933 resultados para generated aggregation functions
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BACKGROUND: Clinical practice does not always reflect best practice and evidence, partly because of unconscious acts of omission, information overload, or inaccessible information. Reminders may help clinicians overcome these problems by prompting the doctor to recall information that they already know or would be expected to know and by providing information or guidance in a more accessible and relevant format, at a particularly appropriate time. OBJECTIVES: To evaluate the effects of reminders automatically generated through a computerized system and delivered on paper to healthcare professionals on processes of care (related to healthcare professionals' practice) and outcomes of care (related to patients' health condition). SEARCH METHODS: For this update the EPOC Trials Search Co-ordinator searched the following databases between June 11-19, 2012: The Cochrane Central Register of Controlled Trials (CENTRAL) and Cochrane Library (Economics, Methods, and Health Technology Assessment sections), Issue 6, 2012; MEDLINE, OVID (1946- ), Daily Update, and In-process; EMBASE, Ovid (1947- ); CINAHL, EbscoHost (1980- ); EPOC Specialised Register, Reference Manager, and INSPEC, Engineering Village. The authors reviewed reference lists of related reviews and studies. SELECTION CRITERIA: We included individual or cluster-randomized controlled trials (RCTs) and non-randomized controlled trials (NRCTs) that evaluated the impact of computer-generated reminders delivered on paper to healthcare professionals on processes and/or outcomes of care. DATA COLLECTION AND ANALYSIS: Review authors working in pairs independently screened studies for eligibility and abstracted data. We contacted authors to obtain important missing information for studies that were published within the last 10 years. For each study, we extracted the primary outcome when it was defined or calculated the median effect size across all reported outcomes. We then calculated the median absolute improvement and interquartile range (IQR) in process adherence across included studies using the primary outcome or median outcome as representative outcome. MAIN RESULTS: In the 32 included studies, computer-generated reminders delivered on paper to healthcare professionals achieved moderate improvement in professional practices, with a median improvement of processes of care of 7.0% (IQR: 3.9% to 16.4%). Implementing reminders alone improved care by 11.2% (IQR 6.5% to 19.6%) compared with usual care, while implementing reminders in addition to another intervention improved care by 4.0% only (IQR 3.0% to 6.0%) compared with the other intervention. The quality of evidence for these comparisons was rated as moderate according to the GRADE approach. Two reminder features were associated with larger effect sizes: providing space on the reminder for provider to enter a response (median 13.7% versus 4.3% for no response, P value = 0.01) and providing an explanation of the content or advice on the reminder (median 12.0% versus 4.2% for no explanation, P value = 0.02). Median improvement in processes of care also differed according to the behaviour the reminder targeted: for instance, reminders to vaccinate improved processes of care by 13.1% (IQR 12.2% to 20.7%) compared with other targeted behaviours. In the only study that had sufficient power to detect a clinically significant effect on outcomes of care, reminders were not associated with significant improvements. AUTHORS' CONCLUSIONS: There is moderate quality evidence that computer-generated reminders delivered on paper to healthcare professionals achieve moderate improvement in process of care. Two characteristics emerged as significant predictors of improvement: providing space on the reminder for a response from the clinician and providing an explanation of the reminder's content or advice. The heterogeneity of the reminder interventions included in this review also suggests that reminders can improve care in various settings under various conditions.
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The interaction of the low-lying pseudoscalar mesons with the ground-state baryons in the charm sector is studied within a coupled-channel approach using a t-channel vector-exchange driving force. The amplitudes describing the scattering of the pseudoscalar mesons off the ground-state baryons are obtained by solving the Lippmann-Schwinger equation. We analyze in detail the effects of going beyond the t=0 approximation. Our model predicts the dynamical generation of several open-charm baryon resonances in different isospin and strangeness channels, some of which can be clearly identified with recently observed states.
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Following a model based on the SU(8) symmetry that treats heavy pseudoscalars and heavy vector mesons on an equal footing, as required by heavy quark symmetry, we study the interaction of baryons and mesons in coupled channels within an unitary approach that generates dynamically poles in the scattering T-matrix. We concentrate in the exotic channels with negative charm quantum number for which there is the experimental claim of one state.
