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Pulmonary aspiration is the passage of food, gastroesophageal reflux and/or saliva to the airway in a manner sufficient to cause chronic or recurrent respiratory symptoms. It is an important cause of recurrent pneumonia, progressive lung disease, bronchiectasis and even death. Aspiration is intermittent and often occurs in children with underlying medical conditions or syndromes that cause respiratory symptoms similar to chronic pulmonary aspiration, so diagnosis of aspiration is often delayed until there is a significant lung injury. The available diagnostic methods and their limitations, and treatment options of chronic pulmonary aspiration in the pediatric population are described., Competing Interests: The authors report no conflicts of interest in this work., (Sociedad Argentina de Pediatría.)

(Series Information) European Papers - A Journal on Law and Integration, 2021 6(2), 1193-1228 | Article | (Table of Contents) I. Preliminary remarks. - II. The increasing attractiveness of cartels in the age of big data analytics. - III. Collusion between rational algorithms: the relation between market transparency and artificial intelligence in a world of big data. - IV. Existing vs created market conditions: tacit collusion or algorithmic concerted practices? - V. The limited role played by intent and imputability in the antitrust realm: the case of parent company liability and its applicability by analogy to the relation undertakings vis-à-vis algorithms. - VI. Big data analytics does create competitive concerns: should the Commission and national competition authorities commit to tackling algorithmic collusion? - VII. Conclusions. | (Abstract) Due to digital markets' transparency, algorithmic collusion may occur even if algorithms are designed to maximize profits rather than to conspire. The literature suggests that competition rules may not cover algorithmic collusion, being the latter an example of tacit collusion: by monitoring market conditions, each algorithm unilaterally and rationally decides to maintain supra-competitive prices. Data analytics ease the monitoring and reaction to competitors' behaviours, increasing the number of markets subject to tacit collusion. Yet, intention to conspire seems absent. In this Article, it is submitted that algorithmic collusion is different from tacit collusion and can be tackled under EU competition law. In the traditional scenario, undertakings base their rational decisions on the existing markets conditions. While designing their algorithms to maximize profits, undertakings are contributing to create the conditions allowing "tacit" collusion to occur. Moreover, a quasi-strict liability regime applies to antitrust offences, so that intention and imputability play limited roles. As a consequence, if algorithms programmed to maximize profits end up colluding, a rebuttable presumption of the existence of a concerted practice should apply. The practice should be prohibited unless undertakings can prove that, in the specific case, a concerted practice did not occur or that art. 101(3) TFEU applies. Moreover, competition rules may be enforced even without ascertaining any antitrust infringement. Competitive concerns are enough to adopt commitment decisions. Here, the Commission (or a National Competition Authority) may negotiate with the concerned undertakings technical remedies to prevent algorithmic collusion by intervening on the way the algorithms work.

Objectives: Unilateral sinonasal disease is commonly encountered in practice and represents an issue of major concern since neoplasms may mimic inflammatory conditions. This paper aims to describe the demographic, clinical and radiological patterns of unilateral pathologies and, accordingly, to establish a guiding algorithm for diagnosis and management., Material and Methods: We conducted a retrospective review of medical records of patients with unilateral sinus opacification on CT scan who underwent endoscopic nasal surgery in our department from January 2011 to December 2017., Results: Of the 150 patients included, 97(64.7%) and 53(35.3%) had inflammatory and neoplastic pathology, respectively. In the neoplastic group, malignancy was present in 35% of patients. Neoplastic conditions were more common in males (p=0.02) and older patients (56±18 years vs. 38±18, p<.01). Nasal mass or polyp was observed in 56.7% patients. Chronic sinusitis was the most prevalent inflammatory condition, whereas inverted papilloma and osteoma were the most frequent neoplasms. Facial neuralgia, paraesthesia, epistaxis and, on CT scan, superior Lund-Mackay scores, bone remodelling and erosion were significantly more common in neoplastic conditions. Excellent agreement between punch biopsy and postoperative histological results was obtained (k=.883, p<.001)., Conclusion: A sequential and careful management of unilateral lesions is mandatory. Based on our experience, we propose that, as routine, physical examination should be complemented with nasal endoscopy, CT scan and punch biopsy, in case of visible mass. Although clinical and radiological information might raise suspicion of some conditions, final diagnosis can only be established with histological examination of the surgical specimen., (Copyright © 2019 Sociedad Española de Otorrinolaringología y Cirugía de Cabeza y Cuello. Publicado por Elsevier España, S.L.U. All rights reserved.)

