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We analize the Mexican peso-US dollar exchange parity the volatility using three models in order to evaluate the exchange rate risk performance and the these models capability of modeling such risk. The period June 21st, 2017 to June 21st, 2022 is marked by singular events that pressed this exchange rate parity, making it of great interest to study the tools that can be used to measure this uncertainty besides the study of the exchange rate uncertainty itself. The arrival of a leftwing politician to the presidency was an unprecedented event. At the beginning of 2020 the price war in the oil market and the emergence of the COVID-19 pandemic had important effects in the world economy. Finally, the war in Ukraine added pressures to the international trade of raw materials, inducing an inflationary episode with bad expectations about the economic performance around the world. The exchange rate scenarios posed by the aforesaid events provide us with a natural context to test which of the posited volatility models offers a better fit. Unanimously, the results under the three models suggest that during the first year of the President López Obrador period the exchange rate uncertainty was reduced compared to previous levels, returning again to those minor levels after the forced closure of economic activities due to the emergence of COVID-19, even though the exchange fluctuation band has been slightly higher than before the pandemic and the war on East Europe. [ABSTRACT FROM AUTHOR]

We show that the Hausdorff dimension of any proper Teichmüller horocycle flow orbit closure on any irreducible |$\textrm {SL}{(2,\textbf {R})}$| -invariant subvariety of Abelian or quadratic differentials is bounded away from the dimension of the subvariety in terms of the polynomial mixing rate of the Teichmüller horocycle flow on the subvariety. The proof is based on abstract methods for measurable flows adapted from work of Bourgain and Katz on sparse ergodic theorems. [ABSTRACT FROM AUTHOR]

Through a quantile regression, it is shown that from 1990 to 2018 the impacts of business investments, dollar debt and the exchange rate are differentiated for the various levels of exchange earnings of a group of Mexican companies. The value of the dollar and foreign currency debt negatively impact earnings, and investments in property, plant and equipment, and net working capital have a greater influence on such earnings. The relationship between foreign exchange earnings and investments in recent, intangible assets and net working capital has not been previously studied. These results can be useful for investment planning as a means of managing the risk of foreign exchange losses. [ABSTRACT FROM AUTHOR]

Building on reinvigorated scholarly debates on the concept of value, this paper examines forms of valuation that coexist with and challenge those typically associated with capitalist natures. Based on archival, ethnographic, and interview data, we analyze a historical case of the Venezuelan Society of Speleology (SVE) that since 1967 has been exploring and mapping the country's caves. Its results are published in a national cave survey that the group manages. Not only is each cave entry the representation and materialization of the group's volunteer efforts. Each is also part of a relational regime of valuation by which all caves are worth mapping. The survey's classificatory logic not only transforms underground value, it also acts as boundary object bringing together diverse actors and promoting the SVE's collective ethos, at least in theory, of valuing all members. The survey is the fulcrum of distinct regimes of valuation, wherein value and values are two sides of the same coin. The spaces where these value/s are enacted matters, suggesting the critical contributions that geographers can make in understanding the spatial qualities that contribute to—or hinder—the materialization of certain regimes of valuation over others. [ABSTRACT FROM AUTHOR]

This paper addresses the use of objects within mealtime practices of 12-14 months old children in two day-care centers in Brasilia. It aims at understanding the qualities of the triadic interactions of teacher-object-child. A research was conducted in order to favor such interactions during everyday school routine. Empirical data collection consisted in non-participant observation, video recording of mealtime episodes, written notes and photos. Microgenetic analyses focused on actions, dialogues and metacommunicative aspects which allowed the identification of the emergence of triadic relationships during mealtime. Special emphasis was drawn on a variety of engagements with food and eating utensils during the educational settings. Results suggest that objects, engagements, and ways of communication in the triadic relationships are related with actions, appropriation and understanding of the use of objects, mealtime actions and cultural practices. Conclusions reveal that important aspects related to meaning making during mealtime in early childhood education and show how the triadic engagement allow the emergence of canonical actions, and the role of the caregiver's leadership, as well as, the variegatedsemiotical dynamics into the triadic relations. [ABSTRACT FROM AUTHOR]

This paper shows the analysis carried out to determine which macroeconomic risk factors affect the delinquency of the mortgage portfolio securitized in Mexico. Hypothetical risk factors were constructed based on the review of relevant literature and the analysis of principal components of a set of economic variables. Using econometric tools, the relationships between delinquencies and hypothetical risk factors were analyzed, as well as between the former and the economic variables. Evidence shows that economic openness and international money market conditions are risk factors that can affect delinquency. Evidence was also found that the postulated variables are relevant to explain the delinquency of the portfolio studied. [ABSTRACT FROM AUTHOR]

