Project PROMETHEUS: Design and Construction of a Radio Frequency Quadrupole at TAEK

The PROMETHEUS Project is ongoing for the design and development of a 4-vane radio frequency quadrupole (RFQ) together with its H+ ion source, a low energy beam transport (LEBT) line and diagnostics section. The main goal of the project is to achieve the acceleration of the low energy ions up to 1.5 MeV by an RFQ (352 MHz) shorter than 2 meter. A plasma ion source is being developed to produce a 20 keV, 1 mA H+ beam. Simulation results for ion source, transmission and beam dynamics are presented together with analytical studies performed with newly developed RFQ design code DEMIRCI. Simulation results shows that a beam transmission 99% could be achieved at 1.7 m downstream reaching an energy of 1.5 MeV. As the first phase an Aluminum RFQ prototype, the so-called cold model, will be built for low power RF characterization. In this contribution the status of the project, design considerations, simulation results, the various diagnostics techniques and RFQ manufacturing issues are discussed.Comment: 4 pages, 8 figures, Proceedings of the 2nd International Beam Instrumentation Conference 2013 (IBIC'13), 16-19 Sep 2013, WEPC02, p. 65

Semi-Supervised Deep Learning for Multi-Tissue Segmentation from Multi-Contrast MRI

Segmentation of thigh tissues (muscle, fat, inter-muscular adipose tissue (IMAT), bone, and bone marrow) from magnetic resonance imaging (MRI) scans is useful for clinical and research investigations in various conditions such as aging, diabetes mellitus, obesity, metabolic syndrome, and their associated comorbidities. Towards a fully automated, robust, and precise quantification of thigh tissues, herein we designed a novel semi-supervised segmentation algorithm based on deep network architectures. Built upon Tiramisu segmentation engine, our proposed deep networks use variational and specially designed targeted dropouts for faster and robust convergence, and utilize multi-contrast MRI scans as input data. In our experiments, we have used 150 scans from 50 distinct subjects from the Baltimore Longitudinal Study of Aging (BLSA). The proposed system made use of both labeled and unlabeled data with high efficacy for training, and outperformed the current state-of-the-art methods with dice scores of 97.52%, 94.61%, 80.14%, 95.93%, and 96.83% for muscle, fat, IMAT, bone, and bone marrow tissues, respectively. Our results indicate that the proposed system can be useful for clinical research studies where volumetric and distributional tissue quantification is pivotal and labeling is a significant issue. To the best of our knowledge, the proposed system is the first attempt at multi-tissue segmentation using a single end-to-end semi-supervised deep learning framework for multi-contrast thigh MRI scans.Comment: 20 pages, 9 figures, Journal of Signal Processing System

Search for electroweak production of charginos and neutralinos in WH events in proton-proton collisions at s√=13 TeV

Results are reported from a search for physics beyond the standard model in proton-proton collision events with a charged lepton (electron or muon), two jets identified as originating from a bottom quark decay, and significant imbalance in the transverse momentum. The search was performed using a data sample corresponding to 35.9 fb−1, collected by the CMS experiment in 2016 at s√=13 TeV. Events with this signature can arise, for example, from the electroweak production of gauginos, which are predicted in models based on supersymmetry. The event yields observed in data are consistent with the estimated standard model backgrounds. Limits are obtained on the cross sections for chargino-neutralino (χ~±1χ~02) production in a simplified model of supersymmetry with the decays χ±1→W±χ~01andχ~02→Hχ01. Values of mχ~±1 between 220 and 490 GeV are excluded at 95% confidence level by this search when the χ~01 is massless, and values of mχ~01 are 1 excluded up to 110 GeV for mχ~±1≈450 GeV

