The influence of food web structure on the diet, mercury dynamics and bioenergetics of northern pike in reservoirs of the upper South Saskatchewan River Basin

This project investigated the influence of community structure in reservoirs on trophodynamics, growth and mercury biomagnification in the apex consumer and fisheries target species northern pike (Esox lucius). Where lake whitefish (Coregonus clupeaformis) were abundant in the prey community, pike were found to be piscivorous, consuming predominantly lake whitefish and other large-bodied fish species. Benthivorous feeding behavior was observed in reservoirs without abundant lake whitefish stocks, and amphipods formed the predominant prey consumed by pike. Growth rates of pike were found to be significantly lower under the benthivorous trophic regime. Benthivorous pike had lower mercury concentrations, consistent with lower dietary exposure, than piscivorous pike, but higher biomagnification consistent with low food conversion efficiency and slower growth. A bioenergetics analysis showed elevated feeding rates and activity levels in benthivorous pike on a diet of comparatively low energy density, relative to piscivorous pike, confirming a trophic bottleneck in response to trophic simplification and highlighting the importance of trophic coupling between pelagic resources and apex consumers in reservoirs

Transient Resonance Passage of a Mistuned Bladed Disk with and without Underplatform Dampers

In this work, the vibration response of an academic free-standing turbine blisk is analyzed in regard to transient resonance passages. Measurement data are recorded using strain gauges and tip timing to evaluate the blades first bending mode both linearly and with two different types of underplatform dampers. These results are validated against steady-state responses and show good agreement with each other. To examine the effects of a transient resonance passage, response functions of each blade are evaluated both with and without the underplatform dampers. It is shown that friction damping is able to inhibit any appearance of a transient ring-down. Additionally, a multi-mass oscillator model with frictional contacts is analyzed, which qualitatively exhibits the same dynamics as the measurements. Due to geometric mistuning, all blades exhibit different vibration responses. This can lead to a transient amplitude amplification, which is observed on several blades. Analogously, this phenomenon can be mitigated by friction damping

And now for something completely different: running Lisp on GPUs

The internal parallelism of compute resources increases permanently, and graphics processing units (GPUs) and other accelerators have been gaining importance in many domains. Researchers from life science, bioinformatics or artificial intelligence, for example, use GPUs to accelerate their computations. However, languages typically used in some of these disciplines often do not benefit from the technical developments because they cannot be executed natively on GPUs. Instead existing programs must be rewritten in other, less dynamic programming languages. On the other hand, the gap in programming features between accelerators and common CPUs shrinks permanently. Since accelerators are becoming more competitive with regard to general computations, they will not be mere special-purpose processors in the future. It is a valid assumption that future GPU generations can be used in a similar or even the same way as CPUs and that compilers or interpreters will be needed for a wider range of computer languages. We present CuLi, an interactive Lisp interpreter, that performs all computations on a CUDA-capable GPU. The host system is needed only for the input and the output. At the moment, Lisp programs running on CPUs outperform Lisp programs on GPUs, but we present trends indicating that this might change in the future. Our study gives an outlook on the possibility of running Lisp programs or other dynamic programming languages on next-generation accelerators

Smart Grid-aware scheduling in data centres

© 2016 In several countries the expansion and establishment of renewable energies result in widely scattered and often weather-dependent energy production, decoupled from energy demand. Large, fossil-fuelled power plants are gradually replaced by many small power stations that transform wind, solar and water power into electrical power. This leads to changes in the historically evolved power grid that favours top-down energy distribution from a backbone of large power plants to widespread consumers. Now, with the increase of energy production in lower layers of the grid, there is also a bottom-up flow of the grid infrastructure compromising its stability. In order to locally adapt the energy demand to the production, some countries have started to establish Smart Grids to incentivise customers to consume energy when it is generated. This paper investigates how data centres can benefit from variable energy prices in Smart Grids. In view of their low average utilisation, data centre providers can schedule the workload dependent on the energy price. We consider a scenario for a data centre in Paderborn, Germany, hosting a large share of interruptible and migratable computing jobs. We suggest and compare two scheduling strategies for minimising energy costs. The first one merely uses current values from the Smart Meter to place the jobs, while the other one also estimates the future energy price in the grid based on weather forecasts. In spite of the complexity of the prediction problem and the inaccuracy of the weather data, both strategies perform well and have a strong positive effect on the utilisation of renewable energy and on the reduction of energy costs. This work improves and extends the paper of the same title published on the SustainIT conference (Mäsker et al., 2015). While that paper puts more emphasis on the utilisation of green energy, the new algorithms find a better balance between energy costs and turnaround time. We slightly alter the scenario using a more realistic multi-queue batch system and improve the scheduling algorithms which can be tuned to prioritise turnaround time or green energy utilisation