Chile's General Law of Education (LGE) states that one of the purposes of education is the spiritual development of all its schooled population. In turn, other legal documents claim that the Institutional Educational Project should define how schools are to approach that statement. This article analyses the frequency of keywords, based on a theoretical framework and revision of the Vision and Mission sections of the Educational Projects of 20 schools from Valparaíso, in order to show how this statement is approached and what those approaches imply. [ABSTRACT FROM AUTHOR]

Given integers g,n ≥ 0 satisfying 2−2g−n , let Mg,n be the moduli space of connected, oriented, complete, finite area hyperbolic surfaces of genus g with n cusps. We study the global behavior of the Mirzakhani function B : Mg,n → R≥0 which assigns to X ∈ Mg,n the Thurston measure of the set of measured geodesic laminations on X of hyperbolic length ≤ 1. We improve bounds of Mirzakhani describing the behavior of this function near the cusp of Mg,n and deduce that B is square-integrable with respect to the Weil–Petersson volume form. We relate this knowledge of B to statistics of counting problems for simple closed hyperbolic geodesics. [ABSTRACT FROM AUTHOR]

Throughout the process of transformation since 1999 known as the Bolivarian Revolution, harsh class and food system contradictions have unfolded in Venezuela, pitting against one another the forces of the pervasive consumer culture favoring imported foods, the input-intensive Green Revolution agricultural model that represents a state-led push toward food self-sufficiency, and an emerging agroecological paradigm pushed forward by grassroots movements who have seized political openings through the largely supportive policy environment. The Bolivarian University of Venezuela, itself a product of the revolutionary process, founded the Program Degree in Agroecology (PDA) in 2004 to expand agroecological practices and knowledge, based on alternative pedagogical approaches. Over the next decade, over a thousand PDA graduates have come to occupy institutional spaces and productive projects in urban and rural areas, contributing to vertical and horizontal agroecological scaling. PDA graduates and educators play a key role in the growing movement of urban agriculture that confronts the economic crisis. The PDA has created key mediators in the form of human talent for territorializing agroecology and institutionalizing pro-peasant policy in Venezuela. As a political outlier, Venezuela is an important case for studying the strategies for territorializing what we refer to as socially committed, situated agroecology. [ABSTRACT FROM AUTHOR]

Abstract Autoencoders are neural networks which perform feature learning on data. Many variants can be found in the literature, but their implementations are scarce, in separate software pieces and utilizing different languages and frameworks. The ruta package implements a unified foundation for the construction and training of autoencoders on top of Keras and Tensorflow, and allows for easy access to the main functionalities as well as full customization of their diverse aspects. [ABSTRACT FROM AUTHOR]

Abstract Consistency is related with reasonableness. This paper proposes a graphical method to visualize and rectify different inconsistencies for fuzzy reciprocal preference relations (FPRs), and the consistency includes the ordinal and cardinal consistencies. Ordinal inconsistency implies cardinal inconsistency, but not vice versa, and cardinal consistency of FPRs includes additive consistency and multiplicative consistency. Therefore, there are four types of inconsistencies, includes: (1) the additive inconsistency; (2) the multiplicative inconsistency; (3) the ordinal and additive inconsistencies, and (4) the ordinal and multiplicative inconsistencies. First, Gower plots are proposed to visualize the ordinal and cardinal inconsistencies on a two-dimensional plane. Then, some optimization models are formulated to rectify the four different types of inconsistences, respectively. Some examples are illustrated to show how the models work, and comparisons with the existing methods are also offered to show the advantages of the proposed methods. [ABSTRACT FROM AUTHOR]

Background: The literature on fiscal theory and policy has shown evidence regarding the procyclical stance of public spending in relation to the economic cycle in developing countries, and particularly in the case of Latin American economies. This paper studies the relationship of budget spending and the economic cycle in Mexico for the 1980-2016 period, it seeks to clarify whether the shift in fiscal policy can be characterized as a tendency towards an anticyclical stance. Methodology: To analyze the quarterly seasonally adjusted series of budget expenditure and gdp (at constant 2008 prices), their cyclical components were estimated using the Hodrick-Prescott filter. To explain the cycle of expenditure through the product cycle, a regression was estimated with Markov regime changes in which the state probabilities vary according to the volatility of the product. Subsequently, the time-varying volatilities of both series were estimated as well as their dynamic conditional correlations and the latter were analyzed based on the economic cycle. Results: The evidence is consistent with an expenditure policy that has been both procyclical and counter-cyclical at different times of the period under study, as the previous literature has shown, but in recent years there has been a notable decrease in the emphasis of the procyclicality of the budget public expenditure, which even suggests that fiscal policy has become acyclical. Conclusions: Unless the policy makers act towards other direction, fiscal policy can be expected to remain acyclical and, therefore, budgetary spending will continue to have non significant impact on the management of the Mexican economy cycle. [ABSTRACT FROM AUTHOR]

