Energy harvesting through arterial wall deformation: A FEM approach to fluid–structure interactions and magneto-hydrodynamics

Engineers are confronted with the energy demand of active medical implants in patients with increasing life expectancy. Scavenging energy from the patient’s body is envisioned as an alternative to conventional power sources. Joining in this effort towards human-powered implants, we propose an innovative concept that combines the deformation of an artery resulting from the arterial pressure pulse with a transduction mechanism based on magneto-hydrodynamics. To overcome certain limitations of a preliminary analytical study on this topic, we demonstrate here a more accurate model of our generator by implementing a three-dimensional multiphysics finite element method (FEM) simulation combining solid mechanics, fluid mechanics, electric and magnetic fields as well as the corresponding couplings. This simulation is used to optimize the generator with respect to several design parameters. A first validation is obtained by comparing the results of the FEM simulation with those of the analytical approach adopted in our previous study. With an expected overall conversion efficiency of 20% and an average output power of 30 μW, our generator outperforms previous devices based on arterial wall deformation by more than two orders of magnitude. Most importantly, our generator provides sufficient power to supply a cardiac pacemaker.

Low extracellular (ECF) glucose affects the neurochemical profile in severe head-injured patients

Glucose (Gluc) is the main energy source for the brain. After severe head-injury energy demand is massively increased and supply is often decreased. In pilot microdialysis studies, many patients with severe head-injury had undetectable glucose concentrations, probably reflecting changes in metabolism and/or reduced supply. We therefore investigated whether patients with low ECF glucose (criterion: < 50 microM for > or = 5 hrs), LOWgluc, differ from patients with higher glucose levels (NORMALgluc) We also tested the interrelationships between other parameters such as lactate, glutamate, K+, brain O2 and CO2, ICP, CPP, and CBF in these two groups. We found that patients with low ECF glucose, LOWgluc, have significantly lower lactate concentrations than patients with "normal" glucose, NORMALgluc, levels do. Spearman correlations between glucose and most other parameters were similar in both patient groups. However, glutamate correlated positively with glucose, lactate, brain CO2 and negatively with brain O2 in the NORMALgluc patient group, whereas glutamate did not significantly correlate with any of these parameters in the LOWgluc group. There was also no correlation between outcome and the dialysate glucose. The results indicate that low ECF glucose is almost always present in severe head-injury. Moreover, the lack of correlation between low glucose and outcome, however, suggests that other energy substrates, such as lactate, are important after TBI.

Eccentric exercise in coronary patients: central hemodynamic and metabolic responses

With lengthening (eccentric) muscle contractions, the magnitude of locomotor-muscle mass and strength increase has been demonstrated to be greater compared with shortening (concentric) muscle contractions. In healthy subjects, energy demand and heart rate responses with eccentric exercise are small relative to the amount of muscle force produced. Thus, eccentric exercise may be an attractive alternative to resistance exercise for patients with limited cardiovascular exercise tolerance.

Understanding E-Bike Users' Behaviour, Motives, and Barriers to the Use - An Empirical Study with high Potential for Mobility Management

A representative study among e-bike owners and tenants in Switzerland (n = 1652) provides a deeper understanding of e-bike users characteristics, motives, values, usage behavior, and barriers to the use. In a micro simulation the implications of the findings for the energy demand and CO2 emissions are estimated.

Inhibition of the kynurenine-NAD+ pathway leads to energy failure and exacerbates apoptosis in pneumococcal meningitis

Pneumococcal meningitis causes neurological sequelae, including learning and memory deficits in up to half of the survivors. In both humans and in animal models of the disease, there is apoptotic cell death in the hippocampus, a brain region involved in learning and memory function. We previously demonstrated that in an infant rat model of pneumococcal meningitis, there is activation of the kynurenine (KYN) pathway in the hippocampus, and that there was a positive correlation between the concentration of 3-hydroxykynurenine and the extent of hippocampal apoptosis. To clarify the role of the KYN pathway in the pathogenesis of hippocampal apoptosis in pneumococcal meningitis, we specifically inhibited 2 key enzymes of the KYN pathway and assessed hippocampal apoptosis, KYN pathway metabolites, and nicotinamide adenine dinucleotide (NAD) concentrations by high-performance liquid chromatography. Pharmacological inhibition of kynurenine 3-hydroxylase and kynureninase led to decreased cellular NAD levels and increased apoptosis in the hippocampus. The cerebrospinal fluid levels of tumor necrosis factor and interleukin-1? and -? were not affected. Our data suggest that activation of the KYN pathway in pneumococcal meningitis is neuroprotective by compensating for an increased NAD demand caused by infection and inflammation;this mechanism may prevent energy failure and apoptosis in the hippocampus.

