Temperature and pollution control in flames

We apply control theory for PDEs to flame control. The targeted flame is calculated with complex chemistry. For pollutant control in flames we study both the control of temperature distribution in the flame and flame length at given fuel rate in the flow. Approximate state and sensitivity evaluations as well as mesh adaptation are used to keep the complexity as low as possible and get mesh independent results. In addition, a new recursive semi-deterministic global optimization approach is tested

Effect of Irrigation Management on Water Productivity Indicators of Alfalfa

Introduction Over the last years, long-term average rainfall has experienced a meaningful decrease (from 250 to 206 mm per year) leading to continuous drought in Iran. In addition, population growth and increasing demand for food put more pressure on the limited available water resources. Thus, the quantitative and qualitative improvement of agricultural products become a necessity. There is 640,000 hectares of alfalfa cultivated land, standing for 5.4% of the total cultivated area. One of the most basic obstacles in these farms is the unsuitable model of water consumption management. Previous studies were conducted with the aim of evaluating the mutual effects of different treatments in controlled plots. Nonetheless, there is a need for large-scale investigations to monitor and improve water productivity in agricultural systems. In this research, the focus was on irrigation management and optimizing irrigation timing as a potential solution to enhance water productivity, considering the fixed irrigation cycles and traditional use of available water resources. The study began by assessing the current water productivity in 11 alfalfa farms located across four regions in Zanjan province, ensuring a suitable spatial distribution. Subsequently, the impact of irrigation management, particularly the adjustment of irrigation timing, was evaluated to determine its effectiveness in improving water productivity in these farms. Materials and Methods Eleven alfalfa farms, covering a total area of 28 hectares, were initially selected in the agricultural lands of Zanjan province. The majority of these farms were equipped with sprinkler irrigation systems. From these 11 farms, two specific farms were chosen to implement the proposed methods aimed at improving water productivity. These selected farms served as experimental sites where the irrigation management techniques were applied and evaluated. Improvement solutions were mainly focused on irrigation management. Each farm was divided into two parts; one part with real conditions (farmers' management) and the second one with controlled conditions. In the controlled treatments, irrigation management was implemented through optimization of irrigation time. A nutritional program was also prepared according to the soil quality of the fields and applied in the controlled treatments. In each farm, basic information such as area, physical and chemical properties of soil and water quality were determined. Irrigation information (such as inflow discharge and irrigation schedule) was measured and determined at least three times during the cropping season. Soil moisture were measured before and after irrigation in order to calculate the water application efficiency. The amount of harvested product and production costs were obtained at the end of the cropping season through measurements and interviews with farmers. In this research, the indicators including the volume of irrigation water, the water use efficiency, and the physical and economic efficiency of water have been calculated to analyze the water productivity. Results and Discussion The volume of irrigation water in alfalfa farms was measured as 14250 m3/ha on average (with the lowest and highest consumption values of 9849 and 20576 m3/ha, respectively). The average of irrigation water in farms with surface irrigation systems equals to 17,806 and in farms equipped with sprinkle irrigation systems is about 13,460 m3/ha. While the net water requirement of alfalfa in study area was 7160 to 7290 m3/ha. The minimum and maximum values of water application efficiency were 38.3 and 82%, respectively, with average of 64%. The average of application efficiency in surface and sprinkle irrigation systems were obtained 50 and 67%, respectively. The measured alfalfa yield ranged from a minimum of 6.5 ton/ha to a maximum of 14.1 ton/ha, with an average yield of 10.4 ton/ha. After implementing the revised irrigation program in the controlled plots, the harvested water decreased by an average of 49.5%. It was observed that the irrigation schedule in most farms followed a traditional and estimated pattern, with the depth of irrigation water in the middle of the growing season exceeding the net irrigation requirement. The water use efficiency (WUE) values varied between 0.42 and 1.28 kg/m3, with a minimum value of 0.42 kg/m3 and a maximum value of 1.28 kg/m3. The average WUE was calculated as 0.79 kg/m3. Analyzing the correlation between water consumption and the water use efficiency index revealed a decreasing trend. As the volume of irrigation water increased, the water use efficiency index experienced a decline. Specifically, an increase of 1000 m3 in irrigation water resulted in a decrease of 0.04 kg/m3 in the water use efficiency index. The implementation of the corrected irrigation program and appropriate to the water demand led to an increase of the mentioned index by 72%. Conclusion The lack of proper irrigation programs that consider climatic conditions and the actual needs of the alfalfa plant was identified as a key factor contributing to high water consumption in the farms. Additionally, the inefficient selection and design of the irrigation system led to lower irrigation efficiency than expected. Despite the majority of farms being equipped with sprinkle irrigation systems, the harvested water did not decrease significantly due to inadequate water management practices. These factors ultimately resulted in a decline in both physical and economic productivity indicators in the alfalfa farms. However, the results of the study highlighted that implementing corrected irrigation management, particularly through modifications to the irrigation timing, can lead to a significant decrease in volume of irrigation water and an improvement in both physical and economic productivity