We propose that gravity, when formulated in the quantum level, can make quantum effects more pronounced. This is demonstrated by considering the effect of the generalized uncertainty principle or GUP (a consequence of quantum gravity theories) on entanglement (a quantum effect). We apply the GUP to continuous-variable systems. In particular, we study the following cases: the modified uncertainty relation of two identical entangled particles [G. Rigolin, Found. Phys. Lett. 15, 293 (2002)], and the inseparability conditions for entangled particles in the bipartite [Duan et al., Phys. Rev. Lett. 84, 2722 (2000)] and tripartite [van Loock and Furusawa, Phys Rev A 67, 052315 (2003)] cases. Rigolin showed a decrease in the lower bound of the product of the uncertainties of the position and momentum for two identical entangled particles while Duan and van Loock derived inseparability conditions for Einstein-Podolsky-Rosen-like (EPR-like) operators. In all three cases, the GUP correction resulted in a higher value of the bounds: a higher lower bound for the Rigolin's result and a higher upper bound for the inseparability condition in Duan and van Loock's relations. In Rigolin's case, the GUP correction decreased the disagreement with the Heisenberg uncertainty relation while in Duan's and Loock's case, the inseparability and entanglement conditions are enhanced. Interestingly, the GUP corrections tend to boost quantum mechanical effects. [ABSTRACT FROM AUTHOR]

Chile’s General Law of Education states that one of the purposes of education is the spiritual development of all its schooled population. Furthermore, guidelines in Chile’s education system place school directors as key players in student’s learning. This article presents the results of a research involving school directors from Valparaíso, Chile. The aim of this research was to identify how directors of secular and religious schools understand their students’ spiritual development. We studied this aspect in particular through semi-structured interviews conducted with 20 participants. Results show that directors understand spirituality as a typically human ability that can be strengthened in schools and, thus, they believe it to be highly important in schools. In addition, they see a strong relation between spiritual development and ethical and moral development. This study also shows differences in how secular and religious schools’ directors understand this relation. This opens the way for more in-depth analysis regarding spiritual development in Chile’s education system, especially considering that directors generally believe it to be a part of a holistic and quality education. [ABSTRACT FROM AUTHOR]

The Support Vector Machine (SVM) is one of the most powerful algorithms for machine learning and data mining in numerous and heterogenous application domains. However, in spite of its competitiveness, SVM suffers from scalability problems which drastically worsens its performance in terms of memory requirements and execution time. As a consequence, there is a strong emergence of approaches for supporting SVM in efficiently addressing the aforementioned problems without affecting its classification capabilities. In this scenario, methods for Training Set Selection (TSS) represent a suitable and consolidated pre-processing technique to compute a reduced but representative training dataset, and improve SVM’s scalability without deprecating its classification accuracy. Recently, TSS has been formulated as an optimization problem characterized by two objectives (the classification accuracy and the reduction rate) and solved through the application of evolutionary algorithms. However, so far, all the evolutionary approaches for TSS have been based on a so-called multi-objective a priori technique, where multiple objectives are aggregated together into a single objective through a weighted combination. This paper proposes to apply, for the first time, a Pareto-based multi-objective optimization approach to the TSS problem in order to explicitly deal with both its objectives and offer a better trade-off between SVM’s classification and reduction performance. The benefits of the proposed approach are validated by a set of experiments involving well-known datasets taken from the UCI Machine Learning Database Repository. As shown by statistical tests, the application of a Pareto-based multi-objective optimization approach improves on state-of-the-art TSS techniques and enhances SVM efficiency. [ABSTRACT FROM AUTHOR]

Religion classes are found throughout the entire school system in Chile. These are mostly conducted by Catholic teachers who form their own professional identity from internal demands (imposed by the Catholic Church) and external demands (imposed by the school culture, social media, students and their families). This paper presents a reference framework for the professional teacher identity and analyses the linguistic structures and persuasion strategies present in three documents that directly question this group of teachers, building an identity profile of them. Discursive mechanisms are identified which legitimise identity traits. The way in which said productions influence the thoughts and actions of their readership is also analysed. A documentary study design is used based on critical documentary analysis. The investigation shows breaks in the discourse and an existing tension between the mission and the profession, underlining that the Catholic religion teacher is first and foremost an evangeliser. The performance capacity of this discourse on the listeners is discussed along with the effect of the almost complete absence of references to teaching professionalism and the possible influence on the development and results of the subject. [ABSTRACT FROM PUBLISHER]

