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Pole figures for NIST project

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Materials informatics

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Presentation 10 15 v1

Alicia White

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Mahdi Roozbahani

Images of PE400tilt6l Files

alohse

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dnazarian

Improvements in algorithms, technology, and computation are directly impacting the landscape of information use in materials science. The 3 V’s of Big Data (volume, velocity, and variety) are becoming evermore apparent within all sectors of the field. Novel approaches will be required to confront the emerging data deluge and extract the richest knowledge from simulated and empirical information in complex evolving 3-D spaces. Microstructure Informatics (μInformatics) is an emerging suite of signal processing techniques, advanced statistical tools, and data science methods tailored specifically for this new frontier. μInformatics curates and transforms large collections of materials science information using efficient workflows to extract knowledge of bi-directional structure-property/processing connections for most material classes. In this talk, a few early case studies in data-driven methods to solve materials science problems will be explored. Emerging spatial statistics tools will be explored that enable an objective comparison of static and evolving 3-D material volumes from molecular dynamics simulation, micro-CT, and Scanning Electron Microscopy. Also, the statistics will provide a foundation to create improved bottom-up homogenization relationships in fuel cell materials. Lastly, applications of the Materials Knowledge System, a data-driven meta-model to create top-down localization relationships will be explored for phase field model and finite element model information.

Data Science Solutions by Materials Scientists: The Early Case Studies

Tony Fast

Higher-Order Localization Relationships Using the MKS Approach

Tony Fast

Dream3D and its Extension to Abaqus Input Files

Matthew Priddy

A talk for the Institute of Data Analytics and High Performance Computing Chalk and Talk lunch series on Thursday April 25, 2014. This high level talk discusses materials science on the grounds of the information that drive new discoveries in materials science. Understanding the nature of the data that encompasses the landscape of materials science is important for the next generation workforce and the emerging discipline of Materials Data Scientist

The Materials Data Scientist

Tony Fast

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Materials informatics

Om 50 x

Om 5 x

Presentation 10 15 v1

Final presentation (2)

Images of PE400tilt6l Files

Orientation algorithm (1)

Data Science Solutions by Materials Scientists: The Early Case Studies

Higher-Order Localization Relationships Using the MKS Approach

Dream3D and its Extension to Abaqus Input Files

The Materials Data Scientist

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Al6061 Nanoindentation results

alikhosravani

Ni pure mg corrected data

alikhosravani

PCA on Optical images

alikhosravani

Nist project final report

alikhosravani

Nist project final report

alikhosravani

Nist project final report

alikhosravani

Nist project final report

alikhosravani

Nist project class report

alikhosravani

HIGH THROUGHPUT MICROSTRUCTURE-MECHANICAL PROPERTY DATA COLLECTION

alikhosravani

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Al6061 Nanoindentation results

Ni pure mg corrected data

PCA on Optical images

Nist project final report

Nist project class report

HIGH THROUGHPUT MICROSTRUCTURE-MECHANICAL PROPERTY DATA COLLECTION

Último

Factor Causing low production and physiology of mamary Gland

Rcvets

Triploidy ...............................pptx

Cherry

ERTHROPOIESIS: Dr. E. Muralinath & R. Gnana Lahari

muralinath2

There are two types of lymphocytes namely B-cells and T-cells, which are critical for the immune system. In addition, several accessory cells and effector cells also participate. The site of development and maturation of B-cells occurs in bursa fabricius in birds, and bone marrow in mammals. During the course of immune response. B-cells mature into plasma cells and secrete antibodies (immunoglobulins). The B-cells possess the capability to specifically recognize each antigen and produce antibodies (i.e. immunoglobulins) against it.

