Castro, Rodrigo y Chamorro, Emmanuel (eds.) (2021)Para una crítica del neoliberalismo: Foucault y Nacimiento de la Biopolítica Madrid: Lengua de Trapo, 538 p. ISBN 978-84-8381-265-5.

Slavoj �i�ek un filósofo polémico, al que algunos han llegado a considerar una especie de farsante mediático. Este escrito pretende reivindicarlo como uno de los pensadores interesantes y renovadores de la izquierda contemporánea. Se analizan tres aspectos, que son su crítica a la ideología hegemónica del capitalismo en su fase actual, su crítica a las diferentes versiones de la izquierda existente y algunas de sus propuestas políticas. Aunque sus reflexiones sean discutibles sus reflexiones proporcionan uno de los materiales más valiosos (...) para una teoría contemporánea de la emancipación social. (shrink)

Este trabajo analiza el hilo conductor que va de Pierre Hadot a François Jullien pasando por Michel Foucault, y que se sostiene en el papel de la filosofía como transformador de sí para alcanzar una vida verdadera. Hadot y Foucault buscan referentes en las escuelas antiguas grecorromanas, mientras que François Jullien lo hace en la sabiduría tradicional china. Pero en todos los casos es una búsqueda del pasado para volver al presente y así actualizar este diálogo con los antiguos. Pierre (...) Hadot hablará de la filosofía como ejercicio espiritual; Michel Foucault, como del cuidado de sí, y François Jullien, como del aprendizaje del vivir existiendo. La continuidad está en esta voluntad de hacer de la filosofía un instrumento para construirse como sujeto ético, cuyo resultado es otro modo de vida, una vida verdadera. (shrink)

Balibar, Étienne (2021)Spinoza político: Lo transindividualTraducción de Alfonso DíezBarcelona: Gedisa, 304 p.ISBN 978-84-18525-15-5.

Cano, Germán Transición NietzscheValencia: Pre-Textos, 344 p.ISBN 9788417830991.

Sanz, Marco (2021)La emancipación de los cuerpos: Teoremas críticos sobre la enfermedadMadrid: Akal, 154 p.ISBN 978-84-460-5037-7.

Vázquez García, Francisco Cómo hacer cosas con Foucault: Instrucciones de usoMadrid: Dado Ediciones, 238 p.ISBN 9788412123258.

El artículo aborda la pandemia del covid-19 como elemento contingente y su efecto de develamiento respecto de algunas manifestaciones contemporáneas de la ideología neoliberal en Latinoamérica. De esta forma, en base a conceptos filosóficos y psicoanalíticos de orientación lacaniana planteados fundamentalmente por Slavoj Žižek, se examinan los usos críticos de la noción de ideología en sus diversas manifestaciones: miedo al otro, imposición de la lógica del empresario de sí, destrucción de lazos sociales, extractivismo de recursos naturales y fetichización de los (...) discursos de unidad frente a la pandemia. La hipótesis radica en que la pandemia presenta una oportunidad para repensar la subjetividad contemporánea, mediante la confrontación con el Real que bordea a la simbolización y, en definitiva, a la captura ideológica, a fin de poner en cuestión la afirmación de que no hay alternativa. (shrink)

Nowadays, batteries play an important role in a lot of different applications like energy storage, electro-mobility, consumer electronic and so on. All the battery types have a common factor that is their complexity, independently of its nature. Usually, the batteries have an electrochemical nature. Several different test are accomplished to check the batteries performance, and commonly, it is predictable how they work depending of their technology. The present research describes the hybrid intelligent system created to accomplish fault detection over a (...) Lithium Iron Phosphate—LiFePO4 power cell type, commonly used in electro-mobility applications. The approach is based on the cell temperatures behaviour for voltage and current specific values. Taken into account the operating range of a real system based on a LiFePO4 cell, a large set of points of operation have been used to achieve the dataset. The different behaviour zones have been obtained by clustering as a first step. Then, different regression techniques have been used over each cluster. Polynomial regression, artificial neural networks and support vector regression were the combined techniques to develop the hybrid intelligent model proposed. The intelligent system gives very good results over the operating range, detecting all the faults tested during the validation. (shrink)

