DEVELOPMENT AND EVALUATION OF AN ADAPTIVE NEURO FUZZY INFERENCE SYSTEM FOR THE CALCULATION OF SOIL WATER RECHARGE IN A WATERSHED

Modeling of groundwater recharge is one of the most important topics in hydrology due to its essential application to water resources management. In this study, an Adaptive Neuro Fuzzy Inference System (ANFIS) method is used to simulate groundwater recharge for watersheds. In-situ observational datasets for temperature, precipitation, evapotranspiration, (ETo) and groundwater recharge of the Lake Karla, Thessaly, Greece watershed were taken into consideration for the present study. The datasets consisted of monthly average values of the last almost 50 years, where 70% of the values used for learning with the rest for the testing phase. The testing was performed under a set of different membership functions without expert’s knowledge acquisition and with the support of a five-layer neural network. Experimental verification shows that, the 3-3-3 combination under the trapezoid membership function with the hybrid neural network support and the 2-2-2 combination under the g-bell membership function with the same neural network support perform the best among all combinations with RMSE 4.78881 and 4.12944 giving on average 5% deviation from the observed values

MODELING OF HYDROLOGICAL AND ENVIRONMENTAL PROCESSES THROUGH OPENMI AND WEB SERVICES

Integrated collaborative modeling has been proven lately to be the most accurate computer methodology that allows modelers to scrutinize the environmental processes using a holistic approach. Due to the dynamic and interdependent nature, such processes involve the interlinking of hydrological, meteorological, environmental, ecosystems and socioeconomical characteristics. In this paper we deal with the development and the integration of a collaborative system of models devoted to the water quantity and quality monitoring, and also to the management of water resources in a watershed. The system is also tailored by a socio-economical study that highlights the impact of the aforementioned management to the local community of the region under study. Models that integrate the collaborative system need to be coupled so that to run simultaneously under the spatial and temporal synchronization condition. To achieve such a simultaneous synchronization, the Open Modeling Interface, (OpenMI) is invoked. The system has been applied and tested to the Lake Karla watershed in Thessaly region, Greece. However due to the loose integration methodology used for its development and to its open ended property, the system can be easily parametrized to offer such an analysis on other similar case studies. An extension to the OpenMI standard provides the remote simultaneous run of models using web services and allowing the development of a cloud repository of models for future use

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

The emerging landscape of single-molecule protein sequencing technologies

Single-cell profiling methods have had a profound impact on the understanding of cellular heterogeneity. While genomes and transcriptomes can be explored at the single-cell level, single-cell profiling of proteomes is not yet established. Here we describe new single-molecule protein sequencing and identification technologies alongside innovations in mass spectrometry that will eventually enable broad sequence coverage in single-cell profiling. These technologies will in turn facilitate biological discovery and open new avenues for ultrasensitive disease diagnostics.This Perspective describes new single-molecule protein sequencing and identification technologies alongside innovations in mass spectrometry that will eventually enable broad sequence coverage in single-cell proteomics.</p

American Psalm, World Psalm

https://digitalcommons.montclair.edu/all_books/1119/thumbnail.jp

A New Strategy For Optimal Control Of Continuous Tandem Cold Metal Rolling

The control of continuous tandem cold rolling of metal strip is similar to the control of stand-alone tandem cold rolling except that additional challenges occur during the passage of the weld, which generally is done at reduced speed. The more significant issues that must be considered are the following: 1) reducing the length of strip near the weld that has excessive excursions in thickness; 2) reducing the excursions in tension and roll force as the weld goes through a stand; and 3) maintaining the mass flow balance in the mill. This paper presents the results of an investigation of the application of the state-dependent Riccati equation (SDRE) technique developed for improvement in the control of stand-alone tandem cold rolling, to continuous tandem cold rolling, particularly during passage of the weld. Two methods of control during this regime of operation are evaluated and a preferred method is selected. Using the preferred method, it was determined by simulation that the SDRE technique has the capability for successfully controlling the mill during weld passage, so that this novel approach offers a strong potential for improvement in the control of both the stand-alone and continuous tandem cold rolling processes. © 2010 IEEE