There is strong upswing in conservation and restoration efforts in Latin America ( LA), particularly in the recent decades after several countries have committed to international agreements such as the Aichi targets of the Convention on Biological Diversity, Initiative 20×20, and the Bonn Challenge. To fulfill these agreements, the practice of ecological restoration has to be defined based on ecological knowledge, but also on the specific social, economic, and legal aspects of each country in the region. Here, we give some examples about the national understanding of ecological restoration in 10 countries of LA. We identify difficulties and opportunities to define restoration priorities and needs, and discuss some approaches to cope with economic constraints and agreements, including the potential role of restoration networks in this process. On the basis of the socioecological complexity of these countries and the expectations they have in relation to restoration, we proposed four approaches to guide restoration practice and policy in the region: (1) including biodiversity and ecosystem services approach into ecosystem restoration initiatives; (2) promoting restoration in their frequently human-modified landscapes; (3) accounting for cost-benefit trade-offs; and (4) assembling 'horizontal' communication frameworks. These approaches should be based at national levels, but adapted to local-regional levels, in a bottom-up perspective. We consider that national and international restoration networks in the region can help to overcome difficulties, fostering a solid scientific community, helping to develop national approaches that better match the specific conditions of each country and enhancing communication among different groups of stakeholders. [ABSTRACT FROM AUTHOR]

The evolution of agroecological wisdom in Venezuela is established in three historical periods. The appearance of oil in the country at the beginning of the twentieth century, followed by the development of the agro-industrial model, produced drastic economic and cultural changes. However, environmental movements, academics, and peasant groups promoted sustainable agriculture, resulting in a multifocal origin for agroecology. Emerging legal frameworks later favored the institutionalization of agroecology. Currently, agroecology has both academic and institutional structures and is widely promoted by urban and rural movements. Nevertheless, tensions with the industrial agriculture paradigm are notorious in the public policies of national food and agricultural programs, representing a real challenge for those fighting to achieve sustainable agriculture. [ABSTRACT FROM PUBLISHER]

In classification problems, it is very common to have ordinal data in the variables, in both explanatory and class variables. When the class variable should increase according to a subset of explanatory variables, the problem must satisfy the monotonicity constraint. It is well known that standard classification tree algorithms, such as CART or C4.5, are not guaranteed to produce monotonic trees, even if the data set is completely monotone. Recently, some classifiers have been designed to handle these kinds of problems. In decision trees, growing and pruning mechanisms have been updated to improve the monotonicity of the trees. In this paper, we study the suitability of using these mechanisms in the generation of Random Forests. For this, we propose a simple ensemble pruning mechanism based on the degree of monotonicity of the resulting trees. The performance of several decision trees are evaluated through experimental studies on monotonic data sets. We deduce that the trees produced by the Random Forest also hold the monotonicity restriction but achieve a slightly better predictive performance than standard algorithms. [ABSTRACT FROM AUTHOR]

This paper shows evidence about the compliance of the Wagner's Law at the level of the Mexican states during the period 1980-2007. This law sets that the growth of public spending is explained as a result of increased economic activity. To test compliance with the law, this study use the specification proposed by Peacock and Wiseman (1961), Musgrave (1969), and Goffman and Mahar (1971), which sets that public spending and output variables are related in their levels. The bulk of empirical research on the fulfillment of the law at the global level has been conducted investigating whether Wagner's Law is fulfilled in the country level, with few studies on its fulfillment at the level of states, provinces or regions into a country. By means of econometric methods of panel data analysis, the whole set of the states of the Mexican Republic is studied, so as three subgroups classified according to their GDP per capita. The results of the cointegration analysis suggest evidence in favor of compliance with the Wagner's Law in the study period and that compliance is a function of the level of development achieved by the states. [ABSTRACT FROM AUTHOR]

The text provides the reader with some theoretical reflections on human values in their relationship to self development from a culturalconstructivist perspective. We emphasize that the concept of self has theoretical aspects that need to be explored to advance alternative explanations about values. Our perspective emphasizes the dynamics of duality and inclusive separation of psychological processes taking place between subject and culture, as well as the role of semiotic systems in the emergence, organization, and development of values. We will address the development of self, here conceived as dialogical self, as well as how constructive and non-constructive values can enable us to better understand the emergence and role of emotions in human development. Finally, the analysis of certain biographical aspects of a former Colombian guerrilla illustrates and highlights the main concepts discussed throughout the text. [ABSTRACT FROM AUTHOR]

A 29 years-old female, with history of twonormal vaginal deliveries, came to the hospital with a pelvic presentation and almost a complete cervical dilatation. A pelvic delivery was planned. The legs, pelvis, thorax and arms were delivered without problems bur the head was retained The Mauriceau-Smellie-Veit maneuver was failed and two Piper forceps applications intented without success. A symphisiotomy was performed under local anesthesia. A female baby was delivered with Apgar-score 0-2-4.The mother had an uterine, vaginal, vesical and urethral injury. The pubic injury was treated with an osteosinthesis by the orthopedic department. The baby was a term female, with 3020 goof weight and 40 weeks Capurro. She had also abraquial plexus injury, anoxic encephalopathy, and anemia, Mother and baby were discharged seven weeks after delivery. Five years later, both are totally recovered, without any sequel. The baby has a physical and intellectual development according to her age. There was a medical and ethic problem in applying an emergency surgical intervention without experience, but in this case was life-saving for the baby. Symphisiotomy is a surgical intervention, which should be learned during the residency. [ABSTRACT FROM AUTHOR]

