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We present ANNz2, a new implementation of the public software for photometric redshift (photo-z) estimation of Collister & Lahav, which now includes generation of full probability distribution functions (PDFs). ANNz2 utilizes multiple machine learning methods, such as artificial neural networks and boosted decision/regression trees. The objective of the algorithm is to optimize the performance of the photo-z estimation, to properly derive the associated uncertainties, and to produce both single-value solutions and PDFs. In addition, estimators are made available, which mitigate possible problems of non-representative or incomplete spectroscopic training samples. ANNz2 has already been used as part of the first weak lensing analysis of the Dark Energy Survey, and is included in the experiment's first public data release. Here we illustrate the functionality of the code using data from the tenth data release of the Sloan Digital Sky Survey and the Baryon Oscillation Spectroscopic Survey. The code is available for download at http://github.com/IftachSadeh/ANNZ.

The 80% mortality rate of pancreatic-cancer (PC) makes early diagnosis a challenge. Oral fluids (OF) may be considered the ultimate body fluid for non-invasive examinations. We have developed techniques to improve visualization of minor OF proteins thereby overcoming major barriers to using OF as a diagnostic fluid. The aim of this study was to establish a short discriminative panel of OF biomarkers for the detection of PC. Unstimulated OF were collected from PC patients and controls (n = 30). High-abundance-proteins were depleted and the remaining proteins were analyzed by two-dimensional-gel-electrophoresis and quantitative dimethylation-liquid-chromatography-tandem mass-spectrometry. Label-free quantitative-mass-spectrometry analysis (qMS) was performed on 20 individual samples (n = 20). More than 100 biomarker candidates were identified in OF samples, and 21 had a highly differential expression profile. qMS analysis yielded a ROC-plot AUC value of 0.91 with 90.0% sensitivity and specificity for a combination of five biomarker candidates. We found a combination of five biomarkers for PC. Most of these proteins are known to be related to PC or other gastric cancers, but have never been detected in OF. This study demonstrates the importance of novel OF depletion methodologies for increased protein visibility and highlights the clinical applicability of OF as a diagnostic fluid.

The ability of any Machine Learning method to classify the spectra of galaxies depending on the properties of the stellar component rests on the information content of the data. The well-known degeneracies found in population synthesis models suggest this information might be so entangled as to challenge the most sophisticated Deep Learning approaches. This contribution focuses on the traditional definition of entropy to explore this problem from a fundamental viewpoint. We find that the information content – when interpreting the spectrum as a probability distribution function – is reduced to a few spectral intervals that are strongly correlated. Dimensionality reduction via PCA suggests the standard 4000Å break strength and Balmer absorption are the two most informative regions in the analysis of galaxy spectra.

In this paper we investigate how implementing machine learning could improve the efficiency of the search for Trans-Neptunian Objects (TNOs) within Dark Energy Survey (DES) data when used alongside orbit fitting. The discovery of multiple TNOs that appear to show a similarity in their orbital parameters has led to the suggestion that one or more undetected planets, an as yet undiscovered \"Planet 9\", may be present in the outer solar system. DES is well placed to detect such a planet and has already been used to discover many other TNOs. Here, we perform tests on eight different supervised machine learning algorithms, using a data set consisting of simulated TNOs buried within real DES noise data. We found that the best performing classifier was the Random Forest which, when optimized, performed well at detecting the rare objects. We achieve an area under the receiver operating characteristic (ROC) curve, (AUC) = 0.996 0.001. After optimizing the decision threshold of the Random Forest, we achieve a recall of 0.96 while maintaining a precision of 0.80. Finally, by using the optimized classifier to pre-select objects, we are able to run the orbit-fitting stage of our detection pipeline five times faster.

Public support is crucial for successful implementation of wastewater reuse projects. This paper analyses the findings of a questionnaire-type survey (256 participants) conducted to determine the attitude of Israeli urban public towards possible urban reuse options. The paper summarises the support / objection to 13 reuse options and the correlation between support and environmental awareness and perceptions. Results show that a high proportion of the participants supported options perceived as low-contact, such as irrigation of public parks (96%), sidewalk landscaping (95%) and use in the construction industry (94%), while higher-contact reuse options found less support (e.g. commercial launderettes, 60%). No correlation was found between biographical characteristics and support (education, gender, income, age). Based on the results, public campaigns in Israel should focus on disseminating information regarding wastewater treatment technologies, discuss health related issues, highlight the positive economic impact of water reuse and generate a positive public opinion, as these factors tend to influence individuals to support reuse projects.