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(HadronPhysics2, Grant Agreement No. 227431) under the Seventh Framework Programme of EU
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The soil CO2 emission has high spatial variability because it depends strongly on soil properties. The purpose of this study was to (i) characterize the spatial variability of soil respiration and related properties, (ii) evaluate the accuracy of results of the ordinary kriging method and sequential Gaussian simulation, and (iii) evaluate the uncertainty in predicting the spatial variability of soil CO2 emission and other properties using sequential Gaussian simulations. The study was conducted in a sugarcane area, using a regular sampling grid with 141 points, where soil CO2 emission, soil temperature, air-filled pore space, soil organic matter and soil bulk density were evaluated. All variables showed spatial dependence structure. The soil CO2 emission was positively correlated with organic matter (r = 0.25, p < 0.05) and air-filled pore space (r = 0.27, p < 0.01) and negatively with soil bulk density (r = -0.41, p < 0.01). However, when the estimated spatial values were considered, the air-filled pore space was the variable mainly responsible for the spatial characteristics of soil respiration, with a correlation of 0.26 (p < 0.01). For all variables, individual simulations represented the cumulative distribution functions and variograms better than ordinary kriging and E-type estimates. The greatest uncertainties in predicting soil CO2 emission were associated with areas with the highest estimated values, which produced estimates from 0.18 to 1.85 t CO2 ha-1, according to the different scenarios considered. The knowledge of the uncertainties generated by the different scenarios can be used in inventories of greenhouse gases, to provide conservative estimates of the potential emission of these gases.
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The soil penetration resistance is an important indicator of soil compaction and is strongly influenced by soil water content. The objective of this study was to develop mathematical models to normalize soil penetration resistance (SPR), using a reference value of gravimetric soil water content (U). For this purpose, SPR was determined with an impact penetrometer, in an experiment on a Dystroferric Red Latossol (Rhodic Eutrudox), at six levels of soil compaction, induced by mechanical chiseling and additional compaction by the traffic of a harvester (four, eight, 10, and 20 passes); in addition to a control treatment under no-tillage, without chiseling or additional compaction. To broaden the range of U values, SPR was evaluated in different periods. Undisturbed soil cores were sampled to quantify the soil bulk density (BD). Pedotransfer functions were generated correlating the values of U and BD to the SPR values. By these functions, the SPR was adequately corrected for all U and BD data ranges. The method requires only SPR and U as input variables in the models. However, different pedofunctions are needed according to the soil layer evaluated. After adjusting the pedotransfer functions, the differences in the soil compaction levels among the treatments, previously masked by variations of U, became detectable.
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Modeling concentration-response function became extremely popular in ecotoxicology during the last decade. Indeed, modeling allows determining the total response pattern of a given substance. However, reliable modeling is consuming in term of data, which is in contradiction with the current trend in ecotoxicology, which aims to reduce, for cost and ethical reasons, the number of data produced during an experiment. It is therefore crucial to determine experimental design in a cost-effective manner. In this paper, we propose to use the theory of locally D-optimal designs to determine the set of concentrations to be tested so that the parameters of the concentration-response function can be estimated with high precision. We illustrated this approach by determining the locally D-optimal designs to estimate the toxicity of the herbicide dinoseb on daphnids and algae. The results show that the number of concentrations to be tested is often equal to the number of parameters and often related to the their meaning, i.e. they are located close to the parameters. Furthermore, the results show that the locally D-optimal design often has the minimal number of support points and is not much sensitive to small changes in nominal values of the parameters. In order to reduce the experimental cost and the use of test organisms, especially in case of long-term studies, reliable nominal values may therefore be fixed based on prior knowledge and literature research instead of on preliminary experiments
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Considering that the soil aggregation reflects the interaction of chemical, physical and biological soil factors, the aim of this study was evaluate alterations in aggregation, in an Oxisol under no-tillage (NT) and conventional tillage (CT), since over 20 years, using as reference a native forest soil in natural state. After analysis of the soil profile (cultural profile) in areas under forest management, samples were collected from the layers 0-5, 5-10, 10-20 and 20-40 cm, with six repetitions. These samples were analyzed for the aggregate stability index (ASI), mean weighted diameter (MWD), mean geometric diameter (MGD) in the classes > 8, 8-4, 4-2, 2-1, 1-0.5, 0.5-0.25, and < 0.25 mm, and for physical properties (soil texture, water dispersible clay (WDC), flocculation index (FI) and bulk density (Bd)) and chemical properties (total organic carbon - COT, total nitrogen - N, exchangeable calcium - Ca2+, and pH). The results indicated that more intense soil preparation (M < NT < PC) resulted in a decrease in soil stability, confirmed by all stability indicators analyzed: MWD, MGD, ASI, aggregate class distribution, WDC and FI, indicating the validity of these indicators in aggregation analyses of the studied soil.
