Actualización en técnicas de la cirugía de cataratas. Revisión bibliográfica

A. Valorar la evolución de las diferentes técnicas quirúrgicas a lo largo de la historia de la cirugía de catarata B. Evaluar los diferentes avances en la obtención de la potencia de LIO más adecuada y las lentes intraoculares C. Ventajas e Inconvenientes de las técnicas más avanzadas de la cirugía de cataratas: La importancia de la formación en técnicas quirúrgicas oftalmológicas. D. Guía de cuidados de enfermería específicos para la cirugía de cataratas.Máster en Enfermería Oftalmológic

A Global Positioning System Used to Monitor the Physical Performance of Elite Beach Handball Referees in a Spanish Championship

Beach handball is a fully developed sporting discipline on all five continents which has attracted the attention of researchers in the last decade, resulting in a proliferation of different studies focusing on players but not on referees. The main objective of this cross-sectional research was to determine the physical demands on elite male beach handball referees in four different competitions: U18 male; U18 female; senior male; and senior female. Twelve elite federated male referees (age: 30.86 ± 8 years; body height: 175.72 ± 4.51 cm; body weight: 80.18 ± 17.99 kg; fat percentage: 20.1 ± 4.41%; national or international experience) belonging to the Technical Committee of the Royal Spanish Handball Federation were recruited for this the study. The physical demands required of referees in official matches were measured by installing a GPS device. The sampling frequency used to record their speed and distance was 15 Hz. A triaxial accelerometer (100 Hz) was used to determine their acceleration. An analysis of variance (ANOVA) between competitions with post hoc comparisons using the Bonferroni adjustment was used to compare among categories. A higher distance covered in zone 1 and speeds of 0 to 6 km-h−1 were recorded. Most accelerations and decelerations occurred in zones 0 and 1 (zone 0: 0 to 1 m·s−2; zone 1: 1 to 2 m·s−2). The lack of differences (p > 0.05) between most analysed variables suggest quite similar physical demands of the four analysed competitions. These results provide relevant information to design optimal training plans oriented to the real physical demands on referees in an official competition

Online cheaters: Profiles and motivations of internet users who falsify their data online

The digital environment, which includes the Internet and social networks, is propitious for digital marketing. However, the collection, filtering and analysis of the enormous, constant flow of information on social networks is a major challenge for both academics and practitioners. The aim of this research is to assist the process of filtering the personal information provided by users when registering online, and to determine which user profiles lie the most, and why. This entailed conducting three different studies. Study 1 estimates the percentage of Spanish users by stated sex and generation who lie the most when registering their personal data by analysing a database of 5,534,702 participants in online sweepstakes and quizzes using a combination of error detection algorithms, and a test of differences in proportions to measure the profiles of the most fraudulent users. Estimates show that some user profiles are more inclined to make mistakes and others to forge data intentionally, the latter being the majority. The groups that are most likely to supply incorrect data are older men and younger women. Study 2 explores the main motivations for intentionally providing false information, and finds that the most common reasons are related to amusement, such as playing pranks, and lack of faith in the company's data privacy and security measures. These results will enable academics and companies to improve mechanisms to filter out cheaters and avoid including them in their databases

What's on the horizon? A bibliometric analysis of personal data collection methods on social networks

In Digital Marketing, the capture of consumers' personal data from social networks is essential for better targeting of commercial actions. The methods for collecting this information are arousing growing interest among the scientific community. This paper offers a comprehensive review of the literature on the issue and its management. To this end, a bibliometric study of 866 publications on the Web of Science between 1997 and 2022 was conducted to identify the most relevant trends through analysis of the most significant articles, keywords, authors, institutions and countries. In addition, visualisation software (VOS) was used to illustrate the relationships established through bibliographic coupling, keyword co-occurrence, authors and co-citation. The results indicate that the USA and Australia are the countries that publish the most in this field, while Finland and Australia have the highest number of publications per capita. Finally, the progress of research is discussed and future research directions are suggested

Cooperativas, sociedades laborales y mutualidades de previsión social: 25 años de progreso de la economía social de mercado bajo la constitución de 1978

This paper analyses the evolution of the leading market social economy organisations in Spain since the Constitution of 1978. The first part concerns a study of co-operatives and workers societies; the second refers to mutual societies. An analysis of the institutional framework, this sector's quantitative evolution, the responses to changes in the business background and the social impact of their activities enable us to conclude that over the period studied these companies have very significantly reinforced their position in the market. At the same time, they have consolidated their institutional recognition and their social image. Nevertheless, this very positive result should not obscure certain structural problems limiting their potential for development. The fragmentation of the three sub-sectors examined and the differences in legal treatment in financial and tax matters affecting mutual societies are questions that have to be resolved over coming years, with the aim of improving the competitive position of these organisations.co-operatives, worker associations, mutual societies, market social economy.

