507 research outputs found

    Prioritising alternatives for maintenance of water distribution networks: A group decision approach

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    Difficulties related to the group decision-making process in the water supply sector, such as physical and economic losses, irrational use of water and maintenance costs, highlight the need to develop procedures to support decisions, reducing unnecessary water use and wastage. This study focused on the rational use of water resources and reduction of water losses, based on the assumption that it is far more economical to develop and improve existing systems rather than build new systems in parallel to the existing one. This study aimed to support a group decision-making process in the maintenance section of a water supply company. A model is proposed consisting of 2 phases, which aggregates individual preferences to achieve a group decision. The first phase is based on the ELECTRE II method, analysing individual preferences, while the second is based on the COPELAND method to aggregate individual preferences. From this model, we developed a software program to prioritise alternatives, simultaneously taking into account subjective and objective criteria, and thereby giving decision makers a clear and comprehensive overview of alternatives, indicating the most suitable alternative based on the preferences of group members from different areas

    Fusion PET-CT imaging of neurolymphomatosis

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    In a patient suffering from peripheral neuropathy due to neurolymphomatosis, fused PET-CT imaging, performed on a novel in-line PET-CT system, showed multiple small nodular lesions extending along the peripheral nerves corresponding to an early relapse of a transformed B-cell non-Hodgkin's lymphom

    A Radio Determination of the Time of the New Moon

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    The detection of the New Moon at sunset is of importance to communities based on the lunar calendar. This is traditionally undertaken with visual observations. We propose a radio method which allows a higher visibility of the Moon relative to the Sun and consequently gives us the ability to detect the Moon much closer to the Sun than is the case of visual observation. We first compare the relative brightness of the Moon and Sun over a range of possible frequencies and find the range 5--100\,GHz to be suitable. The next consideration is the atmospheric absorption/emission due to water vapour and oxygen as a function of frequency. This is particularly important since the relevant observations are near the horizon. We show that a frequency of 10\sim 10 GHz is optimal for this programme. We have designed and constructed a telescope with a FWHM resolution of 0 ⁣ ⁣^\circ{}\!\!.6 and low sidelobes to demonstrate the potential of this approach. At the time of the 21 May 2012 New Moon the Sun/Moon brightness temperature ratio was 72.7±2.272.7 \pm 2.2 in agreement with predictions from the literature when combined with the observed sunspot numbers for the day. The Moon would have been readily detectable at 2\sim 2^{\circ} from the Sun. Our observations at 16\,hr\,36\,min UT indicated that the Moon would have been at closest approach to the Sun 16\,hr\,25\,min earlier; this was the annular solar eclipse of 00\,hr\,00\,min\,UT on 21 May 2012.Comment: 11 pages, 15 figures, accepted for publication in MNRA

    General and differential therapy in the field of logopedics and phoniatrics

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    Autistic adults benefit from and enjoy learning via social interaction as much as neurotypical adults do

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    Background: Autistic people show poor processing of social signals (i.e. about the social world). But how do they learn via social interaction? // Methods: 68 neurotypical adults and 60 autistic adults learned about obscure items (e.g. exotic animals) over Zoom (i) in a live video-call with the teacher, (ii) from a recorded learner-teacher interaction video and (iii) from a recorded teacher-alone video. Data were analysed via analysis of variance and multi-level regression models. // Results: Live teaching provided the most optimal learning condition, with no difference between groups. Enjoyment was the strongest predictor of learning: both groups enjoyed the live interaction significantly more than other condition and reported similar anxiety levels across conditions. // Limitations: Some of the autistic participants were self-diagnosed—however, further analysis where these participants were excluded showed the same results. Recruiting participants over online platforms may have introduced bias in our sample. Future work should investigate learning in social contexts via diverse sources (e.g. schools). // Conclusions: These findings advocate for a distinction between learning about the social versus learning via the social: cognitive models of autism should be revisited to consider social interaction not just as a puzzle to decode but rather a medium through which people, including neuro-diverse groups, learn about the world around them. // Trial registration: Part of this work has been pre-registered before data collection https://doi.org/10.17605/OSF.IO/5PGA

    Exotic magnetism in the alkali sesquoxides Rb4O6 and Cs4O6

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    Among the various alkali oxides the sesquioxides Rb4O6 and Cs4O6 are of special interest. Electronic structure calculations using the local spin-density approximation predicted that Rb4O6 should be a half-metallic ferromagnet, which was later contradicted when an experimental investigation of the temperature dependent magnetization of Rb4O6 showed a low-temperature magnetic transition and differences between zero-field-cooled (ZFC) and field-cooled (FC) measurements. Such behavior is known from spin glasses and frustrated systems. Rb4O6 and Cs4O6 comprise two different types of dioxygen anions, the hyperoxide and the peroxide anions. The nonmagnetic peroxide anions do not contain unpaired electrons while the hyperoxide anions contain unpaired electrons in antibonding pi*-orbitals. High electron localization (narrow bands) suggests that electronic correlations are of major importance in these open shell p-electron systems. Correlations and charge ordering due to the mixed valency render p-electron-based anionogenic magnetic order possible in the sesquioxides. In this work we present an experimental comparison of Rb4O6 and the related Cs4O6. The crystal structures are verified using powder x-ray diffraction. The mixed valency of both compounds is confirmed using Raman spectroscopy, and time-dependent magnetization experiments indicate that both compounds show magnetic frustration, a feature only previously known from d- and f-electron systems