Introduction. TLR´s play a role in host defense in HIV infection recognizing the viral DNA or RNA. Their activation induces a signaling pathway that includes the proteins MyD88, IRAK4, TRAF6 and the transcription factor NF-kBp65. Objective. To determine the expression of TLR7, TLR8 and TLR9, and activation of its signaling pathway in monocytes from patients infected with HIV. Methods. Expression of TLR7, TLR8 and TLR9 was determined in monocytes from HIV-infected patients (n = 13) and control subjects (n = 13), which were activated with specific ligands. The expression of MyD88 and NF-kBp65 were determined by flow cytometry; IRAK4 and TRAF6 were studied by immunoblotting. Results. No statistical difference was found in the expression of TLR7, 8 and 9 in monocytes from patients compared to controls, but we observed the non-significant increased expression of TLR9 in patients. The activation showed no significant difference in the expression of MyD88 and NF-kBp65 in patients when compared to controls, but were decreased in stimulated cells over non-stimulated cells. IRAK4 and TRAF6 were not detected. Conclusions. No statistical difference was observed in the expression of intracellular TLRs, MyD88 and NFkBp65 in monocytes from patients compared to controls. This was probably due to effective antiretroviral therapy being received at the time of study entry. Additional studies are needed (ARTV) under controlled conditions that include infected patients with and without ARVT, responders and non- responders, and work with different cell populations. [ABSTRACT FROM AUTHOR]

Thin films of copper(I) oxide (Cu2O) were electrodeposited on fluorine-doped tin oxide predeposited glass substrates, by reduction of Cu2+ from Cu(II) acetate acid aqueous solutions. The Cu2O was potentiostatically grown at a potential value of −0.450 V (vs. SMSE) at 70 °C. The Cu2O thin films were characterized by means of scanning electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy (XPS), optical transmission, electrochemical impedance spectroscopy, and photoelectrochemical experiments. Through these techniques, it was possible to establish the cubic Cu2O phase with a high crystallinity and a strong preferential growth along the [200] and [220] directions. Cu2O thin films show oxygen vacancies with formation of a nonstoichiometric compound with the presence of Cu(0) in the crystal lattice as determined by XPS analysis. In addition, Cu2O was used as the photoanode for the I− oxidation reaction when the system was illuminated ( Φ0 = 50.0 mW cm−2). The films exhibited a clear n-type semiconductor behavior, which was in agreement with the Mott-Schottky results. This behavior was explained by considering the nonstoichiometry of the oxide. [ABSTRACT FROM AUTHOR]

Nowadays society is demanding more and more smart healthcare services that allow monitoring patient status in a non-invasive way, anywhere and anytime. Thus, healthcare applications are currently facing important challenges guided by the u-health (ubiquitous health) and p-health (pervasive health) paradigms. New emerging technologies can be combined with other widely deployed ones to develop such next-generation healthcare systems. The main objective of this paper is to review and provide more details on the work presented in "LOBIN: E-Textile and Wireless-Sensor-Network-Based Platform for Healthcare Monitoring in Future Hospital Environments", published in the IEEE Transactions on Information Technology in Biomedicine, as well as to extend and update the comparison with other similar systems. As a result, the paper discusses the main advantages and disadvantages of using different architectures and communications technologies to develop wearable systems for pervasive healthcare applications. [ABSTRACT FROM AUTHOR]

The Academic Ranking of World Universities (ARWU) or Shanghai Ranking is a de facto standard to determine the position of universities worldwide. Improving ranking positions has become the goal of universities and governments. No wonder therefore that the aggregation of universities in Spain is nowadays suggested as a means to raise the international profile of our university system. In this context, the goal of this study was to test two potential groupings, universities belonging to the same Autonomous Community and campuses of international excellence (CEIs), to determine the ARWU placement that would result. To compute the ARWU indicators of these possible groupings, we used the methodology developed in Docampo (2012b). The results of our analysis clearly show the difficulty of improving ranking positions by calculating the sum of aggregated institutions. As a matter of fact, the only way to place a university cluster from Spain in the top 100 would be to treat all of the Catalan universities as a single institution. The next best ranking for Spain would be achieved by the Habitat 5U (universities of Comunidad Valenciana), BKC (Barcelona and Politècnica de Catalunya) and VLC/Campus (Valencia and Politécnica de Valencia), CEIs which would lie in the 150-200 range. [ABSTRACT FROM AUTHOR]