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We study steady-state correlation functions of nonlinear stochastic processes driven by external colored noise. We present a methodology that provides explicit expressions of correlation functions approximating simultaneously short- and long-time regimes. The non-Markov nature is reduced to an effective Markovian formulation, and the nonlinearities are treated systematically by means of double expansions in high and low frequencies. We also derive some exact expressions for the coefficients of these expansions for arbitrary noise by means of a generalization of projection-operator techniques.
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The intensity correlation functions C(t) for the colored-gain-noise model of dye lasers are analyzed and compared with those for the loss-noise model. For correlation times ¿ larger than the deterministic relaxation time td, we show with the use of the adiabatic approximation that C(t) values coincide for both models. For small correlation times we use a method that provides explicit expressions of non-Markovian correlation functions, approximating simultaneously short- and long-time behaviors. Comparison with numerical simulations shows excellent results simultaneously for short- and long-time regimes. It is found that, when the correlation time of the noise increases, differences between the gain- and loss-noise models tend to disappear. The decay of C(t) for both models can be described by a time scale that approaches the deterministic relaxation time. However, in contrast with the loss-noise model, a secondary time scale remains for large times for the gain-noise model, which could allow one to distinguish between both models.
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Pedotransfer functions (PTF) were developed to estimate the parameters (α, n, θr and θs) of the van Genuchten model (1980) to describe soil water retention curves. The data came from various sources, mainly from studies conducted by universities in Northeast Brazil, by the Brazilian Agricultural Research Corporation (Embrapa) and by a corporation for the development of the São Francisco and Parnaíba river basins (Codevasf), totaling 786 retention curves, which were divided into two data sets: 85 % for the development of PTFs, and 15 % for testing and validation, considered independent data. Aside from the development of general PTFs for all soils together, specific PTFs were developed for the soil classes Ultisols, Oxisols, Entisols, and Alfisols by multiple regression techniques, using a stepwise procedure (forward and backward) to select the best predictors. Two types of PTFs were developed: the first included all predictors (soil density, proportions of sand, silt, clay, and organic matter), and the second only the proportions of sand, silt and clay. The evaluation of adequacy of the PTFs was based on the correlation coefficient (R) and Willmott index (d). To evaluate the PTF for the moisture content at specific pressure heads, we used the root mean square error (RMSE). The PTF-predicted retention curve is relatively poor, except for the residual water content. The inclusion of organic matter as a PTF predictor improved the prediction of parameter a of van Genuchten. The performance of soil-class-specific PTFs was not better than of the general PTF. Except for the water content of saturated soil estimated by particle size distribution, the tested models for water content prediction at specific pressure heads proved satisfactory. Predictions of water content at pressure heads more negative than -0.6 m, using a PTF considering particle size distribution, are only slightly lower than those obtained by PTFs including bulk density and organic matter content.
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An algorithm for computing correlation filters based on synthetic discriminant functions that can be displayed on current spatial light modulators is presented. The procedure is nondivergent, computationally feasible, and capable of producing multiple solutions, thus overcoming some of the pitfalls of previous methods.
