Frequency Comb Assisted Diode Laser Spectroscopy for Measurement of Microcavity Dispersion

While being invented for precision measurement of single atomic transitions, frequency combs have also become a versatile tool for broadband spectroscopy in the last years. In this paper we present a novel and simple approach for broadband spectroscopy, combining the accuracy of an optical fiber-laser-based frequency comb with the ease-of-use of a tunable external cavity diode laser. This scheme enables broadband and fast spectroscopy of microresonator modes and allows for precise measurements of their dispersion, which is an important precondition for broadband optical frequency comb generation that has recently been demonstrated in these devices. Moreover, we find excellent agreement of measured microresonator dispersion with predicted values from finite element simulations and we show that tailoring microresonator dispersion can be achieved by adjusting their geometrical properties

Characteristics comparison of optimal L-band Er-doped ASE sources in different configurations

In this paper, we investigate the 1480nm pumped L-band erbium doped fiber amplified spontaneous emission source of three major configurations: one-stage double-pass forward pump configuration, two-stage with C-band ASE injection configuration, one-stage double-pass bi-directional pump configuration. The characteristics are compared in terms of the output power, pumping conversion efficiency, bandwidth, and mean wavelength stability. It is shown that the one-stage double-pass bi-directional pump configuration has a better performance than the other two configurations

Ensemble Learning for Low-Level Hardware-Supported Malware Detection

Abstract. Recent work demonstrated hardware-based online malware detection using only low-level features. This detector is envisioned as a first line of defense that prioritizes the application of more expensive and more accurate software detectors. Critical to such a framework is the detection performance of the hardware detector. In this paper, we explore the use of both specialized detectors and ensemble learning tech-niques to improve performance of the hardware detector. The proposed detectors reduce the false positive rate by more than half compared to a single detector, while increasing the detection rate. We also contribute approximate metrics to quantify the detection overhead, and show that the proposed detectors achieve more than 11x reduction in overhead compared to a software only detector (1.87x compared to prior work), while improving detection time. Finally, we characterize the hardware complexity by extending an open core and synthesizing it on an FPGA platform, showing that the overhead is minimal.

Hot Photoluminescence in γ-In2Se3Nanorods

The energy relaxation of electrons in γ-In2Se3nanorods was investigated by the excitation-dependent photoluminescence (PL). From the high-energy tail of PL, we determine the electron temperature (Te) of the hot electrons. TheTevariation can be explained by a model in which the longitudinal optical (LO)-phonon emission is the dominant energy relaxation process. The high-quality γ-In2Se3nanorods may be a promising material for the photovoltaic devices

Identification of deleterious non-synonymous single nucleotide polymorphisms using sequence-derived information

<p>Abstract</p> <p>Background</p> <p>As the number of non-synonymous single nucleotide polymorphisms (nsSNPs), also known as single amino acid polymorphisms (SAPs), increases rapidly, computational methods that can distinguish disease-causing SAPs from neutral SAPs are needed. Many methods have been developed to distinguish disease-causing SAPs based on both structural and sequence features of the mutation point. One limitation of these methods is that they are not applicable to the cases where protein structures are not available. In this study, we explore the feasibility of classifying SAPs into disease-causing and neutral mutations using only information derived from protein sequence.</p> <p>Results</p> <p>We compiled a set of 686 features that were derived from protein sequence. For each feature, the distance between the wild-type residue and mutant-type residue was computed. Then a greedy approach was used to select the features that were useful for the classification of SAPs. 10 features were selected. Using the selected features, a decision tree method can achieve 82.6% overall accuracy with 0.607 Matthews Correlation Coefficient (MCC) in cross-validation. When tested on an independent set that was not seen by the method during the training and feature selection, the decision tree method achieves 82.6% overall accuracy with 0.604 MCC. We also evaluated the proposed method on all SAPs obtained from the Swiss-Prot, the method achieves 0.42 MCC with 73.2% overall accuracy. This method allows users to make reliable predictions when protein structures are not available. Different from previous studies, in which only a small set of features were arbitrarily chosen and considered, here we used an automated method to systematically discover useful features from a large set of features well-annotated in public databases.</p> <p>Conclusion</p> <p>The proposed method is a useful tool for the classification of SAPs, especially, when the structure of the protein is not available.</p

Evaluation of SLOG/TCI-III pediatric system on target control infusion of propofol

