Financial Reporting Quality, Corporate Governance, and Idiosyncratic Risk: Evidence from a Frontier Market

We extend current literature by providing empirical evidence on the impacts of financial reporting quality and corporate governance mechanism - two firm-level determinants that are strongly affected by the unique market setting and regulatory framework in emerging/frontier markets - and idiosyncratic risk in Vietnam. Utilizing different panel data analysis techniques, we find high-quality financial reports can mitigate firm-specific risk. Firms with high state ownership tend to have lower idiosyncratic risk too, implying the monitoring role of the government. We also document a positive link between board size and firm specific risk. Our results are thus beneficial for industry regulators and firms in ensuring good governance and reporting framework to better manage firm risk

CKM Favored Semileptonic Decays of Heavy Hadrons at Zero Recoil

We study the properties of Cabibbo-Kobayashi-Maskawa (CKM) favored semileptonic decays of mesons and baryons containing a heavy quark at the point of no recoil. We first use a diagrammatic analysis to rederive the result observed by earlier authors that at this kinematic point the $B$ meson decays via $b\to c$ transitions can only produce a $D$ or $D^*$ meson. The result is generalized to include photon emissions which violate heavy quark flavor symmetry. We show that photons emitted by the heavy quarks and the charged lepton are the only light particles that can decorate the decays $\bar{B}\to D(D^*) + \ell\nu$ at zero recoil, and the similar processes of heavy baryons. Implications for the determinations of the CKM parameter $V_{cb}$ are discussed. Also studied in this paper is the connection between our diagrammatic analysis of suppression of particle emission and the formal observation based on weak currents at zero recoil being generators of heavy quark symmetry. We show that the two approaches can be unified by considering the Isgur-Wise function in the presence of an external source.Comment: 27 pages, including 11 figures using macros FEYNMAN.te

The Rare Decay B→K∗γB\to K^{\ast}\gamma: A More Precise Calculation

Efforts to predict the rare exclusive decay $B\to K^{\ast}\gamma$ from the well known inclusive decay $b\to s\gamma$ are frustrated by the effect of the large recoil momentum. We show how to reduce the large uncertainty in calculating this decay by relating $B\to K^{\ast}\gamma$ to the semileptonic process $B\to\rho e\bar{\nu}$ using the heavy-quark symmetry in B decays and SU(3) flavor symmetry. A direct measurement of the $q^{2}$-spectrum for the semileptonic decay can provide accurate information for the exclusive rare decay.Comment: 15 pages, UTPT-93-02, in REVTEX with one figure in ep

Identification of common genetic risk variants for autism spectrum disorder

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.Peer reviewe

The Physics of the B Factories

This work is on the Physics of the B Factories. Part A of this book contains a brief description of the SLAC and KEK B Factories as well as their detectors, BaBar and Belle, and data taking related issues. Part B discusses tools and methods used by the experiments in order to obtain results. The results themselves can be found in Part C

Prompt charm production in pp collisions at &#8730;<span style="text-decoration:overline">s</span>=7 TeV

Charm production at the LHC in pp collisions at s√=7 TeV is studied with the LHCb detector. The decays D0→K−π+, D+→K−π+π+, D⁎+→D0(K−π+)π+, D+s→ϕ(K−K+)π+, Λ+c→pK−π+, and their charge conjugates are analysed in a data set corresponding to an integrated luminosity of 15 nb−1. Differential cross-sections dσ/dpT are measured for prompt production of the five charmed hadron species in bins of transverse momentum and rapidity in the region 0&#60;pT&#60;8 GeV/c and 2.0&#60;y&#60;4.5. Theoretical predictions are compared to the measured differential cross-sections. The integrated cross-sections of the charm hadrons are computed in the above pT-y range, and their ratios are reported. A combination of the five integrated cross-section measurements gives σ(cc¯)pT&#60;8 GeV/c,2.0&#60;y&#60;4.5=1419±12(stat)±116(syst)±65(frag) μb, where the uncertainties are statistical, systematic, and due to the fragmentation functions

Reappraisal of the importance of mutations in the NS5A-PKR-binding domain of hepatitis C-1b virus in the era of optimally individualized therapy

