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Nodal, excited compactons in the CPN models with V-shaped potentials are analyzed. It is shown that the solutions exist as compact Q-balls and Q-shells. The solutions have a discontinuity in the second derivative associated with the character of the potential, however, their energy and charge densities are both continuous. The excited Q-balls and Q-shells are analyzed as electrically neutral and electrically charged objects.

The Verizon Global Supply Chain organization currently manages thousands of active supplier contracts. These contracts account for several billion dollars of annualized Verizon spend. Managing thousands of suppliers, controlling spend, and achieving the best price per unit (PPU) through negotiations are costly and labor-intensive tasks handled by Verizon strategic sourcing teams. Verizon engages thousands of suppliers for many reasons—best price, diversity, short-term requirements, and so forth. Whereas managing a few larger spend suppliers can be done manually by dedicated sourcing managers, managing thousands of smaller suppliers at the tail spend is challenging, can often introduce risk, and can be expensive. At Verizon, a unique blend of descriptive, predictive, and prescriptive analytics, as well as Verizon-specific sourcing acumen was leveraged to tackle this problem and rationalize Verizon’s tail spend suppliers. Through the creative application of operations research, machine learning, text mining, natural language processing, and artificial intelligence, Verizon reduced spend by millions of dollars and acquired the lowest PPU for the sourced products and services. Other benefits Verizon realized were centralized and transparent contract and supplier relationship management, overhead cost reduction, decreased contract execution lead time, and service quality improvement for Verizon’s strategic sourcing teams.

En este trabajo se obtiene un nuevo modelo de predicci��n de la capacidad de carga para la conexi��n con pasador de barra de acero en estructuras compuestas madera ��� hormig��n. Se usa como herremienta fundamental la modelaci��n num��rica del ensayo ��push out�� de la conexi��n, sustentada en el M��todo de los Elementos Finitos (MEF). En la modelaci��n de la madera se emplean leyes f��sico-constitutivas ortotr��picas, as�� como curvas bilineales de tensi��n-deformaci��n con criterio de fallo de Hill. Para la modelaci��n del hormig��n, se considera el material isotr��pico con el empleo del criterio de da��o pl��stico para r��gimen no lineal (Bonilla, 2008). La simulaci��n num��rica es calibrada frente a resultados experimentales de investigaciones precedentes (Lopes et al., 2003). La adecuada correspondencia entre la respuesta f��sico-mec��nica del esp��cimen virtual y el ensayo experimental de referencia registra indicadores de errores estad��sticos inferiores al 3,5 % de la capacidad de carga real. Se acompa��a el estudio con un dise��o de experimentos de m��ltiples factores y su an��lisis estad��stico por medio del software (STATGRAPHICS CENTURION XV. v-15.1.02, 2006). La ecuaci��n obtenida, a partir del procesamiento estad��stico, describe el comportamiento de la capacidad resistente de la conexi��n con un nivel de confianza de 95 %.

Large-scale service environments rely on autonomous systems for remediating hardware failures efficiently. In production, the autonomous system diagnoses hardware failures based on the rules that the subject matter experts put in the system. This process is increasingly complex given new types of failures and the increasing complexity in the hardware and software configurations. In this paper, we present a machine learning framework that predicts the required remediations for undiagnosed failures, based on the similar repair tickets closed in the past. We explain the methodology in detail for setting up a machine learning model, deploying it in a production environment, and monitoring its performance with the necessary metrics. We also demonstrate the prediction performance on some of the repair actions.

A triangular microstrip patch antenna fed with three microstrip feeds is designed on an equilateral substrate to produce different polarization states. Quarter wavelength transformers are utilized for better impedance matching. The proposed antenna can provide a linear polarization state with wide bandwidth and right and left-hand circular polarization with acceptable axial ratio bandwidth through activating one feed at a time. Other states can be obtained with different phase shifts by involving two or more active feeds. No diodes and hence no DC or AC biasing circuits are used in this design. Various aspects of the antenna have been analyzed such as reflection coefficient Sn, ports isolation, axial ratio, far-field E and H pattern and gain are investigated and optimized through several parametric studies of the antenna variables.

Background To assess the impact of time-of-flight (TOF) positron emission tomography (PET)/computed tomography (CT) image reconstruction on assessment of Takayasu arteritis (TKA). We reviewed 14 patients (15 cases) who underwent TOF-PET/CT. PET images were reconstructed using ordered-subsets expectation maximisation ± TOF. Uptake in 10 vascular regions was assessed using the four-point visual grading system (3, higher than liver uptake; 0, no uptake). The grades in the TOF-PET/CT and non-TOF-PET/CT groups were compared using the sign test. Relationships between visual grade and arterial FDG uptake pattern in the 10 regions and clinical findings were assessed. Results Except for the highest visual grade, the visual grades in all regions were significantly higher in the TOF-PET/CT group (p=0.003). FDG uptake pattern and region were not significant determinants of the effect of TOF reconstruction. Assessment of disease activity was inconsistent between the groups in 6 (4%) of 150 regions when grade 2/3 was defined as active and in 5 (3.3%) of 150 when grade 3 was defined as active. Conclusions Visual grades were significantly higher in all regions when assessed by TOF-PET/CT. Use of the same reconstruction algorithm before and after treatment is recommended when evaluating the response to treatment.