Consistency check of charged hadron multiplicities and fragmentation functions in SIDIS

We derived the conditions on certain combinations of integrals of the fragmentation functions of pion using HERMES data of the sum for the charged pion multiplicities from semi-inclusive deep-inelastic scattering (SIDIS) off the deuteron target. In our derivation the nucleon parton distribution functions (PDFs) are assumed to be isospin SU(2) symmetric. Similar conditions have also been obtained for the fragmentation functions (FFs) of kaon by the sum of charged kaon multiplicities as well. We have chosen several FFs to study the impact of those conditions we have derived. Among those FFs, only that produced in the nonlocal chiral-quark model (NL$\chi$QM) constantly satisfy the conditions. Furthermore, the ratios of the strange PDFs $S(x)$ and the nonstrange PDFs $Q(x,Q^2)$ extracted from the charged pion and kaon multiplicities differ from each other significantly. Finally, we demonstrate that the HERMES pion multiplicity data is unlikely to be compatible with the two widely-used PDFs, namely CTEQ6M and NNPDF3.0.Comment: 11 pages, 5 fig

On the Momentum Dependence of the Flavor Structure of the Nucleon Sea

Difference between the $\bar u$ and $\bar d$ sea quark distributions in the proton was first observed in the violation of the Gottfried sum rule in deep-inelastic scattering (DIS) experiments. The parton momentum fraction $x$ dependence of this difference has been measured over the region $0.02 < x < 0.35$ from Drell-Yan and semi-inclusive DIS experiments. The Drell-Yan data suggested a possible sign-change for $\bar d(x)-\bar u(x)$ near $x \sim 0.3$, which has not yet been explained by existing theoretical models. We present an independent evidence for the $\bar d(x)-\bar u(x)$ sign-change at $x \sim 0.3$ from an analysis of the DIS data. We further discuss the $x$-dependence of $\bar d(x)-\bar u(x)$ in the context of meson cloud model and the lattice QCD formulation.Comment: 5 pages, 5 figures, final versio

Korean Red Ginseng Improves Blood Pressure Stability in Patients with Intradialytic Hypotension

Introduction. Intradialytic hypotension (IDH) is a common complication during hemodialysis which may increase mortality risks. Low dose of Korean red ginseng (KRG) has been reported to increase blood pressure. Whether KRG can improve hemodynamic stability during hemodialysis has not been examined. Methods. The 8-week study consisted of two phases: observation phase and active treatment phase. According to prehemodialysis blood pressure (BP), 38 patients with IDH were divided into group A (BP ≥ 140/90 mmHg, n = 18) and group B (BP < 140/90 mmHg, n = 20). Patients were instructed to chew 3.5 gm KRG slices at each hemodialysis session during the 4-week treatment phase. Blood pressure changes, number of sessions disturbed by symptomatic IDH, plasma levels of vasoconstrictors, blood biochemistry, and adverse effects were recorded. Results. KRG significantly reduced the degree of blood pressure drop during hemodialysis (P < 0.05) and the frequency of symptomatic IDH (P < 0.05). More activation of vasoconstrictors (endothelin-1 and angiotensin II) during hemodialysis was found. The postdialytic levels of endothelin-1 and angiotensin II increased significantly (P < 0.01). Conclusion. Chewing KRG renders IDH patients better resistance to acute BP reduction during hemodialysis via activation of vasoconstrictors. Our results suggest that KRG could be an adjuvant treatment for IDH

RVSL: Robust Vehicle Similarity Learning in Real Hazy Scenes Based on Semi-supervised Learning

Recently, vehicle similarity learning, also called re-identification (ReID), has attracted significant attention in computer vision. Several algorithms have been developed and obtained considerable success. However, most existing methods have unpleasant performance in the hazy scenario due to poor visibility. Though some strategies are possible to resolve this problem, they still have room to be improved due to the limited performance in real-world scenarios and the lack of real-world clear ground truth. Thus, to resolve this problem, inspired by CycleGAN, we construct a training paradigm called \textbf{RVSL} which integrates ReID and domain transformation techniques. The network is trained on semi-supervised fashion and does not require to employ the ID labels and the corresponding clear ground truths to learn hazy vehicle ReID mission in the real-world haze scenes. To further constrain the unsupervised learning process effectively, several losses are developed. Experimental results on synthetic and real-world datasets indicate that the proposed method can achieve state-of-the-art performance on hazy vehicle ReID problems. It is worth mentioning that although the proposed method is trained without real-world label information, it can achieve competitive performance compared to existing supervised methods trained on complete label information.Comment: Accepted by ECCV 202

Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis

<p>Abstract</p> <p>Background</p> <p>Genome-wide identification of specific oligonucleotides (oligos) is a computationally-intensive task and is a requirement for designing microarray probes, primers, and siRNAs. An artificial neural network (ANN) is a machine learning technique that can effectively process complex and high noise data. Here, ANNs are applied to process the unique subsequence distribution for prediction of specific oligos.</p> <p>Results</p> <p>We present a novel and efficient algorithm, named the integration of ANN and BLAST (IAB) algorithm, to identify specific oligos. We establish the unique marker database for human and rat gene index databases using the hash table algorithm. We then create the input vectors, via the unique marker database, to train and test the ANN. The trained ANN predicted the specific oligos with high efficiency, and these oligos were subsequently verified by BLAST. To improve the prediction performance, the ANN over-fitting issue was avoided by early stopping with the best observed error and a k-fold validation was also applied. The performance of the IAB algorithm was about 5.2, 7.1, and 6.7 times faster than the BLAST search without ANN for experimental results of 70-mer, 50-mer, and 25-mer specific oligos, respectively. In addition, the results of polymerase chain reactions showed that the primers predicted by the IAB algorithm could specifically amplify the corresponding genes. The IAB algorithm has been integrated into a previously published comprehensive web server to support microarray analysis and genome-wide iterative enrichment analysis, through which users can identify a group of desired genes and then discover the specific oligos of these genes.</p> <p>Conclusion</p> <p>The IAB algorithm has been developed to construct SpecificDB, a web server that provides a specific and valid oligo database of the probe, siRNA, and primer design for the human genome. We also demonstrate the ability of the IAB algorithm to predict specific oligos through polymerase chain reaction experiments. SpecificDB provides comprehensive information and a user-friendly interface.</p

Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis

<p>Abstract</p> <p>Background</p> <p>Genome-wide identification of specific oligonucleotides (oligos) is a computationally-intensive task and is a requirement for designing microarray probes, primers, and siRNAs. An artificial neural network (ANN) is a machine learning technique that can effectively process complex and high noise data. Here, ANNs are applied to process the unique subsequence distribution for prediction of specific oligos.</p> <p>Results</p> <p>We present a novel and efficient algorithm, named the integration of ANN and BLAST (IAB) algorithm, to identify specific oligos. We establish the unique marker database for human and rat gene index databases using the hash table algorithm. We then create the input vectors, via the unique marker database, to train and test the ANN. The trained ANN predicted the specific oligos with high efficiency, and these oligos were subsequently verified by BLAST. To improve the prediction performance, the ANN over-fitting issue was avoided by early stopping with the best observed error and a k-fold validation was also applied. The performance of the IAB algorithm was about 5.2, 7.1, and 6.7 times faster than the BLAST search without ANN for experimental results of 70-mer, 50-mer, and 25-mer specific oligos, respectively. In addition, the results of polymerase chain reactions showed that the primers predicted by the IAB algorithm could specifically amplify the corresponding genes. The IAB algorithm has been integrated into a previously published comprehensive web server to support microarray analysis and genome-wide iterative enrichment analysis, through which users can identify a group of desired genes and then discover the specific oligos of these genes.</p> <p>Conclusion</p> <p>The IAB algorithm has been developed to construct SpecificDB, a web server that provides a specific and valid oligo database of the probe, siRNA, and primer design for the human genome. We also demonstrate the ability of the IAB algorithm to predict specific oligos through polymerase chain reaction experiments. SpecificDB provides comprehensive information and a user-friendly interface.</p

The effect of paternal psoriasis on neonatal outcomes: a nationwide population-based study

BackgroundPsoriasis is a chronic autoimmune disease involving both environmental and genetic risk factors. Maternal psoriasis often results in poor pregnancies that influence both mothers and newborns. However, the influence of paternal psoriasis on the newborn remains unknown. The aim of this study was to investigate whether paternal psoriasis is associated with increased risk of adverse neonatal outcomes, within a nationwide population-based data setting.MethodsSingleton pregnancies were identified in the Taiwan National Health Insurance database and National Birth Registry between 2004-2011 and classified into four study groups according to whether mothers and spouses had psoriasis (paternal(−)/maternal(−), paternal(+)/maternal(−), paternal(−)/maternal(+), and paternal(+)/maternal(+)). Data were analyzed retrospectively. Adjusted odds ratios (aOR) or hazard ratios (aHR) were calculated to evaluate the risk of neonatal outcomes between groups.ResultsA total of 1,498,892 singleton pregnancies were recruited. Newborns of fathers with psoriasis but not of mothers with psoriasis were associated with an aHR (95% CI) of 3.69 (1.65–8.26) for psoriasis, 1.13 (1.06–1.21) for atopic dermatitis and 1.05 (1.01–1.10) for allergic rhinitis. Newborns of mothers with psoriasis but not of fathers with psoriasis were associated with an aOR (95% CI) of 1.26 (1.12-1.43) for low birth weight (&lt;2500 g) and 1.64 (1.10–2.43) for low Apgar scores, and an aHR of 5.70 (2.71–11.99) for psoriasis.ConclusionNewborns of fathers with psoriasis are associated with significantly higher risk of developing atopic dermatitis, allergic rhinitis and psoriasis. Caution is advised for adverse neonatal outcomes when either or both parents have psoriasis

AMiBA: scaling relations between the integrated Compton-y and X-ray derived temperature, mass, and luminosity

We investigate the scaling relations between the X-ray and the thermal Sunyaev-Zel'dovich Effect (SZE) properties of clusters of galaxies, using data taken during 2007 by the Y.T. Lee Array for Microwave Background Anisotropy (AMiBA) at 94 GHz for the six clusters A1689, A1995, A2142, A2163, A2261, and A2390. The scaling relations relate the integrated Compton-y parameter Y_{2500} to the X-ray derived gas temperature T_{e}, total mass M_{2500}, and bolometric luminosity L_X within r_{2500}. Our results for the power-law index and normalization are both consistent with the self-similar model and other studies in the literature except for the Y_{2500}-L_X relation, for which a physical explanation is given though further investigation may be still needed. Our results not only provide confidence for the AMiBA project but also support our understanding of galaxy clusters.Comment: Accepted by ApJ; 8 pages, 3 figures, 5 table

AMiBA Wideband Analog Correlator

A wideband analog correlator has been constructed for the Yuan-Tseh Lee Array for Microwave Background Anisotropy. Lag correlators using analog multipliers provide large bandwidth and moderate frequency resolution. Broadband IF distribution, backend signal processing and control are described. Operating conditions for optimum sensitivity and linearity are discussed. From observations, a large effective bandwidth of around 10 GHz has been shown to provide sufficient sensitivity for detecting cosmic microwave background variations.Comment: 28 pages, 23 figures, ApJ in press