Objective: This paper presents a methodology to optimize, using Altman's Z-Score for private companies, the prediction of private companies of the Spanish health sector entering a situation of bankruptcy., Method: The proposed method consists of the application of genetic algorithms (GA) to find the coefficients of the formula of the chain of ratios proposed by Altman in the version of the score for private companies which optimize the prediction for Spanish private health companies, maximizing sensitivity and specificity, and thereby reducing type I and type II errors. For this purpose, a sample of 5,903 companies from the Spanish private health sector obtained from the database of the Iberian Balance Analysis System (SABI) between 2007 and 2015 was used., Results: The results show that the predictive model obtained with the AG presents greater accuracy, sensitivity and specificity than that proposed by Altman for private companies with both test data and all sample data., Conclusions: The most important finding of this study was to establish a methodology that can identify the optimized coefficients for the Altman Z-Score, which allows a more accurate prediction of bankruptcy in Spanish private healthcare companies., (Copyright © 2018 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.)

Prostate Cancer (PCa) represents the most common malignant tumor in men but according to the European Association of Urology (EAU) guidelines, a mass screening for PCa diagnosis should not be performed due to over-diagnosis and over-treatment related problems. An early clinical diagnosis is possible, mainly based on digital rectal examination and Prostatic Specific Agent (PSA) testing. However, the only mandatory test to define the presence of PCa is ultrasound guided-biopsy, obtained on multiple samples, which has also a high prognostic value. In this context, diagnostic imaging plays an important role as confirmed by EAU that in a 2016 update of their guidelines on PCa stated the importance of Positron Emission Tomography (PET) with 11 C- or 18 F-choline combined with computed tomography (CT) to identify local relapse, lymph node involvement and metastatic spread at all stages. Consequently, in 2017, the European Association of Nuclear Medicine (EANM) together with the Society of Nuclear Medicine and Molecular Imaging (SNMMI) published new guidelines for 68 Ga-Prostate Specific Membrane Antigen (PSMA) PET/CT to help physicians in the recommendation, execution and interpretation of PET/CT scans in patients with PCa. Thus, the aim of this 'evidence paper' is to define the current diagnostic algorithm in PCa in order to increase the general level of confidence in approaching such a crucial topic., (Copyright © 2017 Elsevier España, S.L.U. y SEMNIM. All rights reserved.)

In the modern world, among the different clinical presentations of osteoarthritis, gonarthrosis and coxarthrosis exhibit the highest prevalence. In this paper, the characteristics of osteoarthritis and the different scales of assessment and classification of this pathology are exposed, to provide an exhibition of current evidence generated around diagnostic algorithms and treatment of osteoarthritis, with emphasis set out in the knee and hip, as these are the most frequent; a rational procedure for monitoring patients with osteoarthritis based on characteristic symptoms and the severity of the condition is also set. Finally, reference is made to the therapeutic benefits of the recent introduction of viscosupplementation with Hylan GF-20.

The symptoms related to the presence of arachnoid cysts in the Central Nervous System depend on the size of the cyst and its growth rate, its location and, in some cases, the associated CSF dynamic disorder. Sometimes there is acute clinical presentation due to cyst rupture or acute bleeding. Although it is generally accepted that asymptomatic or paucisymptomatic cysts do not require surgical treatment, there is no consensus on the therapeutic approach of choice in symptomatic cases. The aim of this paper is to review the literature, analyzing the pros and cons of the three main surgical options (microsurgery, neuroendoscopy, and CSF shunt) based primarily on the location of the cyst. Although treatment must be always individualized, basic management recommendations may be offered., (Copyright © 2015 Sociedad Española de Neurocirugía. Published by Elsevier España. All rights reserved.)

The challenges introduced by AI for the EU anti-discrimination legal framework have been a widely discussed topic among the doctrine. In the light of the 20th anniversary of the EU Charter of Fundamental Rights, the Commission released a regulatory proposal to tackle AI. This paper seeks to determine whether the proposal successfully addresses the existent pitfalls of the EU framework. First, this paper explores the functioning of AI systems that employ machine learning techniques and determines how discrimination takes place. Second, the article examines intellectual property rights as one of the main barriers for accountability and redressal of violations committed by an AI system. Third, the state of the discussion concerning the pitfalls of the existent EU approach towards non-discrimination is addressed. The available academic literature suggests that discriminatory outputs produced by an AI will amount to indirect discrimination in most scenarios. In this sense, cases of indirect proxy discrimination will likely pass the proportionality test, therefore justifying the discriminatory output. The last section of this article studies the Commission’s regulatory proposal. Although the document seems to effectively tackle discrimination caused by biased training data sets, this paper concludes that intellectual property rights and proxy discrimination still constitute significant barriers for the enforcement of anti-discrimination law.