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Intensive land use can lead to a loss of soil physical quality with negative impacts on soil aggregates, resistance to root penetration, porosity, and bulk density. Organic and agroforestry management systems can represent sustainable, well-balanced alternatives in the agroecosystem for promoting a greater input of organic matter than the conventional system. Based on the hypothesis that an increased input of organic matter improves soil physical quality, this study aimed to evaluate the impact of coffee production systems on soil physical properties in two Red-Yellow Oxisols (Latossolos Vermelho-Amarelos) in the region of Caparaó, Espirito Santo, Brazil. On Farm 1, we evaluated the following systems: primary forest (Pf1), organic coffee (Org1) and conventional coffee (Con1). On Farm 2, we evaluated: secondary forest (Sf2), organic coffee intercropped with inga (Org/In2), organic coffee intercropped with leucaena and inga (Org/In/Le2), organic coffee intercropped with cedar (Org/Ced2) and unshaded conventional coffee (Con2). Soil samples were collected under the tree canopy from the 0-10, 10-20 and 20-40 cm soil layers. Under organic and agroforestry coffee management, soil aggregation was higher than under conventional coffee. In the agroforestry system, the degree of soil flocculation was 24 % higher, soil moisture was 80 % higher, and soil resistance to penetration was lower than in soil under conventional coffee management. The macroaggregates in the organic systems, Org/In2, Org/In/Le2, and Org/Ced2 contained, on average, 29.1, 40.1 and 34.7 g kg-1 organic carbon, respectively. These levels are higher than those found in the unshaded conventional system (Con2), with 20.2 g kg-1.
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The construction of a soil after surface coal mining involves heavy machinery traffic during the topographic regeneration of the area, resulting in compaction of the relocated soil layers. This leads to problems with water infiltration and redistribution along the new profile, causing water erosion and consequently hampering the revegetation of the reconstructed soil. The planting of species useful in the process of soil decompaction is a promising strategy for the recovery of the soil structural quality. This study investigated the influence of different perennial grasses on the recovery of reconstructed soil aggregation in a coal mining area of the Companhia Riograndense de Mineração, located in Candiota-RS, which were planted in September/October 2007. The treatments consisted of planting: T1- Cynodon dactylon cv vaquero; T2 - Urochloa brizantha; T3 - Panicum maximun; T4 - Urochloa humidicola; T5 - Hemarthria altissima; T6 - Cynodon dactylon cv tifton 85. Bare reconstructed soil, adjacent to the experimental area, was used as control treatment (T7) and natural soil adjacent to the mining area covered with native vegetation was used as reference area (T8). Disturbed and undisturbed soil samples were collected in October/2009 (layers 0.00-0.05 and 0.10-0.15 m) to determine the percentage of macro- and microaggregates, mean weight diameter (MWD) of aggregates, organic matter content, bulk density, and macro- and microporosity. The lower values of macroaggregates and MWD in the surface than in the subsurface layer of the reconstructed soil resulted from the high degree of compaction caused by the traffic of heavy machinery on the clay material. After 24 months, all experimental grass treatments showed improvements in soil aggregation compared to the bare reconstructed soil (control), mainly in the 0.00-0.05 m layer, particularly in the two Urochloa treatments (T2 and T4) and Hemarthria altissima (T5). However, the great differences between the treatments with grasses and natural soil (reference) indicate that the recovery of the pre-mining soil structure could take decades.
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Management systems involving crop rotation, ground cover species and reduced soil tillage can improve the soil physical and biological properties and reduce degradation. The primary purpose of this study was to assess the effect of various crops grown during the sugarcane fallow period on the production of glomalin and arbuscular mycorrhizal fungi in two Latosols, as well as their influence on soil aggregation. The experiment was conducted on an eutroferric Red Latosol with high-clay texture (680 g clay kg-1) and an acric Red Latosol with clayey texture (440 g kg-1 clay) in Jaboticabal (São Paulo State, Brazil). A randomized block design involving five blocks and four crops [soybean (S), soybean/fallow/soybean (SFS), soybean/millet/soybean (SMS) and soybean/sunn hemp/soybean (SHS)] was used to this end. Soil samples for analysis were collected in June 2011. No significant differences in total glomalin production were detected between the soils after the different crops. However, total external mycelium length was greater in the soils under SMS and SHS. Also, there were differences in easily extractable glomalin, total glomalin and aggregate stability, which were all greater in the eutroferric Red Latosol than in the acric Red Latosol. None of the cover crops planted in the fallow period of sugarcane improved aggregate stability in either Latosol.