The need for cognitive closure is a construct postulated by Kruglanski that explains the motivational aspects which influence decision-making and its impact on the social environment. Initially, it was assessed through a unidimensional scale, later criticized for its poor satisfactory reliability and validity. Regarding these criticisms, Pierro and Kruglanski developed a new 14-item scale to measure two dimensions, which were not previously evaluated: urgency tendency and permanence tendency. Although the Revised Test of Need for Cognitive Closure is more economical in (...) terms of assessment time, it would be optimal to develop a reduced test that can assess faster while maintaining validity and reliability. The present research aims to reduce the Revised Test of Need for Cognitive Closure scale to the Argentinian context. To this end, we worked on a non-experimental design, assessing this scale within a sample of 690 Argentinian university students, and proceeded to perform reliability, as well as confirmatory factor analysis, convergent validity, and factorial invariance analysis. The results indicate a bi-factorial structure of a Need for Cognitive Closure instrument with eight items and two dimensions: urgency tendency and permanence tendency, suggesting good reliability in both of them. In addition, well convergent validity was checked with other validated instruments, and finally, the factor loadings were shown to be invariant. In conclusion, it was demonstrated the reliability and validity of reducing the Revised Test of Need for Cognitive Closure in our social environment. (shrink)

A large part of technological advances, especially in the field of industry, have been focused on the optimization of productive processes. However, the detection of anomalies has turned out to be a great challenge in fields like industry, medicine or stock markets. The present work addresses anomaly detection on a control level plant. We propose the application of different intelligent techniques, which allow to obtain one-class classifiers using real data taken from the correct plant operation. The performance of each classifier (...) is assessed and validated with real created faults, achieving successful overall results. (shrink)

Student performance and its evaluation remain a serious challenge for education systems. Frequently, the recording and processing of students’ scores in a specific curriculum have several flaws for various reasons. In this context, the absence of data from some of the student scores undermines the efficiency of any future analysis carried out in order to reach conclusions. When this is the case, missing data imputation algorithms are needed. These algorithms are capable of substituting, with a high level of accuracy, the (...) missing data for predicted values. This research presents the hybridization of an algorithm previously proposed by the authors called adaptive assignation algorithm, with a well-known technique called multivariate imputation by chained equations. The results show how the suggested methodology outperforms both algorithms. (shrink)

The use of batteries became essential in our daily life in electronic devices, electric vehicles and energy storage systems in general terms. As they play a key role in many devices, their design and implementation must follow a thorough test process to check their features at different operating points. In this circumstance, the appearance of any kind of deviation from the expected operation must be detected. This research deals with real data registered during the testing phase of a lithium iron (...) phosphate—LiFePO4—battery. The process is divided into four different working points, alternating charging, discharging and resting periods. This work proposes a hybrid classifier, based on one-class techniques, whose aim is to detect anomalous situations during the battery test. The faults are created by modifying the measured cell temperature a slight ratio from their real value. A detailed analysis of each technique performance is presented. The average performance of the chosen classifier presents successful results. (shrink)

A dimensional reduction algorithm is applied to an intelligent classification model with the purpose of improving the efficiency and accuracy. The proposed classification model, used to distinguish the operating mode: Hard- and Soft-Switching, is presented and an analysis of the synchronized rectified step-down converter is done. With the aim of improving the accuracy and reducing the computational cost of the model, three different methods for dimensional reduction are applied to the input dataset of the model: self-organizing maps, principal component analysis (...) and correlation matrix. The obtained results show how the number of variable is highly reduced and the performance of the classification model is boosted: the results manifest an improve in the accuracy and efficiency of the classification. (shrink)

