Structure-activity relationship model for estrogen receptor ligands.

Xenoestrogens are spread throughout the environment affecting our daily lives and may produce potential toxic effects on human health. The purpose of this study was to develop a mechanistically reliable model capable of identifying xenoestrogens. Our hypothesis was that there are identifiable structural characteristics among a diverse set of estrogen receptor ligands that differentiate estrogenic and nonestrogenic compounds. The model\u27s learning set was developed by collecting compounds from the National Center for Toxicological Research Estrogen Receptor Binding database (NCTRER) . The categorical-SAR (cat-SAR) expert system was used to build the models and perform leave-none-out, leave-one-out, leave-many-out and external validations for model analysis. The values of all validations were between 0.80 and 0.97. Based on several analyses of rational subsets of compounds included in the NCTRER based on potency or chemical structure, it was observed that the developed SAR models predictivity varied across sets. This indicates that variability in the SAR models or the in vitro assay results themselves must be considered when applying SAR models for prediction or mechanistic analyses of estrogen receptor ligands. Fragment analysis was carried out to study the mechanism of estrogen receptor binding, and various important fragments were identified that demonstrate potential structural characteristics important for binding. Furthermore, this led to the discovery that the cat-SAR expert system was able to make a higher percentage of correct predictions on specific classes of xenoestrogen expressing these key functional groups. In conclusion, this estrogen receptor ligand model has good predictive performance and is based on model attributes that are mechanistically sound

A new class of partial orders

Let $R$ be a unital $*$-ring. For any $a,w,b\in R$, we apply the defined $w$-core inverse to define a new class of partial orders in $R$, called the $w$-core partial order. Suppose $a,b\in R$ are $w$-core invertible. We say that $a$ is below $b$ under the $w$-core partial order, denoted by $a\overset{\tiny{\textcircled{\#}}}\leq_w b$, if $a_w^{\tiny{\textcircled{\#}}} a=a_w^{\tiny{\textcircled{\#}}} b$ and $awa_w^{\tiny{\textcircled{\#}}} =bwa_w^{\tiny{\textcircled{\#}}}$, where $a_w^{\tiny{\textcircled{\#}}}$ denotes the $w$-core inverse of $a$. Characterizations of the $w$-core partial order are given. Also, the relationships with several types of partial orders are considered. In particular, we show that the core partial order coincides with the $a$-core partial order, and the star partial order coincides with the $a^*$-core partial order

Effects of Cryogenic Treatment after Annealing of Ti-6Al-4V Alloy Sheet on Its Formability at Room Temperature

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This is an Open Access article made available under the terms of the Creative Commons Attribution licence CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.In this article, the effects of cryogenic treatment after annealing on the formability of Ti-6Al-4V alloy sheet were experimentally studied. The Ti-6Al-4V titanium alloy was treated by cryogenic treatment after annealing (ACT). Tensile tests were carried out using a universal machine at room temperature. The microstructure evolution of Ti-6Al-4V subjected to ACT was also investigated using an optical microscope (OM). Both the shearing performance and drawing formability were analyzed by punch shearing tests and deep drawing tests, respectively. Results showed that after ACT, the tendency of the β phase can be apparently changing into stable β’ and α’ phases. The elastic modulus is lower than that of the untreated material. It was found that both the yield strength and tensile strength are declined slightly, whereas the ductility is increased significantly. The shear strength in punch shearing is decreased at room temperature and cryogenic temperature. The ratio of smooth zone on the section after ACT3 is much larger than the others. The rollover diameters are not obviously greater than those of the untreated. Additionally, the height of the burr shows a decreasing trend after ACT. During deep drawing, drawing depth is deeper than that of the untreated material, the drawing load after ACT is reduced, and the decreasing tendency of the drawing load slows down. It is noted that the micro-cracks occur at the bottom of the sample.Peer reviewe

Characterizations and representations of left and right hybrid (b, c)-inverses in rings