Hyperion: Building the largest in-memory search tree

Indexes are essential in data management systems to increase the speed of data retrievals. Widespread data structures to provide fast and memory-efficient indexes are prefix tries. Implementations like Judy, ART, or HOT optimize their internal alignments for cache and vector unit efficiency. While these measures usually improve the performance substantially, they can have a negative impact on memory efficiency. In this paper we present Hyperion, a trie-based main-memory key-value store achieving extreme space efficiency. In contrast to other data structures, Hyperion does not depend on CPU vector units, but scans the data structure linearly. Combined with a custom memory allocator, Hyperion accomplishes a remarkable data density while achieving a competitive point query and an exceptional range query performance. Hyperion can significantly reduce the index memory footprint, while being at least two times better concerning the performance to memory ratio compared to the best implemented alternative strategies for randomized string data sets

Sensitive on-site detection of SARS-CoV-2 by ID NOW COVID-19

Point of care detection of SARS-CoV-2 is one pillar in a containment strategy and important to break infection chains. Here we report the sensitive, specific and robust detection of SARS-CoV-2 and respective variants of concern by the ID NOW COVID-19 device.Peer Reviewe

Evaluation of 11 commercially available PCR kits for the detection of monkeypox virus DNA, Berlin, July to September 2022

Before the international spread of monkeypox in May 2022, PCR kits for the detection of orthopoxviruses, and specifically monkeypox virus, were rarely available. Here we describe the evaluation of 11 recently developed commercially available PCR kits for the detection of monkeypox virus DNA. All tested kits are currently intended for research use only and clinical performance still needs to be assessed in more detail, but all were suitable for diagnostics of monkeypox virus, with variations in specificity rather than sensitivity.Peer Reviewe

CC Chemokine Receptor 7–dependent and –independent Pathways for Lymphocyte Homing: Modulation by FTY720

Cognate interaction of chemokine receptor CCR7 on lymphocytes with its ligands CCL19 and CCL21 expressed on high endothelial venules (HEVs) is essential for effective migration of T and B cells across HEVs into secondary lymphoid organs. Plt mice, which lack expression of CCL19 and CCL21-ser, both ligands for CCR7 on HEVs, as well as CCR7-deficient mice, have a defective cell migration and reduced homing of lymphocytes. FTY720, a novel immunosuppressant, causes a reduction of lymphocytes in peripheral blood and tissues and their sequestration into lymphoid tissues. In this study we demonstrate that FTY720 rescues the homing defect in both CCR7−/− mice and plt mice. After FTY720 treatment, the number of CD4+ and CD8+ T cells as well as B cells in peripheral blood is reduced while pertussis toxin–sensitive homing into peripheral lymph nodes, mesenteric lymph node, and Peyer's patches is increased. Immunohistology demonstrates that FTY720 enables these cells to enter lymphoid tissue through HEVs. Thus, our data suggest an alternative G-αi-dependent, CCR7-CCL19/CCL21-independent mechanism for lymphocyte homing through HEVs which is strongly augmented in the presence of FTY720

Secure genome processing in public cloud and HPC environments

Aligning next generation sequencing data requires significant compute resources. HPC and cloud systems can provide sufficient compute capacity, but do not offer the required data security guarantees. HPC environments are typically designed for many groups of trusted users and often only include minimal security enforcement, while Cloud environments are mostly under the control of untrusted entities and companies. In this work we present a scalable pipeline approach that enables the use of public Cloud and HPC environments, while improving the patients’ privacy. The applied techniques include adding noisy data, cryptography, and a MapReduce program for the parallel processing of data