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The ability of superhydrophobic surfacesto resist wetting andrepel impinging water droplets is not less important for practicalapplications than the contact angle and contact angle hysteresis.Here we study novel hydrophobic concrete (with the potential for superhydrophobicity)and its ability to repel incoming droplets (e.g., rain). It is foundthat the onset of the pinning mode can be delayed by changing thesurface topography. Also, the pinning or breakup of droplets of highervelocities depends on the incoming angle. Hydrophobic concrete withbetter pinning resistance showed less tendency for ice accretion. [ABSTRACT FROM AUTHOR]

Describes a grid environment for research and education for the study of weather phenomena. Results of a research that is enabling a major shift toward dynamically adaptive responses to rapidly changing environmental conditions; Adaptive strategies in numerical weather prediction; Radar reflectivity forecasts from the Advanced Regional Prediction System model. INSET: Project Status..

Tropical cyclones (TCs) cause significant disruptions to infrastructure and livelihood. The scale of loss due to TCs may be mitigated by prompt and accurate advisories about TC wind speed. Current advisories are consensus based and have a time delay of about 6 hr between each new update. As part of efforts to increase the frequency of wind speed estimations without compromising on the accuracy, we curate a high‐quality hurricane image and wind speed data set and develop a machine learning (ML) model for frequent wind speed estimation. The image and wind speed pairings are consolidated from different sources. The wind speeds are interpolated hourly to curate the TC wind speed estimation data set. The data set is supplemented with metadata that eases adoption of the data set by the ML community. We have also designed a competition to garner interest and encourage community involvement to build state‐of‐the‐art ML models to estimate wind speeds from satellite images of TCs. The competition winners were able to improve the wind speed estimation by almost 50% over the benchmark model. Key Points: Curated and published a data set for predicting the wind speed of tropical cyclones (TCs) from GOES Clean Longwave Infrared WindowData science challenges can be used to leverage community expertise on model development using the training data set [ABSTRACT FROM AUTHOR]

In order to help scientists in the above ground biomass community and to support the science behind the upcoming BIOMASS, NISAR, and GEDI satellite missions, ESA and NASA are collaborating on the Multi-Mission Algorithm and Analysis Platform (MAAP). The MAAP is a jointly developed and implemented platform that will include not only data (satellite, airborne, in situ data, and products), but also computing capabilities and sets of tools and algorithms developed to support this specific field of research. To best ensure that users are able to collaborate across the platform and to access needed resources, the MAAP requires all data, algorithms, and software to conform to open access and open source policies. In addition to aiding researchers, the MAAP exercise is establishing a collaboration framework between ESA and NASA that focuses on sharing data, science algorithms, and computable resources in order to foster and accelerate scientific research. [ABSTRACT FROM AUTHOR]

The availability of Earth observation data has grown significantly since the first satellites were launched in the 1960s and is expected to grow exponentially in the future with the launch of more powerful and accurate sensors. In light of this data deluge, new scientific and technological methods are needed in order to better understand and analyze Earth observation data.Alternative data sources offer a solution to more accurately and quickly identify interesting scientific events within these large volume Earth observation datasets. Alternative data sources are data which are extracted or generated from non-traditional sources and can include social media data, point of sale transactions and product reviews. While alternative data was originally used in the investment world, there are other non-traditional, domain specific data sources that can be similarly leveraged within the Earth sciences. These data sources include, but are not limited to, the information found in numerous unstructured text documents such as flight reports for airborne field campaigns, agricultural reports and weather forecast discussions. Data extracted from these documents can be used to generate datasets that can be analyzed for spatial, temporal and climatological patterns in order to more effectively identify interesting events or trends. Events and patterns identified in these alternative data sources assist the geosciences community in more efficiently identifying interesting events or use cases and can also help decision makers better understand reporting of anticipated hazards and disasters. These data can in turn be leveraged to build an event database that will help the remote sensing community more effectively discover and use Earth observation data for research and for labelling data for machine learning applications.This presentation will describe the creation of an alternative Earth science dataset from the U.S. National Weather Service's Area Forecast Discussion (AFD) documents. The AFD documents describe the most significant weather issues facing each of the National Weather Service's 122 weather forecast offices. The AFDs are written approximately every six hours, making these documents an optimal choice for identifying interesting atmospheric events or use cases. We will also describe the results of an exploratory use case that leverages the AFD dataset to investigate methods for identifying scientifically relevant events and will also provide a motivating example for the use of these data. [ABSTRACT FROM AUTHOR]

