Ejercicio y sensación de posición articular en la rodilla. Efecto agudo del ejercicio de calentamiento y del ejercicio intenso, en acciones musculares concéntricas y excéntricas.

Objetivo: Describir el efecto agudo de una rutina de calentamiento normalmente utilizada en deportes que llevan algún contacto con el suelo, así como observar y comparar la sensación de la posición articular de la rodilla del miembro dominante luego de realizar una exposición a estímulos de fatiga, ya sea en contracción excéntrica o concéntrica para así comparar su efecto agudo.Diseño: Descriptivo, comparación de medidas repetidas e independientesMuestra: 20 sujetos con una edad media de 19.5 ±1.2, que realizan deporte con un mínimo de volumen semanal con un intervalo de por lo menos 180 a 270 minutos repartido 3 veces por semana, los cuales fueron separados en dos grupos, grupo concéntrico (n=10), grupo excéntrico (n=10)Mediciones: Evaluación de la sensación de posición articular (SPA) de la rodilla, de forma pasiva, a través de un dinamómetro isocinético, en tres momentos diferentes: reposo, luego de un calentamiento y a seguir de un estímulo de fatiga para el cuádriceps, ya sea en forma concéntrica o excéntrica.Resultados: Las medias del error angular absoluto (EAA) de 40° y 60° disminuyeron de la condición de reposo para la condición de post-calentamiento, aunque apenas con significativa estadística (p < 0.05) para la posición objetivo de 40° (8.5 ± 4.4 vs 6.1 ± 4.2). para las medias en la comparación del efecto agudo entre el calentamiento y el estímulo de fatiga no mostraron diferencias estadísticamente significativas, así mismo para la comparación de los dos modos de contracción utilizados, (concéntrico vs excéntrico) no se evidenciaron diferencias estadísticamente significativas (p ˃ 0.05).Conclusiones: El ejercicio de calentamiento mejora la SPA. Los protocolos de ejercicio concéntrico y excéntrico, no fueron lo suficientemente intensos para inducir una fatiga neuromuscular con impórtate repercusión en el aumento del EAA como indicador de la SPA.Objective: To describe the acute effect of a warm-up routine normally used in sports that have some contact with the floor, as well as to observe and compare the sensation of the articular position of the knee of the dominant member after exposure to fatigue stimuli, either in eccentric or concentric contraction to compare its acute effect.Design: Descriptive, comparison of repeated and independent measuresParticipants: 20 subjects with a mean age of 19.5 ± 1.2, who performed sport with a minimum of weekly volume in interval of at least 180 to 270 minutes distributed 3 times per week, which were separated into two groups, concentric group (n=10), eccentric group (n=10)Measurements: Evaluation of the joint position sense (JPS) of the knee, passively, through an isokinetic dynamometer, in three different moments: rest, after a warm up and following a fatigue stimulus for the quadriceps, in either concentric or eccentric.Results: Absolute Angular Error (AAE) mean values of 40° and 60° decreased from resting condition to post-warm-up condition, but with only statistically significant (p <0.05) for the 40° target position (8.5 ± 4.4 vs. 6.1 ± 4.2). For the means in the comparison of the acute effect between the warm-up and the fatigue stimulus did not show statistically significant differences, for the comparison of the two modes of contraction used (concentric vs eccentric), there were no statistically significant differences (p ˃ 0.05).Conclusions: The warm-up exercise improves the JPS. The concentric and eccentric exercise protocols were not intense enough to induce neuromuscular fatigue with a repercussion in the increase of AAE as an indicator of JPS

Practical high-throughput content-based routing using unicast state and probabilistic encodings

We address the problem that existing publish/subscribe messaging systems, including such commonly used ones as Apache’s ActiveMQ and IBM’s WebSphere MQ, exhibit degraded end-to-end throughput performance in a wide-area network setting. We contend that the cause of this problem is the lack of an appropriate routing protocol. Building on the idea of a content-based network, we introduce a protocol called B-DRP that can demonstrably improve the situation. A content-based network is a content-based publish/subscribe system architected as a datagram network: a message is forwarded hop-by-hop and delivered to any and all hosts that have expressed interest in the message content. This fits well with the character of a wide-area messaging system. B-DRP is based on two main techniques: a message delivery mechanism that utilizes and exploits unicast forwarding state, which can be easily maintained using standard protocols, and a probabilistic data structure to effciently represent and evaluate receiver interests. We present the design of B-DRP and the results of an experimental evaluation that demonstrates its support for improved throughput in a wide-area setting

