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Background: Schools are high-risk settings for infectious disease transmission. Wastewater monitoring for infectious diseases has been used to identify and mitigate outbreaks in many near-source settings during the COVID-19 pandemic, including universities and hospitals but less is known about the technology when applied for school health protection. This study aimed to implement a wastewater surveillance system to detect SARS-CoV-2 and other public health markers from wastewater in schools in England. Methods: A total of 855 wastewater samples were collected from 16 schools (10 primary, 5 secondary and 1 post-16 and further education) over 10 months of school term time. Wastewater was analysed for SARS-CoV-2 genomic copies of N1 and E genes by RT-qPCR. A subset of wastewater samples was sent for genomic sequencing, enabling determination of the presence of SARS-CoV-2 and emergence of variant(s) contributing to COVID-19 infections within schools. In total, >280 microbial pathogens and >1200 AMR genes were screened using RT-qPCR and metagenomics to consider the utility of these additional targets to further inform on health threats within the schools. Results: We report on wastewater-based surveillance for COVID-19 within English primary, secondary and further education schools over a full academic year (October 2020 to July 2021). The highest positivity rate (80.4%) was observed in the week commencing 30th November 2020 during the emergence of the Alpha variant, indicating most schools contained people who were shedding the virus. There was high SARS-CoV-2 amplicon concentration (up to 9.2x106 GC/L) detected over the summer term (8th June - 6th July 2021) during Delta variant prevalence. The summer increase of SARS-CoV-2 in school wastewater was reflected in age-specific clinical COVID-19 cases. Alpha variant and Delta variant were identified in the wastewater by sequencing of samples collected from December to March and June to July, respectively. Lead/lag analysis between SARS-CoV-2 concentrations in school and WWTP data sets show a maximum correlation between the two-time series when school data are lagged by two weeks. Furthermore, wastewater sample enrichment coupled with metagenomic sequencing and rapid informatics enabled the detection of other clinically relevant viral and bacterial pathogens and AMR. Conclusions: Passive wastewater monitoring surveillance in schools can identify cases of COVID-19. Samples can be sequenced to monitor for emerging and current variants of concern at the resolution of school catchments. Wastewater based monitoring for SARS-CoV-2 is a useful tool for SARS-CoV-2 passive surveillance and could be applied for case identification and containment, and mitigation in schools and other congregate settings with high risks of transmission. Wastewater monitoring enables public health authorities to develop targeted prevention and education programmes for hygiene measures within undertested communities across a broad range of use cases.

This dissertation approaches network effects from different perspectives and methodologies. Social network effects of immigrants have an impact on the decision of their destination, the presence of this characteristic is exploited in the first chapter to statistically isolate the effect they have on the voting behavior of the district’s representative. Generally, more immigration is correlated with a more liberal voting behavior. The second chapter takes a theoretical approach, a network adoption model is constructed that deviates from the usual linear assumption and incorporates time of adoption and a type-dependent utility function that allows a different utility derivation dependent on the type of members in the networks and not only in size as the linear model assumes. Using simulations, it is found that more heterogeneous populations and the presence of early adopters allow the emergence of clusters and the survival of small platforms even in the presence of strong network effects.

