What does fault tolerant Deep Learning need from MPI?

Deep Learning (DL) algorithms have become the de facto Machine Learning (ML) algorithm for large scale data analysis. DL algorithms are computationally expensive - even distributed DL implementations which use MPI require days of training (model learning) time on commonly studied datasets. Long running DL applications become susceptible to faults - requiring development of a fault tolerant system infrastructure, in addition to fault tolerant DL algorithms. This raises an important question: What is needed from MPI for de- signing fault tolerant DL implementations? In this paper, we address this problem for permanent faults. We motivate the need for a fault tolerant MPI specification by an in-depth consideration of recent innovations in DL algorithms and their properties, which drive the need for specific fault tolerance features. We present an in-depth discussion on the suitability of different parallelism types (model, data and hybrid); a need (or lack thereof) for check-pointing of any critical data structures; and most importantly, consideration for several fault tolerance proposals (user-level fault mitigation (ULFM), Reinit) in MPI and their applicability to fault tolerant DL implementations. We leverage a distributed memory implementation of Caffe, currently available under the Machine Learning Toolkit for Extreme Scale (MaTEx). We implement our approaches by ex- tending MaTEx-Caffe for using ULFM-based implementation. Our evaluation using the ImageNet dataset and AlexNet, and GoogLeNet neural network topologies demonstrates the effectiveness of the proposed fault tolerant DL implementation using OpenMPI based ULFM

Complete genome sequence of Torque teno indri virus 1, a novel anellovirus in blood from a free-living lemur

ABSTRACT We identified Torque teno indri virus 1 (TTIV1), the first anellovirus in a free-living lemur ( Indri indri ). The complete circular 2,572-nucleotide (nt) TTIV1 genome is distantly related to torque teno sus virus. Phylogenetic and sequence analyses support TTIV1 as a putative member of a new genus within the Anelloviridae family. </jats:p

Node Filtering and Face Routing for Sensor Network

Main Contributions •Efficient Algorithms for identifying Redundant Sensor Nodes •New Technique for Filtering Redundant Nodes in Sensor Network •Reliable Algorithm for Message Routing - Forwarding •User Friendly Prototype Implementation in Java •Results of Experimental Investigatio

Virtual tour

Interactive 3D Visualization of Architectural models might be the best way to get some idea about an Architecture Plan. Photo-realistic visualization often attracts the investors and customers for whom the architectural blueprints are obscure. Architectural Visualization is considered to have a bright future ahead of it as more and more architects and real estate developers are using this technology. Virtual Walk-through can give not only ideas about your building but its interiors and design too. The Architectural Virtual Environment also most widely used in Gaming and Entertainment Industry in creating a complex movie scenes or a game environment

Practice and Lived Experience of Menstrual Exiles (Chhaupadi) among Adolescent Girls in Far Western Nepal. December 2018

Background: Menstrual exile, also known as Chhaupadi, is a tradition of “untouchability” in far-western Nepal. Forbidden from touching other people and objects, women and girls are required to live away from the community, typically in a livestock shed, during menstruation. We assessed the lived experiences of Chhaupadi among Nepalese adolescent girls in the far-western Achham district of Nepal, observed the safety and sanitation of their living spaces during Chhaupadi, and assessed the perceptions of local adult stakeholders towards the practice of Chhaupadi. Methods: We collected data from 107 adolescent girls using a self-administered survey in two local schools in Achham. We also conducted a focus group discussion with seven girls, held key informant interviews, and observed the girls’ living spaces during Chhaupadi, using a checklist. Descriptive statistics of the quantitative survey and thematic analyses of qualitative interviews are presented. Results: The majority of the girls (n = 77, 72%) practiced exile, or Chhaupadi, during their menstruation, including 3 (4%) exiled to traditional Chhau sheds, 63 (82%) to livestock sheds, and 11 (14%) to courtyards outside their home. The remaining girls (n = 30, 28%) stayed inside the house, yet practiced some form of menstrual taboos. Of the 77 observed living spaces where the girls stayed during exile, only 30% (n = 23) had a toilet facility. Most exiled girls (97.4%) were restricted from eating dairy products. Participants reported having various psychological problems, including lonliness and difficulty sleeping while practicing Chhaupadi. Three of the girls were physically abused; nine were bitten by a snake. Notably high proportions of the living spaces lacked ventilation/windows (n = 20, 26%), electricity (n = 29, 38%), toilets (n = 54, 70%) and a warm blanket and mattress for sleeping (n = 29, 38%). Our qualitative findings supported our quantitative results. Conclusions: Chhaupadi has been condemned by human rights organizations. While the government has banned the practice, implementation on the ban is proceeding slowly, especially in far-western Nepal. Thus, as a temporary measure, public health professionals must work towards promoting the health and safety of Nepalese women and girls still practicing Chhaupadi