Past studies have reported that mutations in the protein kinase R-binding domain (PKRBD) sequences of hepatitis C virus (HCV) NS5A proteins are correlated with response to fixed-duration interferon (IFN)-based therapy in patients infected with HCV-1b. In this study, we investigated whether the substitutions in PKRBD, including the IFN sensitivity-determining region (ISDR) and 26 additional downstream amino acids from ISDR, will have effects upon patients infected with chronic HCV-1b in the era of individualized therapy with peginterferon and ribavirin. Thirty-seven patients were treated with optimally tailored therapy guided by baseline viral load combined with rapid and early virological responses while 23 patients were treated without guidance and/or assigned suboptimal treatment duration. The amino acid sequences of the PKRBD were determined by PCR and sequencing. The overall sustained virological response (SVR) rate of patients who received optimally individualized therapy was 78.4%, which was better than the SVR rate of patients who received suboptimal therapy (47.8%, P = 0.015). Multivariate analysis showed that optimally individualized therapy (P = 0.019) and 80/80/80 adherence (P = 0.006) were independent favourable predictors of SVR in the entire cohort. Further sub-analysis of the predictive factors of SVR in patients treated with optimally individualized therapy showed that mutations in the 26-amino acid downstream from the ISDR (P = 0.024) were the only independent predictor of SVR. We concluded that mutations in 26-amino acid downstream portion from the ISDR remained a prognosticator of SVR in the era of optimally tailored therapy

Prediction of lead (Pb) adsorption on attapulgite clay using the feasibility of data intelligence models

This study investigates the performance of support vector machine (SVM), multivariate adaptive regression spline (MARS), and random forest (RF) models for predicting the lead (Pb) adsorption by attapulgite clay. Models are constructed using batch stochastic data of heavy metal (HM) concentrations under different physicochemical conditions. Implementation of auto-hyper-parameter tuning using grid-search approach and comparative analysis is performed against the benchmark artificial intelligence (AI) models. Models are constructed based on Pb concentration (IC), the dosage of attapulgite clay (dose), contact time (CT), pH, and NaNO3 (SN). Principle component analysis (PCA) and correlation analysis (CA) methods are integrated to assess the importance of the applied predictors and their relationship with the target. Research findings approved the potential of the grid-RF model as a marginal superior predictive model against the grid-SVM in terms of MAE, i.e., 3.29 and 3.34, respectively; moreover, the md scored the same, i.e., 0.93, which reveals the potential predictability for both. Nonetheless, grid-MARS and standalone MARS models remained likewise in their predictability. IC parameter demonstrated the highest influential among all the predictors with the highest value of importance in the case of all three evaluators. The solution pH and dose stands together with marginal differences in case of PCA method; however, solution pH and CT appeared with similarity impact using the PCA method. Graphical abstract: [Figure not available: see fulltext.]. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature

RainPredRNN: A New Approach for Precipitation Nowcasting with Weather Radar Echo Images Based on Deep Learning

Precipitation nowcasting is one of the main tasks of weather forecasting that aims to predict rainfall events accurately, even in low-rainfall regions. It has been observed that few studies have been devoted to predicting future radar echo images in a reasonable time using the deep learning approach. In this paper, we propose a novel approach, RainPredRNN, which is the combination of the UNet segmentation model and the PredRNN_v2 deep learning model for precipitation nowcasting with weather radar echo images. By leveraging the abilities of the contracting-expansive path of the UNet model, the number of calculated operations of the RainPredRNN model is significantly reduced. This result consequently offers the benefit of reducing the processing time of the overall model while maintaining reasonable errors in the predicted images. In order to validate the proposed model, we performed experiments on real reflectivity fields collected from the Phadin weather radar station, located at Dien Bien province in Vietnam. Some credible quality metrics, such as the mean absolute error (MAE), the structural similarity index measure (SSIM), and the critical success index (CSI), were used for analyzing the performance of the model. It has been certified that the proposed model has produced improved performance, about 0.43, 0.95, and 0.94 of MAE, SSIM, and CSI, respectively, with only 30% of training time compared to the other methods. © 2022 by the authors. Licensee MDPI, Basel, Switzerland