<p>Abstract</p> <p>Background</p> <p>The target-controlled infusion-III (SLOG/TCI-III) system was derived from a model set up by the local pediatric population for target control infusion of propofol.</p> <p>Methods</p> <p>The current study aimed at evaluating the difference between target concentrations of propofol and performance, which was measured using the SLOG/TCI-III system in children. Thirty children fulfilling the I-II criteria according to American Society of Anesthesiology were enrolled in the study. The target plasma concentration of propofol was fed into the SLOG/TCI-III system and compared with the measured concentrations of propofol. Blood samples were collected and analyzed by high performance liquid chromatography with fluorescence detector. The performance error (PE) was determined for each measured blood propofol concentration. The performances of the TCI-III system were determined by the median performance error (MDPE), the median absolute performance error (MDAPE), and Wobble (the median absolute deviation of each PE from the MDPE), respectively.</p> <p>Results</p> <p>Concentration against target concentration showed good linear correlation: concentration = 1.3428 target concentration - 0.2633 (r = 0.8667). The MDPE and MDAPE of the pediatric system were 10 and 22%, respectively, and the median value for Wobble was 24%. MDPE and MDAPE were less than 15 and 30%, respectively.</p> <p>Conclusions</p> <p>The performance of TCI-III system seems to be in the accepted limits for clinical practice in children.</p

Live Cell Monitoring of hiPSC Generation and Differentiation Using Differential Expression of Endogenous microRNAs

Human induced pluripotent stem cells (hiPSCs) provide new possibilities for regenerative therapies. In order for this potential to be achieved, it is critical to efficiently monitor the differentiation of these hiPSCs into specific lineages. Here, we describe a lentiviral reporter vector sensitive to specific microRNAs (miRNA) to show that a single vector bearing multiple miRNA target sequences conjugated to different reporters can be used to monitor hiPSC formation and subsequent differentiation from human fetal fibroblasts (HFFs). The reporter vector encodes EGFP conjugated to the targets of human embryonic stem cell (hESC) specific miRNAs (miR-302a and miR-302d) and mCherry conjugated to the targets of differentiated cells specific miRNAs (miR-142-3p, miR-155, and miR-223). The vector was used to track reprogramming of HFF to iPSC. HFFs co-transduced with this reporter vector and vectors encoding 4 reprogramming factors (OCT4, SOX2, KLF4 and cMYC) were mostly positive for EGFP (67%) at an early stage of hiPSC formation. EGFP expression gradually disappeared and mCherry expression increased indicating less miRNAs specific to differentiated cells and expression of miRNAs specific to hESCs. Upon differentiation of the hiPSC into embryoid bodies, a large fraction of these hiPSCs regained EGFP expression and some of those cells became single positive for EGFP. Further differentiation into neural lineages showed distinct structures demarcated by either EGFP or mCherry expression. These findings demonstrate that a miRNA dependent reporter vector can be a useful tool to monitor living cells during reprogramming of hiPSC and subsequent differentiation to lineage specific cells

Search for Charged Higgs Bosons in e+e- Collisions at \sqrt{s} = 189 GeV

A search for pair-produced charged Higgs bosons is performed with the L3 detector at LEP using data collected at a centre-of-mass energy of 188.6 GeV, corresponding to an integrated luminosity of 176.4 pb^-1. Higgs decays into a charm and a strange quark or into a tau lepton and its associated neutrino are considered. The observed events are consistent with the expectations from Standard Model background processes. A lower limit of 65.5 GeV on the charged Higgs mass is derived at 95 % confidence level, independent of the decay branching ratio Br(H^{+/-} -> tau nu)

Production of Embryonic and Fetal-Like Red Blood Cells from Human Induced Pluripotent Stem Cells

We have previously shown that human embryonic stem cells can be differentiated into embryonic and fetal type of red blood cells that sequentially express three types of hemoglobins recapitulating early human erythropoiesis. We report here that we have produced iPS from three somatic cell types: adult skin fibroblasts as well as embryonic and fetal mesenchymal stem cells. We show that regardless of the age of the donor cells, the iPS produced are fully reprogrammed into a pluripotent state that is undistinguishable from that of hESCs by low and high-throughput expression and detailed analysis of globin expression patterns by HPLC. This suggests that reprogramming with the four original Yamanaka pluripotency factors leads to complete erasure of all functionally important epigenetic marks associated with erythroid differentiation regardless of the age or the tissue type of the donor cells, at least as detected in these assays. The ability to produce large number of erythroid cells with embryonic and fetal-like characteristics is likely to have many translational applications