    Forecasting Electricity Demand by Neural Networks and Definition of Inputs by Multi-Criteria Analysis

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    The planning of efficient policies based on forecasting electricity demand is essential to guarantee the continuity of energy supply for consumers. Some techniques for forecasting electricity demand have used specific procedures to define input variables, which can be particular to each case study. However, the definition of independent and casual variables is still an issue to be explored. There is a lack of models that could help the selection of independent variables, based on correlate criteria and level of importance integrated with artificial networks, which could directly impact the forecasting quality. This work presents a model that integrates a multi-criteria approach which provides the selection of relevant independent variables and artificial neural networks to forecast the electricity demand in countries. It provides to consider the particularities of each application. To demonstrate the applicability of the model a time series of electricity consumption from a southern region of Brazil was used. The dependent inputs used by the neural networks were selected using a traditional method called Wrapper. As a result of this application, with the multi-criteria ELECTRE I method was possible to recognize temperature and average evaporation as explanatory variables. When the variables selected by the multi-criteria approach were included in the predictive models, were observed more consistent results together with artificial neural networks, better than the traditional linear models. The Radial Basis Function Networks and Extreme Learning Machines stood out as potential techniques to be used integrated with a multi-criteria method to better perform the forecasting

    Inverse relationship between anemia in the third trimester of pregnancy and low birth weight in a reference maternity unit of a carribean region of Colombia

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    Anemia is common amongst women in developing countries. Although a relationship has been established between gestational anemia and negative perinatal outcomes, it remains a controversial debate as opposite associations have been found. This study assessed the relationship between gestational anemia in the third trimester and low birth weight (LBW) in the ESE Clinica Maternidad Rafael Calvo, a reference maternity unit in the department of Bolivar, Colombia

    A multi-criteria approach for the selection of wastewater treatment systems

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    The inefficiency of Wastewater Treatment Systems (WTS) might be a source of hydrological and environmental pollution, and it also causes problems to public health. The advances of technology have contributed to the development of a diversity of new WTS, but it generates a gap for decision-making regards to the correct use of these treatment systems, with a high number of available alternatives, not easily measurable and often presenting conflicting criteria. In this context, this work presents a literature review aiming to identify relevant economic, social, technical and environmental criteria, which can be used in the selection of WTS. Thus, 48 criteria were identified, as well and their importance was ranked according to a group of academics. Furthermore, an illustrative application was conducted considering 20 available WTS and 12 criteria. The ELECTRE 11 method was used to rank and allocate the most suitable WTS. This research contributes with a multi-criteria model for the evaluation of WTS and to show its relevance in a real world situation

    Impaired CD8+ T-Cell Reactivity against Viral Antigens in Cancer Patients with Solid Tumors

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    Background: : Patients with hematological malignancies are at increased risk for various infections. In patients with solid cancer, a variety of immunosuppressive mechanisms affecting T-cell response are described. We hypothesized that patients with advanced solid tumors may exhibit an impaired recognition of viral antigens. To test this, the capability of CD8+ T cells to recognize recall antigens from influenza and vaccinia virus was compared in patients and healthy individuals. Since all patients and most of the healthy individuals had been vaccinated against vaccinia years ago, comparison of the two groups was expected to be especially informative with respect to distinct effector T-cell reactivity. Materials and Methods: : Our test population included 16 healthy individuals and 12 patients with advanced solid cancers who were currently not receiving chemotherapy. We stimulated peripheral blood mononuclear cells (PBMC) ex vivo with the well-characterized influenza A matrix 58-66 peptide and the immunogenic and HLA-A*0201 restricted peptide epitope SLSAYIIRV derived from the modified vaccinia virus Ankara (MVA). A specific CD8+ T-cell reactivity was determined by quantitative real-time polymerase chain reaction (qRT-PCR) measuring changes in interferon gamma (IFN-γ) mRNA expression levels. Results: : We found that significantly fewer cancer patients than healthy individuals exhibited specific T-cell recognition of the vaccinia epitope (25% and 69%, respectively). In addition, strength of the T-cell responses against both viral peptides was significantly reduced in cancer patients. Conclusion: : Patients with advanced tumors are less likely to mount a T-cell response against viral epitopes. These findings may have implications for the design of immunotherapeutic interventions against virus-induced diseases, including tumor
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