Interacting spinor and scalar fields in Bianchi type-I Universe filled with viscous fluid: exact and numerical solutions

We consider a self-consistent system of spinor and scalar fields within the framework of a Bianchi type I gravitational field filled with viscous fluid in presence of a $\Lambda$ term. Exact self-consistent solutions to the corresponding spinor, scalar and BI gravitational field equations are obtained in terms of $\tau$, where $\tau$ is the volume scale of BI universe. System of equations for $\tau$ and \ve, where \ve is the energy of the viscous fluid, is deduced. Some special cases allowing exact solutions are thoroughly studied.Comment: 18 pages, 6 figure

Fermi Large Area Telescope Constraints on the Gamma-ray Opacity of the Universe

The Extragalactic Background Light (EBL) includes photons with wavelengths from ultraviolet to infrared, which are effective at attenuating gamma rays with energy above ~10 GeV during propagation from sources at cosmological distances. This results in a redshift- and energy-dependent attenuation of the gamma-ray flux of extragalactic sources such as blazars and Gamma-Ray Bursts (GRBs). The Large Area Telescope onboard Fermi detects a sample of gamma-ray blazars with redshift up to z~3, and GRBs with redshift up to z~4.3. Using photons above 10 GeV collected by Fermi over more than one year of observations for these sources, we investigate the effect of gamma-ray flux attenuation by the EBL. We place upper limits on the gamma-ray opacity of the Universe at various energies and redshifts, and compare this with predictions from well-known EBL models. We find that an EBL intensity in the optical-ultraviolet wavelengths as great as predicted by the "baseline" model of Stecker et al. (2006) can be ruled out with high confidence.Comment: 42 pages, 12 figures, accepted version (24 Aug.2010) for publication in ApJ; Contact authors: A. Bouvier, A. Chen, S. Raino, S. Razzaque, A. Reimer, L.C. Reye

Gamma-ray and radio properties of six pulsars detected by the fermi large area telescope

We report the detection of pulsed γ-rays for PSRs J0631+1036, J0659+1414, J0742-2822, J1420-6048, J1509-5850, and J1718-3825 using the Large Area Telescope on board the Fermi Gamma-ray Space Telescope (formerly known as GLAST). Although these six pulsars are diverse in terms of their spin parameters, they share an important feature: their γ-ray light curves are (at least given the current count statistics) single peaked. For two pulsars, there are hints for a double-peaked structure in the light curves. The shapes of the observed light curves of this group of pulsars are discussed in the light of models for which the emission originates from high up in the magnetosphere. The observed phases of the γ-ray light curves are, in general, consistent with those predicted by high-altitude models, although we speculate that the γ-ray emission of PSR J0659+1414, possibly featuring the softest spectrum of all Fermi pulsars coupled with a very low efficiency, arises from relatively low down in the magnetosphere. High-quality radio polarization data are available showing that all but one have a high degree of linear polarization. This allows us to place some constraints on the viewing geometry and aids the comparison of the γ-ray light curves with high-energy beam models

Validation of a novel multivariate method of defining HIV-associated cognitive impairment

Background. The optimum method of defining cognitive impairment in virally suppressed people living with HIV is unknown. We evaluated the relationships between cognitive impairment, including using a novel multivariate method (NMM), patient– reported outcome measures (PROMs), and neuroimaging markers of brain structure across 3 cohorts. Methods. Differences in the prevalence of cognitive impairment, PROMs, and neuroimaging data from the COBRA, CHARTER, and POPPY cohorts (total n = 908) were determined between HIV-positive participants with and without cognitive impairment defined using the HIV-associated neurocognitive disorders (HAND), global deficit score (GDS), and NMM criteria. Results. The prevalence of cognitive impairment varied by up to 27% between methods used to define impairment (eg, 48% for HAND vs 21% for NMM in the CHARTER study). Associations between objective cognitive impairment and subjective cognitive complaints generally were weak. Physical and mental health summary scores (SF-36) were lowest for NMM-defined impairment (P < .05). There were no differences in brain volumes or cortical thickness between participants with and without cognitive impairment defined using the HAND and GDS measures. In contrast, those identified with cognitive impairment by the NMM had reduced mean cortical thickness in both hemispheres (P < .05), as well as smaller brain volumes (P < .01). The associations with measures of white matter microstructure and brain-predicted age generally were weaker. Conclusion. Different methods of defining cognitive impairment identify different people with varying symptomatology and measures of brain injury. Overall, NMM-defined impairment was associated with most neuroimaging abnormalities and poorer selfreported health status. This may be due to the statistical advantage of using a multivariate approac

