Tameness and Artinianness of Graded Generalized Local Cohomology Modules

Let $R=\bigoplus_{n\geq 0}R_n$, \fa\supseteq \bigoplus_{n> 0}R_n and $M$ and $N$ be a standard graded ring, an ideal of $R$ and two finitely generated graded $R$-modules, respectively. This paper studies the homogeneous components of graded generalized local cohomology modules. First of all, we show that for all $i\geq 0$, H^i_{\fa}(M, N)_n, the $n$-th graded component of the $i$-th generalized local cohomology module of $M$ and $N$ with respect to \fa, vanishes for all $n\gg 0$. Furthermore, some sufficient conditions are proposed to satisfy the equality \sup\{\en(H^i_{\fa}(M, N))| i\geq 0\}= \sup\{\en(H^i_{R_+}(M, N))| i\geq 0\}. Some sufficient conditions are also proposed for tameness of H^i_{\fa}(M, N) such that i= f_{\fa}^{R_+}(M, N) or i= \cd_{\fa}(M, N), where f_{\fa}^{R_+}(M, N) and \cd_{\fa}(M, N) denote the $R_+$-finiteness dimension and the cohomological dimension of $M$ and $N$ with respect to \fa, respectively. We finally consider the Artinian property of some submodules and quotient modules of H^j_{\fa}(M, N), where $j$ is the first or last non-minimax level of H^i_{\fa}(M, N).Comment: 18pages, with some revisions and correction

CO2 Utilization via Integration of an Industrial Post-Combustion Capture Process with a Urea Plant: Process Modelling and Sensitivity Analysis

Carbon capture and utilization (CCU) may offer a response to climate change mitigation from major industrial emitters. CCU can turn waste CO(2)emissions into valuable products such as chemicals and fuels. Consequently, attention has been paid to petrochemical industries as one of the best options for CCU. The largest industrial CO(2)removal monoethanol amine-based plant in Iran has been simulated with the aid of a chemical process simulator, i.e., Aspen HYSYS(R)v.10. The thermodynamic properties are calculated with the acid gas property package models, which are available in Aspen HYSYS(R). The results of simulation are validated by the actual data provided by Kermanshah Petrochemical Industries Co. Results show that there is a good agreement between simulated results and real performance of the plant under different operational conditions. The main parameters such as capture efficiency in percent, the heat consumption in MJ/kg CO2 removed, and the working capacity of the plant are calculated as a function of inlet pressure and temperature of absorber column. The best case occurred at the approximate temperature of 40 to 42 degrees C and atmospheric pressure with CO2 removal of 80.8 to 81.2%; working capacity of 0.232 to 0.233; and heat consumption of 4.78 MJ/kg CO2

Techno-economic assessment and optimization of a solar-assisted industrial post-combustion CO2 capture and utilization plant

This paper studies the techno-economic feasibility of the solar-assisted regeneration process of the largest industrial CO2 removal monoethanolamine-based plant in Iran. The plant incorporating parabolic troughs is modelled using System Advisor Model software and the weather data are derived from the European Commission''s Photovoltaic Geographical Information System. Sensitivity analyses are realized to evaluate the effect of important parameters, i.e., the solar multiple and the hours of storage, and to reveal the optimum case. The studied impacts are linked to the overall net energy generation and the levelized cost of heat (LCOH). The optimum case is found to have a solar multiple of 3.1 and 18-hours of storage, resulting in a solar share of 0.7 and a LCOH of 3.85 (¢/kWh). When compared to the base case (solar multiple of 2 and 6 h of storage), the optimum solution results in a similar LCOH but it achieves the generation of an additional 16, 112 MWhth annually. The thermal energy supplied by the solar system leads to an annual reduction in the natural gas consumption of approximately 3.8 million m3 that results in a CO2 emission reduction of 7.1 kton. © 2021 The Author

Comprehensive thermodynamic and operational optimization of a solar-assisted LiBr/water absorption refrigeration system

Absorption cooling systems have been investigated for many years due to their ability to use low-grade heat instead of electricity as the energy source. The aim of this work is to advance the performance of a single-effect Lithium bromide/water absorption cooling system. Taking the generator and evaporator temperatures as variables, the system is optimized to maximize exergetic and energetic efficiencies at different operational conditions using a multi-objective–multi-variable Genetic Algorithm. The Group Method of Data Handling neural network approach is adopted to derive correlations between the design variables and operational parameters. Finally, the system is coupled to evacuated tube solar collectors and compared to a similar system. The results reflect a maximum improvement in energetic and exergetic efficiencies of about 9.1% and 3.0%, respectively. This translates into savings of 187 dollars for every square meter of solar collector at present time. This improvement is achieved by decreasing the mean temperature of the generator by 6.2 °C and increasing the mean temperature of the evaporator by 1.6 °C. In the case of applying low-grade heat such as solar energy, it brings about both an improvement in the thermodynamic performances and a reduction in the generator temperature