In this research work a novel two-step system for anomaly detection is presented and tested over several real datasets. In the first step the novel Exploratory Projection Pursuit, Beta Hebbian Learning algorithm, is applied over each dataset, either to reduce the dimensionality of the original dataset or to face nonlinear datasets by generating a new subspace of the original dataset with lower, or even higher, dimensionality selecting the right activation function. Finally, in the second step Principal Component Analysis anomaly detection (...) is applied to the new subspace to detect the anomalies and improve its classification capabilities. This new approach has been tested over several different real datasets, in terms of number of variables, number of samples and number of anomalies. In almost all cases, the novel approach obtained better results in terms of area under the curve with similar standard deviation values. In case of computational cost, this improvement is only remarkable when complexity of the dataset in terms of number of variables is high. (shrink)

Detecting intrusions in large networks is a highly demanding task. In order to reduce the computation demand of analysing every single packet travelling along one of such networks, some years ago flows were proposed as a way of summarizing traffic information. Very few research works have addressed intrusion detection in flows from a visualizations perspective. In order to bridge this gap, the present paper proposes the application of a novel projection method (Beta Hebbian Learning) under this framework. With the aim (...) to validate this method, 8 traffic segments, containing many flows, have been analysed by means of this projection method. The promising results obtained for these segments, extracted from the University of Twente dataset, validate the proposed application. (shrink)

This paper aims to enhance security in IoT device networks through a visual tool that utilizes three projection techniques, including Beta Hebbian Learning (BHL), t-distributed Stochastic Neighbor Embedding (t-SNE) and ISOMAP, in order to facilitate the identification of network attacks by human experts. This work research begins with the creation of a testing environment with IoT devices and web clients, simulating attacks over Message Queuing Telemetry Transport (MQTT) for recording all relevant traffic information. The unsupervised algorithms chosen provide a set (...) of projections that enable human experts to visually identify most attacks in real-time, making it a powerful tool that can be implemented in IoT environments easily. (shrink)

In this study, a hybrid model based on intelligent techniques is developed to predict the active power generated in a bioclimatic house by a low power wind turbine. Contrary to other researches that predict the generated power taking into account the speed and the direction of the wind, the model developed in this paper only uses the speed of the wind, measured mainly in a weather station from the government meteorological agency (MeteoGalicia). The wind speed is measured at different heights, (...) against the usual measurements in others researches, which uses the wind speed and the direction measured in a weather station on the wind turbine nacelle. The prediction is performed 30 minutes ahead, what ensures that the Building Management System knows the energy generated by the low power wind turbine 30 minutes before, and it can adapt the consumption of different equipment in the house to optimize the power use. The main objective is to allow the Building Management System to optimize the uses of energy, taking into account the predicted amount of energy that will be produced and the energy consumed in the house. The developed model uses a hybrid topology with four clusters to improve the prediction, achieving an error lower than 6.5% for Mean Absolute Error measured in a final test. To perform this test, part of the original dataset was isolated from the beginning of the training process to check the model with a dataset that is not used before, simulating the model as it is receiving new data. (shrink)

One of the main challenges in medicine is to guarantee an appropriate drug supply according to the real needs of patients. Closed-loop strategies have been widely used to develop automatic solutions based on feedback variables. However, when the variable of interest cannot be directly measured or there is a lack of knowledge behind the process, it turns into a difficult issue to solve. In this research, a novel algorithm to approach this problem is presented. The main objective of this study (...) is to provide a new general algorithm capable of determining the influence of a certain clinical variable in the decision making process for drug supply and then defining an automatic system able to guide the process considering this information. Thus, this new technique will provide a way to validate a given physiological signal as a feedback variable for drug titration. In addition, the result of the algorithm in terms of fuzzy rules and membership functions will define a fuzzy-based decision system for the drug delivery process. The method proposed is based on a Fuzzy Inference System whose structure is obtained through a decision tree algorithm. A four-step methodology is then developed: data collection, preprocessing, Fuzzy Inference System generation, and the validation of results. To test this methodology, the analgesia control scenario was analysed. Specifically, the viability of the Analgesia Nociception Index as a guiding variable for the analgesic process during surgical interventions was studied. Real data was obtained from fifteen patients undergoing cholecystectomy surgery. (shrink)

