CICLOBIOMA: Proyecto Aprendizaje-Servicio Universidad Complutense de Madrid

CICLOBIOMA es un Proyecto de Aprendizaje-Servicio de la Universidad Complutense de Madrid en el marco de la “Convocatoria Proyectos Aprendizaje-Servicio Complutense 2019” y del Convenio suscrito entre la Universidad Complutense de Madrid y el Ayuntamiento de Madrid de 4 de julio de 2017 para impulsar proyectos basados en el aprendizaje-servicio. CICLOBIOMA consiste en el planteamiento y el desarrollo experimental de soluciones a problemas científicos con enorme proyección y calado social, que se enmarcan en los Objetivos del Desarrollo Sostenible (ODS 11 y 12) y que tienen como meta reducir el impacto ambiental negativo de las ciudades mediante el aprovechamiento de residuos agroalimentarios para la producción de biomateriales y para la obtención de compuestos de alto valor en diferentes industrias

Transcriptional analysis of Rhazya stricta in response to jasmonic acid

Background: Jasmonic acid (JA) is a signal transducer molecule that plays an important role in plant development and stress response; it can also efficiently stimulate secondary metabolism in plant cells. Results: RNA-Seq technology was applied to identify differentially expressed genes and study the time course of gene expression in Rhazya stricta in response to JA. Of more than 288 million total reads, approximately 27% were mapped to genes in the reference genome. Genes involved during the secondary metabolite pathways were up- or downregulated when treated with JA in R. stricta. Functional annotation and pathway analysis of all up- and downregulated genes identified many biological processes and molecular functions. Jasmonic acid biosynthetic, cell wall organization, and chlorophyll metabolic processes were upregulated at days 2, 6, and 12, respectively. Similarly, the molecular functions of calcium-transporting ATPase activity, ADP binding, and protein kinase activity were also upregulated at days 2, 6, and 12, respectively. Time-dependent transcriptional gene expression analysis showed that JA can induce signaling in the phenylpropanoid and aromatic acid pathways. These pathways are responsible for the production of secondary metabolites, which are essential for the development and environmental defense mechanism of R. stricta during stress conditions. Conclusions: Our results suggested that genes involved in flavonoid biosynthesis and aromatic acid synthesis pathways were upregulated during JA stress. However, monoterpenoid indole alkaloid (MIA) was unaffected by JA treatment. Hence, we can postulate that JA plays an important role in R. stricta during plant development and environmental stress conditions. How to cite: Hajrah, NH, Rabah SO, Alghamdi MK, et al. Transcriptional analysis of Rhazya stricta in response to jasmonic acid. Electron J Biotechnol 2021;50. https://doi.org/10.1016/j.ejbt.2021.01.00

EstuPlan: Methodology for the development of creativity in the resolution of scientific and social problems

Creative thinking is necessary to generate novel ideas and solve problems."EstuPlan" is a methodology in which knowledge and creativity converge for the resolution of scientific problems with social projection. It is a training programme that integrates teachers, laboratory technicians and PhD students, master and undergraduate students which form working groups for the development of projects. Projects have a broad and essential scope and projection in terms of environmental problems, sustainable use of natural resources, food, health, biotechnology or biomedicine. The results show the success of this significant learning methodology using tools to develop creativity in responding to scientific and social demand for problem-solving to transfer academic knowledge to different professional environments. Bioplastics, Second Life of Coffee, LimBio, Algae oils, Ecomers, Caring for the life of your crop and Hate to Deforestate are currently being developed

Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020

EstuPlan: Methodology for the development of creativity in the resolution of scientific and social problems

