Benchmark data and model independent event classification for the large hadron collider

We describe the outcome of a data challenge conducted as part of the Dark Machines (https://www.darkmachines.org) initiative and the Les Houches 2019 workshop on Physics at TeV colliders. The challenged aims to detect signals of new physics at the Large Hadron Collider (LHC) using unsupervised machine learning algorithms. First, we propose how an anomaly score could be implemented to define model-independent signal regions in LHC searches. We define and describe a large benchmark dataset, consisting of > 1 billion simulated LHC events corresponding to 10 fb−1 of proton-proton collisions at a center-of-mass energy of 13 TeV. We then review a wide range of anomaly detection and density estimation algorithms, developed in the context of the data challenge, and we measure their performance in a set of realistic analysis environments. We draw a number of useful conclusions that will aid the development of unsupervised new physics searches during the third run of the LHC, and provide our benchmark dataset for future studies at https://www.phenoMLdata.org. Code to reproduce the analysis is provided at https://github.com/bostdiek/DarkMachines-UnsupervisedChallenge

The dUTPase Enzyme Is Essential in Mycobacterium smegmatis

Thymidine biosynthesis is essential in all cells. Inhibitors of the enzymes involved in this pathway (e.g. methotrexate) are thus frequently used as cytostatics. Due to its pivotal role in mycobacterial thymidylate synthesis dUTPase, which hydrolyzes dUTP into the dTTP precursor dUMP, has been suggested as a target for new antitubercular agents. All mycobacterial genomes encode dUTPase with a mycobacteria-specific surface loop absent in the human dUTPase. Using Mycobacterium smegmatis as a fast growing model for Mycobacterium tuberculosis, we demonstrate that dUTPase knock-out results in lethality that can be reverted by complementation with wild-type dUTPase. Interestingly, a mutant dUTPase gene lacking the genus-specific loop was unable to complement the knock-out phenotype. We also show that deletion of the mycobacteria-specific loop has no major effect on dUTPase enzymatic properties in vitro and thus a yet to be identified loop-specific function seems to be essential within the bacterial cell context. In addition, here we demonstrated that Mycobacterium tuberculosis dUTPase is fully functional in Mycobacterium smegmatis as it rescues the lethal knock-out phenotype. Our results indicate the potential of dUTPase as a target for antitubercular drugs and identify a genus-specific surface loop on the enzyme as a selective target

Trifluoromethylation of Aliphatic Halogen Compounds

Aryl, heteroaryl or vinyl halides can be trifluoromethylated using CF3CO2Na-Cul. With alkyl iodides, however, the method fails, yielding trifluoroacetyl esters instead. Allylic halogens can be substituted with Burton's reagent, obtained from dihalogenodifluoromethane via CF3CdHal and transmetallation with Cul. A new access to trifluoropropionic acid is thereby found. Prop-2-ynyl bromide produces trifluoromethylallene. Attempts at trifluoromethylation of bromoacetate with CF3CO2Na-Cul in NMP (N-methyl-2-pyrrolidone) solution led to formation of the trifluoroacetoxy derivative and of a formal adduct of hexafluoroacetone to the alpha-position of NMP

Reactivity in [4+2] Cycloadditions of New 4-trifluoromethyl-1,3-oxazin-6-ones - Access To Functionalized 2-trifluoromethyl Pyridines

Recently discovered 4-trifluoromethyl-1,3-oxazin-6-ones react with electron-poor dienophiles as 2-aza-1,3-dienes in Diels-Alder cycloadditions to give new 2-trifluoromethyl pyridines (3a-d, 4a-c). Regioselectivity is excellent in the case of unsymmetrical dienophiles. These new pyridines permit further useful transformations

Image fusion for dynamic contrast enhanced magnetic resonance imaging

Twellmann T, Saalbach A, Gerstung O, Leach MO, Nattkemper TW. Image fusion for dynamic contrast enhanced magnetic resonance imaging. Biomed Eng Online. 2004;3(1): 35.BACKGROUND: Multivariate imaging techniques such as dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) have been shown to provide valuable information for medical diagnosis. Even though these techniques provide new information, integrating and evaluating the much wider range of information is a challenging task for the human observer. This task may be assisted with the use of image fusion algorithms. METHODS: In this paper, image fusion based on Kernel Principal Component Analysis (KPCA) is proposed for the first time. It is demonstrated that a priori knowledge about the data domain can be easily incorporated into the parametrisation of the KPCA, leading to task-oriented visualisations of the multivariate data. The results of the fusion process are compared with those of the well-known and established standard linear Principal Component Analysis (PCA) by means of temporal sequences of 3D MRI volumes from six patients who took part in a breast cancer screening study. RESULTS: The PCA and KPCA algorithms are able to integrate information from a sequence of MRI volumes into informative gray value or colour images. By incorporating a priori knowledge, the fusion process can be automated and optimised in order to visualise suspicious lesions with high contrast to normal tissue. CONCLUSION: Our machine learning based image fusion approach maps the full signal space of a temporal DCE-MRI sequence to a single meaningful visualisation with good tissue/lesion contrast and thus supports the radiologist during manual image evaluation

One second vector and scalar magnetic measurements at the low-latitude Choutuppal (CPL) magnetic observatory

One second measurements of the geomagnetic field variations, which meet INTERMAGNET quality and transmission specifications, require very special conditions to be maintained at the observatories over sustained periods of time, which pose serious challenges for the operators, particularly when infrastructural and environmental conditions are far from ideal. This work presents the progressive steps, which led to the successful setup of such measurements at the new magnetic observatory of the Council of Scientific and Industrial Research (CSIR)-National Geophysical Research Institute (NGRI) in the Choutuppal (CPL) campus, Hyderabad (HYB), India. The 1 s magnetic measurements in trial mode commenced in 2015 using the newly developed observatory-grade 1 s fluxgate magnetometer, GEOMAG-02MO, from Research Centre GEOMAGNET (GM), Ukraine, and the Overhauser proton precession magnetometer, GSM-90F1, along with the data acquisition system, Magrec-4B from Mingeo, Hungary. Iterative tuning of the setup led to the generation of good quality data from 2016 onward. The processes of commissioning this setup in low-latitude conditions, with the aim of producing 1 s definitive data, and the characteristics of the data from this new instrument are presented here

Non-Isocyanate Polythiourethanes (NIPTUs) from Cyclodithiocarbonate Telechelic Polyethers

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