Energy-Efficient Management Of Heterogeneous Wireless Sensor Networks

Various applications for the purposes of event detection, localization, and monitoring can benefit from the use of wireless sensor networks (WSNs). Wireless sensor networks are generally easy to deploy, with flexible topology and can support diversity of tasks thanks to the large variety of sensors that can be attached to the wireless sensor nodes. To guarantee the efficient operation of such a heterogeneous wireless sensor networks during its lifetime an appropriate management is necessary. Typically, there are three management tasks, namely monitoring, (re) configuration, and code updating. On the one hand, status information, such as battery state and node connectivity, of both the wireless sensor network and the sensor nodes has to be monitored. And on the other hand, sensor nodes have to be (re)configured, e.g., setting the sensing interval. Most importantly, new applications have to be deployed as well as bug fixes have to be applied during the network lifetime. All management tasks have to be performed in a reliable, time- and energy-efficient manner. The ability to disseminate data from one sender to multiple receivers in a reliable, time- and energy-efficient manner is critical for the execution of the management tasks, especially for code updating. Using multicast communication in wireless sensor networks is an efficient way to handle such traffic pattern. Due to the nature of code updates a multicast protocol has to support bulky traffic and endto-end reliability. Further, the limited resources of wireless sensor nodes demand an energy-efficient operation of the multicast protocol. Current data dissemination schemes do not fulfil all of the above requirements. In order to close the gap, we designed the Sensor Node Overlay Multicast (SNOMC) protocol such that to support a reliable, time-efficient and energy-efficient dissemination of data from one sender node to multiple receivers. In contrast to other multicast transport protocols, which do not support reliability mechanisms, SNOMC supports end-to-end reliability using a NACK-based reliability mechanism. The mechanism is simple and easy to implement and can significantly reduce the number of transmissions. It is complemented by a data acknowledgement after successful reception of all data fragments by the receiver nodes. In SNOMC three different caching strategies are integrated for an efficient handling of necessary retransmissions, namely, caching on each intermediate node, caching on branching nodes, or caching only on the sender node. Moreover, an option was included to pro-actively request missing fragments. SNOMC was evaluated both in the OMNeT++ simulator and in our in-house real-world testbed and compared to a number of common data dissemination protocols, such as Flooding, MPR, TinyCubus, PSFQ, and both UDP and TCP. The results showed that SNOMC outperforms the selected protocols in terms of transmission time, number of transmitted packets, and energy-consumption. Moreover, we showed that SNOMC performs well with different underlying MAC protocols, which support different levels of reliability and energy-efficiency. Thus, SNOMC can offer a robust, high-performing solution for the efficient distribution of code updates and management information in a wireless sensor network. To address the three management tasks, in this thesis we developed the Management Architecture for Wireless Sensor Networks (MARWIS). MARWIS is specifically designed for the management of heterogeneous wireless sensor networks. A distinguished feature of its design is the use of wireless mesh nodes as backbone, which enables diverse communication platforms and offloading functionality from the sensor nodes to the mesh nodes. This hierarchical architecture allows for efficient operation of the management tasks, due to the organisation of the sensor nodes into small sub-networks each managed by a mesh node. Furthermore, we developed a intuitive -based graphical user interface, which allows non-expert users to easily perform management tasks in the network. In contrast to other management frameworks, such as Mate, MANNA, TinyCubus, or code dissemination protocols, such as Impala, Trickle, and Deluge, MARWIS offers an integrated solution monitoring, configuration and code updating of sensor nodes. Integration of SNOMC into MARWIS further increases performance efficiency of the management tasks. To our knowledge, our approach is the first one, which offers a combination of a management architecture with an efficient overlay multicast transport protocol. This combination of SNOMC and MARWIS supports reliably, time- and energy-efficient operation of a heterogeneous wireless sensor network.

Gut Microbiota Orchestrates Energy Homeostasis during Cold.

Microbial functions in the host physiology are a result of the microbiota-host co-evolution. We show that cold exposure leads to marked shift of the microbiota composition, referred to as cold microbiota. Transplantation of the cold microbiota to germ-free mice is sufficient to increase insulin sensitivity of the host and enable tolerance to cold partly by promoting the white fat browning, leading to increased energy expenditure and fat loss. During prolonged cold, however, the body weight loss is attenuated, caused by adaptive mechanisms maximizing caloric uptake and increasing intestinal, villi, and microvilli lengths. This increased absorptive surface is transferable with the cold microbiota, leading to altered intestinal gene expression promoting tissue remodeling and suppression of apoptosis-the effect diminished by co-transplanting the most cold-downregulated strain Akkermansia muciniphila during the cold microbiota transfer. Our results demonstrate the microbiota as a key factor orchestrating the overall energy homeostasis during increased demand.