Decrease of time of model synthesis in intellectual monitoring systems

The article investigates modern intellectual monitoring systems (IMS), which are able to predict the consequences of the adopted control decisions of decision support systems (DSS), thanks to the modeling of the characteristics of monitored objects. The drawbacks of existing implementations of IMS show when working in crisis monitoring. Since crisis monitoring imposes a number of restrictions on the speed of DSS and the high probability of failure of the trained IMS models, the use of existing implementations of IMS is problematic. The reasons of the existence of these shortcomings, and the algorithms with which it is connected lies in existing methodology. The paper investigates advantages and disadvantages of existing methods for the formation of inter-level relations in the IMS. A particular attention is paid to the method of classification of input data arrays (IDA) according to their characteristics, to the corresponding class of model synthesis algorithm (MSA). This paper proposes to improve the well-known method of classifying MIA by using unique adaptive classifiers for each of the MSA class.У статті досліджено сучасні моніторингові інтелектуальні системи (МІС), які здатні прогнозувати наслідки прийнятих керуючих рішень систем підтримки прийняття рішень (СППР) завдяки моделюванню характеристик об’єктів моніторингу. Продемонстровано недоліки існуючих реалізацій МІС при роботі в умовах кризового моніторингу. Так як кризовий моніторинг накладає ряд обмежень на швидкість роботи СППР та велику вірогідність виходу навчених моделей МІС із строю, то використання існуючих реалізацій МІС є проблематичним. Досліджено причини існування даних недоліків та алгоритми, з якими це пов’язано. Досліджено переваги та недоліки існуючих методів формування міжрівневих зв’язків у МІС. Особливу увагу звернено на метод класифікації масивів вхідних даних (МВД) за їх характеристиками до відповідного класу алгоритмів синтезу моделей (АСМ). Запропоновано вдосконалити відомий метод класифікації масивів вхідних даних за допомогою використання унікальних адаптивних класифікаторів для кожного із класів алгоритмів синтезу моделей із списку реалізованих у системі.В статье исследованы современные мониторинговые интеллектуальные системы (МИС), которые способны прогнозировать последствия принимаемых управляющих решений систем поддержки принятия решений (СППР) благодаря моделированию характеристик объектов мониторинга. Продемонстрированы недостатки существующих реализаций МИС при работе в условиях кризисного мониторинга. Так как кризисный мониторинг накладывает ряд ограничений на скорость работы СППР и большую вероятность выхода обученных моделей МИС из строя, то использование существующих реализаций МИС является проблематичным. Исследованы причины существования данных недостатков и алгоритмы, с которыми это связано. Исследованы преимущества и недостатки существующих методов формирования межуровневых связей в МИС. Особое внимание обращено на метод классификации массивов входных данных (МВД) по их характеристикам к соответствующему классу алгоритмов синтеза моделей (АСМ). Предложено усовершенствовать известный метод классификации МВД посредством использования уникальных адаптивных классификаторов для каждого из классов АСМ

Nanostructured Films of Semiconducting Molybdenum Disulfide Obtained Through Exfoliation-Restacking Method

Preparing MoS2 films in mild conditions, using deposition of suspended MoS2 nanoplatelets onto the substrate is described. For this purpose, the nanosized MoS2 particles were obtained via restacking of MoS2 single layers produced by chemical exfoliation of bulk MoS2 crystals in liquid media. X-Ray diffraction study of the films showed that the basal planes of MoS2 crystallites are mainly oriented in the plane paral-lel to the substrate. Atomic force microscopy examination revealed the dependence of the film surface to-pography, as well as the roughness characteristics on the film thickness, which varied in the range of 0.03-2.2 m. Optical absorption spectra of the obtained MoS2 films were found to contain the same absorption bands as the spectra of thin natural MoS2 single crystals. Dark conductivity of the films was determined to be ~ 10–3 S∙сm–1 at 300 K. The present MoS2 films were found to be photosensitive in the range of 300-800 nm, providing the maximum value of photocurrent under photoexcitation at ~ 440 nm. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3505

Quantum Error Correction via Convex Optimization

We show that the problem of designing a quantum information error correcting procedure can be cast as a bi-convex optimization problem, iterating between encoding and recovery, each being a semidefinite program. For a given encoding operator the problem is convex in the recovery operator. For a given method of recovery, the problem is convex in the encoding scheme. This allows us to derive new codes that are locally optimal. We present examples of such codes that can handle errors which are too strong for codes derived by analogy to classical error correction techniques.Comment: 16 page

Generalized Jacobi identities and ball-box theorem for horizontally regular vector fields

