Asymptotically flat boundary conditions for the U(1)3U(1)^3 model for Euclidean Quantum Gravity

A generally covariant $U(1)^3$ gauge theory describing the $G_N \to 0$ limit of Euclidean general relativity is an interesting test laboratory for general relativity, specially because the algebra of the Hamiltonian and diffeomorphism constraints of this limit is isomorphic to the algebra of the corresponding constraints in general relativity. In the present work, we study boundary conditions and asymptotic symmetries of the $U(1)^3$ model and show that while asymptotic spacetime translations admit well-defined generators, boosts and rotations do not. Comparing with Euclidean general relativity, one finds that exactly the non-Abelian part of the $SU(2)$ Gauss constraint which is absent in the $U(1)^3$ model plays a crucial role in obtaining boost and rotation generators.Comment: 11 page

Production of Arachidonic Acid and Eicosapentaenoic Acid by Mortierella alpina CBS 528.72 on Date Waste

Arahidonska (ARA) i eikozapentaenska (EPA) kiselina, koje proizvodi plijesan Mortierella alpina, važne su za zdravlje ljudi. Uvjeti fermentacije mogu utjecati na sastav masnih kiselina u dobivenom ulju. Kao podloga za fermentaciju uglavnom se koristi obnovljivi i jeftini agro-industrijski otpad. Svrha je ovoga rada bila ispitati istodobnu proizvodnju tih dviju kiselina fermentacijom na čvrstoj podlozi s pomoću plijesni Mortierella alpina CBS 528.72. Otpad od datulja odabran je kao izvor ugljika, a sojina sačma kao izvor dušika. Primjenom Plackett-Burmanovog dizajna procijenjen je utjecaj 11 varijabli na proizvodnju ARA i EPA. Analizom dobivenih rezultata utvrđeno je da su glavne varijable, koje bitno utječu na proizvodnju, starost populacije nacijepljene plijesni, te dodatak lanenog ulja i izvora dušika. Te su tri varijable zatim ispitane pomoću centralno složenog dizajna za optimiranje proizvodnje obiju kiselina. Naposljetku, proveden je test radi potvrde predviđenih optimalnih uvjeta pomoću eksperimentalnih rezultata. Pokazalo se da je moguće optimirati proizvodnju ARA i EPA na otpadu od datulja s pomoću plijesni M. alpina CBS 528.72 prilagođavanjem varijabli procesa fermentacije na čvrstoj podlozi.Arachidonic acid (ARA) and eicosapentaenoic acid (EPA) are important for human health and are produced by the fungus Mortierella alpina. Fermentation conditions may affect fatty acid profile of produced oil. Substrates in solid-state fermentation are usually renewable and low-cost agro-industrial waste. The aim of this research is to study simultaneous production of ARA and EPA by M. alpina CBS 528.72 in solid-state fermentation. Date waste and soybean meal served as carbon and nitrogen sources, respectively. Plackett-Burman design was used to evaluate the impact of eleven process variables on ARA and EPA production. Analysis of the results showed that the main variables with significant impact on production include seed age, and supplementation of linseed oil and nitrogen. These three variables were then studied in a central composite design for the optimization of production of both fatty acids. Finally, reconfirmation test was conducted to obtain experimental results from predicted optimum conditions. This report showed that simultaneous optimization of the production of ARA and EPA by M. alpina CBS 528.72 on date waste can be achieved by modification of process variables in solid-state fermentation

Agricultural mechanization, a key to food security in developing countries: strategy formulating for Iran