Landslide Mapping Along the Karnali Highway, Nepal using High-Resolution Imagery

The Karnali highway (Figure 1) is the only major transportation link that connects the remote Karnali region to the provincial capital in Province 6 of Nepal. This area becomes inaccessible by roads during every rainy season due to landslides. Despite the known landslide frequency, there have been no systematic landslide inventories conducted along this highway to date. Recent advancements in remote-sensing technologies have significantly increased our ability to map landslides of various sizes rapidly with less in situ surveys or human interaction. Landslide susceptibility, hazard and risk studies require a complete landslide inventory, which might only be possible from very high-resolution (VHR) and high-resolution (HR) imagery. Recent launch of Sentinel-2 in 2015 has provided free access to HR imagery enabling landslide detection at finer scales then what was possible with previous open source satellite imagery obtained from Landsat and ASTER. Satellites providing VHR imagery are commercially owned, expensive and not freely available expect for when disasters charter is activated. NextView licensing agreement, a partnership between the US government and US commercial vendors provides access to VHR imagery to federal agencies in support of scientific research [1]. This partnership provides access to VHR imagery obtained from the DigitalGlobe (DG) constellation which enables mapping of small landslides (< 100 m2). In this study, VHR imagery from DG and HR imagery from Sentinel-2 will be used to map landslides along the Karnali highway using a semi automatic method based on object-oriented analysis (OOA) to create most recent and up-to-date landslide inventory. The effectiveness of this remote sensing based landslide inventory to produce a susceptibility map and its predictive capacity will be tested

Bi-criteria evaluation of the MIKE SHE model for a forested watershed on the South Carolina coastal plain

Hydrological models are important tools for effective management, conservation and restoration of forested wetlands. The objective of this study was to test a distributed hydrological model, MIKE SHE, by using bi-criteria (i.e., two measurable variables, streamflow and water table depth) to describe the hydrological processes in a forested watershed that is characteristic of the lower Atlantic Coastal Plain. Simulations were compared against observations of both streamflow and water table depth measured on a first-order watershed (WS80) on the Santee Experimental Forest in South Carolina, USA. Model performance was evaluated using coefficient of determination (&lt;i&gt;R&lt;/i&gt;&lt;sup&gt;2&lt;/sup&gt;) and Nash-Sutcliffe's model efficiency (&lt;i&gt;E&lt;/i&gt;). The &lt;i&gt;E&lt;/i&gt; and root mean squared error (RMSE) were chosen as objective functions for sensitivity analysis of parameters. The model calibration and validation results demonstrated that the streamflow and water table depth were sensitive to most of the model input parameters, especially to surface detention storage, drainage depth, soil hydraulic properties, plant rooting depth, and surface roughness. Furthermore, the bi-criteria approach used for distributed model calibration and validation was shown to be better than the single-criterion in obtaining optimum model input parameters, especially for those parameters that were only sensitive to some specific conditions. Model calibration using the bi-criteria approach should be advantageous for constructing the uncertainty bounds of model inputs to simulate the hydrology for this type of forested watersheds. &lt;i&gt;R&lt;/i&gt;&lt;sup&gt;2&lt;/sup&gt; varied from 0.60–0.99 for daily and monthly streamflow, and from 0.52–0.91 for daily water table depth. &lt;i&gt;E&lt;/i&gt; changed from 0.53–0.96 for calibration and 0.51–0.98 for validation of daily and monthly streamflow, while &lt;i&gt;E&lt;/i&gt; varied from 0.50–0.90 for calibration and 0.66–0.80 for validation of daily water table depth. This study showed that MIKE SHE could be a good candidate for simulating streamflow and water table depth in coastal plain watersheds

Escherichia coli and Enterococcus faecalis are able to incorporate and enhance a pre-formed Gardnerella vaginalis biofilm

Gardnerella vaginalis is the most frequent microorganism found in bacterial vaginosis (BV), while Escherichia coli and Enterococcus faecalis are amongst the most frequent pathogens found in urinary tract infections (UTIs). This study aimed to evaluate possible interactions between UTIs pathogens and G. vaginalis using an in vitro dual-species biofilm model. Our results showed that dual-species biofilms reached significantly higher bacterial concentration than mono-species biofilms. Moreover, visualization of dual-populations species in the biofilms, using the epifluorescence microscopy, revealed that all of the urogenital pathogens co-existed with G. vaginalis. In conclusion, our work demonstrates that uropathogens can incorporate into mature BV biofilms.This work was supported by Portuguese National Funds (FCT) under the Strategic Project of UID/BIO/04469/2013 unit and co-funded by the project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462). JC and DM acknowledge the financial support of individual grants SFRH/BD/93963/2013 and SFRH/BD/87569/2012, respectively. NC is an Investigador FCT

COMPARISON OF DRAINMOD BASED WATERSHED SCALE MODELS

Watershed scale hydrology and water quality models (DRAINMOD-DUFLOW, DRAINMOD-W, DRAINMOD-GIS and WATGIS) that describe the nitrogen loadings at the outlet of poorly drained watersheds were examined with respect to their accuracy and uncertainty in model predictions. Latin Hypercube Sampling (LHS) was applied to determine the impact of uncertainty in estimating field exports and decay coefficients on the uncertainty of the simulated nitrogen loads at the outlet of a 2950 ha coastal plain watershed in eastern North Carolina. Mean daily flow predictions were all within 1 % of the observed flows. Except for the WATGIS model, mean daily nitrate-nitrogen load predictions were within 2 % of the observed load. Statistical test indicated no difference between the predictions of the different models. Uncertainty analysis indicated that uncertainty in quantifying the field exports has greater impact on the uncertainty of outlet loads than does the uncertainty associated with decay coefficient. The uncertainty of predicted outputs from the DRAINMOD-GIS and WATGIS models are similar