Nitrification-denitrification in WSP: a mechanism for permanent nitrogen removal in maturation ponds

A pilot-scale primary maturation pond was spiked with 15N-labelled ammonia (15NH4Cl) and 15N labelled nitrite (Na15NO2), in order to improve current understanding of the dynamics of inorganic nitrogen transformations and removal in WSP systems. Stable isotope analysis of δ15N showed that nitrification could be considered as an intermediate step in WSP, which is masked by simultaneous denitrification, under conditions of low algal activity. Molecular microbiology analysis showed that denitrification can be considered a feasible mechanism for permanent nitrogen removal in WSP, which may be supported either by ammonia-oxidising bacteria (AOB) or by methanotrophs, in addition to nitrite-oxidising bacteria (NOB). However, the relative supremacy of the denitrification process over other nitrogen removal mechanisms (e.g., biological uptake) depends upon phytoplanktonic activity

Mining energy consumption as a function of ore grade decline: the case of lead and zinc

Demand for raw materials is increasing exponentially. To satisfy that demand, more minerals need to be mined from the Earth’s crust. As a result, minerals are being exhausted, and ore grades decline. Lower ore grade mines also mean more energy, which in turn entails fossil fuel emissions and more climate change. This paper estimates the specific energy for the beneficiation process of metals lead and zinc as case studies. The evaluation is performed with specialized software, HSC Chemistry which assesses the specific energy for every stage: comminution, flotation, and refining. Different scenarios have been established to simulate the behavior of a mine when it approaches depletion. Preliminary results show that energy consumption for lead would increase by five times when compared to the current situation if ore grades decrease until the level of tailings, while for zinc by almost two

Limit of recovery: How future evolution of ore grades could influence energy consumption and prices for Nickel, Cobalt, and PGMs

The unique properties of certain metals have made them indispensable in manufacturing advanced technological devices and for use in the green economy. However, these metals are not infinite, and the average ore grades in mines have been decreasing in recent decades. This study examines energy consumption as a function of ore grade decline for Nickel, Cobalt, and platinum group metals (PGMs), using simulations created with HSC Chemistry software. A limit of recovery (LOR) for each commodity was also defined. A comparative analysis of the evolution of ore grades, energy costs, and market prices was additionally carried out. According to the simulations, extracting nickel from sulfide ore tailings would be profitable if the price doubled. As for Cobalt, it would only be feasible if the market price increased considerably. For PGMs, even if the ore grade reached the LOR, it would still be profitable to recover them under certain circumstances explored in the paper

Evaluation of the Influence of Different Grades of Reinforcing Steel on the Seismic Performance of Concrete reinforced Frame Structures with Nonlinear Static Analysis

In this investigation, the elasto-plastic behavior and the seismic performance of concrete reinforced frame structures reinforced are evaluated by applying the Pushover method. This evaluation is done on several cases: with high ductility steel (Grade 40), conventional steel (Grade 60) and high strength steel (Grade 75). For the previous, the capacity curve graph obtained from the displacement coefficient method was used to measure the capacity of the structure. In addition, the performance of the structure for different levels of seismic design are evaluated with the resulting values of ductility and rigidity of each case. The results showed that reinforcing a structure with a Grade 40 reinforcing steel increases the energy dissipation capacity, and if reinforced with a Grade 75 reinforcing steel increases the strength capacity in the structure. Finally, the comparative result of the various cases are presented to demonstrate the influence of reinforcing steel on the plastic behavior of concrete reinforced frame structures

Distributed and parallel Ada and the Ada 9X recommendations

Recently, the DoD has sponsored work towards a new version of Ada, intended to support the construction of distributed systems. The revised version, often called Ada 9X, will become the new standard sometimes in the 1990s. It is intended that Ada 9X should provide language features giving limited support for distributed system construction. The requirements for such features are given. Many of the most advanced computer applications involve embedded systems that are comprised of parallel processors or networks of distributed computers. If Ada is to become the widely adopted language envisioned by many, it is essential that suitable compilers and tools be available to facilitate the creation of distributed and parallel Ada programs for these applications. The major languages issues impacting distributed and parallel programming are reviewed, and some principles upon which distributed/parallel language systems should be built are suggested. Based upon these, alternative language concepts for distributed/parallel programming are analyzed

Knowledge Registration Module Design for Enterprise Resilience Enhancement

[EN] The present situation characterized by the coronavirus pandemic has made businesses to be aware about the importance of being resilient to face undesirable impacts like the one caused by this pandemic. One of the constituent capacities of enterprise resilience is the recovery ability to bounce back and restore the operations after disruptions¿ occurrence. This paper is focused on the recovery perspective of enterprise resilience and its enhancement through knowledge registration. This research proposes the design of the Knowledge Registration Module addressed to the register of valuable information at different knowledge level with the main aim to reuse this piece of information to facilitate the recovery process when the same or an unexpected similar disruptive event occurs. Future research lines will be based on applying the knowledge approach to real cases to study the influence of knowledge management in the enhancement of enterprise resilience.This research was supported by the Programme to support the academic career of the faculty of the Universitat Politecnica de Valencia 2019/2020 as part of Project 'Enterprise and Supply Chain Resilience Enhancement' granted to Dr. Raquel Sanchis, who wishes to thank Universita Politecnica delle Marche, particularly the Department of Industrial Engineering and Mathematical Science, for its support, during her stay, to conduct the present research.Sanchis, R.; Marcucci, G.; Alarcón Valero, F.; Poler, R. (2021). Knowledge Registration Module Design for Enterprise Resilience Enhancement. IFAC-PapersOnLine. 54(1):1029-1034. https://doi.org/10.1016/j.ifacol.2021.08.1221029103454

(BIO)Technological Images about Human Self-construction on Spain Context: A Preliminar Study

The study of (bio) technology has a great social significance. As time goes by, the human being is getting more linked to technology. (Bio)technology and society are, therefore, two inseparable fields. Furthermore, this study shows the importance of setting a new context of analysis for (bio)technology. This context will be a polycontexture formed by biological, technical, psychological, sociological and axiological factors. In order to analyze this polycontexture, we consider that one of the most powerful methods is that used by social imageries. Social imageries have been studied by many researchers, but we believe that Juan Luis Pintos has developed the best method. In the end, this paper concludes that the materialization of this polycontexture is the cyborg metaphor. Keywords: Cyborg; Policontexture; Juan Luis Pintos; Socials Imagerie

Ab initio data-analytics study of carbon-dioxide activation on semiconductor oxide surfaces

The excessive emissions of carbon dioxide (CO2) into the atmosphere threaten to shift the CO2 cycle planet-wide and induce unpredictable climate changes. Using artificial intelligence (AI) trained on high-throughput first principles based data for a broad family of oxides, we develop a strategy for a rational design of catalytic materials for converting CO2 to fuels and other useful chemicals. We demonstrate that an electron transfer to the π-antibonding orbital of the adsorbed molecule and the associated bending of the initially linear molecule, previously proposed as the indicator of activation, are insufficient to account for the good catalytic performance of experimentally characterized oxide surfaces. Instead, our AI model identifies the common feature of these surfaces in the binding of a molecular O atom to a surface cation, which results in a strong elongation and therefore weakening of one molecular C-O bond. This finding suggests using the C-O bond elongation as an indicator of CO2 activation. Based on these findings, we propose a set of new promising oxide-based catalysts for CO2 conversion, and a recipe to find more