[EN] Creative thinking is necessary to generate novel ideas and solve problems. "EstuPlan" is a methodology in which knowledge and creativity converge for the resolution of scientific problems with social projection. It is a training programme that integrates teachers, laboratory technicians and PhD students, master and undergraduate students which form working groups for the development of projects. Projects have a broad and essential scope and projection in terms of environmental problems, sustainable use of natural resources, food, health, biotechnology or biomedicine. The results show the success of this significant learning methodology using tools to develop creativity in responding to scientific and social demand for problem-solving to transfer academic knowledge to different professional environments. Bioplastics, Second Life of Coffee, LimBio, Algae oils, Ecomers, Caring for the life of your crop and Hate to Deforestate are currently being developed.Astudillo Calderón, S.; De Díez De La Torre, L.; García Companys, M.; Ortega Pérez, N.; Rodríguez Martínez, V.; Alzahrani, S.; Alonso Valenzuela, R.... (2019). EstuPlan: Methodology for the development of creativity in the resolution of scientific and social problems. En HEAD'19. 5th International Conference on Higher Education Advances. Editorial Universitat Politècnica de València. 711-717. https://doi.org/10.4995/HEAD19.2019.9205OCS71171

Detection of Distributed Denial of Service (DDOS) Attacks Using Artificial Neural Networks on Cloud

This dissertation proposes a technique for detecting a significant threat to the availability of cloud services. By definition, a Distributed Denial of Service Attack (DDoS) refers to an attack in which multiple systems compromised by Trojan are maliciously used to target a single system. The attack leads to the denial of a particular service on the target system. In a DDoS attack, the target system and the systems used to perform the attack are all victims of the action. First, we present a survey of the various mechanisms, both traditional and modern, that are applied in detecting cloud-based DDoS attacks. We then propose a DDoS detection system using artificial neural networks that will detect known and unknown DDoS attacks with integration with signatures approach. The proposed method has two major subsystems: (1) Data collection: a traffic generator has been developed to collect data corresponding to different DDoS types, and (2) distributed DDoS detection: two different approaches are used; a neural network algorithm, as anomaly- based detection and signature based detection. The Amazon public cloud was used for running the fast cluster engine with varying cores of machines. The experiment results achieved the highest accuracy and detection rate compared to signature-based or neural networks-based approach. The findings in this research can be extended to allow the application of the proposed technology for bigger network traffic

Scalable network traffic analysis on cloud computing platform

Understanding and quantifying network performance usually requires the analysis of a large volume of network traffic. Current network analysis does not scale well during the analysis of Terabyte or Petabyte traffic. Due to the emergence of a distributed computing platform, Spark facilitates the analysis of a large volume of data. However, there is no seamless method to analyze the vast volume of network traffic. In this study, the network traffic analysis framework on Amazon cloud computing environment has been developed. Different network scenarios were created in CloudSim to analyze the generated network traffic using scalable clustering machine learning techniques. The proposed system has two major subsystems; (i) data collection: the generation of different network traffic corresponding to different network topologies; and (ii) data analysis and distributed processing: Amazon EC2 was used for running the Spark program with different machine cores. The model took place on Spark MLlib and used three different clustering algorithms. The scalable K-means++ (K-means::) clustering algorithm was selected based in its speed and scalability for testing the system. It was faster than K-means and than GMM. The time for the analysis of K-means:: is 30.10% less than K-means and 75.18% less than for GMM algorithm for 150 million-line records of data. These findings allow the application of this technology for more complex problems with vast network traffic and large network topologies

Actividad antioxidante de Mentha longifolia L. y sus aplicaciones

"Introducción" Mentha longifolia L. tiene una amplia distribución geográfica que puede considerarse un signo de adaptabilidad que se refleja en la existencia de diferentes quimiotipos. Además de sus usos tradicionales se podrían explorar otras alternativas. "Objetivos y resultados" El material vegetal es un quimiotipo de M. longifolia L. de Arabia Saudita y el objetivo principal es analizar sus posibles usos alternativos. Para alcanzar este objetivo se va a analizar la capacidad antioxidante del extracto acuoso (Té) de M. longifolia L. Además, se realizará el análisis de su composición fitoquímica para identificar los diferentes metabolitos implicados en su capacidad antioxidante. Entre los objetivos parciales se encuentran: - Incrementar la concentración de algunos fitoquímicos mediante la elicitación tanto biótica como abiótica en el cultivo de las plantas de M. longifolia L. - Estudiar el posible uso del té de M. longifolia L. en el control biológico del hongo fitopatógeno responsable de la antracnosis del olivo, C. gloesporioides. - Estudiar el posible uso del té de M. longifolia L. en la síntesis verde de nanopartículas de plata