Social support, self-efficacy and academic satisfaction of university students during the COVID-19 lockdown

This work aimed to analyze the relationships between the students perceived institutional support, teachers’ support, peers’ support, and their academic satisfaction, mediated by their self-efficacy in information and comunication technologies (ICT). Participants were 157 students who were studying from first to fourth year in different disciplines of the Valencia University. Structural equation models with latent factors were tested. A final model had satisfactory fit indices to the observed data. It is worth highlighting the strong direct effect of the teaching staff support on student’ academic satisfaction, with less weight, although significant, being the effect of institutional support. In conclusion, teacher’s figure is of paramount importance for student’s academic satisfaction.Este trabajo tuvo como objetivo analizar las relaciones entre el apoyo institucional percibido por los estudiantes, el apoyo de los profesores, el apoyo de los compañeros y su satisfacción académica, mediada por su autoeficacia en las tecnologías de la información y la comunicación (TIC). Participaron 157 estudiantes que cursaban de primero a cuarto año en diferentes disciplinas de la Universidad de Valencia. Se probaron modelos de ecuaciones estructurales con factores latentes. El modelo final aportó índices de ajuste satisfactorios a los datos observados. Cabe destacar el fuerte efecto directo del apoyo del profesorado sobre la satisfacción académica de los estudiantes, mientras que tuvo menor peso, aunque también significativo, el efecto del apoyo institucional. En conclusión, la figura del docente es de suma importancia para la satisfacción académica de los estudiantes

An intelligent self-configurable mechanism for distributed energy storage systems

