Wafer-scale graphene/ferroelectric hybrid devices for low-voltage electronics

Preparing graphene and its derivatives on functional substrates may open enormous opportunities for exploring the intrinsic electronic properties and new functionalities of graphene. However, efforts in replacing SiO$_{2}$ have been greatly hampered by a very low sample yield of the exfoliation and related transferring methods. Here, we report a new route in exploring new graphene physics and functionalities by transferring large-scale chemical vapor deposition single-layer and bilayer graphene to functional substrates. Using ferroelectric Pb(Zr$_{0.3}$Ti$_{0.7}$)O$_{3}$ (PZT), we demonstrate ultra-low voltage operation of graphene field effect transistors within $\pm1$ V with maximum doping exceeding $10^{13}\,\mathrm{cm^{-2}}$ and on-off ratios larger than 10 times. After polarizing PZT, switching of graphene field effect transistors are characterized by pronounced resistance hysteresis, suitable for ultra-fast non-volatile electronics.Comment: 4 pages, 3 figures; EPL 2011; In pres

Forty years literature review of primary lung lymphoma

There are several unresolved issues through out the literature regarding the entity of primary lung lymphoma. Extensive literature review of this uncommon pathology is carried out

Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes

publisher: Elsevier articletitle: Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes journaltitle: Cell articlelink: https://doi.org/10.1016/j.cell.2018.05.046 content_type: article copyright: © 2018 Elsevier Inc

Determination of angry condition based on EEG, speech and heartbeat

This paper determines the angry emotion condition by analyzing and recognizing speech signal, EEG signal, as well as detecting the heartbeat. For the speech analyzing experiment, several digital signal processing methods such as autocorrelation and linear predication technique was introduced to analyze the features. Then, Artificial Neural Network (ANN) was used to classify each parameter features such as mean fundamental frequency, maximum fundamental frequency, standard deviation fundamental frequency, mean amplitude, pause length ratio and first formant frequency to recognize the emotion. For the EEG analysis, the raw EEG signal was undergone preprocessing to remove the artifacts to minimal. Some features as mean, standard deviation, the peak amplitude, the peak amplitude in alpha band (PAA) and the peak frequency in alpha band (PAF) of the EEG signals were extracted. The selected features were classified by using ANN to obtain the maximum classification accuracy rate. Meanwhile, a heartbeat monitoring circuit was developed to measure the heartbeat. The result showed that angry emotion has relatively low condition in mean value, maximum peak amplitude and relatively high peak frequency in alpha band (PAF) of the EEG signals. The mean fundamental frequency, standard deviation fundamental frequency and mean intensity of the speech signal are good in determining the angry emotion. This method can be used further to recognize angry emotion of patient during counseling session

A Versatile Assay for High-Throughput Gene Expression Profiling on Universal Array Matrices

We report a flexible, sensitive, and quantitative gene-expression profiling system for assaying more than 400 genes, with three probes per gene, for 96 samples in parallel. The cDNA-mediated annealing, selection, extension and ligation (DASL) assay targets specific transcripts, using oligonucleotides containing unique address sequences that can hybridize to universal arrays. Cell-specific gene expression profiles were obtained using this assay for hormone-treated cell lines and laser-capture microdissected cancer tissues. Gene expression profiles derived from this assay were consistent with those determined by qRT-PCR. The DASL assay has been automated for use with a bead-based 96-array matrix system. The combined high-throughput assay and readout system is accurate and efficient, and can cost-effectively profile the expression of hundreds of genes in thousands of samples

Algorithm for diagnosing hypertension using out‐of‐office blood pressure measurements

Abstract The authors developed and validated a diagnostic algorithm using the optimal upper and lower cut‐off values of office and home BP at which ambulatory BP measurements need to be applied. Patients presenting with high BP (≥140/90 mm Hg) at the outpatient clinic were referred to measure office, home, and ambulatory BP. Office and home BP were divided into hypertension, intermediate (requiring diagnosis using ambulatory BP), and normotension zones. The upper and lower BP cut‐off levels of intermediate zone were determined corresponding to a level of 95% specificity and 95% sensitivity for detecting daytime ambulatory hypertension by using the receiver operator characteristic curve. A diagnostic algorithm using three methods, OBP‐ABP: office BP measurement and subsequent ambulatory BP measurements if office BP is intermediate zone; OBP‐HBP‐ABP: office BP, subsequent home BP measurement if office BP is within intermediate zone and subsequent ambulatory BP measurement if home BP is within intermediate zone; and HBP‐ABP: home BP measurement and subsequent ambulatory BP measurements if home BP is within intermediate zone, were developed and validated. In the development population (n = 256), the developed algorithm yielded better diagnostic accuracies than 75.8% (95%CI 70.1–80.9) for office BP alone and 76.2% (95%CI 70.5–81.3) for home BP alone as follows: 96.5% (95%CI: 93.4–98.4) for OBP‐ABP, 93.4% (95%CI: 89.6–96.1) for OBP‐HBP‐ABP, and 94.9% (95%CI: 91.5–97.3%) for HBP‐ABP.  In the validation population (n = 399), the developed algorithm showed similarly improved diagnostic accuracy. The developed algorithm applying ambulatory BP measurement to the intermediate zone of office and home BP improves the diagnostic accuracy for hypertension

Class 1 integronase gene and tetracycline resistance genes tetA and tetC in different water environments of Jiangsu Province, China

Class 1 integronase gene (intI1) and tetracycline resistance genes (tetA and tetC) from various environmental sites in Jiangsu Province (China) were detected using qualitative PCR (polymerase chain reaction) and quantified with SYBR Green-based qRT-PCR (quantitative real-time PCR) in this study. Qualitative PCR assays demonstrated that intI1, tetA and tetC occurred in the water environments of Taihu Lake, the Nanjing section of the Yangtze River, a sewage treatment plant (STP) in Nanjing City, and two drinking water treating bioreactors. qRT-PCR results showed that abundance of intI1 in lake water and sediments was lower than the tet genes, for a given sample site and date (P < 0.05). On a volumetric basis, lake sediments contained higher concentrations of the three genes by four to five orders of magnitude than water samples, and lake water and sediments sampled in April contained fewer copies of all the genes than the samples collected in June and August (P < 0.05). The levels of intI1, tetA and tetC in the Yangtze River water increased significantly after the river flowed through Nanjing City (P < 0.05). 94.1% integron, 97.2% tetA and 98.3% tetC were removed by the activated sludge process in the STP, and more than 80% of each gene was removed in both of the two biofilters in terms of relative concentration based on sample volume. However, on the basis of DNA mass, lower removals were obtained for both the activated sludge and biofiltration processes. © Springer Science+Business Media, LLC 2009.link_to_subscribed_fulltex