B lymphocytes, Receptors, Maturation and Activation

Bhanu Krishan

GBSN - Microbiology (Unit 7) Microbiology in Everyday Life

Areesha Ahmad

Recent observations of galaxy clusters and groups with misalignments between their central AGN jets and X-ray cavities, or with multiple misaligned cavities, have raised concerns about the jet – bubble connection in cooling cores, and the processes responsible for jet realignment. To investigate the frequency and causes of such misalignments, we construct a sample of 16 cool core galaxy clusters and groups. Using VLBA radio data we measure the parsec-scale position angle of the jets, and compare it with the position angle of the X-ray cavities detected in Chandra data. Using the overall sample and selected subsets, we consistently find that there is a 30% – 38% chance to find a misalignment larger than ∆Ψ = 45◦ when observing a cluster/group with a detected jet and at least one cavity. We determine that projection may account for an apparently large ∆Ψ only in a fraction of objects (∼35%), and given that gas dynamical disturbances (as sloshing) are found in both aligned and misaligned systems, we exclude environmental perturbation as the main driver of cavity – jet misalignment. Moreover, we find that large misalignments (up to ∼ 90◦ ) are favored over smaller ones (45◦ ≤ ∆Ψ ≤ 70◦ ), and that the change in jet direction can occur on timescales between one and a few tens of Myr. We conclude that misalignments are more likely related to actual reorientation of the jet axis, and we discuss several engine-based mechanisms that may cause these dramatic changes.

Jet reorientation in central galaxies of clusters and groups: insights from V...

Sérgio Sacani

Film Coated Tablet and Film Coating raw materials.pdf

Pharmatech-rx

Cellular Communication and regulation of communication mechanisms to sing the...

Nistarini College, Purulia (W.B) India

SCHISTOSOMA HEAMATOBIUM life cycle .pdf

DebdattaGhosh6

Isolation of AMF by wet sieving and decantation method pptx

GOWTHAMIM22

Presentation for the Most Influential Paper (MIP) award at the IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) 2024 Abstract: Existing defect prediction models use product or process metrics and machine learning methods to identify defect- prone source code entities. Different classifiers (e.g., linear regression, logistic regression, or classification trees) have been investigated in the last decade. The results achieved so far are sometimes contrasting and do not show a clear winner. In this paper we present an empirical study aiming at statistically analyzing the equivalence of different defect predictors. We also propose a combined approach, coined as CODEP (COmbined DEfect Predictor), that employs the classification provided by different machine learning techniques to improve the detection of defect-prone entities. The study was conducted on 10 open source software systems and in the context of cross-project defect prediction, that represents one of the main challenges in the defect prediction field. The statistical analysis of the results indicates that the investigated classifiers are not equivalent and they can complement each other. This is also confirmed by the superior prediction accuracy achieved by CODEP when compared to stand-alone defect predictors.

MIP Award presentation at the IEEE International Conference on Software Analy...

Annibale Panichella

Mining Activity and Investment Opportunity in Myanmar.pptx

KyawThanTint

Studying the escaping atmospheres of highly irradiated exoplanets is critical for understanding the physical mechanisms that shape the demographics of close-in planets. A number of planetary outflows have been observed as excess H/He absorption during/after transit. Such an outflow has been observed for WASP-69b by multiple groups that disagree on the geometry and velocity structure of the outflow. Here, we report the detection of this planet’s outflow using Keck/NIRSPEC for the first time. We observed the outflow 1.28 hr after egress until the target set, demonstrating the outflow extends at least 5.8 × 105 km or 7.5 Rp This detection is significantly longer than previous observations, which report an outflow extending ∼2.2 planet radii just 1 yr prior. The outflow is blueshifted by −23 km s−1 in the planetary rest frame. We estimate a current mass-loss rate of 1 M⊕ Gyr−1 . Our observations are most consistent with an outflow that is strongly sculpted by ram pressure from the stellar wind. However, potential variability in the outflow could be due to time-varying interactions with the stellar wind or differences in instrumental precision.

WASP-69b’s Escaping Envelope Is Confined to a Tail Extending at Least 7 Rp

Sérgio Sacani

Virulence Analysis of Citrus canker caused by Xanthomonas axonopodis pv. citr...