Abstract Background Mechanization is a multi-dimensional concept and widely used in agriculture. There is, however, a major difference between the application of mechanization in developed and developing countries The developing countries tend to design their own strategies in food security given the challenges they face in all aspects of their economy including feeding a growing population, reducing poverty, protecting the environment, managing the effects of climate change and fighting malnutrition all which may further contribute to a reduction in economic growth and political instability. The goal of the strategies, with the help of appropriate technologies, is to lead to a sustainable agricultural development and, ultimately, food security. The policy making in each country should be based on its own conditions. This article uses Iran as an example of a developing country and considers the country’s specific climate as well as political and economic conditions to present development-oriented policies for achieving sustainable food security based on agricultural mechanization that may be adaptable to other developing countries. The main objective of this paper is to identify and provide guidelines to the current and future challenges of Iran’s food security, and it argues that for any strategy to succeed in producing a sustainable agricultural production, it will need a proper analysis and a formulation of an appropriate mechanization plan. Methods To achieve the objective of a self-sustaining agricultural mechanization strategy, a SWOT analysis technique was used to identify the strengths, weaknesses, opportunities and threats and help us provide a framework by which policies can be defined. The framework includes internal and external factors that affect the development of agricultural mechanization and seek to provide ideas for agricultural development with the help of mechanization. These factors were then prioritized using the Hierarchical Analysis Method, and based on the obtained results, the final strategies were extracted and prioritized by the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), a multi-criteria decision analysis method. Results and conclusion According to the results, weaknesses and threats were the most important factors. Environmental threats, especially water shortages, economic problems as well as availability of the mechanization fleet and compatibility of the equipment within the country’s agricultural system were identified as the most important factors affecting the agricultural development. In order to achieve sustainable food security, with regards to the identified factors the necessary recommendations and Governmental-support policies in the agricultural sector were presented: 1. reforming the country’s planting pattern according to the climatic conditions considering the relative advantage of agricultural production, 2. modernizing the mechanization fleet; 3. investing in research and development of agriculture and modern knowledge; the production and import of agricultural machinery and modern technologies according to their suitability with the country's conditions and future needs of the country; strengthening of the supply chain and maintenance services

Applying multi-criteria decision making method to analyze stability and mechanization patterns in small farms

This study aimed to analyze stability and mechanization patterns in small-scale farms in Khuzestan province, Iran, and their implications for productivity and profitability. The objectives were to assess the sustainability level of farmers, determine the stability level of the farms, identify the optimal mechanization pattern, and evaluate the implications of moving towards sustainability. To achieve these objectives, the research employed multi-criteria decision making (MCDM) methods, which allowed for the assessment of multiple criteria and the evaluation of various alternatives. The study focused on farmers and operators managing small farms below 5 ha in Karoon and Behbahan counties, with a sample size of 48 farmers. The findings of the study indicated that the majority of farmers (75.7%) fell into the “very little” sustainability group, indicating significant challenges in terms of stability and mechanization. Only a small percentage of farmers (0.5%) were classified as having a “high” sustainability level. The average stability level among the sample was 18.09, with a range from 7.98 to 79.89. The study also identified the optimal mechanization pattern for the study region, which required an increase in the availability of necessary tools. The ideal planning model suggested that moving towards sustainability would involve specializing in specific products that align with the region's facilities. This specialization would reduce tool variety and eliminate some tools from the current model. Additionally, the study found that implementing the optimal mechanization pattern would result in a gross return of 4.2 billion Rials, indicating increased productivity and profitability. In conclusion, small-scale farms in Khuzestan province face various obstacles that affect their productivity and profitability. By analyzing stability and mechanization patterns using MCDM methods, this study highlighted the need for increased sustainability and identified the optimal mechanization pattern for the region. The implications of moving towards sustainability include reduced tool variety, specialization in specific products, and increased gross returns. These findings can guide policymakers and farmers in improving the productivity and profitability of small-scale farms

Determination of nickel and chromium content in serum, emulsion, skin and viscera of Iranian tuna fish

1409-1414Contamination of heavy metals, namely, nickel and chromium was evaluated in serum, emulsion and tissues of Euthynnus affinis and Thunnus tonggol collected from Persian Gulf. The concentration of metals was determined by Graphite Furnace Atomic Absorption Spectrometry (GFAAS). Tissues analysis revealed that viscera in Euthynnus affinis accumulated the highest levels of Ni and Cr. Nickel concentration in the non-edible parts of the examined fish (viscera in both fish species and skin in Thunnus tonggol) were higher than the established values by World Health Organization (WHO), whilst concentration of chromium for all samples were higher than maximum permissible limits determined by the WHO, except for serum of Thunnus tonggol

Production of Arachidonic Acid and Eicosapentaenoic Acid by Mortierella alpina CBS 528.72 on Date Waste

