Charmless hadronic B decays involving scalar mesons: Implications to the nature of light scalar mesons

The hadronic charmless B decays into a scalar meson and a pseudoscalar meson are studied within the framework of QCD factorization. Although the light scalar mesons $f_0(980)$ and $a_0(980)$ are widely perceived as primarily the four-quark bound states, in practice it is difficult to make quantitative predictions based on the four-quark picture for light scalars. Hence, predictions are made in the 2-quark model for the scalar mesons. Based on the QCD sum rule method, we have derived the leading-twist light-cone distribution amplitudes of scalar mesons and their decay constants. The short-distance approach suffices to explain the observed large rates of $f_0(980)K^-$ and $f_0(980)\bar K^0$ that receive major penguin contributions from the $b\to ss\bar s$ process. When $f_0(980)$ is assigned as a four-quark bound state, there exist extra diagrams contributing to $B\to f_0(980)K$. Therefore, a priori the $f_0(980)K$ rate is not necessarily suppressed for a four-quark state $f_0(980)$. The calculated $\bar B^0\to a_0^+(980)\pi^-$ and $a_0^+(980)K^-$ rates exceed slightly the current experimental limits. If the branching ratio of $\bar B^0\to a_0^+(1450)\pi^-$ is measured at the level of $(4\sim 6)\times 10^{-6}$ while $a_0^+(980)\pi^-$ is found to be smaller, say, of order $(1\sim 2)\times 10^{-6}$ or even smaller than this, it will be likely to imply a 2-quark nature for $a_0(1450)$ and a four-quark assignment for $a_0(980)$. The penguin-dominated modes $a_0(980)K$ and $a_0(1450)K$ receive dominant weak annihilation contributions.Comment: 42 pages and 5 figures. Form factors for B to excited scalar mesons are calculated, signs are flipped for the decay constants of excited states (Appendix B), Tables 5 to 9 are revised. Version to appear in PR

Factors Affecting the Growth and Production of Milk-Clotting Enzyme by Amylomyces rouxii in Rice Liquid Medium

Amylomyces rouxii is one of the main fungi usually coexisting with yeasts in Chinese yeast ball, the starter of chiu-niang, a traditional Chinese fermented product from rice. In the present study, growth and production of milk-clotting enzyme (MCE) in gelatinous rice liquid culture of A. rouxii as influenced by waxy (gelatinous) rice content in the medium (5–20 %), temperature (25–40 °C), cultivation time (1–6 days), shaking speeds (0–150 rpm) and metal ions (Na+, K+, Zn2+, Mg2+, Mn2+, Cu2+, Ca2+, Fe3+ and Al3+) were investigated. Results revealed that rice content in the medium, shaking speed, temperature and cultivation time all affected the mycelial propagation and the production of milk-clotting enzyme by A. rouxii in the rice liquid culture. The maximum milk-clotting enzyme activity of ca. 1.22 unit/mL of medium was observed in the 3-day static culture of test organism grown at 30 °C in the medium containing 20 % of gelatinous rice, while mycelial propagation increased with the increase of cultivation time and shaking speed. Furthermore, a significant increase (p<0.05) in the milk-clotting enzyme activity of ca. 1.90 unit/mL of medium, which was about 1.55-fold of the control, was observed when Al3+ was added to the rice liquid medium

Visual gene-network analysis reveals the cancer gene co-expression in human endometrial cancer

Abstract Background Endometrial cancers (ECs) are the most common form of gynecologic malignancy. Recent studies have reported that ECs reveal distinct markers for molecular pathogenesis, which in turn is linked to the various histological types of ECs. To understand further the molecular events contributing to ECs and endometrial tumorigenesis in general, a more precise identification of cancer-associated molecules and signaling networks would be useful for the detection and monitoring of malignancy, improving clinical cancer therapy, and personalization of treatments. Results ECs-specific gene co-expression networks were constructed by differential expression analysis and weighted gene co-expression network analysis (WGCNA). Important pathways and putative cancer hub genes contribution to tumorigenesis of ECs were identified. An elastic-net regularized classification model was built using the cancer hub gene signatures to predict the phenotypic characteristics of ECs. The 19 cancer hub gene signatures had high predictive power to distinguish among three key principal features of ECs: grade, type, and stage. Intriguingly, these hub gene networks seem to contribute to ECs progression and malignancy via cell-cycle regulation, antigen processing and the citric acid (TCA) cycle. Conclusions The results of this study provide a powerful biomarker discovery platform to better understand the progression of ECs and to uncover potential therapeutic targets in the treatment of ECs. This information might lead to improved monitoring of ECs and resulting improvement of treatment of ECs, the 4th most common of cancer in women.Peer Reviewe

Rhythm-Flexible Voice Conversion without Parallel Data Using Cycle-GAN over Phoneme Posteriorgram Sequences

Speaking rate refers to the average number of phonemes within some unit time, while the rhythmic patterns refer to duration distributions for realizations of different phonemes within different phonetic structures. Both are key components of prosody in speech, which is different for different speakers. Models like cycle-consistent adversarial network (Cycle-GAN) and variational auto-encoder (VAE) have been successfully applied to voice conversion tasks without parallel data. However, due to the neural network architectures and feature vectors chosen for these approaches, the length of the predicted utterance has to be fixed to that of the input utterance, which limits the flexibility in mimicking the speaking rates and rhythmic patterns for the target speaker. On the other hand, sequence-to-sequence learning model was used to remove the above length constraint, but parallel training data are needed. In this paper, we propose an approach utilizing sequence-to-sequence model trained with unsupervised Cycle-GAN to perform the transformation between the phoneme posteriorgram sequences for different speakers. In this way, the length constraint mentioned above is removed to offer rhythm-flexible voice conversion without requiring parallel data. Preliminary evaluation on two datasets showed very encouraging results.Comment: 8 pages, 6 figures, Submitted to SLT 201

