Bayesian optimization for materials design

We introduce Bayesian optimization, a technique developed for optimizing time-consuming engineering simulations and for fitting machine learning models on large datasets. Bayesian optimization guides the choice of experiments during materials design and discovery to find good material designs in as few experiments as possible. We focus on the case when materials designs are parameterized by a low-dimensional vector. Bayesian optimization is built on a statistical technique called Gaussian process regression, which allows predicting the performance of a new design based on previously tested designs. After providing a detailed introduction to Gaussian process regression, we introduce two Bayesian optimization methods: expected improvement, for design problems with noise-free evaluations; and the knowledge-gradient method, which generalizes expected improvement and may be used in design problems with noisy evaluations. Both methods are derived using a value-of-information analysis, and enjoy one-step Bayes-optimality

Malignant phyllodes tumors display mesenchymal stem cell features and aldehyde dehydrogenase/disialoganglioside identify their tumor stem cells.

IntroductionAlthough breast phyllodes tumors are rare, there is no effective therapy other than surgery. Little is known about their tumor biology. A malignant phyllodes tumor contains heterologous stromal elements, and can transform into rhabdomyosarcoma, liposarcoma and osteosarcoma. These versatile properties prompted us to explore their possible relationship to mesenchymal stem cells (MSCs) and to search for the presence of cancer stem cells (CSCs) in phyllodes tumors.MethodsParaffin sections of malignant phyllodes tumors were examined for various markers by immunohistochemical staining. Xenografts of human primary phyllodes tumors were established by injecting freshly isolated tumor cells into the mammary fat pad of non-obese diabetic-severe combined immunodeficient (NOD-SCID) mice. To search for CSCs, xenografted tumor cells were sorted into various subpopulations by flow cytometry and examined for their in vitro mammosphere forming capacity, in vivo tumorigenicity in NOD-SCID mice and their ability to undergo differentiation.ResultsImmunohistochemical analysis revealed the expression of the following 10 markers: CD44, CD29, CD106, CD166, CD105, CD90, disialoganglioside (GD2), CD117, Aldehyde dehydrogenase 1 (ALDH), and Oct-4, and 7 clinically relevant markers (CD10, CD34, p53, p63, Ki-67, Bcl-2, vimentin, and Globo H) in all 51 malignant phyllodes tumors examined, albeit to different extents. Four xenografts were successfully established from human primary phyllodes tumors. In vitro, ALDH+ cells sorted from xenografts displayed approximately 10-fold greater mammosphere-forming capacity than ALDH- cells. GD2+ cells showed a 3.9-fold greater capacity than GD2- cells. ALDH+/GD2+cells displayed 12.8-fold greater mammosphere forming ability than ALDH-/GD2- cells. In vivo, the tumor-initiating frequency of ALDH+/GD2+ cells were up to 33-fold higher than that of ALDH+ cells, with as few as 50 ALDH+/GD2+ cells being sufficient for engraftment. Moreover, we provided the first evidence for the induction of ALDH+/GD2+ cells to differentiate into neural cells of various lineages, along with the observation of neural differentiation in clinical specimens and xenografts of malignant phyllodes tumors. ALDH+ or ALDH+/GD2+ cells could also be induced to differentiate into adipocytes, osteocytes or chondrocytes.ConclusionsOur findings revealed that malignant phyllodes tumors possessed many characteristics of MSC, and their CSCs were enriched in ALDH+ and ALDH+/GD2+ subpopulations

Ontology-based Fuzzy Markup Language Agent for Student and Robot Co-Learning

An intelligent robot agent based on domain ontology, machine learning mechanism, and Fuzzy Markup Language (FML) for students and robot co-learning is presented in this paper. The machine-human co-learning model is established to help various students learn the mathematical concepts based on their learning ability and performance. Meanwhile, the robot acts as a teacher's assistant to co-learn with children in the class. The FML-based knowledge base and rule base are embedded in the robot so that the teachers can get feedback from the robot on whether students make progress or not. Next, we inferred students' learning performance based on learning content's difficulty and students' ability, concentration level, as well as teamwork sprit in the class. Experimental results show that learning with the robot is helpful for disadvantaged and below-basic children. Moreover, the accuracy of the intelligent FML-based agent for student learning is increased after machine learning mechanism.Comment: This paper is submitted to IEEE WCCI 2018 Conference for revie

A Novel Two-Component Response Regulator Links rpfwith Biofilm Formation and Virulence of Xanthomonasaxonopodis pv. Citri