Arachidonic acid (ARA) and eicosapentaenoic acid (EPA) are important for human health and are produced by the fungus Mortierella alpina. Fermentation conditions may affect fatty acid profile of produced oil. Substrates in solid-state fermentation are usually renewable and low-cost agro-industrial waste. The aim of this research is to study simultaneous production of ARA and EPA by M. alpina CBS 528.72 in solid-state fermentation. Date waste and soybean meal served as carbon and nitrogen sources, respectively. Plackett-Burman design was used to evaluate the impact of eleven process variables on ARA and EPA production. Analysis of the results showed that the main variables with significant impact on production include seed age, and supplementation of linseed oil and nitrogen. These three variables were then studied in a central composite design for the optimization of production of both fatty acids. Finally, reconfirmation test was conducted to obtain experimental results from predicted optimum conditions. This report showed that simultaneous optimization of the production of ARA and EPA by M. alpina CBS 528.72 on date waste can be achieved by modification of process variables in solid-state fermentation

Stability, physicochemical, rheological and sensory properties of beverage containing encapsulated jujube extract with sodium alginate stabilized by sodium alginate and Gellan gum

Functional beverages are expanding in the world and since fruits are valuable food sources and are known as sources of antioxidant and phenolic compounds, their extracts and juices in these beverages can be used in different forms. The aim was to protect jujube extract by encapsulating it in the beads to enrich the beverage with phenolic compounds. On the other, gellan and alginate are known as stabilizers and suspend the particles in beverages and make fluid gel and trap particles in their structures. Gellan and sodium alginate were used to suspend alginate beads in antioxidant beverages. Four groups of samples were prepared with 0.15% and 0.3% sodium alginate concentrations and 0.05% and 0.31% gellan concentrations. The results showed that bead suspension were observed appropriately in C (0.3% alginate, 0.05% gellan gum) and D treatments (0.3% alginate, 1% gellan gum). The best sensory properties (overall acceptability= 4) were observed in C treatment (0.3% alginate, 0.05% gellan gum). On the first day of the assay, the highest pH was related to D treatment (3.83) and the lowest was related B treatment (3.57). Increasing of gellan and alginate into the beverage changed the viscosity behavior which led to show highest viscosity (417 cp in D beverage, 30 rpm) and inhibited the beads sedimentation (C and D beverages)

The effects of policy fluctuations on energy indices in Iran’s agriculture sector

Energy is one of the primary factors in production and simultaneously one of the principal commodities. In recent years, the significance of strategic planning in optimizing energy consumption has increased. By examining energy indicators and the impact of various economic policies on them, it is possible to attain a comprehension of past conditions and a picture of the future in different energy sectors. The data spanning from 1947 to 2019 were used through a Non-Linear Autoregressive Distributed Lag (NARDL) for analyzing non-linear effects of policy instability on energy indicators in the agricultural sector of Iran. The results indicated an association among the variables, wherein positive fluctuations in agricultural value-added, with a coefficient of 0.13, and conversely negative fluctuations with a coefficient of -0.09, significantly affected long-term energy consumption. It is notable that the second coefficient lacked statistical significance. Additionally, the asymmetrical effects of other variables on energy consumption and productivity in agricultural practices was confirmed

Application of machine learning to predict of energy use efficiency and damage assessment of almond and walnut production

A study was conducted in Shahrekord city, Iran, focusing on improving the production of almond and walnut crops on rural agricultural lands. The gardeners selected for the study shared similar characteristics and production histories. One of the major challenges in producing these crops was the manual harvesting process, which required a significant amount of human labor in the region. To collect data, questionnaires and face-to-face interviews were conducted. The study used machine learning models, specifically artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) models, to predict energy use efficiency and environmental impacts in almond and walnut production. Among the models used, the ANFIS model with a three-level topology was found to be the most accurate in predicting output energy generation and environmental impacts in both almond and walnut production. The R2 values for the testing stage ranged from 0.969 to 0.996 for output energy generation and 0.994 to 0.997 for environmental impacts. The study demonstrated the effectiveness of using machine learning models like ANN and ANFIS in predicting energy use efficiency and environmental impacts in almond and walnut production, which can aid in planning and managing these crops more sustainably and efficiently in the future