Depression, lifestyle factors and cognitive function in people living with HIV and comparable HIV-negative controls

We investigated whether differences in cognitive performance between people living with HIV (PLWH) and comparable HIV-negative people were mediated or moderated by depressive symptoms and lifestyle factors. METHODS: A cross-sectional study of 637 'older' PLWH aged ≥ 50 years, 340 'younger' PLWH aged < 50 years and 276 demographically matched HIV-negative controls aged ≥ 50 years enrolled in the Pharmacokinetic and Clinical Observations in People over Fifty (POPPY) study was performed. Cognitive function was assessed using a computerized battery (CogState). Scores were standardized into Z-scores [mean = 0; standard deviation (SD) = 1] and averaged to obtain a global Z-score. Depressive symptoms were evaluated via the Patient Health Questionnaire (PHQ-9). Differences between the three groups and the effects of depression, sociodemographic factors and lifestyle factors on cognitive performance were evaluated using median regression. All analyses accounted for age, gender, ethnicity and level of education. RESULTS: After adjustment for sociodemographic factors, older and younger PLWH had poorer overall cognitive scores than older HIV-negative controls (P < 0.001 and P = 0.006, respectively). Moderate or severe depressive symptoms were more prevalent in both older (27%; P < 0.001) and younger (21%; P < 0.001) PLWH compared with controls (8%). Depressive symptoms (P < 0.001) and use of hashish (P = 0.01) were associated with lower cognitive function; alcohol consumption (P = 0.02) was associated with better cognitive scores. After further adjustment for these factors, the difference between older PLWH and HIV-negative controls was no longer significant (P = 0.08), while that between younger PLWH and older HIV-negative controls remained significant (P = 0.01). CONCLUSIONS: Poorer cognitive performances in PLWH compared with HIV-negative individuals were, in part, mediated by the greater prevalence of depressive symptoms and recreational drug use reported by PLWH

Investigating large-scale brain dynamics using field potential recordings: Analysis and interpretation

New technologies to record electrical activity from the brain on a massive scale offer tremendous opportunities for discovery. Electrical measurements of large-scale brain dynamics, termed field potentials, are especially important to understanding and treating the human brain. Here, our goal is to provide best practices on how field potential recordings (EEG, MEG, ECoG and LFP) can be analyzed to identify large-scale brain dynamics, and to highlight critical issues and limitations of interpretation in current work. We focus our discussion of analyses around the broad themes of activation, correlation, communication and coding. We provide best-practice recommendations for the analyses and interpretations using a forward model and an inverse model. The forward model describes how field potentials are generated by the activity of populations of neurons. The inverse model describes how to infer the activity of populations of neurons from field potential recordings. A recurring theme is the challenge of understanding how field potentials reflect neuronal population activity given the complexity of the underlying brain systems

Harnessing the NEON data revolution to advance open environmental science with a diverse and data-capable community

It is a critical time to reflect on the National Ecological Observatory Network (NEON) science to date as well as envision what research can be done right now with NEON (and other) data and what training is needed to enable a diverse user community. NEON became fully operational in May 2019 and has pivoted from planning and construction to operation and maintenance. In this overview, the history of and foundational thinking around NEON are discussed. A framework of open science is described with a discussion of how NEON can be situated as part of a larger data constellation—across existing networks and different suites of ecological measurements and sensors. Next, a synthesis of early NEON science, based on >100 existing publications, funded proposal efforts, and emergent science at the very first NEON Science Summit (hosted by Earth Lab at the University of Colorado Boulder in October 2019) is provided. Key questions that the ecology community will address with NEON data in the next 10 yr are outlined, from understanding drivers of biodiversity across spatial and temporal scales to defining complex feedback mechanisms in human–environmental systems. Last, the essential elements needed to engage and support a diverse and inclusive NEON user community are highlighted: training resources and tools that are openly available, funding for broad community engagement initiatives, and a mechanism to share and advertise those opportunities. NEON users require both the skills to work with NEON data and the ecological or environmental science domain knowledge to understand and interpret them. This paper synthesizes early directions in the community’s use of NEON data, and opportunities for the next 10 yr of NEON operations in emergent science themes, open science best practices, education and training, and community building