Abstract: In the last decade, the highest levels of greenhouse gases (GHG) in the atmosphere have been recorded, with carbon dioxide (CO2) being one of the GHGs that most concerns mankind due to the rate at which it is generated on the planet. Given its long time of permanence in the atmosphere (between 100 to 150 years); this has deployed research in the scientific field focused on the absorption and desorption of CO2 in the atmosphere. This work presents the study of CO2 adsorption employing
materials based on graphene oxide (GO), such as GO foams with different oxidation percentages (3.00%, 5.25%, and 9.00%) in their structure, obtained via an environmentally friendly method. The characterization of CO2 adsorption was carried out in a closed system, within which were placed the GO foams and other CO2 adsorbent materials (zeolite and silica gel). Through a controlled chemical reaction, production of CO2 was conducted to obtain CO2 concentration curves inside the system and calculate from these the efficiency, obtained between 86.28 and 92.20%, yield between 60.10 and 99.50%, and effectiveness of CO2 adsorption of the materials under study. The results obtained suggest that GO foams are a promising material for carbon capture and the future development of a new clean technology, given their highest CO2 adsorption efficiency and yield.

Abstract: There is a recently established correspondence between database tuples as causes for query answers in databases and tuple-based repairs of inconsistent databases with respect to denial constraints. In this work, answer-set programs that specify database repairs are used as a basis for solving computational and reasoning problems around causality in databases, including causal responsibility. Furthermore, causes are introduced also at the attribute level by appealing to an attribute-based repair semantics that uses null values. Corresponding repair-programs are introduced, and used as a basis for computation and reasoning about attribute-level causes. The answer-set programs are extended in order to capture causality under integrity constraints.

Abstract: Mild cognitive impairment ( AQ1 MCI) is often considered an early stage of dementia, with estimated rates of progression to dementia up to 80�90% after approximately 6 years from the initial diagnosis. Diagnosis of cognitive impairment in dementia is typically based on clinical evaluation, neuropsychological assessments, cerebrospinal fluid (CSF) biomarkers, and neuroimaging. The main goal of diagnosing MCI is to determine its cause, particularly whether it is due to Alzheimer�s disease (AD). However, only a limited percentage of the population has access to etiological confirmation, which has led to the emergence of peripheral fluid biomarkers as a diagnostic tool for dementias, including MCI due to AD. Recent advances in biofluid assays have enabled the use of sophisticated statistical models and multimodal machine learning (ML) algorithms for
the diagnosis of MCI based on fluid biomarkers from CSF, peripheral blood, and saliva, among others. This approach has shown promise for identifying specific causes of MCI, including AD. After a PRISMA analysis, 29 articles revealed a trend
towards using multimodal algorithms that incorporate additional biomarkers such as neuroimaging, neuropsychological tests, and genetic information. Particularly, neuroimaging is commonly used in conjunction with fluid biomarkers for both crosssectional and longitudinal studies. Our systematic review suggests that cost-effective longitudinal multimodal monitoring data, representative of diverse cultural populations and utilizing white-box ML algorithms, could be a valuable contribution to the development of diagnostic models for AD due to MCI. Clinical assessment and biomarkers, together with ML techniques, could prove pivotal in improving diagnostic tools for MCI due to AD.

Abstract: We consider two classes of games in which players are the vertices of a directed graph. Initially, nature chooses one player according to some fixed distribution and gives the player a buck. This player passes the buck to one of the player's out-neighbors in the graph. The procedure is repeated indefinitely. In one class of games, each player wants to minimize the asymptotic expected frequency of times that the player receives the buck. In the other class of games, the player wants to maximize it. The PageRank game is a particular case of these maximizing games. We consider deterministic and stochastic versions of the game, depending on how players select the neighbor to which to pass the buck. In both cases, we prove the existence of pure equilibria that do not depend on the initial distribution; this is achieved by showing the existence of a generalized ordinal potential. If the graph on which the game is played admits a Hamiltonian cycle, then this is the outcome of prior-five Nash equilibrium in the minimizing game. For the minimizing game, we then use the price of anarchy and stability to measure fairness of these equilibria.

Abstract: Perchlorate is an oxidative pollutant toxic to most of terrestrial life by promoting denaturation of macromolecules, oxidative stress, and DNA damage. However, several microorganisms, especially hyperhalophiles, are able to tolerate high levels of this compound. Furthermore, relatively high quantities of perchlorate salts were detected on the Martian surface, and due to its strong hygroscopicity and its ability to substantially decrease the freezing point of water, perchlorate is thought to increase the availability of liquid brine water in hyper-arid and cold environments, such as the Martian regolith. Therefore, perchlorate has been proposed as a compound worth studying to better understanding the habitability of the Martian surface. In the present work, to study the molecular mechanisms of perchlorate resistance, a functional metagenomic approach was used, and for that, a small-insert library was constructed with DNA isolated from microorganisms exposed to perchlorate in sediments of a hypersaline pond in the Atacama Desert, Chile (Salar de Maricunga), one of the regions with the highest levels of perchlorate on Earth. The metagenomic library was hosted in Escherichia coli DH10B strain and exposed to sodium perchlorate. This technique allowed the identification of nine perchlorate-resistant clones and their environmental DNA fragments were sequenced. A total of seventeen ORFs were predicted, individually cloned, and nine of them increased perchlorate resistance when expressed in E. coli DH10B cells. These genes encoded hypothetical conserved proteins of unknown functions and proteins similar to other not previously reported to be involved in perchlorate resistance that were related to different cellular processes such as RNA processing, tRNA modification, DNA protection and repair, metabolism, and protein degradation. Furthermore, these genes also conferred resistance to UV-radiation, 4-nitroquinoline-N-oxide (4-NQO) and/or hydrogen peroxide (H2O2), other stress conditions that induce oxidative stress, and damage in proteins and nucleic acids. Therefore, the novel genes identified will help us to better understand the molecular strategies of microorganisms to survive in the presence of perchlorate and may be used in Mars exploration for creating perchlorate-resistance strains interesting for developing Bioregenerative Life Support Systems (BLSS) based on in situ resource utilization (ISRU).