Let R be an associative ring with unity 1 and let a, b ,c is an element of R. In this paper, several characterizations for left and right hybrid (b, c)-inverses of a are derived. Moreover, their formulae are given by regularities of certain elements. Then, we give characterizations of right (b, c)-inverses and right annihilator (b, c)-inverses of the product of three elements. Finally, relations among the right hybrid (b, c)-inverse of paq, the right (qb, c)-inverse of aq and the right annihilator (b, cp)-inverse of aq are given.This research is supported by the National Natural Science Foundation of China (No. 11801124), the Natural Science Foundation of Anhui Province (No. 1808085QA16), the Fundamental Research Funds for the Central Universities (No. JZ2018HGTB0233) and was partially financed by Portuguese Funds through FCT (Fundação para a Ciência e a Tecnologia) within the Projects UIDB/00013/2020 and UIDP/00013/2020

A Constrained BA Algorithm for Rate-Distortion and Distortion-Rate Functions

The Blahut-Arimoto (BA) algorithm has played a fundamental role in the numerical computation of rate-distortion (RD) functions. This algorithm possesses a desirable monotonic convergence property by alternatively minimizing its Lagrangian with a fixed multiplier. In this paper, we propose a novel modification of the BA algorithm, wherein the multiplier is updated through a one-dimensional root-finding step using a monotonic univariate function, efficiently implemented by Newton's method in each iteration. Consequently, the modified algorithm directly computes the RD function for a given target distortion, without exploring the entire RD curve as in the original BA algorithm. Moreover, this modification presents a versatile framework, applicable to a wide range of problems, including the computation of distortion-rate (DR) functions. Theoretical analysis shows that the outputs of the modified algorithms still converge to the solutions of the RD and DR functions with rate $O(1/n)$, where $n$ is the number of iterations. Additionally, these algorithms provide $\varepsilon$-approximation solutions with $O\left(\frac{MN\log N}{\varepsilon}(1+\log |\log \varepsilon|)\right)$ arithmetic operations, where $M,N$ are the sizes of source and reproduced alphabets respectively. Numerical experiments demonstrate that the modified algorithms exhibit significant acceleration compared with the original BA algorithms and showcase commendable performance across classical source distributions such as discretized Gaussian, Laplacian and uniform sources.Comment: Version_

Learning to screen Glaucoma like the ophthalmologists

GAMMA Challenge is organized to encourage the AI models to screen the glaucoma from a combination of 2D fundus image and 3D optical coherence tomography volume, like the ophthalmologists

Information Bottleneck Revisited: Posterior Probability Perspective with Optimal Transport

Information bottleneck (IB) is a paradigm to extract information in one target random variable from another relevant random variable, which has aroused great interest due to its potential to explain deep neural networks in terms of information compression and prediction. Despite its great importance, finding the optimal bottleneck variable involves a difficult nonconvex optimization problem due to the nonconvexity of mutual information constraint. The Blahut-Arimoto algorithm and its variants provide an approach by considering its Lagrangian with fixed Lagrange multiplier. However, only the strictly concave IB curve can be fully obtained by the BA algorithm, which strongly limits its application in machine learning and related fields, as strict concavity cannot be guaranteed in those problems. To overcome the above difficulty, we derive an entropy regularized optimal transport (OT) model for IB problem from a posterior probability perspective. Correspondingly, we use the alternating optimization procedure and generalize the Sinkhorn algorithm to solve the above OT model. The effectiveness and efficiency of our approach are demonstrated via numerical experiments.Comment: ISIT 202

5-Fluoro-1-(4-meth­oxy­benz­yl)indoline-2,3-dione

In the title compound, C16H12FNO3, the dihedral angle between the benzene ring and the plane of the indole ring system is 71.60 (6)°. In the crystal, mol­ecules stack along the b axis through π–π inter­actions between the adjacent indole-2,3-dione units with a centroid–centroid distance of 3.649 (3) Å. Inter­molecular C—H⋯O=C and C—H⋯π inter­actions further stabilize the structure, forming a three-dimensional framework