Next generation of smart grid technologies demand intel- ligent capabilities for communication, interaction, monitoring, storage, and energy transmission. Multiagent systems are envisioned to provide autonomic and adaptability features to these systems in order to gain advantage in their current environments. In this paper we present a mechanism for providing distributed energy storage systems (DESSs) with intelligent capabilities. In more detail, we propose a self-con gurable mechanism which allows a DESS to adapt itself according to the future environmental requirements. This mechanism is aimed at reducing the costs at which energy is purchased from the market.This work has been partially supported by projects TIN2012-36586-C03-01 and TIN2011-27652-C03-01.Alberola Oltra, JM.; Julian Inglada, VJ.; García-Fornes, A. (2014). An intelligent self-configurable mechanism for distributed energy storage systems. Cybernetics and Systems. 45(3):292-305. https://doi.org/10.1080/01969722.2014.894859S292305453Abbey , C. and G. Joos . “Coordination of Distributed Storage with Wind Energy in a Rural Distribution System.” Paper presented at Industry Applications Conference, 42nd IAS Annual Meeting, September 23–27, 2007, New Orleans, USA .Alberola , J. M. , V. Julian , and A. Garcia-Fornes . “Multi-Dimensional Transition Deliberation for Organization Adaptation in Multiagent Systems.” Paper presented at the 11th International Conference on Aut. Agents and MAS (AAMAS12), June 4–8, 2012, Valencia, Spain .Chouhan , N. S. and M. Ferdowsi . “Review of Energy Storage Systems.” Paper presented at North American Power Symposium (NAPS), October 4–6, 2009, Mississippi, USA.Conejo, A. J., Plazas, M. A., Espinola, R., & Molina, A. B. (2005). Day-Ahead Electricity Price Forecasting Using the Wavelet Transform and ARIMA Models. IEEE Transactions on Power Systems, 20(2), 1035-1042. doi:10.1109/tpwrs.2005.846054Costa , L. , F. Bourry , J. Juban , and G. Kariniotakis . “Management of Energy Storage Coordinated with Wind Power under Electricity Market Conditions.” Paper presented at 10th International Conference on Probabilistic Methods Applied to Power Systems, May 25–29, 2008, Rincón, Puerto Rico .Eyer , J. and G. Corey . “Energy Storage for the Electricity Grid: Benefits and Market Potential Assessment Guide.” Sandia National Laboratories, 2010. Technical Report .Jiang , Z. “Agent-Based Control Framework for Distributed Energy Resources Microgrids.” Paper presented at International Conference on Intelligent Agent Technology, December 18–22, 2006, Hong Kong .Karnouskos , S. and T. N. De Holanda . “Simulation of a Smart Grid City with Software Agents.” Paper presented at Third UKSim European Symposium on Computer Modeling and Simulation, November 25–27, 2009, Athens, Greece .Ketter, W., Collins, J., & Reddy, P. (2013). Power TAC: A competitive economic simulation of the smart grid. Energy Economics, 39, 262-270. doi:10.1016/j.eneco.2013.04.015Lakshman, A., & Malik, P. (2010). Cassandra. ACM SIGOPS Operating Systems Review, 44(2), 35. doi:10.1145/1773912.1773922Logenthiran, T., Srinivasan, D., Khambadkone, A. M., & Aung, H. N. (2012). Multiagent System for Real-Time Operation of a Microgrid in Real-Time Digital Simulator. IEEE Transactions on Smart Grid, 3(2), 925-933. doi:10.1109/tsg.2012.2189028Maly, D. K., & Kwan, K. S. (1995). Optimal battery energy storage system (BESS) charge scheduling with dynamic programming. IEE Proceedings - Science, Measurement and Technology, 142(6), 453-458. doi:10.1049/ip-smt:19951929Mihailescu , R. C. , M. Vasirani , and S. Ossowski . “Dynamic Coalition Formation and Adaptation for Virtual Power Stations in Smart Grids.” Paper presented at 2nd International Workshop on Agent Technologies for Energy Systems, May 2, 2011, Taipei, Taiwan .Mohd , A. , E. Ortjohann , A. Schmelter , N. Hamsic , and D. Morton . “Challenges in Integrating Distributed Energy Storage Systems into Future Smart Grid.” Paper presented at IEEE International Symposium on Industrial Electronics, June 30–July 2, 2008, Cambridge, UK .Mohsenian-Rad, A.-H., & Leon-Garcia, A. (2010). Optimal Residential Load Control With Price Prediction in Real-Time Electricity Pricing Environments. IEEE Transactions on Smart Grid, 1(2), 120-133. doi:10.1109/tsg.2010.2055903Momoh , J. A. “Smart Grid Design for Efficient and Flexible Power Networks Operation and Control.” Paper presented at IEEE PES Power Systems Conference and Exposition, March 15–18, 2009, Seattle, USA .Nguyen, C. P., & Flueck, A. J. (2012). Agent Based Restoration With Distributed Energy Storage Support in Smart Grids. IEEE Transactions on Smart Grid, 3(2), 1029-1038. doi:10.1109/tsg.2012.2186833Nourai , A. “Installation of the First Distributed Energy Storage System (DESS) At American Electric Power.” Sandia National Laboratories, 2007. Technical Report.Oyarzabal , J. , J. Jimeno , J. Ruela , A. Engler , and C. Hardt . “Agent Based Micro Grid Management System.” Paper presented at International Conference on Future Power Systems, November 16–18, 2005, Amsterdam, Netherlands .Pinson, P., Chevallier, C., & Kariniotakis, G. N. (2007). Trading Wind Generation From Short-Term Probabilistic Forecasts of Wind Power. IEEE Transactions on Power Systems, 22(3), 1148-1156. doi:10.1109/tpwrs.2007.901117Pipattanasomporn , M. , H. Feroze , and S. Rahman . “Multi-agent Systems in a Distributed Smart Grid: Design and Implementation.” Paper presented at IEEE/PES Power Systems Conference and Exposition, March 15–18, 2009, Seattle, USA .Reddy , P. P. and M. M. Veloso . “Factored Models for Multiscale Decision Making in Smart Grid Customers.” Paper presented at the Twenty-sixth AAAI Conference on Artificial Intelligence, July 22–26, 2012, Toronto, Canada .Ribeiro, P. F., Johnson, B. K., Crow, M. L., Arsoy, A., & Liu, Y. (2001). Energy storage systems for advanced power applications. Proceedings of the IEEE, 89(12), 1744-1756. doi:10.1109/5.975900Schutte , S. and M. Sonnenschein . “Mosaik-Scalable Smart Grid Scenario Specification.” Paper presented at Proceedings of the 2012 Winter Simulation Conference (WSC), December 9–12, 2012, Berlin, Germany .Sioshansi, R., Denholm, P., Jenkin, T., & Weiss, J. (2009). Estimating the value of electricity storage in PJM: Arbitrage and some welfare effects. Energy Economics, 31(2), 269-277. doi:10.1016/j.eneco.2008.10.005Szkuta, B. R., Sanabria, L. A., & Dillon, T. S. (1999). Electricity price short-term forecasting using artificial neural networks. IEEE Transactions on Power Systems, 14(3), 851-857. doi:10.1109/59.780895Van Dam, K. H., Houwing, M., Lukszo, Z., & Bouwmans, I. (2008). Agent-based control of distributed electricity generation with micro combined heat and power—Cross-sectoral learning for process and infrastructure engineers. Computers & Chemical Engineering, 32(1-2), 205-217. doi:10.1016/j.compchemeng.2007.07.012Vosen, S. (1999). Hybrid energy storage systems for stand-alone electric power systems: optimization of system performance and cost through control strategies. International Journal of Hydrogen Energy, 24(12), 1139-1156. doi:10.1016/s0360-3199(98)00175-xVytelingum , P. , T. D. Voice , S. Ramchurn , A. Rogers , and N. R. Jennings . “Agent-Based Micro-Storage Management for the Smart Grid.” Paper presented at Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems, May 10–14, 2010a, Toronto, Canada .Vytelingum , P. , T. D. Voice , S. Ramchurn , A. Rogers , and N. R. Jennings . “Intelligent Agents for the Smart Grid.” Paper presented at the 9th International Conference on Autonomous Agents and Multiagent Systems, May 10–14, 2010b, Toronto, Canada