Available data in machine learning applications is becoming increasingly complex, due to higher dimensionality and difficult classes. There exists a wide variety of approaches to measuring complexity of labeled data, according to class overlap, separability or boundary shapes, as well as group morphology. Many techniques can transform the data in order to find better features, but few focus on specifically reducing data complexity. Most data transformation methods mainly treat the dimensionality aspect, leaving aside the available information within class labels which can be useful when classes are somehow complex. This paper proposes an autoencoder-based approach to complexity reduction, using class labels in order to inform the loss function about the adequacy of the generated variables. This leads to three different new feature learners, Scorer, Skaler and Slicer. They are based on Fisher’s discriminant ratio, the Kullback-Leibler divergence and least-squares support vector machines, respectively. They can be applied as a preprocessing stage for a binary classification problem. A thorough experimentation across a collection of 27 datasets and a range of complexity and classification metrics shows that class-informed autoencoders perform better than 4 other popular unsupervised feature extraction techniques, especially when the final objective is using the data for a classification task. [ABSTRACT FROM AUTHOR]

Available data in machine learning applications is becoming increasingly complex, due to higher dimensionality and difficult classes. There exists a wide variety of approaches to measuring complexity of labeled data, according to class overlap, separability or boundary shapes, as well as group morphology. Many techniques can transform the data in order to find better features, but few focus on specifically reducing data complexity. Most data transformation methods mainly treat the dimensionality aspect, leaving aside the available information within class labels which can be useful when classes are somehow complex. This paper proposes an autoencoder-based approach to complexity reduction, using class labels in order to inform the loss function about the adequacy of the generated variables. This leads to three different new feature learners, Scorer, Skaler and Slicer. They are based on Fisher’s discriminant ratio, the Kullback-Leibler divergence and least-squares support vector machines, respectively. They can be applied as a preprocessing stage for a binary classification problem. A thorough experimentation across a collection of 27 datasets and a range of complexity and classification metrics shows that class-informed autoencoders perform better than 4 other popular unsupervised feature extraction techniques, especially when the final objective is using the data for a classification task. [ABSTRACT FROM AUTHOR]

This article presents a Seri narrative text that contains the description of a route by boat to a bay that is on the way to Baja California from Haxöl Iihom (El Desemboque del Río San Ignacio), one of two Seri villages located along the coast of the Gulf of California. The narrator of the text, Francisco Morales Herrera, also provides his audience with a description of the origin of the place name of the bay that is the destination of the trip, An Iquitj Quih An Him Ipácatx 'Where The Pants Were Thrown'. [ABSTRACT FROM AUTHOR]

The relationship between manufacturing exports and manufacturing sector productivity in Mexico is analyzed. A number of studies suggest that the most productive companies tend to compete more successfully in foreign markets and at the same time these same companies are the ones that decide to export and to channel the necessary resources to raise their productivity rates. In the present document we find that productivity in the manufacturing sector does indeed determine the level of exports in this sector, if investment occurs, or instead, if both are determined simultaneously. Contrary to the findings of Cuevas (2008), in the sense that labor productivity constitutes the principal determinant in manufacturing exports in the case of Mexico in recent years, we present evidence here that the causality between the two variables moves in the opposite direction. [ABSTRACT FROM AUTHOR]

Abstract: The analysis of data complexity is a proper framework to characterize the tackled classification problem and to identify domains of competence of classifiers. As a practical outcome of this framework, the proposed data complexity measures may facilitate the choice of a classifier for a given problem. The aim of this paper is to study the behaviour of a fuzzy rule based classification system and its relationship to data complexity. We use as a case of study the fuzzy hybrid genetic based machine learning method presented in [H. Ishibuchi, T. Yamamoto, T. Nakashima, Hybridization of fuzzy GBML approaches for pattern classification problems, IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics 35 (2) (2005) 359–365]. We examine several metrics of data complexity over a wide range of data sets built from real data and try to extract behaviour patterns from the results. We obtain rules which describe both good or bad behaviours of the fuzzy rule based classification system. These rules use values of data complexity metrics in their antecedents, so we try to predict the behaviour of the method from the data set complexity metrics prior to its application. Therefore, we can establish the domains of competence of this fuzzy rule based classification system. [Copyright &y& Elsevier]

The objective of this study is to ascertain whether financial development influenced economic growth after 1990 (the analysis includes the period 1990 - 2004), a period during which a series of reforms was carried out tending to liberalize Mexico's financial sector. The McKinnon-Shaw hypothesis establishes that government restrictions on the financial sector restrict and distort the process of development in this sector and thereby inhibit the process of economic growth. The estimated incidence of financial development on economic growth is realized using a dynamic aggregate production function, similar to that employed by Asteriou and Price (2000). In contrast with the results obtained by Tinoco, Torres and Venegas (2008), we find that financial development had a positive impact on economic growth in the period under review. [ABSTRACT FROM AUTHOR]

Learning with imbalanced data is one of the recent challenges in machine learning. Various solutions have been proposed in order to find a treatment for this problem, such as modifying methods or the application of a preprocessing stage. Within the preprocessing focused on balancing data, two tendencies exist: reduce the set of examples (undersampling) or replicate minority class examples (oversampling). Undersampling with imbalanced datasets could be considered as a prototype selection procedure with the purpose of balancing datasets to achieve a high classification rate, avoiding the bias toward majority class examples. Evolutionary algorithms have been used for classical prototype selection showing good results, where the fitness function is associated to the classification and reduction rates. In this paper, we propose a set of methods called evolutionary undersampling that take into consideration the nature of the problem and use different fitness functions for getting a good trade-off between balance of distribution of classes and performance. The study includes a taxonomy of the approaches and an overall comparison among our models and state of the art undersampling methods. The results have been contrasted by using nonparametric statistical procedures and show that evolutionary undersampling outperforms the nonevolutionary models when the degree of imbalance is increased. [ABSTRACT FROM AUTHOR]