TALAPATI ARUNA CHENNA VYDYANAD

GBSN - Microbiology (Unit 6) Human and Microbial interaction

Areesha Ahmad

In-Pond Raceway Systems (IPRS) represent a cutting-edge method in pond aquaculture, effectively combining the advantages of confining fish in a restricted area within the pond with the efficiency of a flowing water system. This innovative approach facilitates water circulation within the pond, mimicking the natural flow found in riverine environments. By creating this dynamic water movement, IPRS significantly enhances the pond's productivity potential. The core principle of IPRS involves the installation of specific components that work in concert to circulate and refresh the water within the pond, all while preventing any discharge into the surrounding environment. This setup effectively utilizes a dividing partition, or baffle, to create a circular water flow pattern. As a result, the water undergoes continuous mixing and movement, optimizing conditions for fish growth and minimizing stagnation.

In-pond Race way systems for Aquaculture (IPRS).pptx

MAGOTI ERNEST

The Scientific names of some important families of Industrial plants .pdf

Mohamed Said

In recent years, the growth of scientific data and the increasing need for data sharing and collaboration in the field of environmental chemistry has led to the creation of various software and databases that facilitate research and development into the safety and toxicity of chemicals. The US-EPA Center for Computational Toxicology and Exposure has been developing software and databases that serve the chemistry community for many years. This presentation will focus on several web-based software applications which have been developed at the USEPA and made available to the community. While the primary software application from the Center is the CompTox Chemicals Dashboard almost a dozen proof-of-concept applications have been built serving various capabilities. The publicly accessible Cheminformatics Modules (https://www.epa.gov/chemicalresearch/cheminformatics) provides access to six individual modules to allow for hazard comparison for sets of chemicals, structure-substructure-similarity searching, structure alerts and batch QSAR prediction of both physicochemical and toxicity endpoints. A number of other applications in development include a chemical transformations database (ChET) and a database of analytical methods and open mass spectral data (AMOS). Each of these depends on the underlying DSSTox chemicals database, a rich source of chemistry data for over 1.2 million chemical substances. I will provide an overview of all tools in development and the integrated nature of the applications based on the underlying chemistry data. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.

Chemistry Data Delivery from the US-EPA Center for Computational Toxicology a...

US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure

Mars is a particularly attractive candidate among known astronomical objects to potentially host life. Results from space exploration missions have provided insights into Martian geochemistry that indicate oxychlorine species, particularly perchlorate, are ubiquitous features of the Martian geochemical landscape. Perchlorate presents potential obstacles for known forms of life due to its toxicity. However, it can also provide potential benefits, such as producing brines by deliquescence, like those thought to exist on present-day Mars. Here we show perchlorate brines support folding and catalysis of functional RNAs, while inactivating representative protein enzymes. Additionally, we show perchlorate and other oxychlorine species enable ribozyme functions, including homeostasis-like regulatory behavior and ribozyme-catalyzed chlorination of organic molecules. We suggest nucleic acids are uniquely wellsuited to hypersaline Martian environments. Furthermore, Martian near- or subsurface oxychlorine brines, and brines found in potential lifeforms, could provide a unique niche for biomolecular evolution.

Emergent ribozyme behaviors in oxychlorine brines indicate a unique niche for...

Sérgio Sacani

Cyanobacteria (also known as blue-green algae) are ubiquitous photosynthetic microorganisms found in diverse habitats such as fresh water, marine water, moist rocks, etc. The photosynthetic mode of nutrition makes them significant global oxygen producers along with nitrogen-fixing ability of heterocyst and carbon sequestration. Some cyanobacterial species have the ability to perform a dual mode of nutritional procurement. This unique capability of cyanobacteria to utilize both organic (heterotrophic) and inorganic (autotrophic) carbon sources for energy production and growth is termed as mixotrophy which impart nutritional flexibility and competitive ability to them. Cyanobacterial mixotrophy provides the promising avenues in biotechnological applications such as wastewater treatment, bioremediation, pharmaceuticals, food supplements, biofertilizer, coloring agents, synthesis of bioactive compounds and as an agent for eco-friendly bio-fuels generation, etc Mixotrophically grown cyanobacteria, demonstrate significant potential for efficient and economical applications beyond their conventional agricultural application, thereby offering a versatile and impactful resource for future technological and environmental challenges.

mixotrophy in cyanobacteria: a dual nutritional strategy

MansiBishnoi1

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