Abstract: Worldwide, urbanization constitutes a major and growing driver of global change and a distinctive feature of the Anthropocene. Thus, urban development paths present opportunities for technological and societal transformations towards energy efficiency and decarbonization, with benefits for both greenhouse gas (GHG) and air pollution mitigation. This requires a better understanding of the intertwined dynamics of urban energy and land use, emissions, demographics, governance, and societal and biophysical processes. In this study, we address several characteristics of urbanization in Santiago (33.5 degrees S, 70.5 degrees W, 500 m a.s.l.), the capital city of Chile. Specifically, we focus on the multiple links between mobility and air quality, describe the evolution of these two aspects over the past 30 years, and review the role scientific knowledge has played in policy-making. We show evidence of how technological measures (e.g., fuel quality, three-way catalytic converters, diesel particle filters) have been successful in decreasing coarse mode aerosol (PM10) concentrations in Santiago despite increasing urbanization (e.g., population, motorization, urban sprawl). However, we also show that such measures will likely be insufficient if behavioral changes do not achieve an increase in the use of public transportation. Our investigation seeks to inform urban development in the Anthropocene, and our results may be useful for other developing countries, particularly in Latin America and the Caribbean where more than 80% of the population is urban.

Abstract: This paper studies the impact of demand-prioritization on Space-Division Multiplexing Elastic Optical Networks (SDM-EON). For this purpose, we solve the static Routing, Modulation Level, Spatial Mode, and Spectrum Assignment (RMLSSA) problem using 34 different explainable demand-prioritization strategies. Although previous works have applied heuristics or meta-heuristics to perform demand-prioritization, they have not focused on identifying the best prioritization strategies, their inner operation, and the implications behind their good performance by thorough profiling and impact analysis. We focus on a comprehensive analysis identifying the best explainable strategies to sort network demands in SDM-EON, considering the physical-layer impairments found in optical communications. Also, we show that simply using the common shortest path routing might lead to higher resource requirements. Extensive simulation results show that up to 8.33% capacity savings can be achieved on average by balanced routing, up to a 16.69% capacity savings can be achieved using the best performing demand-prioritization strategy compared to the worst-performing ones, the most used demand-prioritization strategy in the literature (serving demands with higher bandwidth requirements first) is not the best-performing one but the one sorting based on the path lengths, and using double-criteria strategies to break ties is key for a good performance. These results are relevant showing that a good combination of routing and demand-prioritization heuristics impact significantly on network performance. Additionally, they increase the understanding about the inner workings of good heuristics, a valuable knowledge when network settings forbid using more computationally complex approaches.

Abstract: Modulation of phytohormones homeostasis is one of the proposed mechanisms to explain plant growth promotion induced by beneficial rhizobacteria (PGPR). However, there is still limited knowledge about the molecular signals and pathways underlying these beneficial interactions. Even less is known concerning the interplay between phytohormones in plants inoculated with PGPR. Auxin and ethylene are crucial hormones in the control of plant growth and development, and recent studies report an important and complex crosstalk between them in the regulation of different plant developmental processes. The objective of this work was to study the role of both hormones in the growth promotion of Arabidopsis thaliana plants induced by the well-known PGPR Burkholderia phytofirmans PsJN. For this, the spatiotemporal expression patterns of several genes related to auxin biosynthesis, perception and response and ethylene biosynthesis were studied, finding that most of these genes showed specific transcriptional regulations after inoculation in roots and shoots. PsJN-growth promotion was not observed in Arabidopsis mutants with an impaired ethylene (ein2-1) or auxin (axr15) signaling. Even, PsJN did not promote growth in an ethylene overproducer (eto2), indicating that a fine regulation of both hormones signaling and homeostasis is necessary to induce growth of the aerial and root tissues. Auxin polar transport is also involved in growth promotion, since PsJN did not promote primary root growth in the pin2 mutant or under chemical inhibition of transport in wild type plants. Finally, a key role for ethylene biosynthesis was found in the PsJN-mediated increase in root hair number. These results not only give new insights of PGPR regulation of plant growth but also are also useful to understand key aspects of Arabidopsis growth control.

Abstract: Large datasets containing the purchasing information of thousands of consumers are difficult to analyze because the possible number of different combinations of products is huge. Thus, market baskets analysis to obtain useful information and find interesting pattern of buying behavior could be a daunting task. Based on the maximum entropy principle, we build a probabilistic model that explains the probability of occurrence of market baskets which is equivalent to Ising models. This type of model allows us to understand and to explore the functional interactions among products that make up the market offer. Additionally, the parameters of the model inferred using Boltzmann learning, allow us to suggest that the buying behavior is very similar to the spin-glass physical system. Moreover, we show that the resulting parameters of the model could be useful to describe the hierarchical structure of the system which leads to interesting information about the different market baskets. (C) 2019 Elsevier B.V. All rights reserved.