Influence of the structural components of artificial turf systems on impact attenuation in amateur football players

The purpose of this research was to evaluate the infuence of the structural components of diferent 3rd generation artifcial turf football feld systems on the biomechanical response of impact attenuation in amateur football players. A total of 12 amateur football players (24.3±3.7 years, 73.5±5.5kg, 178.3±4.1cm and 13.7±4.3 years of sport experience) were evaluated on three third generation artifcial turf systems (ATS) with diferent structural components. ATS were composed of asphalt subbase and 45mm of fbre height with (ATS1) and without (ATS2) elastic layer or compacted granular sub-base, 60mm of fbre height without elastic layer (ATS3). Two triaxial accelerometers were frmly taped to the forehead and the distal end of the right tibia of each individual. The results reveal a higher force reduction on ATS3 in comparison to ATS1 (+6.24%, CI95%: 1.67 to 10.92, ES: 1.07; p<0.05) and ATS2 (+21.08%, CI95%: 16.51 to 25.66, ES: 2.98; p<0.05) elastic layer. Tibia acceleration rate was lower on ATS3 than ATS1 (−0.32, CI95%: −0.60 to −0.03, ES: 4.23; p<0.05) and ATS2 (−0.35, CI95%: −0.64 to −0.06; ES: 4.69; p<0.05) at 3.3m/s. A very large correlation (r=0.7 to 0.9; p<0.05) was found between energy restitution and fbre height in both head and tibial peak acceleration and stride time. In conclusion, structural components (fbre height, infll, sub-base and elastic layer) determine the mechanical properties of artifcial turf felds. A higher force reduction and lower energy restitution diminished the impact received by the player which could protect against injuries associated with impacts compared to harder artifcial turf surfaces

Anthropometric Dimensions and Bone Quality in International Male Beach Handball Players: Junior vs. Senior Comparison

Background: Beach handball is a recent team sport characterized by defensive and offensive actions on a sand surface. Scientific evidence has shown that body composition is fundamental in sports performance. The main objective of this study was to know the body composition, anthropometric characteristics, and bone mineral density of elite beach handball players. Furthermore, another purpose was to analyze the differences between categories (junior and senior) and playing position. Methods: A descriptive, cross-sectional study of 36 male players (18 juniors and 18 seniors) of the Spanish National Beach Handball Team was conducted. Full profile anthropometry and calcaneal ultrasound measurements were used. Results: Significant differences between categories (p < 0.05) were found in: height, body mass, arm span, BMI, muscle mass, fat mass, bone mass, skinfolds, and body perimeters. The somatotype changes depending on the playing position. Bone mineral density of the players was adequate. No significant differences were found by playing position. Conclusions: Senior players had a better body composition due to the presence of less fat mass than junior players. This study provides reference values of elite junior and senior beach handball players and by playing positions. This data is useful for the identification of talents and players who should be trained to improve their body composition

Global Positioning System Analysis of Physical Demands in Elite Women’s Beach Handball Players in an Official Spanish Championship

This cross-sectional study aims to analyze the physical demands of elite beach handball players during an official competition. Nine elite female (mean age: 24.6 ± 4.0 years; body weight: 62.4 ± 4.6 kg; body height: 1.68 ± 0.059 m; training experience: 5 years; training: 6 h/week) beach handball players of the Spanish National Team were recruited for this study. A Global Positioning System was incorporated on each player’s back to analyze their movement patterns. Speed and distance were recorded at a sampling frequency of 15 Hz, whereas acceleration was recorded at 100 Hz by means of a built-in triaxial accelerometer. The main finding of the study is that 53% of the distance travelled is done at speeds between 1.5 and 5 km/h and 30% of the distance is between 9 and 13 km/h (83% of the total distance covered), which shows the intermittent efforts that beach handball involves at high intensity, as reflected in the analysis of the internal load with 62.82 ± 14.73% of the game time above 80% of the maximum heart rate. These data help to orientate training objectives to the physical demands required by the competition in order to optimize the players’ performance

