Fourth Generation Leptons and Muon g−2g-2

We consider the contributions to $g_\mu-2$ from fourth generation heavy neutral and charged leptons, $N$ and $E$, at the one-loop level. Diagrammatically, there are two types of contributions: boson-boson-$N$, and $E$-$E$-boson in the loop diagram. In general, the effect from $N$ is suppressed by off-diagonal lepton mixing matrix elements. For $E$, we consider flavor changing neutral couplings arising from various New Physics models, which are stringently constrained by $\mu\to e\gamma$. We assess how the existence of a fourth generation would affect these New Physics models.Comment: Minor changes, with references update

Speech Dereverberation Based on Integrated Deep and Ensemble Learning Algorithm

Reverberation, which is generally caused by sound reflections from walls, ceilings, and floors, can result in severe performance degradation of acoustic applications. Due to a complicated combination of attenuation and time-delay effects, the reverberation property is difficult to characterize, and it remains a challenging task to effectively retrieve the anechoic speech signals from reverberation ones. In the present study, we proposed a novel integrated deep and ensemble learning algorithm (IDEA) for speech dereverberation. The IDEA consists of offline and online phases. In the offline phase, we train multiple dereverberation models, each aiming to precisely dereverb speech signals in a particular acoustic environment; then a unified fusion function is estimated that aims to integrate the information of multiple dereverberation models. In the online phase, an input utterance is first processed by each of the dereverberation models. The outputs of all models are integrated accordingly to generate the final anechoic signal. We evaluated the IDEA on designed acoustic environments, including both matched and mismatched conditions of the training and testing data. Experimental results confirm that the proposed IDEA outperforms single deep-neural-network-based dereverberation model with the same model architecture and training data

SymmeGuess: Fun beyond Symmetry Learning

Computer application can be used for artistic design and as a means to facilitate the understanding of mathematical concepts. This paper presents a game-based application as a visual learning tool for mathematics and art subjects. The objectives of this application are to enable learners to build their knowledge on symmetry and to explore the beauty of symmetrical patterns with confidence and enjoyment

Direct arene trifluoromethylation enabled by promiscuous activity of fungal laccase

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Graphite-anchored lithium vanadium oxide as anode of lithium ion battery

Graphite-anchored lithium vanadium oxide (Li1.1V0.9O2) has been synthesized via a “one-pot” in situ method. The effects of the synthesis conditions, such as the ratio of reaction components and calcination temperature, on the electrochemical performance are systematically investigated by means of scanning electron microscopy (SEM), X-ray diffraction (XRD), electrochemical impedance spectroscopy (EIS), galvanostatic discharge/charge tests and differential scanning calorimetry (DSC). Compared with the simple mixture of graphite and lithium vanadium oxide, the graphite-anchored lithium vanadium oxide delivers an enhanced reversible capacity, rate capability and cyclic stability. It also shows better thermal stability.Web of Scienc

Charm and Strange Quark Masses and \u3cem\u3ef\u3csub\u3eD\u3csub\u3es\u3c/sub\u3e\u3c/sub\u3e\u3c/em\u3e from Overlap Fermions

We use overlap fermions as valence quarks to calculate meson masses in a wide quark mass range on the 2 + 1-flavor domain-wall fermion gauge configurations generated by the RBC and UKQCD Collaborations. . . . For the remainder of the abstract, please download this article or visit https://doi.org/10.1103/PhysRevD.92.03451

Comparison of the mismatch-specific endonuclease method and denaturing high-performance liquid chromatography for the identification of HBB gene mutations

<p>Abstract</p> <p>Background</p> <p>Beta-thalassemia is a common autosomal recessive hereditary disease in the Meditertanean, Asia and African areas. Over 600 mutations have been described in the beta-globin (<it>HBB</it>), of which more than 200 are associated with a beta-thalassemia phenotype.</p> <p>Results</p> <p>We used two highly-specific mutation screening methods, mismatch-specific endonuclease and denaturing high-performance liquid chromatography, to identify mutations in the <it>HBB </it>gene. The sensitivity and specificity of these two methods were compared. We successfully distinguished mutations in the <it>HBB </it>gene by the mismatch-specific endonuclease method without need for further assay. This technique had 100% sensitivity and specificity for the study sample.</p> <p>Conclusion</p> <p>Compared to the DHPLC approach, the mismatch-specific endonuclease method allows mutational screening of a large number of samples because of its speed, sensitivity and adaptability to semi-automated systems. These findings demonstrate the feasibility of using the mismatch-specific endonuclease method as a tool for mutation screening.</p

Towards Personalized Healthcare in Cardiac Population: The Development of a Wearable ECG Monitoring System, an ECG Lossy Compression Schema, and a ResNet-Based AF Detector

Cardiovascular diseases (CVDs) are the number one cause of death worldwide. While there is growing evidence that the atrial fibrillation (AF) has strong associations with various CVDs, this heart arrhythmia is usually diagnosed using electrocardiography (ECG) which is a risk-free, non-intrusive, and cost-efficient tool. Continuously and remotely monitoring the subjects' ECG information unlocks the potentials of prompt pre-diagnosis and timely pre-treatment of AF before the development of any life-threatening conditions/diseases. Ultimately, the CVDs associated mortality could be reduced. In this manuscript, the design and implementation of a personalized healthcare system embodying a wearable ECG device, a mobile application, and a back-end server are presented. This system continuously monitors the users' ECG information to provide personalized health warnings/feedbacks. The users are able to communicate with their paired health advisors through this system for remote diagnoses, interventions, etc. The implemented wearable ECG devices have been evaluated and showed excellent intra-consistency (CVRMS=5.5%), acceptable inter-consistency (CVRMS=12.1%), and negligible RR-interval errors (ARE<1.4%). To boost the battery life of the wearable devices, a lossy compression schema utilizing the quasi-periodic feature of ECG signals to achieve compression was proposed. Compared to the recognized schemata, it outperformed the others in terms of compression efficiency and distortion, and achieved at least 2x of CR at a certain PRD or RMSE for ECG signals from the MIT-BIH database. To enable automated AF diagnosis/screening in the proposed system, a ResNet-based AF detector was developed. For the ECG records from the 2017 PhysioNet CinC challenge, this AF detector obtained an average testing F1=85.10% and a best testing F1=87.31%, outperforming the state-of-the-art