Purpose - This research is based on the hypothesis that the supply of appropriate perceptual and conceptual information through compensatory sensorial channels may assist people who are blind with anticipatory exploration. The two main goals of the research are: evaluation of different modalities (haptic and audio) and navigation tools; and evaluation of spatial cognitive mapping employed by people who are blind.Design methodology approach - In this research the BlindAid system, which allows the user to explore a virtual environment, was developed and tested. The research included four participants who are totally blind.Findings - The preliminary findings confirm that the system enabled participants to develop comprehensive cognitive maps by exploring the virtual environment. The BlindAid system could be used as a training-simulator for O&M rehabilitation training, as a O&M diagnostic tool, and to support people who are blind in exploring and collecting spatial information in advance.Originality value - This preliminary study aims to highlight which VE properties could provide perceptual and conceptual spatial information and allow users who are blind to gather and expand their spatial information.

We introduce ANNz, a freely available software package for photometric redshift estimation using artificial neural networks. ANNzlearns the relation between photometry and redshift from an appropriate training set of galaxies for which the redshift is already known. Where a large and representative training set is available, ANNzis a highly competitive tool when compared with traditional template‐fitting methods. The ANNzpackage is demonstrated on the Sloan Digital Sky Survey Data Release 1, and for this particular data set the rms redshift error in the range \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\usepackage[OT2,OT1]{fontenc} \\newcommand\\cyr{ \\renewcommand\\rmdefault{wncyr} \\renewcommand\\sfdefault{wncyss} \\renewcommand\\encodingdefault{OT2} \\normalfont \\selectfont} \\DeclareTextFontCommand{\\textcyr}{\\cyr} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} \\landscape $0\\lesssim z\\lesssim 0.7$ \\end{document} is \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\usepackage[OT2,OT1]{fontenc} \\newcommand\\cyr{ \\renewcommand\\rmdefault{wncyr} \\renewcommand\\sfdefault{wncyss} \\renewcommand\\encodingdefault{OT2} \\normalfont \\selectfont} \\DeclareTextFontCommand{\\textcyr}{\\cyr} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} \\landscape $\\sigma _{\\mathrm{rms}\\,}=0.023$ \\end{document} . Nonideal conditions (spectroscopic sets that are small or brighter than the photometric set for which redshifts are required) are simulated, and the impact on the photometric redshift accuracy is assessed.2

The recent supply of large volumes of seawater desalinated water in Israel prompted both the development of new water quality standards and the development of a novel post treatment process, designed to comply with the new standards at a cost effective price. The new process is designed to supply water with alkalinity, Ca2 +  and calcium carbonate precipitation potential values as required in the new criteria, along with the addition of a threshold Mg2 +  concentration recently recommended by the WHO. The current paper describes the process in general, and focuses in particular on attaining these criteria while maintaining a low total hardness concentration (120 mg/L as CaCO3). The process is based on dissolving calcite using H2SO4 and replacing the excess calcium ions generated in this process by Mg2 +  ions (using a specific cation exchange resin—Amberlite) and by Na+ (using a second cation exchange resin—chabazite, from the zeolite group). Once exhausted the resins are re-loaded with Mg2 +  and Na+ by the brine generated in the RO process, thus no unwanted brines are generated. A case study is presented for which operational costs were approximated at 0.034 $US/m3 product water.

Purpose Purpose - Virtual environments (VEs) that represent real spaces (RSs) give people who are blind the opportunity to build a cognitive map in advance that they will be able to use when arriving at the RS. Design/methodology/approach In this research study Nintendo Wii based technology was used for exploring VEs via the Wiici application. The Wiimote allows the user to interact with VEs by simulating walking and scanning the space. Findings By getting haptic and auditory feedback the user learned to explore new spaces. We examined the participants' abilities to explore new simple and complex places, construct a cognitive map, and perform orientation tasks in the RS. Originality/value To our knowledge, this finding presents the first virtual environment for people who are blind that allow the participants to scan the environment and by this to construct map model spatial representations.