Citrus bacterial canker caused by Xanthomonas axonopodis pv. citri is a serious disease that impacts citrus productionworldwide, and X. axonopodis pv. citri is listed as a quarantine pest in certain countries. Biofilm formation is important forthe successful development of a pathogenic relationship between various bacteria and their host(s). To understand themechanisms of biofilm formation by X. axonopodis pv. citri strain XW19, the strain was subjected to transposonmutagenesis. One mutant with a mutation in a two-component response regulator gene that was deficient in biofilmformation on a polystyrene microplate was selected for further study. The protein was designated as BfdR for biofilmformation defective regulator. BfdR from strain XW19 shares 100% amino acid sequence identity with XAC1284 of X.axonopodis pv. citri strain 306 and 30–100% identity with two-component response regulators in various pathogens andenvironmental microorganisms. The bfdR mutant strain exhibited significantly decreased biofilm formation on the leafsurfaces of Mexican lime compared with the wild type strain. The bfdR mutant was also compromised in its ability to causecanker lesions. The wild-type phenotype was restored by providing pbfdR in trans in the bfdR mutant. Our data indicatedthat BfdR did not regulate the production of virulence-related extracellular enzymes including amylase, lipase, protease, andlecithinase or the expression of hrpG, rfbC, and katE; however, BfdR controlled the expression of rpfF in XVM2 medium,which mimics cytoplasmic fluids in planta. In conclusion, biofilm formation on leaf surfaces of citrus is important for cankerdevelopment in X. axonopodis pv. citri XW19. The process is controlled by the two-component response regulator BfdR viaregulation of rpfF, which is required for the biosynthesis of a diffusible signal factor

Magneto Transport of high TCR (temperature coefficient of resistance) La2/3Ca1/3MnO3: Ag Polycrystalline Composites

We report the synthesis, (micro)structural, magneto-transport and magnetization of polycrystalline La2/3Ca1/3MnO3:Agx composites with x = 0.0, 0.1, 0.2, 0.3 and 0.4. The temperature coefficient of resistance (TCR) near ferromagnetic (FM) transition is increased significantly with addition of Ag. The FM transition temperature (TFM) is also increased slightly with Ag addition. Magneto-transport measurements revealed that magneto-resistance MR is found to be maximum near TFM. Further the increased MR of up to 60% is seen above 300 K for higher silver added samples in an applied field of 7 Tesla. Sharp TCR is seen near TFM with highest value of up to 15 % for Ag (0.4) sample, which is an order of magnitude higher than as for present pristine sample and best value yet reported for any polycrystalline LCMO compound. Increased TCR, TFM and significant above room temperature MR of La2/3Ca1/3MnO3:Agx composites is explained on the basis of improved grains size and connectivity with silver addition in the matrix. Better coupled FM domains and nearly conducting grain boundaries give rise to improved physical properties of the La2/3Ca1/3MnO3 manganites.Comment: 16 pages Text + Figs. ACCEPTED: Solid State Communications (Sept. 2006

Ethnicity and maternal and child health outcomes and service coverage in western China: a systematic review and meta-analysis.

BACKGROUND: There is a dearth of accurate information about health outcomes and health service coverage among ethnic minorities in China. We assessed maternal and child health (MCH) outcomes and service coverage among ethnic minorities compared with Han populations in western China. METHODS: We did a systematic review searching English (Embase, MEDLINE, Web of Science) and Chinese (China National Knowledge Infrastructure [CNKI], VIP, Wanfang) databases for population-based studies comparing MCH indicators between ethnic minorities between Jan 1, 1990, and Nov 9, 2016, in any language. For studies making individual comparisons we used the odds ratio (OR) and corresponding 95% CIs as the primary measure to assess the association between MCH indicators and ethnicity. We used a random-effects model to pool odds ratios. FINDINGS: We included 29 Chinese and 16 English language studies, providing 31 individual comparisons and 15 ecological comparisons. Ethnic minority women had lower odds of antenatal care use (pooled crude OR 0·60 [95% CI 0·48-0·75]) and birth in health facilities (0·50 [0·39-0·64]) than did Han women; and their children had higher odds of mortality (2·02 [1·23-3·32]) and lower immunisation (0·34 [0·24-0·47]) than did Han children. After taking account of the potential confounding effects of socioeconomic factors, ethnic minority women were less likely to use antenatal care (pooled adjusted OR 0·54 [0·42-0·71]) or to immunise their children (0·57 [0·44-0·74]) compared with Han women. INTERPRETATION: China has a wealth of primary data that could further our understanding of why ethnic minority populations are lagging behind. As MCH outcomes continue to improve nationally, ethnic minorities will take a greater share of the overall burden of adverse outcomes, requiring strategic investments to address the specific challenges faced by people living in remote areas. FUNDING: China Medical Board