Using Machine-Learning Algorithms for Eutrophication Modeling: Case Study of Mar Menor Lagoon (Spain)

[EN] The Mar Menor is a hypersaline coastal lagoon with high environmental value and a characteristic example of a highly anthropized hydro-ecosystem located in the southeast of Spain. An unprecedented eutrophication crisis in 2016 and 2019 with abrupt changes in the quality of its waters caused a great social alarm. Understanding and modeling the level of a eutrophication indicator, such as chlorophyll-a (Chl-a), benefits the management of this complex system. In this study, we investigate the potential machine learning (ML) methods to predict the level of Chl-a. Particularly, Multilayer Neural Networks (MLNNs) and Support Vector Regressions (SVRs) are evaluated using as a target dataset information of up to nine different water quality parameters. The most relevant input combinations were extracted using wrapper feature selection methods which simplified the structure of the model, resulting in a more accurate and efficient procedure. Although the performance in the validation phase showed that SVR models obtained better results than MLNNs, experimental results indicated that both ML algorithms provide satisfactory results in the prediction of Chl-a concentration, reaching up to 0.7 R-CV(2) (cross-validated coefficient of determination) for the best-fit models.This research was partially funded by the Fundacion Seneca del Centro de Coordinacion de la Investigacion de la Region de Murcia under Project 20813/PI/18, and by Spanish Ministry of Science, Innovation and Universities under grants RTI2018-096384-B-I00 and RTC-2017-6389-5.Jimeno-Sáez, P.; Senent-Aparicio, J.; Cecilia-Canales, JM.; Pérez-Sánchez, J. (2020). Using Machine-Learning Algorithms for Eutrophication Modeling: Case Study of Mar Menor Lagoon (Spain). International Journal of Environmental research and Public Health (Online). 17(4):1-14. https://doi.org/10.3390/ijerph17041189S114174Pérez-Ruzafa, A., Pérez-Ruzafa, I. M., Newton, A., & Marcos, C. (2019). 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Hydrology Research, 48(5), 1214-1225. doi:10.2166/nh.2016.149Charulatha, G., Srinivasalu, S., Uma Maheswari, O., Venugopal, T., & Giridharan, L. (2017). Evaluation of ground water quality contaminants using linear regression and artificial neural network models. Arabian Journal of Geosciences, 10(6). doi:10.1007/s12517-017-2867-6Keller, S., Maier, P., Riese, F., Norra, S., Holbach, A., Börsig, N., … Hinz, S. (2018). Hyperspectral Data and Machine Learning for Estimating CDOM, Chlorophyll a, Diatoms, Green Algae and Turbidity. International Journal of Environmental Research and Public Health, 15(9), 1881. doi:10.3390/ijerph15091881Li, X., Sha, J., & Wang, Z.-L. (2017). Chlorophyll-A Prediction of Lakes with Different Water Quality Patterns in China Based on Hybrid Neural Networks. Water, 9(7), 524. doi:10.3390/w9070524Yi, H.-S., Park, S., An, K.-G., & Kwak, K.-C. (2018). Algal Bloom Prediction Using Extreme Learning Machine Models at Artificial Weirs in the Nakdong River, Korea. 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Assessing the Hydrodynamic Response of the Mar Menor Lagoon to Dredging Inlets Interventions through Numerical Modelling. Water, 10(7), 959. doi:10.3390/w10070959Wei, B., Sugiura, N., & Maekawa, T. (2001). Use of artificial neural network in the prediction of algal blooms. Water Research, 35(8), 2022-2028. doi:10.1016/s0043-1354(00)00464-4(2000). Artificial Neural Networks in Hydrology. I: Preliminary Concepts. Journal of Hydrologic Engineering, 5(2), 115-123. doi:10.1061/(asce)1084-0699(2000)5:2(115)Jimeno-Sáez, P., Senent-Aparicio, J., Pérez-Sánchez, J., & Pulido-Velazquez, D. (2018). A Comparison of SWAT and ANN Models for Daily Runoff Simulation in Different Climatic Zones of Peninsular Spain. Water, 10(2), 192. doi:10.3390/w10020192Nguyen, V. D., Tan, R. R., Brondial, Y., & Fuchino, T. (2007). Prediction of vapor–liquid equilibrium data for ternary systems using artificial neural networks. 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