We consider a family of vector fields and we assume a horizontal regularity on their derivatives. We discuss the notion of commutator showing that different definitions agree. We apply our results to the proof of a ball-box theorem and Poincar\'e inequality for nonsmooth H\"ormander vector fields.Comment: arXiv admin note: material from arXiv:1106.2410v1, now three separate articles arXiv:1106.2410v2, arXiv:1201.5228, arXiv:1201.520

Automated Coronal Hole Detection using Local Intensity Thresholding Techniques

We identify coronal holes using a histogram-based intensity thresholding technique and compare their properties to fast solar wind streams at three different points in the heliosphere. The thresholding technique was tested on EUV and X-ray images obtained using instruments onboard STEREO, SOHO and Hinode. The full-disk images were transformed into Lambert equal-area projection maps and partitioned into a series of overlapping sub-images from which local histograms were extracted. The histograms were used to determine the threshold for the low intensity regions, which were then classified as coronal holes or filaments using magnetograms from the SOHO/MDI. For all three instruments, the local thresholding algorithm was found to successfully determine coronal hole boundaries in a consistent manner. Coronal hole properties extracted using the segmentation algorithm were then compared with in situ measurements of the solar wind at 1 AU from ACE and STEREO. Our results indicate that flux tubes rooted in coronal holes expand super-radially within 1 AU and that larger (smaller) coronal holes result in longer (shorter) duration high-speed solar wind streams

Low Complexity Regularization of Linear Inverse Problems

Inverse problems and regularization theory is a central theme in contemporary signal processing, where the goal is to reconstruct an unknown signal from partial indirect, and possibly noisy, measurements of it. A now standard method for recovering the unknown signal is to solve a convex optimization problem that enforces some prior knowledge about its structure. This has proved efficient in many problems routinely encountered in imaging sciences, statistics and machine learning. This chapter delivers a review of recent advances in the field where the regularization prior promotes solutions conforming to some notion of simplicity/low-complexity. These priors encompass as popular examples sparsity and group sparsity (to capture the compressibility of natural signals and images), total variation and analysis sparsity (to promote piecewise regularity), and low-rank (as natural extension of sparsity to matrix-valued data). Our aim is to provide a unified treatment of all these regularizations under a single umbrella, namely the theory of partial smoothness. This framework is very general and accommodates all low-complexity regularizers just mentioned, as well as many others. Partial smoothness turns out to be the canonical way to encode low-dimensional models that can be linear spaces or more general smooth manifolds. This review is intended to serve as a one stop shop toward the understanding of the theoretical properties of the so-regularized solutions. It covers a large spectrum including: (i) recovery guarantees and stability to noise, both in terms of $\ell^2$-stability and model (manifold) identification; (ii) sensitivity analysis to perturbations of the parameters involved (in particular the observations), with applications to unbiased risk estimation ; (iii) convergence properties of the forward-backward proximal splitting scheme, that is particularly well suited to solve the corresponding large-scale regularized optimization problem

Brief Report: PrEP Eligibility among At-Risk Women in the Southern United States: Associated Factors, Awareness, and Acceptability

Background:Among women in the United States, non-Latina black women in the South have disproportionately high rates of new HIV infections but low use of pre-exposure prophylaxis (PrEP). Effective strategies to identify factors associated with PrEP eligibility could facilitate improved screening, offering, and uptake of PrEP among US women at risk of HIV.Setting and methods:We applied 2014 CDC criteria for PrEP use to at-risk HIV-negative women enrolled in the Southern US sites (Atlanta, Chapel Hill, Birmingham/Jackson, Miami) of the Women's Interagency HIV Study from 2014 to 2015 to estimate PrEP eligibility and assess PrEP knowledge and acceptability. Factors associated with PrEP eligibility were assessed using multivariable models.Results:Among 225 women, 72 (32%) were PrEP-eligible; the most common PrEP indicator was condomless sex. The majority of PrEP-eligible women (88%) reported willingness to consider PrEP. Only 24 (11%) PrEP-eligible women had previously heard of PrEP, and only 1 reported previous use. Education level less than high school [adjusted odds ratio (aOR) 2.56; 95% confidence interval (CI): 1.22 to 5.37], history of sexual violence (aOR 4.52; 95% CI: 1.52 to 17.76), and medium to high self-perception of HIV risk (aOR 6.76; 95% CI: 3.26 to 14.05) were significantly associated with PrEP eligibility in adjusted models.Conclusions:Extremely low PrEP awareness and use despite a high proportion of eligibility and acceptability signify a critical need to enhance PrEP education and delivery for women in this region. Supplementing CDC eligibility criteria with questions about history of sexual violence and HIV risk self-assessment may enhance PrEP screening and uptake among US women

