Socially-integrated resilience in building-level water networks using smart microgrid+net

Environmental change and natural events can impact on multiple dimensions of human life; economic, social, political, physical (built) and natural (ecosystems) environments. Water distribution networks cover both the built and natural realms and are as such inherently vulnerable to accidental or deliberate physical, natural, chemical, or biological threats. An example of such threats include flooding. The damage to water networks from flooding at the building level can include disrupted supply, pipe damage, sink and sewer overflows, fittings and appliance malfunctions etc. as well as the consequential socio-economic loss and distress. It has also been highlighted that the cost of damage caused by disasters including flooding can be correlated to the warning-time given before it occurs. Therefore, contiguous and continuous preparedness is essential to sustain disaster resilience. This paper presents an early stage review to: 1. Understand the challenges and opportunities posed by disaster risks to critical infrastructure at the building level. 2. Examine the role and importance of early warnings within the smart systems context to promote anticipatory preparedness and reduce physical, economic, environmental and social vulnerability 3. Review the opportunities provided by smart water microgrid/net to deliver such an early warning system and 4. Define the basis for a socially-integrated framework for resilience in building water networks based on smart water micro grids and micronets. The objective is to establish the theoretical approach for smart system integration for risk mitigation in water networks at the building level. Also, to explore the importance and scope integration of other social-political dimensions within such framework and associated solutions. The findings will inform further studies to address the gaps in understanding the disaster risks in micro water infrastructure e.g. flooding, and; to develop strategies and systems to strengthen disaster preparedness for effective response and anticipatory action for such risks

SATTY: Word Sense Induction Application in Web Search Clustering

The aim of this paper is to perform Word Sense induction (WSI); which clusters web search results and produces a diversified list of search results. It describes the WSI system developed for Task 11 of SemEval -2013. This paper implements the idea of monotone submodular function optimization using greedy algorithm

Repurposing anticancer drugs for the management of COVID-19

Since its outbreak in the last December, coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 has rapidly spread worldwide at a pandemic proportion and thus is regarded as a global public health emergency. The existing therapeutic options for COVID-19 beyond the intensive supportive care are limited, with an undefined or modest efficacy reported so far. Drug repurposing represents an enthusiastic mechanism to use approved drugs outside the scope of their original indication and accelerate the discovery of new therapeutic options. With the emergence of COVID-19, drug repurposing has been largely applied for early clinical testing. In this review, we discuss some repurposed anticancer drugs for the treatment of COVID-19, which are under investigation in clinical trials or proposed for the clinical testing.info:eu-repo/semantics/publishedVersio

CodePlan: Repository-level Coding using LLMs and Planning

Software engineering activities such as package migration, fixing errors reports from static analysis or testing, and adding type annotations or other specifications to a codebase, involve pervasively editing the entire repository of code. We formulate these activities as repository-level coding tasks. Recent tools like GitHub Copilot, which are powered by Large Language Models (LLMs), have succeeded in offering high-quality solutions to localized coding problems. Repository-level coding tasks are more involved and cannot be solved directly using LLMs, since code within a repository is inter-dependent and the entire repository may be too large to fit into the prompt. We frame repository-level coding as a planning problem and present a task-agnostic framework, called CodePlan to solve it. CodePlan synthesizes a multi-step chain of edits (plan), where each step results in a call to an LLM on a code location with context derived from the entire repository, previous code changes and task-specific instructions. CodePlan is based on a novel combination of an incremental dependency analysis, a change may-impact analysis and an adaptive planning algorithm. We evaluate the effectiveness of CodePlan on two repository-level tasks: package migration (C#) and temporal code edits (Python). Each task is evaluated on multiple code repositories, each of which requires inter-dependent changes to many files (between 2-97 files). Coding tasks of this level of complexity have not been automated using LLMs before. Our results show that CodePlan has better match with the ground truth compared to baselines. CodePlan is able to get 5/6 repositories to pass the validity checks (e.g., to build without errors and make correct code edits) whereas the baselines (without planning but with the same type of contextual information as CodePlan) cannot get any of the repositories to pass them

Natural convection within water-zno nanofluid-filled hemispherical enclosure with a cubic electronic device

This work qualifies and quantifies the nanofluidic natural convective phenomena occurring in a hemispherical enclosure used for electronics applications. This cavity consists of a disk thermally insulated on its rear face, an active cube centered on the disk which generates a constant heat flux and an isothermal dome. The disc of the cavity remains horizontal while its dome is oriented either upwards or downwards. The considered nanofluid is a mixture of water with metallic ZnO nanoparticles. In order to examine the influence of these nanoparticles on the natural convective heat transfer, three values of the volume fraction considered: 0% (pure water), 1% and 5%. The dimensionless governing system of the problem under consideration is solved by means of the control volume method in combination with the SIMPLE algorithm. The structured mesh is composed of triangular surfacic elements and tetrahedral in the volumic domain. Temperature and velocity distributions are presented for some configurations and convective heat transfer is examined for all processed ones. The natural convective heat transfer is quantified by means of Nusselt-Rayleigh-Prandtl correlations.Papers presented at the 13th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Portoroz, Slovenia on 17-19 July 2017 .International centre for heat and mass transfer.American society of thermal and fluids engineers

Modeling and Experimental Study on Characterization of Micromachined Thermal Gas Inertial Sensors

Micromachined thermal gas inertial sensors based on heat convection are novel devices that compared with conventional micromachined inertial sensors offer the advantages of simple structures, easy fabrication, high shock resistance and good reliability by virtue of using a gaseous medium instead of a mechanical proof mass as key moving and sensing elements. This paper presents an analytical modeling for a micromachined thermal gas gyroscope integrated with signal conditioning. A simplified spring-damping model is utilized to characterize the behavior of the sensor. The model relies on the use of the fluid mechanics and heat transfer fundamentals and is validated using experimental data obtained from a test-device and simulation. Furthermore, the nonideal issues of the sensor are addressed from both the theoretical and experimental points of view. The nonlinear behavior demonstrated in experimental measurements is analyzed based on the model. It is concluded that the sources of nonlinearity are mainly attributable to the variable stiffness of the sensor system and the structural asymmetry due to nonideal fabrication

The tale of TILs in breast cancer : A report from The International Immuno-Oncology Biomarker Working Group

Publisher Copyright: © 2021, The Author(s).The advent of immune-checkpoint inhibitors (ICI) in modern oncology has significantly improved survival in several cancer settings. A subgroup of women with breast cancer (BC) has immunogenic infiltration of lymphocytes with expression of programmed death-ligand 1 (PD-L1). These patients may potentially benefit from ICI targeting the programmed death 1 (PD-1)/PD-L1 signaling axis. The use of tumor-infiltrating lymphocytes (TILs) as predictive and prognostic biomarkers has been under intense examination. Emerging data suggest that TILs are associated with response to both cytotoxic treatments and immunotherapy, particularly for patients with triple-negative BC. In this review from The International Immuno-Oncology Biomarker Working Group, we discuss (a) the biological understanding of TILs, (b) their analytical and clinical validity and efforts toward the clinical utility in BC, and (c) the current status of PD-L1 and TIL testing across different continents, including experiences from low-to-middle-income countries, incorporating also the view of a patient advocate. This information will help set the stage for future approaches to optimize the understanding and clinical utilization of TIL analysis in patients with BC.Peer reviewe