Pro-inflammatory responses to PM0.25_{0.25} from airport and urban traffic emissions

Airport particulate matter (PM) emissions are the known source of air pollution in the proximity of an airport. Often large airports are located near metropolises, and airport emissions may have a potentially considerable impact on public health in the surrounding urban areas. However, little is known about the sources that are relevant to air quality and health in the vicinity of airports. Therefore, the effect of the chemical composition of airport-related PM on adverse health risks was investigated in comparison to urban traffic emissions. PM0.25 were collected at the Los Angeles International Airport (LAX) and at a central Los Angeles site (USC campus), along with PM2.5 collected directly from turbine and diesel engines. The chemical composition, oxidative potential (OP) of particles as well as the reactive oxygen species (ROS) activity, inflammatory potential (IL 6, IL 8 and TNF–α) release and cytotoxicity on human bronchial epithelial (16HBE) cells were assessed. Chemical composition measurements confirmed that aircraft emissions were the major source to LAX PM0.25, while the sources of USC samples were more complex, including traffic emissions, suspended road and soil dust, and secondary sulfate. The traffic-related transition metals (Fe and Cu) in LAX and USC samples mainly affected OP values of particles, while multiple factors such as compositions, size distribution and internalized amount of particles contributed to the promotion of ROS generation in 16HBE cells during 4 h exposure. Internalized particles in cells might also play an important role in activating inflammatory responses during 20 h recovery period, with LAX particles being more potent. Our results demonstrate considerable toxicity of airport-related particles, even at low exposure concentrations, which suggests that airport emission as source of PM0.25 may also contribute to the adverse effects on public health attributable to PM

L-systems in Geometric Modeling

We show that parametric context-sensitive L-systems with affine geometry interpretation provide a succinct description of some of the most fundamental algorithms of geometric modeling of curves. Examples include the Lane-Riesenfeld algorithm for generating B-splines, the de Casteljau algorithm for generating Bezier curves, and their extensions to rational curves. Our results generalize the previously reported geometric-modeling applications of L-systems, which were limited to subdivision curves.Comment: In Proceedings DCFS 2010, arXiv:1008.127

Applied Artificial Intelligence and Machine Learning for Video Coding and Streaming : Editorial

The papers in this special section focus on applied artificial inteligence and machine learning for video coding and media streaming.publishedVersionNon peer reviewe

Synchronizing Objectives for Markov Decision Processes

We introduce synchronizing objectives for Markov decision processes (MDP). Intuitively, a synchronizing objective requires that eventually, at every step there is a state which concentrates almost all the probability mass. In particular, it implies that the probabilistic system behaves in the long run like a deterministic system: eventually, the current state of the MDP can be identified with almost certainty. We study the problem of deciding the existence of a strategy to enforce a synchronizing objective in MDPs. We show that the problem is decidable for general strategies, as well as for blind strategies where the player cannot observe the current state of the MDP. We also show that pure strategies are sufficient, but memory may be necessary.Comment: In Proceedings iWIGP 2011, arXiv:1102.374

Modeling sustainability : Population, inequality, consumption, and bidirectional coupling of the Earth and human systems

Over the last two centuries, the impact of the Human System has grown dramatically, becoming strongly dominant within the Earth System in many different ways. Consumption, inequality, and population have increased extremely fast, especially since about 1950, threatening to overwhelm the many critical functions and ecosystems of the Earth System. Changes in the Earth System, in turn, have important feedback effects on the Human System, with costly and potentially serious consequences. However, current models do not incorporate these critical feedbacks. We argue that in order to understand the dynamics of either system, Earth SystemModels must be coupled with Human SystemModels through bidirectional couplings representing the positive, negative, and delayed feedbacks that exist in the real systems. In particular, key Human System variables, such as demographics, inequality, economic growth, and migration, are not coupled with the Earth System but are instead driven by exogenous estimates, such as United Nations population projections.This makes current models likely to miss important feedbacks in the real Earth-Human system, especially those that may result in unexpected or counterintuitive outcomes, and thus requiring different policy interventions from current models.The importance and imminence of sustainability challenges, the dominant role of the Human System in the Earth System, and the essential roles the Earth System plays for the Human System, all call for collaboration of natural scientists, social scientists, and engineers in multidisciplinary research and modeling to develop coupled Earth-Human system models for devising effective science-based policies and measures to benefit current and future generations