Niche-Based Screening in Multiple Myeloma Identifies a Kinesin-5 Inhibitor with Improved Selectivity over Hematopoietic Progenitors

SummaryNovel therapeutic approaches are urgently required for multiple myeloma (MM). We used a phenotypic screening approach using co-cultures of MM cells with bone marrow stromal cells to identify compounds that overcome stromal resistance. One such compound, BRD9876, displayed selectivity over normal hematopoietic progenitors and was discovered to be an unusual ATP non-competitive kinesin-5 (Eg5) inhibitor. A novel mutation caused resistance, suggesting a binding site distinct from known Eg5 inhibitors, and BRD9876 inhibited only microtubule-bound Eg5. Eg5 phosphorylation, which increases microtubule binding, uniquely enhanced BRD9876 activity. MM cells have greater phosphorylated Eg5 than hematopoietic cells, consistent with increased vulnerability specifically to BRD9876’s mode of action. Thus, differences in Eg5-microtubule binding between malignant and normal blood cells may be exploited to treat multiple myeloma. Additional steps are required for further therapeutic development, but our results indicate that unbiased chemical biology approaches can identify therapeutic strategies unanticipated by prior knowledge of protein targets

Dimensions of invasiveness: Links between local abundance, geographic range size, and habitat breadth in Europe's alien and native floras

Understanding drivers of success for alien species can inform on potential future invasions. Recent conceptual advances highlight that species may achieve invasiveness via performance along at least three distinct dimensions: 1) local abundance, 2) geographic range size, and 3) habitat breadth in naturalized distributions. Associations among these dimensions and the factors that determine success in each have yet to be assessed at large geographic scales. Here, we combine data from over one million vegetation plots covering the extent of Europe and its habitat diversity with databases on species' distributions, traits, and historical origins to provide a comprehensive assessment of invasiveness dimensions for the European alien seed plant flora. Invasiveness dimensions are linked in alien distributions, leading to a continuum from overall poor invaders to super invaders - abundant, widespread aliens that invade diverse habitats. This pattern echoes relationships among analogous dimensions measured for native European species. Success along invasiveness dimensions was associated with details of alien species' introduction histories: earlier introduction dates were positively associated with all three dimensions, and consistent with theory-based expectations, species originating from other continents, particularly acquisitive growth strategists, were among the most successful invaders in Europe. Despite general correlations among invasiveness dimensions, we identified habitats and traits associated with atypical patterns of success in only one or two dimensions - for example, the role of disturbed habitats in facilitating widespread specialists. We conclude that considering invasiveness within a multidimensional framework can provide insights into invasion processes while also informing general understanding of the dynamics of species distributions.Deutsche Forschungsgemeinschaft (264740629) Grantová Agentura České Republiky (19-28491X) Grantová Agentura České Republiky (19-28807X) Grantová Agentura České Republiky (RVO 67985939) Austrian Science Fund (I 2086 - B29) Bundesministerium für Bildung und Forschung (01LC1807A) Eusko Jaurlaritza (IT299-10) National Research Foundation of Korea (2018R1C1B6005351) University of Latvia (AAp2016/B041//Zd2016/AZ03) Villum Fonden (16549

Niche-Based Screening in Multiple Myeloma Identifies a Kinesin-5 Inhibitor with Improved Selectivity over Hematopoietic Progenitors

Novel therapeutic approaches are urgently required for multiple myeloma (MM). We used a phenotypic screening approach using co-cultures of MM cells with bone marrow stromal cells to identify compounds that overcome stromal resistance. One such compound, BRD9876, displayed selectivity over normal hematopoietic progenitors and was discovered to be an unusual ATP non-competitive kinesin-5 (Eg5) inhibitor. A novel mutation caused resistance, suggesting a binding site distinct from known Eg5 inhibitors, and BRD9876 inhibited only microtubule-bound Eg5. Eg5 phosphorylation, which increases microtubule binding, uniquely enhanced BRD9876 activity. MM cells have greater phosphorylated Eg5 than hematopoietic cells, consistent with increased vulnerability specifically to BRD9876’s mode of action. Thus, differences in Eg5-microtubule binding between malignant and normal blood cells may be exploited to treat multiple myeloma. Additional steps are required for further therapeutic development, but our results indicate that unbiased chemical biology approaches can identify therapeutic strategies unanticipated by prior knowledge of protein targets