Studies and application of bent crystals for beam steering at 70-GeV IHEP accelerator

This report overviews studies accomplished in the U70 proton synchrotron of IHEP-Protvino during the recent two decades. Major attention is paid to a routine application of bent crystals for beam extraction from the machine. It has been confirmed experimentally that efficiency of beam extraction with a crystal deflector of around 85% is well feasible for a proton beam with intensity up to 1012 protons per cycle. Another trend is to use bent crystals for halo collimation in a high energy collider. New promising options emerge for, say, LHC and ILC based on the "volume reflection" effect, which has been discovered recently in machine study runs at U70 of IHEP (50 GeV) and SPS of CERN (400 GeV).Comment: 12 pages, 14 figure

Charm in cosmic rays (The long-flying component of EAS cores)

Experimental data on cosmic ray cascades with enlarged attenuation lengths (Tien-Shan effect) are presented and analyzed in terms of charm hadroproduction. The very first estimates of charm hadroproduction cross sections from experimental data at high energies are confirmed and compared with recent accelerator results.Comment: 12 pages, 8 figures, LATE

Superfluid pairing in a polarized dipolar Fermi gas

We calculate the critical temperature of a superfluid phase transition in a polarized Fermi gas of dipolar particles. In this case the order parameter is anisotropic and has a nontrivial energy dependence. Cooper pairs do not have a definite value of the angular momentum and are coherent superpositions of all odd angular momenta. Our results describe prospects for achieving the superfluid transition in single-component gases of fermionic polar molecules.Comment: 12 pages, 2 figure

Технологии комплексного интеллектуального анализа клинических данных

The paper presents the system for intelligent analysis of clinical information. Authors describe methods implemented in the system for clinical information retrieval, intelligent diagnostics of chronic diseases, patient’s features importance and for detection of hidden dependencies between features. Results of the experimental evaluation of these methods are also presented.Background: Healthcare facilities generate a large flow of both structured and unstructured data which contain important information about patients. Test results are usually retained as structured data but some data is retained in the form of natural language texts (medical history, the results of physical examination, and the results of other examinations, such as ultrasound, ECG or X-ray studies). Many tasks arising in clinical practice can be automated applying methods for intelligent analysis of accumulated structured array and unstructured data that leads to improvement of the healthcare quality.Aims: the creation of the complex system for intelligent data analysis in the multi-disciplinary pediatric center.Materials and methods: Authors propose methods for information extraction from clinical texts in Russian. The methods are carried out on the basis of deep linguistic analysis. They retrieve terms of diseases, symptoms, areas of the body and drugs. The methods can recognize additional attributes such as «negation» (indicates that the disease is absent), «no patient» (indicates that the disease refers to the patient’s family member, but not to the patient), «severity of illness», «disease course», «body region to which the disease refers». Authors use a set of hand-drawn templates and various techniques based on machine learning to retrieve information using a medical thesaurus. The extracted information is used to solve the problem of automatic diagnosis of chronic diseases. A machine learning method for classification of patients with similar nosology and the method for determining the most informative patients’ features are also proposed.Results: Authors have processed anonymized health records from the pediatric center to estimate the proposed methods. The results show the applicability of the information extracted from the texts for solving practical problems. The records of patients with allergic, glomerular and rheumatic diseases were used for experimental assessment of the method of automatic diagnostic. Authors have also determined the most appropriate machine learning methods for classification of patients for each group of diseases, as well as the most informative disease signs. It has been found that using additional information extracted from clinical texts, together with structured data helps to improve the quality of diagnosis of chronic diseases. Authors have also obtained pattern combinations of signs of diseases.Conclusions: The proposed methods have been implemented in the intelligent data processing system for a multidisciplinary pediatric center. The experimental results show the availability of the system to improve the quality of pediatric healthcare. Обоснование. Медицинские учреждения генерируют большой поток как структурированных, так и неструктурированных данных, содержащих важную информацию о пациентах. В структурированном виде, как правило, хранятся результаты анализов, однако подавляющее количество данных хранится в неструктурированной форме в виде текстов на естественном языке (анамнезы, результаты осмотров, описания результатов обследований, таких как УЗИ, ЭКГ, рентгеновских исследований и др.). Используя методы интеллектуальной обработки накопленных массивов структурированных и неструктурированных данных, можно автоматизировать решение многих задач, возникающих в клинической практике и повысить качество медицинской помощи.Цель исследования: создание комплексной системы интеллектуальной обработки данных в многопрофильном педиатрическом центре.Методы. Извлечение информации из клинических текстов на русском языке осуществляется на основе полного лингвистического анализа. Извлекаются упоминания заболеваний, симптомов, областей тела, лекарственных препаратов. В тексте также распознаются атрибуты заболеваний: «отрицание» (указывает на то, что заболевание отсутствует), «не пациент» (указывает на то, что заболевание относится не к пациенту, а к его родственнику), «тяжесть заболевания», «течение заболевания», «область тела, к которой относится заболевание». Для извлечения информации используются медицинские тезаурусы, набор вручную составленных шаблонов, а также различные методы на основе машинного обучения. Полученные из текстов данные используются для решения задачи автоматической диагностики хронических заболеваний. Предложен метод на основе машинного обучения для классификации пациентов со схожими нозологиями, а также метод для определения наиболее информативных признаков.Результаты. Экспериментальное исследование разработанных методов проводилось на обезличенных историях болезни пациентов педиатрического центра. Проведена оценка качества разработанных методов извлечения информации из клинических текстов на русском языке. Проведена экспериментальная оценка метода автоматической диагностики на данных пациентов с аллергическими заболеваниями и болезными органов дыхания, нефрологическими и ревматическими заболеваниями. Определены наиболее подходящие методы машинного обучения для классификации пациентов для каждой группы заболеваний, а также наиболее информативные признаки. Использование данных, извлеченных из клинических текстов совместно со структурированными данными, позволило повысить качество диагностики хронических заболеваний по сравнению с использованием лишь доступных структурированных данных. Получены также шаблонные комбинации признаков заболеваний.Заключение. Разработанные методы были реализованы в системе интеллектуальной обработки данных в многопрофильном педиатрическом центре. Проведенные исследования свидетельствуют о перспективности использования системы для повышения качества медицинской помощи пациентам детской возрастной категории

