stability and structure analysis of the epitaxial BiFeO3 (BFO) thin films grown on YAlO3 (YAO) substrate. First we observe a phase transition of MC-MA-T occurs in thin sample (<60 nm) with an utter tetragonal-like phase (denoted as MII here) with a large c/a ratio (~1.23). Specifically, MII phase transition process refers to the structural evolution from a monoclinic MC structure at room temperature to a monoclinic MA at higher temperature (150oC) and eventually to a presence of nearly tetragonal structure above 275oC. This phase transition is further confirmed by the piezoforce microscopy measurement, which shows the rotation of polarization axis during the phase transition. A systematic study on structural evolution with thickness to elucidate the impact of strain state is performed. We note that the YAO substrate can serve as a felicitous base for growing T-like BFO because this phase stably exists in very thick film. Thick BFO films grown on YAO substrate exhibit a typical "morphotropic-phase-boundary"-like feature with coexisting multiple phases (MII, MI, and R) and a periodic stripe-like topography. A discrepancy of arrayed stripe morphology in different direction on YAO substrate due to the anisotropic strain suggests a possibility to tune the MPB-like region. Our study provides more insights to understand the strain mediated phase co-existence in multiferroic BFO system.Comment: 18 pages, 6 figures, submitted to Journal of Applied Physic

Acute Viral Hepatitis C-Induced Jaundice in Pregnancy

SummaryObjectiveAcute viral hepatitis C-induced jaundice in pregnancy is very rare and may be fatal. Here, we report a complicated case with acute hepatitis C-induced jaundice in pregnancy with successful managementCase ReportA 27-year-old pregnant woman, gravida 2, para 1, with gestational age of 36 weeks and 5 days, was referred to our hospital due to jaundice and elevated liver enzymes of undetermined cause. She had been suffering from general weakness, diarrhea and vomiting for 1 week, and jaundice with tea-colored urine for 3 days. At our medical center, acute viral hepatitis C-induced jaundice was suspected. Since her general condition deteriorated at 36 weeks and 6 days of gestation, we decided to induce labor. A male baby was born smoothly via the vaginal route, with birth weight 2,857 g, birth length 48.6 cm, and 1- and 5-minute Apgar scores of 7 and 9, respectively. Maternal condition improved dramatically after delivery and her serum liver enzymes and bilirubin levels gradually approached normal ranges.ConclusionMothers and fetuses with acute viral hepatitis C-induced jaundice during pregnancy are at great risk of mortality and morbidity. Timely termination may be one of the choices of treatment when fetal maturity has been reached and the maternal condition has deteriorated

Gallic Acid Induces a Reactive Oxygen Species-Provoked c-Jun NH 2

Idiopathic pulmonary fibrosis is a chronic lung disorder characterized by fibroblasts proliferation and extracellular matrix accumulation. Induction of fibroblast apoptosis therefore plays a crucial role in the resolution of this disease. Gallic acid (3,4,5-trihydroxybenzoic acid), a common botanic phenolic compound, has been reported to induce apoptosis in tumor cell lines and renal fibroblasts. The present study was undertaken to examine the role of mitogen-activated protein kinases (MAPKs) in lung fibroblasts apoptosis induced by gallic acid. We found that treatment with gallic acid resulted in activation of c-Jun NH2-terminal kinase (JNK), extracellular signal-regulated kinase (ERK), and protein kinase B (PKB, Akt), but not p38MAPK, in mouse lung fibroblasts. Inhibition of JNK using pharmacologic inhibitor (SP600125) and genetic knockdown (JNK specific siRNA) significantly inhibited p53 accumulation, reduced PUMA and Fas expression, and abolished apoptosis induced by gallic acid. Moreover, treatment with antioxidants (vitamin C, N-acetyl cysteine, and catalase) effectively diminished gallic acid-induced hydrogen peroxide production, JNK and p53 activation, and cell death. These observations imply that gallic acid-mediated hydrogen peroxide formation acts as an initiator of JNK signaling pathways, leading to p53 activation and apoptosis in mouse lung fibroblasts

Fast-Flux Bot Detection in Real Time

Abstract. The fast-flux service network architecture has been widely adopted by bot herders to increase the productivity and extend the lifes-pan of botnets ’ domain names. A fast-flux botnet is unique in that each of its domain names is normally mapped to different sets of IP addresses over time and legitimate users ’ requests are handled by machines other than those contacted by users directly. Most existing methods for de-tecting fast-flux botnets rely on the former property. This approach is effective, but it requires a certain period of time, maybe a few days, before a conclusion can be drawn. In this paper, we propose a novel way to detect whether a web service is hosted by a fast-flux botnet in real time. The scheme is unique because it relies on certain intrinsic and invariant characteristics of fast-flux bot-nets, namely, 1) the request delegation model, 2) bots are not dedicated to malicious services, and 3) the hardware used by bots is normally infe-rior to that of dedicated servers. Our empirical evaluation results show that, using a passive measurement approach, the proposed scheme can detect fast-flux bots in a few seconds with more than 96 % accuracy, while the false positive/negative rates are both lower than 5%

Development of a deep learning-based tool to assist wound classification

This paper presents a deep learning-based wound classification tool that can assist medical personnel in non-wound care specialization to classify five key wound conditions, namely deep wound, infected wound, arterial wound, venous wound, and pressure wound, given color images captured using readily available cameras. The accuracy of the classification is vital for appropriate wound management. The proposed wound classification method adopts a multi-task deep learning framework that leverages the relationships among the five key wound conditions for a unified wound classification architecture. With differences in Cohen's kappa coefficients as the metrics to compare our proposed model with humans, the performance of our model was better or non-inferior to those of all human medical personnel. Our convolutional neural network-based model is the first to classify five tasks of deep, infected, arterial, venous, and pressure wounds simultaneously with good accuracy. The proposed model is compact and matches or exceeds the performance of human doctors and nurses. Medical personnel who do not specialize in wound care can potentially benefit from an app equipped with the proposed deep learning model

Assessment of Clustered Renewable Energy Systems Interconnected with Low-Voltage Distribution Networks

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