Instance generation via generator instances

Funding: UK EPSRC grant EP/P015638/1.Access to good benchmark instances is always desirable when developing new algorithms, new constraint models, or when comparing existing ones. Hand-written instances are of limited utility and are time-consuming to produce. A common method for generating instances is constructing special purpose programs for each class of problems. This can be better than manually producing instances, but developing such instance generators also has drawbacks. In this paper, we present a method for generating graded instances completely automatically starting from a class-level problem specification. A graded instance in our present setting is one which is neither too easy nor too difficult for a given solver. We start from an abstract problem specification written in the Essence language and provide a system to transform the problem specification, via automated type-specific rewriting rules, into a new abstract specification which we call a generator specification. The generator specification is itself parameterised by a number of integer parameters; these are used to characterise a certain region of the parameter space. The solutions of each such generator instance form valid problem instances. We use the parameter tuner irace to explore the space of possible generator parameters, aiming to find parameter values that yield graded instances. We perform an empirical evaluation of our system for five problem classes from CSPlib, demonstrating promising results.Postprin

Обучение академическому письму: проблемы и решения

Обозначены основные проблемы, с которыми сталкиваются преподаватели и студенты при внедрении курса "Академическое письмо". Проведен анализ письменных работ студентов на английском языке, описаны трудности, которые испытывают студенты при их написани

First observation of a narrow charm-strange meson DsJ(2632) -> Ds eta and D0 K+

We report the first observation of a charm-strange meson DsJ(2632) at a mass of 2632.6+/-1.6 MeV/c^2 in data from SELEX, the charm hadro-production experiment E781 at Fermilab. This state is seen in two decay modes, Ds eta and D0 K+. In the Ds eta decay mode we observe an excess of 49.3 events with a significance of 7.2sigma at a mass of 2635.9+/-2.9 MeV/c^2. There is a corresponding peak of 14 events with a significance of 5.3sigma at 2631.5+/-1.9 MeV/c^2 in the decay mode D0 K+. The decay width of this state is <17 MeV/c^2 at 90% confidence level. The relative branching ratio Gamma(D0K+)/Gamma(Dseta) is 0.16+/-0.06. The mechanism which keeps this state narrow is unclear. Its decay pattern is also unusual, being dominated by the Ds eta decay mode.Comment: 5 pages, 3 included eps figures. v2 as accepted for publication by PR

Non-B DB: a database of predicted non-B DNA-forming motifs in mammalian genomes

Although the capability of DNA to form a variety of non-canonical (non-B) structures has long been recognized, the overall significance of these alternate conformations in biology has only recently become accepted en masse. In order to provide access to genome-wide locations of these classes of predicted structures, we have developed non-B DB, a database integrating annotations and analysis of non-B DNA-forming sequence motifs. The database provides the most complete list of alternative DNA structure predictions available, including Z-DNA motifs, quadruplex-forming motifs, inverted repeats, mirror repeats and direct repeats and their associated subsets of cruciforms, triplex and slipped structures, respectively. The database also contains motifs predicted to form static DNA bends, short tandem repeats and homo(purine•pyrimidine) tracts that have been associated with disease. The database has been built using the latest releases of the human, chimp, dog, macaque and mouse genomes, so that the results can be compared directly with other data sources. In order to make the data interpretable in a genomic context, features such as genes, single-nucleotide polymorphisms and repetitive elements (SINE, LINE, etc.) have also been incorporated. The database is accessed through query pages that produce results with links to the UCSC browser and a GBrowse-based genomic viewer. It is freely accessible at http://nonb.abcc.ncifcrf.gov

A framework for constraint based local search using ESSENCE

Structured Neighbourhood Search (SNS) is a framework for constraint-based local search for problems expressed in the Essence abstract constraint specification language. The local search explores a structured neighbourhood, where each state in the neighbourhood preserves a high level structural feature of the problem. SNS derives highly structured problem-specific neighbourhoods automatically and directly from the features of the ESSENCE specification of the problem. Hence, neighbourhoods can represent important structural features of the problem, such as partitions of sets, even if that structure is obscured in the low-level input format required by a constraint solver. SNS expresses each neighbourhood as a constrained optimisation problem, which is solved with a constraint solver. We have implemented SNS, together with automatic generation of neighbourhoods for high level structures, and report high quality results for several optimisation problems