Magnetic interactions in thiazyl-based magnets: The role of the charge and spin densities

The crystal structure of the organic radical p-O2NC6F4CNSSN was determined at 20 K through a single-crystal neutron-diffraction experiment. It crystallises in the tetragonal space group P41212, unchanged from a previous single-crystal X-ray diffraction experiment at 220 K although there are some changes in molecular geometry and intermolecular contacts arising from the contraction of the unit cell. Polarized neutron diffraction at 1.5 K revealed that the spin distribution is predominantly localised on the N and S atoms of the heterocyclic ring with a small negative spin density on the heterocyclic C atom. Spin populations determined using a multipolar analysis were -0.06, +0.25 and +0.28 on the C, N and S sites, respectively. These spin populations are in excellent agreement with both ab-initio DFT calculations (spin populations on the C, N and S sites of -0.07, 0.22 and 0.31, respectively) and cw-EPR studies which estimated the spin population on the N site as 0.24. The DFT calculated spin density revealed less than 1% spin delocalisation onto the perfluoroaryl ring, several orders of magnitude lower than the density on the heterocyclic ring. cw-ENDOR studies at both X-band (9 GHz) and Q-band (34 GHz) frequencies probed the spin populations at the two chemically distinct F atoms. These spin populations on the F atoms ortho and meta to the dithiadiazolyl ring are of magnitude 10-3 and 10-4 respectively. Additional high-resolution single-crystal X-ray diffraction studies at 100 K analysed within the atoms-in-molecules (AIM) framework gave detailed information on the charge density distributio

The Ras/MAPK Pathway Is Required for Generation of iNKT Cells

iNKT cells derive from CD4+CD8+ DP thymocytes, and are selected by thymocyte-thymocyte interactions through signals from their invariant Vα14-Jα18 TCR and from the costimulatory molecules SLAMF1 and SLAMF6. Genetic studies have demonstrated the contribution of different signaling pathways to this process. Surprisingly, current models imply that the Ras/MAPK pathway, one of the critical mediators of conventional αβ T cell positive selection, is not necessary for iNKT cell development. Using mice defective at different levels of this pathway our results refute this paradigm, and demonstrate that Ras, and its downstream effectors Egr-1 and Egr-2 are required for positive selection of iNKT cells. Interestingly our results also show that there are differences in the contributions of several of these molecules to the development of iNKT and conventional αβ T cells

Apoyo docente, compromiso académico y satisfacción del alumnado universitario

El objetivo es analizar la influencia del compromiso académico sobre la satisfacción de los estudiantes universitarios con su facultad, a partir del apoyo a la autonomía por el profesorado. Se administran escalas de Apoyo a la Autonomía, Compromiso Académico y Satisfacción con la Facultad, a 870 estudiantes universitarios dominicanos (50.6% hombres, 49.4% mujeres). Se aplican Análisis Factoriales Confirmatorios y Modelos de Ecuaciones Estructurales. Los resultados reflejan la influencia del apoyo a la autonomía por los profesores sobre la satisfacción con la facultad a través del compromiso académico, así como el efecto directo de la percepción de apoyo a la autonomía por los profesores sobre la satisfacción de los estudiantes universitarios con su centro educativo.The aim of this paper is to analyze the infl uence of academic engagement on university students’ satisfaction with their faculty from teachers’ autonomy support. Scales of Autonomy Support, Academic Engagement and Satisfaction with the Faculty are administered to 870 Dominican university students (50.6% male and 49.4% female). Confi rmatory Factor Analysis and Structural Equation Modelling are carried out. The results refl ect the infl uence of teachers’ autonomy support on the satisfaction with the faculty mediated by academic engagement, as well as the direct effect of perception of teachers’ autonomy support on university students’ satisfaction with their educational center

