Misspecification and Heterogeneity in Single-Index, Binary Choice Models

We propose a nonparametric approach for estimating single-index, binary-choice models when parametric models such as Probit and Logit are potentially misspecified. The new approach involves two steps: first, we estimate index coefficients using sliced inverse regression without specifying a parametric probability function a priori; second, we estimate the unknown probability function using kernel regression of the binary choice variable on the single index estimated in the first step. The estimated probability functions for different demographic groups indicate that the conventional dummy variable approach cannot fully capture heterogeneous effects across groups. Using both simulated and labor market data, we demonstrate the merits of this new approach in solving model misspecification and heterogeneity problems.Probit; Logit; Sliced Inverse Regression; categorical variables; treatment heterogeneity

Misspecification and Heterogeneity in Single-Index, Binary Choice Models

We propose a nonparametric approach for estimating single-index, binary-choice models when parametric models such as Probit and Logit are potentially misspecified. The new approach involves two steps: first, we estimate index coefficients using sliced inverse regression without specifying a parametric probability function a priori; second, we estimate the unknown probability function using kernel regression of the binary choice variable on the single index estimated in the first step. The estimated probability functions for different demographic groups indicate that the conventional dummy variable approach cannot fully capture heterogeneous effects across groups. Using both simulated and labor market data, we demonstrate the merits of this new approach in solving model misspecification and heterogeneity problems

LRBmat: A Novel Gut Microbial Interaction and Individual Heterogeneity Inference Method for Colorectal Cancer

Many diseases are considered to be closely related to the changes in the gut microbial community, including colorectal cancer (CRC), which is one of the most common cancers in the world. The diagnostic classification and etiological analysis of CRC are two critical issues worthy of attention. Many methods adopt gut microbiota to solve it, but few of them simultaneously take into account the complex interactions and individual heterogeneity of gut microbiota, which are two common and important issues in genetics and intestinal microbiology, especially in high-dimensional cases. In this paper, a novel method with a Binary matrix based on Logistic Regression (LRBmat) is proposed to deal with the above problem. The binary matrix can directly weakened or avoided the influence of heterogeneity, and also contain the information about gut microbial interactions with any order. Moreover, LRBmat has a powerful generalization, it can combine with any machine learning method and enhance them. The real data analysis on CRC validates the proposed method, which has the best classification performance compared with the state-of-the-art. Furthermore, the association rules extracted from the binary matrix of the real data align well with the biological properties and existing literatures, which are helpful for the etiological analysis of CRC. The source codes for LRBmat are available at https://github.com/tsnm1/LRBmat

The Correlated Multi-color Optical Variations of BL Lac Object S5 0716+714

S5 0716+714 is a well-studied BL Lac object in the sky. Verifying the existence of correlations among the flux variations in different bands serves as an important tool to investigate the emission processes. To examine the possible existence of a lag between variations in different optical bands on this source, we employ a discrete correlation function (DCF) analysis on the light curves. In order to obtain statistically meaningful values for the cross-correlation time lags and their related uncertainties, we perform Monte Carlo simulations called "flux redistribution/random subset selection" (FR/RSS). Our analysis confirms that the variations in different optical light curves are strongly correlated. The time lags show a hint of the variations in high frequency band leading those in low frequency band of the order of a few minutes.Comment: 6 pages, 5 figures, 3 tables. This paper has been accepted for publication in PASA

Optical Coherence Tomographic Finding in a Case of Macular Coloboma

PURPOSE: To report the optical coherence tomography (OCT) findings in a patient with unilateral macular coloboma. METHODS: A 12-year-old male was presented with macular coloboma in the left eye. The optical coherence tomography was performed with fluorescein angiography (FA). RESULTS: The OCT revealed the crater-like depression in the macula, demonstrating atrophic neurosensory retina, and an absence of retinal pigment epithelium and choroid in the lesion. FA showed hypofluorescence corresponding to the size of the lesion in both early and late frames without leakage of dye at any stage. CONCLUSIONS: The OCT can be beneficial to confirm the diagnosis of macular coloboma