Background:The acquisition of experience is a major concern for nurses in intensive care units. Although the emotional component of the clinical practice of these nurses has been widely studied, greater examination is required to determine how this component influences their learning and practical experience.Objective:To discover the relationships between emotion, memory and learning and the impacts on nursing clinical practice.Research design:This is a qualitative phenomenological study. The data were collected from open, in-depth interviews. A total of 22 intensive care unit nurses (...) participated in this research between January 2012 and December 2014.Ethical considerations:The School of Nursing Ethics Committee approved the study, which complied with ethical principles and required informed consent.Findings:We found a clear relationship between emotion, memory and the acquisition of experience. This relationship grouped three dimensions: (1) satisfaction, to relieve the patient’s pain or discomfort, give confidence and a sense of security to the patient, enable the presence of family members into the intensive care unit and provide family members with a realistic view of the patient’s situation; (2) error experience, which nurses feel when a patient dies, when they fail to accompany a patient in his or her decision to abandon the struggle to live or when they fail to lend support to the patient’s family; and (3) the feel bad–feel good paradox, which occurs when a mistake in the patient’s care or handling of his or her family is repaired.Conclusion:Emotion is a capacity that impacts on nurses’ experience and influences improvements in clinical practice. Recalling stories of satisfaction helps to reinforce good practice, while recalling stories of errors helps to identify difficulties in the profession and recognise new forms of action. The articulation of emotional competencies may support the development of nursing ethics in the intensive care unit to protect and defend their patients and improve their relationships with families in order to maximise the potential for patient care. (shrink)

Nowadays, the quality standards of higher education institutions pay special attention to the performance and evaluation of the students. Then, having a complete academic record of each student, such as number of attempts, average grade and so on, plays a key role. In this context, the existence of missing data, which can happen for different reasons, leads to affect adversely interesting future analysis. Therefore, the use of imputation techniques is presented as a helpful tool to estimate the value of missing (...) data. This work deals with the academic records of engineering students, in which imputation techniques are applied. More specifically, it is assessed and compared to the performance of the multivariate imputation by chained equations methodology, the adaptive assignation algorithm based on multivariate adaptive regression splines and a hybridization based on self-organisation maps with Mahalanobis distances and AAA algorithm. The results show that proposed methods obtain successfully results regardless the number of missing values, in general terms. (shrink)

The present research describes a novel adaptive anomaly detection method to optimize the performance of nonlinear and time-varying systems. The proposal integrates a centroid-based approach with the real-time identification technique Recursive Least Squares. In order to find anomalies, the approach compares the present system dynamics with the average (centroid) of the dynamics found in earlier states for a given setpoint. The system labels the dynamics difference as an anomaly if it rises over a determinate threshold. To validate the proposal, two (...) different datasets obtained from a level control plant operation have been used, to which anomalies have been artificially added. The results shown have determined a satisfactory performance of the method, especially in those processes with low noise. (shrink)

Batteries are a fundamental storage component due to its various applications in mobility, renewable energies and consumer electronics among others. Regardless of the battery typology, one key variable from a user’s perspective is the remaining energy in the battery. It is usually presented as the percentage of remaining energy compared to the total energy that can be stored and is labeled State Of Charge (SOC). This work addresses the development of a hybrid model based on a Lithium Iron Phosphate (LiFePO4) (...) power cell, due to its broad implementation. The proposed model calculates the SOC, by means of voltage and electric current as inputs and the latter as the output. Therefore, four models based on k-Means, Agglomerative Clustering, Gaussian Mixture and Spectral Clustering techniques have been tested in order to obtain an optimal solution. (shrink)