Apoyo docente, compromiso académico y satisfacción del alumnado universitario

El objetivo es analizar la influencia del compromiso académico sobre la satisfacción de los estudiantes universitarios con su facultad, a partir del apoyo a la autonomía por el profesorado. Se administran escalas de Apoyo a la Autonomía, Compromiso Académico y Satisfacción con la Facultad, a 870 estudiantes universitarios dominicanos (50.6% hombres, 49.4% mujeres). Se aplican Análisis Factoriales Confirmatorios y Modelos de Ecuaciones Estructurales. Los resultados reflejan la influencia del apoyo a la autonomía por los profesores sobre la satisfacción con la facultad a través del compromiso académico, así como el efecto directo de la percepción de apoyo a la autonomía por los profesores sobre la satisfacción de los estudiantes universitarios con su centro educativo.The aim of this paper is to analyze the infl uence of academic engagement on university students’ satisfaction with their faculty from teachers’ autonomy support. Scales of Autonomy Support, Academic Engagement and Satisfaction with the Faculty are administered to 870 Dominican university students (50.6% male and 49.4% female). Confi rmatory Factor Analysis and Structural Equation Modelling are carried out. The results refl ect the infl uence of teachers’ autonomy support on the satisfaction with the faculty mediated by academic engagement, as well as the direct effect of perception of teachers’ autonomy support on university students’ satisfaction with their educational center

A novel mitochondrial Kv1.3-caveolin axis controls cell survival and apoptosis

The voltage-gated potassium channel Kv1.3 plays an apparent dual physiological role by participating in activation and proliferation of leukocytes as well as promoting apoptosis in several types of tumor cells. Therefore, Kv1.3 is considered a potential pharmacological target for immunodeficiency and cancer. Different cellular locations of Kv1.3, at the plasma membrane or the mitochondria, could be responsible for such duality. While plasma membrane Kv1.3 facilitates proliferation, the mitochondrial channel modulates apoptotic signaling. Several molecular determinants of Kv1.3 drive the channel to the cell surface, but no information is available about its mitochondrial targeting. Caveolins, which are able to modulate cell survival, participate in the plasma membrane targeting of Kv1.3. The channel, via a caveolin-binding domain (CDB), associates with caveolin 1 (Cav1), which localizes Kv1.3 to lipid raft membrane microdomains. The aim of our study was to understand the role of such interactions not only for channel targeting but also for cell survival in mammalian cells. By using a caveolin association-deficient channel (Kv1.3 CDBless), we demonstrate here that while the Kv1.3-Cav1 interaction is responsible for the channel localization in the plasma membrane, a lack of such interaction accumulates Kv1.3 in the mitochondria. Kv1.3 CDBless severely affects mitochondrial physiology and cell survival, indicating that a functional link of Kv1.3 with Cav1 within the mitochondria modulates the pro-apoptotic effects of the channel. Therefore, the balance exerted by these two complementary mechanisms fine-tune the physiological role of Kv1.3 during cell survival or apoptosis. Our data highlight an unexpected role for the mitochondrial caveolin-Kv1.3 axis during cell survival and apoptosis

Neighbour-disjoint multipath for low-power and lossy networks

In this article, we describe a neighbour disjoint multipath (NDM) scheme that is shown to be more resilient amidst node or link failures compared to the two well-known node disjoint and edge disjoint multipath techniques. A centralised NDM was first conceptualised in our initial published work utilising the spatial diversity among multiple paths to ensure robustness against localised poor channel quality or node failures. Here, we further introduce a distributed version of our NDM algorithm adapting to the low-power and lossy network (LLN) characteristics. We implement our distributed NDM algorithm in Contiki OS on top of LOADng—a lightweight On-demand Ad hoc Distance Vector Routing protocol. We compare this implementation's performance with a standard IPv6 Routing Protocol for Low power and Lossy Networks (RPL), and also with basic LOADng, running in the Cooja simulator. Standard performance metrics such as packet delivery ratio, end-to-end latency, overhead and average routing table size are identified for the comparison. The results and observations are provided considering a few different application traffic patterns, which serve to quantify the improvements in robustness arising from NDM. The results are confirmed by experiments using a public sensor network testbed with over 100 nodes