Applying a Heuristic Approach for a Minimum-cost Operating Strategy for Tap Water

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive

Factors Affecting the Growth and Production of Milk-Clotting Enzyme by Amylomyces rouxii in Rice Liquid Medium

Amylomyces rouxii is one of the main fungi usually coexisting with yeasts in Chinese yeast ball, the starter of chiu-niang, a traditional Chinese fermented product from rice. In the present study, growth and production of milk-clotting enzyme (MCE) in gelatinous rice liquid culture of A. rouxii as influenced by waxy (gelatinous) rice content in the medium (5–20 %), temperature (25–40 °C), cultivation time (1–6 days), shaking speeds (0–150 rpm) and metal ions (Na+, K+, Zn2+, Mg2+, Mn2+, Cu2+, Ca2+, Fe3+ and Al3+) were investigated. Results revealed that rice content in the medium, shaking speed, temperature and cultivation time all affected the mycelial propagation and the production of milk-clotting enzyme by A. rouxii in the rice liquid culture. The maximum milk-clotting enzyme activity of ca. 1.22 unit/mL of medium was observed in the 3-day static culture of test organism grown at 30 °C in the medium containing 20 % of gelatinous rice, while mycelial propagation increased with the increase of cultivation time and shaking speed. Furthermore, a significant increase (p<0.05) in the milk-clotting enzyme activity of ca. 1.90 unit/mL of medium, which was about 1.55-fold of the control, was observed when Al3+ was added to the rice liquid medium

Distributed Training Large-Scale Deep Architectures

Scale of data and scale of computation infrastructures together enable the current deep learning renaissance. However, training large-scale deep architectures demands both algorithmic improvement and careful system configuration. In this paper, we focus on employing the system approach to speed up large-scale training. Via lessons learned from our routine benchmarking effort, we first identify bottlenecks and overheads that hinter data parallelism. We then devise guidelines that help practitioners to configure an effective system and fine-tune parameters to achieve desired speedup. Specifically, we develop a procedure for setting minibatch size and choosing computation algorithms. We also derive lemmas for determining the quantity of key components such as the number of GPUs and parameter servers. Experiments and examples show that these guidelines help effectively speed up large-scale deep learning training

Activation of β-Adrenoceptors by Dobutamine May Induce a Higher Expression of Peroxisome Proliferator-Activated Receptors δ (PPARδ) in Neonatal Rat Cardiomyocytes

Recent evidence showed the role of peroxisome proliferator-activated receptors (PPARs) in cardiac function. Cardiac contraction induced by various agents is critical in restoring the activity of peroxisome proliferator-activated receptors δ (PPARδ) in cardiac myopathy. Because dobutamine is an agent widely used to treat heart failure in emergency setting, this study is aimed to investigate the change of PPARδ in response to dobutamine. Neonatal rat cardiomyocytes were used to examine the effects of dobutamine on PPARδ expression levels and cardiac troponin I (cTnI) phosphorylation via Western blotting analysis. We show that treatment with dobutamine increased PPARδ expression and cTnI phosphorylation in a time- and dose-dependent manner in neonatal rat cardiomyocytes. These increases were blocked by the antagonist of β1-adrenoceptors. Also, the action of dobutamine was related to the increase of calcium ions and diminished by chelating intracellular calcium. Additionally, dobutamine-induced action was reduced by the inhibition of downstream messengers involved in this calcium-related pathway. Moreover, deletion of PPARδ using siRNA generated the reduction of cTnI phosphorylation in cardiomyocytes treated with dobutamine. Thus, we concluded that PPARδ is increased by dobutamine in cardiac cells

Factors Predicting Emotional Cue-Responding Behaviors of Nurses in Taiwan: An Observational Study

Objective Responding to emotional cues is an essential element of therapeutic communication. The purpose of this study is to examine nurses' competence of responding to emotional cues (CRE) and related factors while interacting with standardized patients with cancer. Methods This is an exploratory and predictive correlational study. A convenience sample of registered nurses who have passed the probationary period in southern Taiwan was recruited to participate in 15-minute videotaped interviews with standardized patients. The Medical Interview Aural Rating Scale was used to describe standardized patients' emotional cues and to measure nurses' CRE. The State-Trait Anxiety Inventory was used to evaluate nurses' anxiety level before the conversation. We used descriptive statistics to describe the data and stepwise regression to examine the predictors of nurses' CRE. Results A total of 110 nurses participated in the study. Regardless of the emotional cue level, participants predominately responded to cues with inappropriate distancing strategies. Prior formal communication training, practice unit, length of nursing practice, and educational level together explain 36.3% variances of the nurses' CRE. Conclusions This study is the first to explore factors related to Taiwanese nurses' CRE. Compared to nurses in other countries, Taiwanese nurses tended to respond to patients' emotional cues with more inappropriate strategies. We also identified significant predictors of CRE that show the importance of communication training. Future research and education programs are needed to enhance nurses' CRE and to advocate for emotion-focused communication