Closed-loop administration of propofol for the control of hypnosis in anesthesia has evidenced an outperformance when comparing it with manual administration in terms of drug consumption and post-operative recovery of patients. Unlike other systems, the success of this strategy lies on the availability of a feedback variable capable of quantifying the current hypnotic state of the patient. However, the appearance of anomalies during the anesthetic process may result in inaccurate actions of the automatic controller. These anomalies may come from the (...) monitors, the syringe pumps, the actions of the surgeon or even from alterations in patients. This could produce adverse side effects that can affect the patient postoperative and reduce the safety of the patient in the operating room. Then, the use of anomaly detection techniques plays a significant role to avoid this undesirable situations. This work assesses different one-class intelligent techniques to detect anomalies in patients undergoing general anesthesia. Due to the difficulty of obtaining real data from anomaly situations, artificial outliers are generated to check the performance of each classifier. The final model presents successful performance. (shrink)

Automatic control of physiological variables is one of the most active areas in biomedical engineering. This paper is centered in the prediction of the analgesic variables evolution in patients undergoing surgery. The proposal is based on the use of hybrid intelligent modelling methods. The study considers the Analgesia Nociception Index to assess the pain in the patient and remifentanil as intravenous analgesic. The model proposed is able to make a one-step-ahead prediction of the remifentanil dose corresponding to the current state (...) of the patient. The input information is the previous remifentanil dose, the ANI variable and the electromyogram signal. Modelling techniques used are Artificial Neural Networks and Support Vector machines for Regression combined with clustering methods. Both training and validation were done with a real dataset from different patients. Results obtained show the potential of this methodology to calculate the drug dose corresponding to a given analgesic state of the patient. (shrink)

Esta investigación da cuenta de cómo ha sido expresada, interpretada y fundada poéticamente la ciudad colombiana durante el siglo XX en las obras de los poetas colombianos Luis Vidales (Suenan Timbres), Rogelio Echavarría (El Transeúnte) y Juan Manuel Roca (Luna de ciegos y Los ladrones nocturnos). Indaga cómo estos tres poetas colombianos han fundado ciudades como textos escriturales y levantado cartografías simbólicas citadinas; realiza una interpretación de los universos de sus poéticas, de las constelaciones simbólicas que asume el (...) poema como universo del lenguaje, el cual construye topologías imaginarias sobre la ciudad, revelando arquetipos fundamentales, presentes en la poesía urbana colombiana. (shrink)

The paper compares the suitability of two different epistemologies of counterfactuals—(EC) and (W)—to elucidate modal knowledge. I argue that, while both of them explain the data on our knowledge of counterfactuals, only (W)—Williamson’s epistemology—is compatible with all counterpossibles being true. This is something on which Williamson’s counterfactual-based account of modal knowledge relies. A first problem is, therefore, that, in the absence of further, disambiguating data, Williamson’s choice of (W) is objectionably biased. A second, deeper problem is that (W) cannot satisfactorily (...) elucidate modal knowledge. Third, from a naturalistic perspective, the nature of this second problem favours (EC) against (W). (shrink)

The paper argues against Peacocke's moderate rationalism in modality. In the first part, I show, by identifying an argumentative gap in its epistemology, that Peacocke's account has not met the Integration Challenge. I then argue that we should modify the account's metaphysics of modal concepts in order to avoid implausible consequences with regards to their possession conditions. This modification generates no extra explanatory gap. Yet, once the minimal modification that avoids those implausible consequences is made, the resulting account cannot support (...) Peacocke's moderate rationalism. (shrink)

The paper presents a dilemma for both epistemic and non-epistemic versions of conceivability-based accounts of modal knowledge. On the one horn, non-epistemic accounts do not elucidate the essentialist knowledge they would be committed to. On the other, epistemic accounts do not elucidate everyday life de re modal knowledge. In neither case, therefore, do conceivability accounts elucidate de re modal knowledge.