In a recently published paper in JMLR, Demšar (2006) recommends a set of non-parametric statistical tests and procedures which can be safely used for comparing the performance of classifiers over multiple data sets. After studying the paper, we realize that the paper correctly introduces the basic procedures and some of the most advanced ones when comparing a control method. However, it does not deal with some advanced topics in depth. Regarding these topics, we focus on more powerful proposals of statistical procedures for comparing n x n classifiers. Moreover, we illustrate an easy way of obtaining adjusted and comparable p-values in multiple comparison procedures. [ABSTRACT FROM AUTHOR]

The subgroup discovery, domain of application of CN2-SD, is defined as: “given a population of individuals and a property of those individuals, we are interested in finding a population of subgroups as large as possible and have the most unusual statistical characteristic with respect to the property of interest”. The subgroup discovery algorithm CN2-SD, based on a separate and conquer strategy, has to face the scaling problem which appears in the evaluation of large size data sets. To avoid this problem, in this paper we propose the use of instance selection algorithms for scaling down the data sets before the subgroup discovery task. The results show that CN2-SD can be executed on large data set sizes pre-processed, maintaining and improving the quality of the subgroups discovered. [Copyright &y& Elsevier]

In this document we analyze the process of capital market integration in the countries making up the North American Free Trade Agreement (NAFTA) for the period 1984-2002, using an econometric model that captures their long-term relationships. Unit root tests by Perron and Zivot (1989) and by Andrews (1992) make it possible to identify structural changes in the Mexican Stock Exchange (BMV) Prices and Quotations Index (IPC). The study of long-term relations between these markets is based on the Johansen, Mosconi and Nielsen model (2000) which extends a co-integration analysis to a case in which structural changes occur. The empirical evidence suggests that integration among NAFTA's capital markets is changing over time, with periods even when the intensity of their relations declines. [ABSTRACT FROM AUTHOR]

Abstract: The generation of predictive models is a frequent task in data mining with the objective of generating highly precise and interpretable models. The data reduction is an interesting preprocessing approach that can allow us to obtain predictive models with these characteristics in large size data sets. In this paper, we analyze the rule classification model based on decision trees using a training selected set via evolutionary stratified instance selection. This method faces the scaling problem that appears in the evaluation of large size data sets, and the trade off interpretability-precision of the generated models. [Copyright &y& Elsevier]

Abstract: VP16 is a virion phosphoprotein of herpes simplex virus and a transcriptional activator of the viral immediate-early (IE) genes. We identified four novel VP16 phosphorylation sites (Ser18, Ser353, Ser411, and Ser452) at late times in infection but found no evidence of phosphorylation of Ser375, a residue reportedly phosphorylated when VP16 is expressed from a transfected plasmid. A virus carrying a Ser375Ala mutation of VP16 was viable in cell culture but with a slow growth rate. The association of the mutant VP16 protein with IE gene promoters and subsequent IE gene expression was markedly reduced during infection, consistent with prior transfection and in vitro results. Surprisingly, the association of Oct-1 with IE promoters was also diminished during infection by the mutant strain. We propose that Ser375 is important for the interaction of VP16 with Oct-1, and that the interaction is required to enable both proteins to bind to IE promoters. [Copyright &y& Elsevier]

Abstract: Evolutionary algorithms has been recently used for prototype selection showing good results. An important problem that we can find is the scaling up problem that appears evaluating the Evolutionary Prototype Selection algorithms in large size data sets. In this paper, we offer a proposal to solve the drawbacks introduced by the evaluation of large size data sets using evolutionary prototype selection algorithms. In order to do this we have proposed a combination of stratified strategy and CHC as representative evolutionary algorithm model. This study includes a comparison between our proposal and other non-evolutionary prototype selection algorithms combined with the stratified strategy. The results show that stratified evolutionary prototype selection consistently outperforms the non-evolutionary ones, the main advantages being: better instance reduction rates, higher classification accuracy and reduction in resources consumption. [Copyright &y& Elsevier]