Evaporation and Condensation of Clusters

Influence of surrounding matter on the properties of clusters is considered by an approach combining the methods of statistical and quantum mechanics. A cluster is treated as a bound N-particle system and surrounding matter as thermostat. It is shown that, despite arbitrary strong interactions between particles, cluster energy can be calculated by using the controlled perturbation theory. The accuracy of the latter is found to be much higher than that of the quasiclassical approximation. Spectral distribution is obtained by minimizing conditional entropy. Increasing the thermostat temperature leads to the depletion of bound states. The characteristic temperature when bound states become essentially depleated defines the temperature of cluster evaporation. The inverse process of lowering the thermostate temperature, yielding the filling of bound states, corresponds to cluster condensation.Comment: 1 file, 15 pages, RevTex, 4 table

Proton Extraction from IHEP Accelerator Using Bent Crystals

IHEP Protvino has pioneered the wide practical use of bent crystals as optical elements in high-energy beams for beam extraction and deflection on permanent basis since 1989. In the course of IHEP experiments, crystal channeling has been developed into efficient instrument for particle steering at accelerators, working in predictable, reliable manner with beams of very high intensity over years. Crystal systems extract 70 GeV protons from IHEP main ring with efficiency of 85% at intensity of 1.E12, basing on multi-pass mechanism of channeling proposed theoretically and realised experimentally at IHEP. Today, six locations on the IHEP 70-GeV main ring of the accelerator facility are equipped by crystal extraction systems, serving mostly for routine applications rather than for research and allowing a simultaneous run of several particle physics experiments, thus significantly enriching the IHEP physics program. The long successful history of large-scale crystal exploitation at IHEP should help to incorporate channeling crystals into accelerator systems worldwide in order to create unique systems for beam delivery. We report recent results from the research and exploitation of crystal extraction systems at IHEP.Comment: Invited talk at the International workshop "Relativistic Channeling and Related Coherent Phenomena", Frascati (Rome) 23-26 March 200

Dimers, Effective Interactions, and Pauli Blocking Effects in a Bilayer of Cold Fermionic Polar Molecules

We consider a bilayer setup with two parallel planes of cold fermionic polar molecules when the dipole moments are oriented perpendicular to the planes. The binding energy of two-body states with one polar molecule in each layer is determined and compared to various analytic approximation schemes in both coordinate- and momentum-space. The effective interaction of two bound dimers is obtained by integrating out the internal dimer bound state wave function and its robustness under analytical approximations is studied. Furthermore, we consider the effect of the background of other fermions on the dimer state through Pauli blocking, and discuss implications for the zero-temperature many-body phase diagram of this experimentally realizable system.Comment: 18 pages, 10 figures, accepted versio

Double volume reflection of a proton beam by a sequence of two bent crystals

The doubling of the angle of beam deflection due to volume reflection of protons by a sequence of two bent silicon crystals was experimentally observed at the 400 GeV proton beam of the CERN SPS. A similar sequence of short bent crystals can be used as an efficient primary collimator for the Large Hadron Collider

Measurement of Leading Proton and Neutron Production in Deep Inelastic Scattering at HERA

Deep--inelastic scattering events with a leading baryon have been detected by the H1 experiment at HERA using a forward proton spectrometer and a forward neutron calorimeter. Semi--inclusive cross sections have been measured in the kinematic region 2 <= Q^2 <= 50 GeV^2, 6.10^-5 <= x <= 6.10^-3 and baryon p_T <= MeV, for events with a final state proton with energy 580 <= E' <= 740 GeV, or a neutron with energy E' >= 160 GeV. The measurements are used to test production models and factorization hypotheses. A Regge model of leading baryon production which consists of pion, pomeron and secondary reggeon exchanges gives an acceptable description of both semi-inclusive cross sections in the region 0.7 <= E'/E_p <= 0.9, where E_p is the proton beam energy. The leading neutron data are used to estimate for the first time the structure function of the pion at small Bjorken--x.Comment: 30 pages, 9 figures, 2 tables, submitted to Eur. Phys.

Measurement of the polarisation of W bosons produced with large transverse momentum in pp collisions at sqrt(s) = 7 TeV with the ATLAS experiment

This paper describes an analysis of the angular distribution of W->enu and W->munu decays, using data from pp collisions at sqrt(s) = 7 TeV recorded with the ATLAS detector at the LHC in 2010, corresponding to an integrated luminosity of about 35 pb^-1. Using the decay lepton transverse momentum and the missing transverse energy, the W decay angular distribution projected onto the transverse plane is obtained and analysed in terms of helicity fractions f0, fL and fR over two ranges of W transverse momentum (ptw): 35 < ptw < 50 GeV and ptw > 50 GeV. Good agreement is found with theoretical predictions. For ptw > 50 GeV, the values of f0 and fL-fR, averaged over charge and lepton flavour, are measured to be : f0 = 0.127 +/- 0.030 +/- 0.108 and fL-fR = 0.252 +/- 0.017 +/- 0.030, where the first uncertainties are statistical, and the second include all systematic effects.Comment: 19 pages plus author list (34 pages total), 9 figures, 11 tables, revised author list, matches European Journal of Physics C versio