The X-linked hyper-IgM syndrome (X-HIGM1) is a rare primary immunodeficiency disorder (PID) caused by mutations in the gene encoding the CD154 protein, also known as CD40 ligand (CD40LG). X-HIGM1 is characterized by normal or elevated serum levels of IgM in association with decreased levels of IgG, IgA, and IgE. The CD40LG protein expressed on activated T cells interacts with its receptor protein, CD40, on B lymphocytes and dendritic cells. Mutations in the CD40LG gene lead to the production of an abnormal CD40L protein that fails to attach to its receptor, CD40 on B cells resulting in failure to produce IgG, IgA, and IgE antibodies. In the present study, we investigated the molecular defects underlying such a PID in a patient presenting with clinical history of pneumonia and acute respiratory distress syndrome (ARDS) at 7 months of age and diagnosed as transient hypogammaglobulinemia with decreased levels of IgG and increased levels of IgM. We have identified a novel and yet to be reported frame shift deletion of a single base pair (c.229delA) in exon 2 (p.Arg77AspfsTer6) of the CD40L gene ensuing the premature truncation of the protein by 6 amino acids by targeted gene sequencing. This frame shift mutation identified as a CD40L variant was found to be pathogenic which was also validated by Sanger sequencing. The in-silico analysis of c.229 del A mutation also predicted the change to be pathological affecting the structure and function of the CD40L (CD40L, CD154) protein and its protein-protein interaction properties., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Aims: Understand what progress has been made toward a functionally predictive lower urinary tract (LUT) model, identify knowledge gaps, and develop from them a path forward., Methods: We surveyed prominent mathematical models of the basic LUT components (bladder, urethra, and their neural control) and categorized the common modeling strategies and theoretical assumptions associated with each component. Given that LUT function emerges from the interaction of these components, we emphasized attempts to model their connections, and highlighted unmodeled aspects of LUT function., Results: There is currently no satisfactory model of the LUT in its entirety that can predict its function in response to disease, treatment, or other perturbations. In particular, there is a lack of physiologically based mathematical descriptions of the neural control of the LUT., Conclusions: Based on our survey of the work to date, a potential path to a predictive LUT model is a modular effort in which models are initially built of individual tissue-level components using methods that are extensible and interoperable, allowing them to be connected and tested in a common framework. A modular approach will allow the larger goal of a comprehensive LUT model to be in sight while keeping individual efforts manageable, ensure new models can straightforwardly build on prior research, respect potential interactions between components, and incentivize efforts to model absent components. Using a modular framework and developing models based on physiological principles, to create a functionally predictive model is a challenge that the field is ready to undertake., (© 2022 Wiley Periodicals LLC.)

Presence of ectopic thyroid tissue in unusual locations is a rare phenomenon. Herein we present the case of a 55 year old lady, who on evaluation of dyspnoea was detected to have a mediastinal mass. Initial radiological evaluation showed the presence of a mass arising from the wall of the oesophagus which was presumed most likely to be leiomyosarcoma. She underwent surgical resection of the mass, but on histopathological examination, it turned out to be a nodular goiter which was lying within the smooth muscle layer of the oesophageal wall., (© Journal of the Association of Physicians of India 2011.)

Earth science data are being collected for various science needs and applications, processed using different algorithms at multiple resolutions and coverages, and then archived at different archiving centers for distribution and stewardship causing difficulty in data discovery. Curation, which typically occurs in museums, art galleries, and libraries, is traditionally defined as the process of collecting and organizing information around a common subject matter or a topic of interest. Curating data sets around topics or areas of interest addresses some of the data discovery needs in the field of Earth science, especially for unanticipated users of data. This paper describes a methodology to automate search and selection of data around specific phenomena. Different components of the methodology including the assumptions, the process, and the relevancy ranking algorithm are described. The paper makes two unique contributions to improving data search and discovery capabilities. First, the paper describes a novel methodology developed for automatically curating data around a topic using Earth science metadata records. Second, the methodology has been implemented as a stand-alone web service that is utilized to augment search and usability of data in a variety of tools.

We study the effect of small-amplitude fast vibrations and small-amplitude spatial patterns on various systems involving wetting and liquid flow, such as superhydrophobic surfaces, membranes and flow pipes. First, we introduce a mathematical method of averaging the effect of small spatial and temporal patterns and substituting them with an effective force. Such an effective force can change the equilibrium state of a system as well as a phase state, leading to surface texture-induced and vibration-induced phase control. Vibration and patterns can effectively jam holes in vessels with liquid, separate multi-phase flow, change membrane properties, result in propulsion and locomotion and lead to many other multi-scale, nonlinear effects including the shark-skin effect. We discuss the application of such effects to blood flow for novel biomedical 'haemophobic' applications which can prevent blood clotting and thrombosis by controlling the surface pattern at a wall of a vessel (e.g. a catheter or stent).This article is part of the themed issue 'Bioinspired hierarchically structured surfaces for green science'., (© 2016 The Author(s).)

Most of the genome is transcribed to transcripts of no protein-coding potential. However, these transcripts do not represent transcriptional 'noise', rather they play an important role in cellular metabolism and development. Non-coding transcripts of 200 bases to 100 kb length are termed as long non-coding RNAs, majority of which are yet to be characterised thoroughly. Long non-coding RNAs (lncRNAs) play a significant role in cellular process ranging from transcriptional to post-transcriptional regulation. In this review, we highlight the recent efforts to characterise the major functions of lncRNAs in breast cancer. lncRNA expression is altered in several cancer types. Further, the aberrant regulation of lncRNAs promotes tumour development as they are involved in several cancer-associated pathways.