Objective: Re-evaluate the effective dose (E) of typical nuclear medicine procedures using the new ICRP-103 weighting factors and the latest dosimetry data and relate E with Background Equivalent Radiation Time (BERT)., Material and Methods: Effective dose associated with radiopharmaceuticals and nuclear medicine procedures has been calculated for the following ages: adult, 15, 10, 5 and 1 year. Dosimetry data have been extracted from ICRP-106, ICRP-80, ICRP-53 and/or manufacturer's brochure., Results: The relationship of the data of effective dose associated with radiopharmaceuticals and explorations is shown. The new tissue weighting factors result in a decreased value of the effective dose, except in cases that particularly affect the breast, in which it increases. The effective dose associated with nuclear medicine procedures is in the range 0.1-60 mSv. BERT ranges from a few days to 20 years. The effective dose associated to tests in children is generally higher than the effective dose for an adult., Conclusions: The results shown in this paper are an updated collection of effective dose values for commonly used radiopharmaceuticals in nuclear medicine. Expressing the effective dose equivalent time in units of natural radiation helps to explain issues associated with radiation exposure to patients and healthcare personnel., (2009 Elsevier España, S.L. y SEMNIM. All rights reserved.)

Purpose: The main purpose of the paper is to evaluate an automated method for blood vessels segmentation in color fundus images, due to its important role in the diagnosis of several pathologies such as diabetes. The final objective is to introduce the algorithm into a Computer Aided Diagnosis (CAD) tool that would be available in those local medical centers without specialists., Method: An automated method for blood vessels segmentation in color fundus images was implemented and tested. The algorithm starts with the extraction of vessel centerlines, which are used as guidelines for the subsequent vessel filling phase. The outputs of four directional differential operators are processed in order to select connected sets of candidate points to be further classified as centerline pixels using vessel derived features. The final segmentation is obtained using an iterative region growing method that integrates the contents of several binary images, resulting from vessel width dependent morphological filters. The method was evaluated using the images of two publicly available databases (STARE and DRIVE) and a database with 24 images., Results: The algorithm outperforms other published algorithms and approximates the average accuracy of a human observer without a significant degradation of sensitivity and specificity. In addition, results have been subject to the experts' valuation that they think that retinal vessels remain represented with valuable accuracy on having analyzed the test's images., Conclusion: Due to the good segmentation results, the algorithm proposed could be implemented as part of a complete CAD tool in the local medical centers. This would reduce cost and diagnosis time.

Mental retardation affects 1-3% of the population. Its etiology is heterogeneous and approximately 47% of cases are caused by genetic factors. The aim of this paper is to report on etiologies of mental retardation, to present updates on new technologies of molecular diagnosis, and to analyze their limitations for the appropriate and rational use of them. Finally, an algorithm based on genetics is suggested for the study of mental retardation by reporting on the techniques available in Argentina and in developed countries. A well-defined etiology will lead to the proper management of children with mental retardation, and suitable family counseling.

Dementia is a chronic progressive mental disorder, which adversely affects different domains as memory, thinking, comprehension, judgment, orientation, calculation or language. People with dementia eventually lose the ability to carry out routine daily activities such as dressing, toileting, traveling and handling money. Memory impairment and dementia are commonly seen by physicians in multiple disciplines including primary care, geriatrics, neurology, and psychiatry. We discuss the pros and cons of brief cognitive tests such as the Mini-mental State Examination (MMSE) and test for executive functions to detect cognitive impairment in community patients. Diagnosis must meet standard diagnostic criteria, including tests of cognitive, global and behavioral functioning and activities of daily living. Preliminary diagnosis often takes place in primary care, usually followed by specialist assessment. In this paper we discuss operational criteria for diagnosis in primary care. An algorithm for practical physicians is proposed.