This novel 360-degree video tutorial demonstrates mitral valve repair through a right antero-lateral minithoracotomy approach. Using integrative technology, the viewer can immerse themselves into the procedure by manipulating the directional viewpoint and magnification online via their computer���s mouse or finger scrolling on a tablet or smartphone device. The Procedure To start the procedure, anesthesia is provided per institution protocol. Single or double-lumen intubation is used, depending on case complexity. A transesophageal echocardiography (TOE) aids correct cannula placement, and anatomical and functional mitral valve views. Defibrillator pads are then placed across the chest wall, and patient positioning is supine with right chest elevation and right arm tucked laterally. Two Iron Assistant instrument holders are positioned on each side of the patient to hold the endoscopic camera and atriotomy retractor. Then, right femoral vessels are cannulated through a 3���4cm incision inferior to the inguinal ligament. Next, a multistage vacuum-assisted femoral venous cannula (Bio-Medicus-Medtronic, size 21Fr or 25Fr) and a straight flexible arterial cannula (Edwards Optisite, size 18Fr or 20Fr) are introduced via guidewire. TOE confirms correct placement, and the cannulas are connected to the cardiopulmonary bypass machine and bypass is commenced. A 4���6cm right submammary incision then enters the third or fourth intercostal space. An endoscopic 0-degree camera is introduced through a 10mm port, one space above the minithoracotomy. CO2 is then connected to this port. After this, the minithoracotomy is accessed by an Alexis wound retractor and a Geister rib retractor, with the latter placed atop a malleable plate to retract the diaphragm. Next, a pericardiotomy is performed one-third of the way back from the front of the pericardium. This leaves enough tissue for closing the pericardium later and permits a pericardial shelf that, laterally retracted, secures the right lung. The left atrium (LA) is exposed by placing two suture retractors in the posterior pericardial tissue, and a third suture in the interatrial groove, with the latter exteriorized through a 5mm anterior chest port just lateral to the sternal border. The ascending aorta is then cannulated endoscopically with two pledgeted purse string sutures. Using one of these sutures, a root cannula is inserted, connecting to the cardioplegia and vent line respectively. A detachable Glauber clamp is placed into the ascending aorta, and anterograde cardioplegia delivered into the aortic root. Then a left atriotomy is performed. A detachable atrial lift retractor (ValveGate Tm-Geister) is placed and secured through the parasternal port. The existing plate is repositioned over the diaphragm into the inferior-posterior LA wall. Adequate venting is achieved by continuous suction through the aortic root and by placing a malleable cannula in one of the pulmonary veins. This results in good and direct visualization of the mitral valve. The video accompanying this article presents two cases. The first shows redundant posterior leaflet with P1 and P2 prolapse, and a competent P3 and anterior leaflet. The valve is repaired by trimming the prolapsed P1 chordae and resecting a wedge of P2, and the gap is repaired with continuous Prolene suture. The second case shows a prolapsing P2 from chordae rupture. A fabricated neochordae is implanted spanning from the papillary muscle to the edge of the leaflet. The neochordae is created using the ValveGate Mohr ruler, which facilitates the creation of the loops with Gore-Tex suture. In both cases, a semirigid complete mitral ring is placed with interrupted sutures. A water pressure test shows good valve competence. The atriotomy is then closed. Ventricular pacing wires are positioned and exteriorized through the parasternal port. The cross-clamp is then removed after deairing maneuvers, but the aortic root vent is kept in as long as possible to facilitate complete deairing. Following cardiac reperfusion and echocardiographic assessment, the root cannula is removed and the two purse sutures knotted. The pericardium is then approximated with interrupted sutures. A drain is placed one or two intercostal spaces below the minithoracotomy. Femoral decannulation is completed once the patient is stable. The purse strings are then knotted, with occasional placement of an extra haemostatic suture. The minithoracotomy and groin access are then closed in layers.References 1. Speziale G, Santarpino G, Moscarelli M, et al. Minimally invasive mitral valve reconstruction: Is it an "all-comers" procedure? Journal of cardiac surgery. 2021. 2. Modi P, Hassan A, Chitwood WR, Jr. Minimally invasive mitral valve surgery: a systematic review and meta-analysis. Eur J Cardiothorac Surg. 2008;34(5):943-952. 3. Cetinkaya A, Geier A, Bramlage K, et al. Long-term results after mitral valve surgery using minimally invasive versus sternotomy approach: a propensity matched comparison of a large single-center series. BMC cardiovascular disorders. 2021;21(1):314. 4. Dokollari A, Cameli M, Kalra D-KS, et al. Learning curve predictors for minimally invasive mitral valve surgery; how far should the rabbit hole go? Journal of cardiac surgery. 2020;35(11):2934-2942. 5. Holzhey DM, Shi W, Borger MA, et al. Minimally invasive versus sternotomy approach for mitral valve surgery in patients greater than 70 years old: a propensity-matched comparison. Ann Thorac Surg. 2011;91(2):401-405.

La elección de una carrera es una decisión importante a las que se enfrentan los jóvenes en su proceso de formación, no es una tarea sencilla, y en muchas ocasiones el estudiante no cuenta con las herramientas o con la asistencia en orientación vocacional que permitan la toma de decisión de una carrera. De esta forma, el presente proyecto aborda la problemática de la poca orientación vocacional y a su vez la poca promoción de las áreas STEM. A partir de esta necesidad identificada la propuesta central del proyecto es diseñar e implementar un prototipo de una aplicación web empleando técnicas de Data Mining para la orientación vocacional y promoción de carreras STEM. Para el desarrollo del prototipo se implementó la metodología SCRUM, la cual fue seleccionada debido a la flexibilidad, la obtención oportuna de resultados y rápido aprendizaje, que permitieron desarrollar de forma integral las fases de requerimientos e investigación, construcción del modelo, diseño del prototipo y de la encuesta, implementación de las técnicas, despliegue y pruebas. En síntesis, se alcanzó el objetivo propuesto de diseñar un prototipo de una aplicación web capaz de analizar los datos y recomendar un área vocacional STEM a uno o varios individuos, esto utilizando algoritmos de clasificación como Decision Tree, KNN y SMV. En cuanto a los resultados el algoritmo SVM dio un 72,41% de accuracy, Decision tree y KNN 62% Es importante resaltar, que para generar esta recomendación el sistema tiene en cuenta una serie de variables de entrada que estiman el interés que posee el estudiante para desempeñarse en determinadas áreas STEM, sin embargo, no se contemplan otros factores que también tienen influencia en la decisión de una carrera profesional y que pueden ser de carácter psicológico, económico o de otra índole. choose a career it is an important decision that young people face when they finish school, it is not an easy task, and in many cases the student does not have the tools or the assistance in vocational guidance to allow them to choose a career. Based on this identified need, the central proposal of the project is to design and implement a prototype of a web application using Data Mining techniques for vocational guidance and promotion of STEM careers. For the development of the prototype, the SCRUM methodology was implemented, which was selected due to its flexibility, the timely obtaining of results and rapid learning, which allowed the comprehensive development of the requirements and research phases, model construction, prototype design and of the survey, implementation of techniques, deployment and testing. In summary, the proposed objective of designing a prototype of a web application capable of analyzing the data and recommending a STEM vocational area to one or more individuals was achieved, using classification algorithms such as Decision Tree, KNN and SMV. Regarding the results, the SVM algorithm gave a 72.41% accuracy, Decision tree and KNN 62% It is important to highlight that to generate this recommendation the system takes into account a series of input variables that estimate the interest that the student has to perform in certain STEM areas, however, other factors that influence the decision of a professional career such as psychological, economic or social are not taken into account.