Learning to Represent Patches

Patch representation is crucial in automating various software engineering tasks, like determining patch accuracy or summarizing code changes. While recent research has employed deep learning for patch representation, focusing on token sequences or Abstract Syntax Trees (ASTs), they often miss the change's semantic intent and the context of modified lines. To bridge this gap, we introduce a novel method, Patcherizer. It delves into the intentions of context and structure, merging the surrounding code context with two innovative representations. These capture the intention in code changes and the intention in AST structural modifications pre and post-patch. This holistic representation aptly captures a patch's underlying intentions. Patcherizer employs graph convolutional neural networks for structural intention graph representation and transformers for intention sequence representation. We evaluated Patcherizer's embeddings' versatility in three areas: (1) Patch description generation, (2) Patch accuracy prediction, and (3) Patch intention identification. Our experiments demonstrate the representation's efficacy across all tasks, outperforming state-of-the-art methods. For example, in patch description generation, Patcherizer excels, showing an average boost of 19.39% in BLEU, 8.71% in ROUGE-L, and 34.03% in METEOR scores

Gamma-ray blazars: the view from AGILE

During the first 3 years of operation the Gamma-Ray Imaging Detector onboard the AGILE satellite detected several blazars in a high gamma-ray activity: 3C 279, 3C 454.3, PKS 1510-089, S5 0716+714, 3C 273, W Comae, Mrk 421, PKS 0537-441 and 4C +21.35. Thanks to the rapid dissemination of our alerts, we were able to obtain multiwavelength data from other observatories such as Spitzer, Swift, RXTE, Suzaku, INTEGRAL, MAGIC, VERITAS, and ARGO as well as radio-to-optical coverage by means of the GASP Project of the WEBT and the REM Telescope. This large multifrequency coverage gave us the opportunity to study the variability correlations between the emission at different frequencies and to obtain simultaneous spectral energy distributions of these sources from radio to gamma-ray energy bands, investigating the different mechanisms responsible for their emission and uncovering in some cases a more complex behaviour with respect to the standard models. We present a review of the most interesting AGILE results on these gamma-ray blazars and their multifrequency data.Comment: 25 pages, 10 figures, accepted for publication on Advances in Space Research. Talk presented at the 38th COSPAR Scientific Assembly (Bremen, Germany; July 18-25, 2010

Ethanol Extract from Ampelopsis sinica Root Exerts Anti-Hepatitis B Virus Activity via Inhibition of p53 Pathway In Vitro

Ampelopsis sinica root is widely used in Chinese folk medicine for treating liver disorders caused by the hepatitis B virus (HBV). The present study was performed in order to investigate the anti-HBV activity and mechanisms of the ethanol extract from A. sinica root (EASR) in vitro. The antiviral activity of EASR was examined by detecting the levels of HBsAg, HBeAg and extracellular HBV DNAs in stable HBV-producing human hepatoblastoma HepG2 2.2.15 cells. We found that EASR effectively suppressed the secretion of HBsAg and HBeAg from HepG2 2.2.15 cells in a dose-dependent manner, and it also suppressed the amount of extracellular HBV DNA. After EASR treatment, the percentage of apoptotic cells was found to be significantly higher than that of control by flow cytometric analysis. A luciferase reporter gene assay was used to determine the effects of EASR on the activities of HBV promoters and intracellular signaling pathways. The results showed that EASR selectively inhibited the activities of HBV promoters (Cp, S1p and Fp) and the p53 signaling pathway in HepG2 cells significantly. These data indicate that EASR exerts anti-HBV effects via inhibition of HBV promoters and the p53-associated signaling pathway, which helps to elucidate the mechanism underlying the potential therapeutic value of EASR

The Fermi blazars divide

Flat Spectrum Radio Quasars (FSRQs) and BL Lac objects detected in the first three months of the Fermi survey neatly separate in the gamma-ray spectral index vs gamma-ray luminosity plane. BL Lac objects are less luminous and have harder spectra than broad line blazars. We suggest that this division has its origin in the different accretion regimes of the two classes of objects. Using the gamma-ray luminosity as a proxy for the observed bolometric one we show that the boundary between the two subclasses of blazars can be associated with the threshold between the regimes of optically thick accretion disks and of radiatively inefficient accretion flows, which lies at an accretion rate of the order of 0.01 the Eddington rate. The spectral separation in hard (BL Lacs) and soft (FSRQs) objects can then result from the different radiative cooling suffered by the relativistic electrons in jets propagating in different ambients. We argue that the bulk of the most luminous blazars alread detected by Fermi should be characterised by large black hole masses, around 10^9 solar masses, and predict that lowering the gamma-ray flux threshold the region of the alpha_gamma-L_gamma plane corresponding to steep spectral indices and lower luminosities will be progressively populated by FSRQs with lower mass black holes, while the region of hard spectra and large luminosities will remain forbidden.Comment: 5 pages, 1 figure, revised version accepted for publication as a letter in MNRA