Objectives: Patient movement during SPECT acquisition of images is a frequent cause of artefacts in myocardial perfusion SPECT studies. In this paper we propose an algorithm for the correction of longitudinal movements., Materials and Methods: The method is based on the calculation of the correlation between unidimensional functions obtained from successive projections with a window obtained automatically to eliminate unwanted data points before calculating the correlation. The algorithm was assessed on studies obtained from a cardiac phantom and from those corresponding to ten patients. Seven of these patients had significant movement during SPECT acquisition and those corresponding to the other three studies, in which no movement was observed, were used as a control., Results: In the phantom studies obtained, the mean error of the calculated displacements was less than 0.5 pixels when the window proposed was employed. The error reached 2.8 pixels when the length of the window increased. In patient studies, the method succeeded in reducing the patient motion in all cases and the three control studies remained unchanged. When no window was used to limit the correlation, three out of the seven studies that originally presented movements did not improve and one control study got worse., Conclusion: The results obtained indicate the utility of the algorithm and demonstrate the need to window the data before calculating the correlation.

Over the past decade, concern has grown regarding the risks generated by the use of artificial intelligence systems. One of the main problems associated with the use of these systems is the harm they have been proven to cause to the fundamental right to equality and non-discrimination. In this context, it is vital that we examine existing and proposed regulatory instruments that aim to address this particular issue, especially taking into consideration the difficulties of applying the abstract nature that typically characterises legal instruments and, in particular, the equality and non-discrimination legal framework, to the specific instructions that are needed when coding an artificial intelligence instrument that aims to be non-discriminatory. This paper focuses on examining how article 10 of the new EU Artificial Intelligence Act proposal may be the starting point for a new form of regulation that adapts to the needs of algorithmic systems.

Our objective in this paper is to present and discuss the complexification of the process of platformization of journalism by Facebook, triggered by the implementation of the Facebook Journalism Project (FJP), in January 2017. Since then, the platform has been associating itself with new and varied actors, expanding its fronts and positioning itself as a coordinator of activities related to journalistic institutions. At the same time, it continued to offer itself as an infrastructure for the development of journalistic products and businesses. Based on the Platform Studies and methodologically inspired by the Cartography of Controversies, we present the FJP and public demonstrations by journalists, researchers and other actors involved in its implementation. The diversification of partnerships, the inclusion of pedagogical actions, the renegotiation of prescriptive and normative dimensions that guide journalistic institutions, and the consolidation of the platform as an infrastructure are the main issues discussed at the conclusions. Nosso objetivo neste artigo é apresentar e discutir a complexificação do processo de plataformização do jornalismo pelo Facebook, a partir da implementação do Facebook Journalism Project (FJP), em janeiro de 2017. Desde então, a plataforma vem se associando a novos e variados atores, ampliando suas frentes de atuação e se posicionando como uma coordenadora de atividades relacionadas às instituições jornalísticas. Ao mesmo tempo, continuou a se oferecer como infraestrutura para o desenvolvimento dos produtos e negócios jornalísticos. Ancorados nos Estudos de Plataforma e inspirados metodologicamente na Cartografia das Controvérsias, apresentamos o FJP e manifestações públicas de jornalistas, pesquisadores e outros atores interessados em sua implementação. A diversificação das parcerias, a inclusão de ações pedagógicas, a renegociação das dimensões prescritivas e normativas que orientam as instituições jornalísticas, e a consolidação da plataforma como infraestrutura são algumas das questões discutidas ao final do artigo. Nuestro objetivo en este trabajo es presentar y discutir la complejización del proceso de plataformización de periodismo por parte de Facebook, a partir de la implementación del Facebook Journalism Project (FJP), en enero de 2017. Desde entonces, la plataforma se ha ido asociando con nuevos y variados actores, ampliando sus frentes y posicionándose como coordinadora de actividades relacionadas con las instituciones periodísticas. Al mismo tiempo, continuó ofreciéndose como infraestructura para el desarrollo de productos y negocios periodísticos. Basados en los Estudios de Plataforma e inspirados metodológicamente en la Cartografía de Controversias, presentamos el FJP y demostraciones públicas de periodistas, investigadores y otros actores interesados en su implementación. La diversificación de las alianzas, la inclusión de acciones pedagógicas, la renegociación de las dimensiones prescriptivas y normativas que orientan las instituciones periodísticas, y la consolidación de la plataforma como infraestructura son algunos de los temas discutidos al final del artículo.