During infection by herpes simplex virus type 1 (HSV-1), the virion protein VP16 activates the transcription of viral immediate-early (IE) genes. Genetic and biochemical assays have shown that the potent transcriptional activation domain of VP16 can associate with general transcription factors and with chromatin-modifying coactivator proteins of several types. The latter interactions are particularly intriguing because previous reports indicate that HSV-1 DNA does not become nucleosomal during lytic infection. In the present work, chemical cross-linking and immunoprecipitation assays were used to probe the presence of activators, general transcription factors, and chromatin-modifying coactivators at IE gene promoters during infection of HeLa cells by wild-type HSV-1 and by RP5, a viral strain lacking the VPI6 transcriptional activation domain. The presence of VP16 and Oct-1 at IE promoters did not depend on the activation domain. In contrast, association of RNA polymerase II, TATA-binding protein, histone acetyltransferases (p300 and CBP), and ATP-dependent remodeling proteins (BRG1 and hBRM) with IE gene promoters was observed in wild-type infections but was absent or reduced in cells infected by RP5. In contrast to the previous evidence for nonnucleosomal HSV-1 DNA, histone H3 was found associated with viral DNA at early times of infection. Interestingly, histone H3 was underrepresented on IE promoters in a manner dependent on the VP16 activation domain. Thus, the VP16 activation domain is responsible for recruiting general transcription factors and coactivators to IE promoters and also for dramatically reducing the association of histones with those promoters. [ABSTRACT FROM AUTHOR]

This paper presents a real-coded memetic algorithm that applies a crossover hill-climbing to solutions produced by the genetic operators. On the one hand, the memetic algorithm provides global search (reliability) by means of the promotion of high levels of population diversity. On the other, the crossover hill-climbing exploits the self- adaptive capacity of real-parameter crossover operators with the aim of producing an effective local tuning on the solutions (accuracy). An important aspect of the memetic algorithm proposed is that it adaptively assigns different local search probabilities to individuals. It was observed that the algorithm adjusts the global/local search balance according to the particularities of each problem instance. Experimental results show that, for a wide range of problems, the method we propose here consistently outperforms other real-coded memetic algorithms which appeared in the literature. [ABSTRACT FROM AUTHOR]

Evolutionary Adaptive Defuzzification Methods are a kind of defuzzification methods based on using a parametrical defuzzification expression tuned with evolutionary algorithms. Their goal is to increase the accuracy of the fuzzy system without loosing its interpretability. They induce a kind of rule cooperation in the defuzzification interface. This paper deals with Evolutionary Adaptive Defuzzification Methods. We study their common general expression, the different defuzzification methods that can be obtained from it, their interpretation, and their accuracy. We consider two applications in order to analyze their accuracy in practice. We get some useful results for practical fuzzy systems designed by means of this kind of Intelligent Hybrid System. [ABSTRACT FROM AUTHOR]

Tentacles of Condylactis gigantea were exposed successively to H2O–NaASW dilutions, isosmotic 1 mol/l MgSO4–NaASW mixtures and returned to H2O–NaASW dilutions to explore the possible isotonicity of isosmotic MgSO4 and the reversibility of the effects of this solution on the ionosmotic characteristics of the tentacles. Total tissue water responded as predicted by van''t Hoff''s osmotic relation to H2O–diluted seawater but was not clearly affected by the admixture of seawater with isosmotic MgSO4, suggesting that this solution may act as an isotonic medium. However, total tissue water, potassium, chloride and sodium contents, as well chloride and sodium spaces were lower in MgSO4–NaASW mixtures than in H2O–diluted seawater as a consequence of the loss of these electrolytes and presumably other osmolytes accompanied by an osmotic water loss. The loss of osmolytes did not appear to be compensated by MgSO4 uptake by the tentacles with a consequent reduction of the cell compartment. Therefore, in MgSO4–NaASW mixtures, inulin space approached total tissue water, resulting in considerable uncertainty in the estimation cell volume. When the tentacles were re-exposed to H2O–diluted seawater, tissue ionic contents and ionic and inulin spaces did not revert completely to the values obtained previous to exposure to isosmotic MgSO4. Therefore, although 1 mol/l MgSO4 solution was isosmotic with artificial seawater, it could not efficiently replace the latter as an isotonic medium. [Copyright &y& Elsevier]

In this paper, we present a consensus model for multiperson decision making (MPDM) problems with different preference structures based on two consensus criteria: 1) a consensus measure which indicates the agreement between experts' opinions and 2) a measure of proximity to find out how far the individual opinions are from the group opinion. These measures are calculated by comparing the positions of the alternatives between the individual solutions and collective solution. In such a way, the consensus situation is evaluated in each moment in a more realistic way. With these measures, we design a consensus support system that is able to substitute the actions of the moderator. In this system, the consensus measure is used to guide the consensus process until the final solution is achieved while the proximity measure is used to guide the discussion phases of the consensus process. The consensus support system has a feedback mechanism to guide the discussion phases based on the proximity measure. This feedback mechanism is based on simple and easy rules to help experts change their opinions in order to obtain a degree of consensus as high as possible. The main improvement of this consensus model is that it supports consensus process automatically, without moderator, and, in such a way, the possible subjectivity that the moderator can introduce in the consensus process is avoided. [ABSTRACT FROM AUTHOR]