Experimental evaluation of the cloud-native application design

Cloud-Native Applications (CNA) are designed to run on top of cloud computing infrastructure services with inherent support for self-management, scalability and resilience across clustered units of application logic. Their systematic design is promising especially for recent hybrid virtual machine and container environments for which no dominant application development model exists. In this paper, we present a case study on a business application running as CNA and demonstrate the advantages of the design experimentally. We also present Dynamite, an application auto-scaler designed for containerised CNA. Our experiments on a Vagrant host, on a private OpenStack installation and on a public Amazon EC2 testbed show that CNA require little additional engineering

The effect of sun-dried raisins (Vitis vinifera L.) on the in vitro composition of the gut microbiota

Modulation of the human gut microbiota has proven to have beneficial effects on host health. Sun-dried raisins exhibited prebiotic potential

Service Prototyping Lab Report - 2016 (Y1)

The annual activity report of the Service Prototyping Lab at Zurich University of Applied Sciences. Research trends and initiatives, research projects, transfer to education and local industry, academic community involvement, qualification and scientific development over the period of one year are among the covered topics

Self-managing cloud-native applications : design, implementation and experience

Running applications in the cloud efficiently requires much more than deploying software in virtual machines. Cloud applications have to be continuously managed: (1) to adjust their resources to the incoming load and (2) to face transient failures replicating and restarting components to provide resiliency on unreliable infrastructure. Continuous management monitors application and infrastructural metrics to provide automated and responsive reactions to failures (health management) and changing environmental conditions (auto-scaling) minimizing human intervention. In the current practice, management functionalities are provided as infrastructural or third party services. In both cases they are external to the application deployment. We claim that this approach has intrinsic limits, namely that separating management functionalities from the application prevents them from naturally scaling with the application and requires additional management code and human intervention. Moreover, using infrastructure provider services for management functionalities results in vendor lock-in effectively preventing cloud applications to adapt and run on the most effective cloud for the job. In this paper we discuss the main characteristics of cloud native applications, propose a novel architecture that enables scalable and resilient self-managing applications in the cloud, and relate on our experience in porting a legacy application to the cloud applying cloud-native principles

Combining reinforcement learning with supervised deep learning for neural active scene understanding

Awarded with the Dr. Waldemar Jucker award 2020 of the GSTWhile vision in living beings is an active process where image acquisition and classification are intertwined to gradually refine perception, much of today’s computer vision is build on the inferior paradigm of episodic classification of i.i.d. samples. We aim at improved scene understanding for robots by taking the sequential nature of seeing over time into account. We present a supervised multi-task approach to answer questions about different aspects of a scene such as the relationship between objects, their quantity or the their relative positions to the camera. For each question, we train a different output head which operates on input from one shared recurrent convolutional neural network that accumulates information over time steps. In parallel, we train an additional output head using reinforcement learning (RL) that uses the reduction in cumulative loss from the supervised heads as reward signal. It thereby learns to gradually improve the prediction confidence of e.g. partially occluded objects by moving the camera to a more favourable angle with respect to these objects. We present preliminary results on simulated RGB-D image sequences that show superior performance of our RL-based approach in answering questions quicker and more accurately than using static or random camera movement

Efficient delivery of robotics programming educational content using cloud robotics

In this paper, we report on our use of cloud-robotics solutions to teach a Robotics Applications Programming course at Zurich University of Applied Sciences (ZHAW). The usage of Kubernetes based cloud computing environment combined with real robots - turtlebots and Niryo arms - allowed us to: 1) minimize the set up times required to provide a Robotic Operating System (ROS) simulation and development environment to all students independently of their laptop architecture and OS; 2) provide a seamless “simulation to real” experience preserving the exciting experience of writing software interacting with the physical world; and 3) sharing GPUs across multiple student groups, thus using resources efficiently. We describe our requirements, solution design, experience working with the solution in the educational context and areas where it can be further improved. This may be of interest to other educators who may want to replicate our experience