This study puts forward the results of a comprehensive literature review that allows of the exploration of the big data phenomenon as in technical terms as well in socio-political and philosophical ones, through the reading of authors such as Rob Kitchin (2014), Dawn E. Holmes (2017), and so forth. It is here offered a new critical approach to Big Data as long as the analysis have permitted us to evaluate not only the components of this new data science, but also the onto-epistemological consequences derived from the development and implementation of Big Data as in the scientific field as well in the quotidian. Also, this paper permits us to understand the linkage between Big Data and set theory in the construction of an onto-epistemology related to a political conservatism so that we are able to have the complete panorama in order to elaborate, in the near future, strategies to sublate such a phenomenon.

This article aims to present a debate over the increasingly complex and widespread use of measurement indicators and performance of digital content in the journalistic industry, considering the case study of La Nación, one of the leading news institutions in Argentina. The paper reconstructs the introduction and architecture of metrics measurement in the newsroom of La Nación, and the journalists’ perceptions and experiences regarding these organizational changes. The focus will be on the adoption of the Score, an algorithmic metric developed in-house at La Nación, designed with journalistic input and eventually modified to include economic factors. The findings confirming the tensions between professional and commercial logics produced by adopting digital metrics in the newsroom; and suggesting that journalists experiences metrics as strong disciplining influence. All this is involved in an uncertain context implicating the financing of Argentinean digital media along with the decline in the traditional journalistic business model.

In the era of the data revolution (Kitchin, 2014), new kinds of data and data sources allow researchers to share innovative ways of studying society and its dynamics to comprehend the peculiarities related to the territory. In fact, the analysis of space-time data extracted from social media can support the comprehension of complex social phenomena such as, for example, mobility (Noulas, Scellato, Lathia, & Mascolo, 2012; Yuan et al., 2017; Zhang et al., 2016) or where and when certain social activities are carried out, such e.g., the participation in big events, tourist experiences or the monitoring and management of emergencies and security. Following the actual dissemination of use of social media in the cities, the analysis of the spatial dimension is considered particularly promising in the field of urban analysis (Singleton et al., 2018) and in the emerging line of digital studies. Nowadays, the intentional action of many people is increasingly contributing to the production and sharing of spatial data with a relevant impact on the construction of Territorial Information Systems (Zupi, 2017). This new category of spatial data is commonly known "Volunteered Geographic Information" (VGI) (Goodchild, 2007). The analysis of this kind of data leads to an innovative scenario for the collection and diffusion of geographic information from millions of users all over the world. It provides valuable insight into their perceptions and needs, opinions on places, events, and daily routes, which allow researchers to better follow traces about the knowledge of the local identities of a given place (Campaign, 2014), information flows, and social networks within society (Stefanidis et al., 2013). However, a clear awareness of the limits of these tools of investigation is needed. For instance, problems may arise regarding representativeness of population, or even technical issues, such as for scarping systems which are not able to offer all the effective amount of data available to the researcher. Despite this, these kinds of studies are taking hold in the social sciences which are paying particular attention to both data and source contextualisation. As a result, they are interesting and valid tools to study issues that classic instruments are not able to perform. Among the different kinds of digital platforms, Twitter allows the combination of textual and geo-referenced data, making this platform an interesting choice, for instance, to detect or monitor different kinds of events (Korkmaz et al.,2015), or it could be used to study the dissemination of influence (Generous et al., 2014). Algorithms are, in this way, extraordinary tools for organising and spreading information. According to these claims, our work aims to understand, both theoretically and methodologically, how the research about territory, as a field of study, has been adapted to prolifically use data coming from algorithms of geo-location or geoparsing (Middleton et al, 2018).Specifically, this work aims to critically discuss the elements and the steps that characterize this emerging approach in order to highlight how the use of geo-localized data can be advantageous for territorial analysis and for which kinds of phenomena..Thus, after showing the most commonly used ways of collecting information about territory using algorithms, we will discuss strategies and techniques of analysis used to combine online (social media) and offline (territorial) sources and try to identify the possible applications for each type of technique. Moreover, a third step allows us to identify the different meanings and operational processes made regarding the concept of territory. That will allow us to recognize the different conceptions of sociological space emerging from the analysis and suggest how to avoid the use of geo-localized data with a simple data-driven perspective (Kitchin, 2014) that does not consider the sociological peculiarities of the space. We will try to answer these questions by examining papers that used Twitter as the source of data. In particular, the analysis of articles will be led thanks to a third kind of content analysis following Rositi’s categorisation (Rositi, 1988). Also, the extraction of the articles will be made using PRISMA methodology (Moher et. Al, 2018) for systematic review.