ABSTRACT The recent advent of 3D in Electron Microscopy (EM) has allowed for detection of detailed sub-cellular nanometer resolution structures. While being a scientific breakthrough, this has also caused an explosion in dataset size, necessitating the development of automated workflows. Automated workflows typically benefit reproducibility and throughput compared to manual analysis. The risk of automation is that it ignores the expertise of the microscopy user that comes with manual analysis. To mitigate this risk, this paper presents a hybrid paradigm. We propose a ‘human-in-the-loop’ (HITL) approach that combines expert microscopy knowledge with the power of large-scale parallel computing to improve EM image quality through advanced image restoration algorithms. An interactive graphical user interface, publicly available as an ImageJ plugin, was developed to allow biologists to use our framework in an intuitive and user-friendly fashion. We show that this plugin improves visualization of EM ultrastructure and subsequent (semi-)automated segmentation and image analysis.
We present the fabrication and characterization of a subpicogram micromechanical oscillator in a slot waveguide that is actuated through optical gradient force. The tunable slot width in fact creates an optomechanical phase modulator on a Silicon-on-Insulator-Chip.
The use of graphical processing units (GPUs) for general purpose calculations has gained a lot of attention, since speed-up factors of 10x-50x compared to single-threaded CPU execution are not uncommon. This makes the use of GPUs for scientific number crunching applications very appealing. However, GPU programming is challenging, requiring a significant programming expertise in order to get these significant accelerations. The low-level programming required to harvest the GPU parallel power is a major drawback for research both in industry and in academics. In a research environment algorithms typically have to be rapidly tested and adjusted as a proof of concept and little time can be spend on implementation optimization.
In this tutorial we present Quasar, a new programming framework that takes care of many common challenges for GPU programming, e.g. memory management, load balancing, scheduling. Quasar consist of a high level programming language with a similar abstraction level as Python or Matlab, making it well suited for rapid prototyping. We demonstrate the use of this programming language for a number of examples. We show how we can start from a straight forward parallelization and further improve it based on the feedback from the profiler and automated profiling analysis. Finally attendees will be able to exercise with Quasar and the IDE tools in a hands-on part of the tutorial.
Tutorial goals
The goal of the proposed tutorial is to introduce high level programming of heterogeneous hardware to the participants. A second goal is to get attendees acquainted with relevant development tools and how, based on the feedback from these tools, they can easily improve their developed algorithms without the need of low-level optimizations. You will benefit from the tutorial by
1) having a low barrier of entry for GPU programming
2) having shorter development cycles compared to classical low-level languages for heterogeneous hardware, due to the use of a high-level programming language
Metabolic-associated fatty liver disease (MAFLD) represents a spectrum of disease states ranging from simple steatosis to non-alcoholic steatohepatitis (NASH). Hepatic macrophages, specifically Kupffer cells (KCs), are suggested to play important roles in the pathogenesis of MAFLD through their activation, although the exact roles played by these cells remain unclear. Here, we demonstrated that KCs were reduced in MAFLD being replaced by macrophages originating from the bone marrow. Recruited macrophages existed in two subsets with distinct activation states, either closely resembling homeostatic KCs or lipid-associated macrophages (LAMs) from obese adipose tissue. Hepatic LAMs expressed Osteopontin, a biomarker for patients with NASH, linked with the development of fibrosis. Fitting with this, LAMs were found in regions of the liver with reduced numbers of KCs, characterized by increased Desmin expression. Together, our data highlight considerable heterogeneity within the macrophage pool and suggest a need for more specific macrophage targeting strategies in MAFLD.
A landfill (Hooge Maey, Flanders, Belgium) was subjected to an in-depth study in order to explain the origin of phosphine detected in high amounts in landfill gas during a previous study. The spatial and temporal variability of the phosphine concentration in landfill gas was assessed. Twenty four wells were monitored and differences in phosphine concentration up to one log unit were observed (3.2-32.4 microg/m3). The phosphine concentration in each well was constant in time over a period of 4 months. No correlation was found between the phosphine concentration and methane, carbon dioxide, hydrogen sulphide, ethene or ethane concentration. In a series of laboratory tests, it was shown that phosphine was emitted during batch fermentation tests inoculated with landfill leachate when Fe0 or Al0 specimens were added. Conditions favouring corrosion of iron gave rise to higher emissions of phosphine. The phosphine concentration in the headspace of a batch test rose to 1.43 mg/m3 after 27 days of incubation. Weight loss of corroding steel coupons correlated with phosphine emission. Calculations showed that all phosphine emitted from the 0.005 km3 landfill (160 g/year) could be attributed to corrosion of metals. No evidence of de novo synthesis could be established
In this paper, we propose a novel, miniaturized non-dispersive infrared (NDIR) CO2 sensor implemented on a silicon chip. The sensor has a simple structure, consisting of a hollow metallic cylindrical cavity along with access waveguides. A detailed analysis of the proposed sensor is presented. Simulation with 3D ray tracing shows that an integrating cylinder with 4 mm diameter gives an equivalent optical path length of 3.5 cm. The sensor is fabricated using Deep Reactive Ion Etching (DRIE) and wafer bonding. The fabricated sensor was evaluated by performing a CO2 concentration measurement, showing a limit of detection of ∼100 ppm. The response time of the sensor is only ∼2.8 s, due to its small footprint. The use of DRIE-based waveguide structures enables mass fabrication, as well as the potential co-integration of flip-chip integrated midIR light-emitting diodes (LEDs) and photodetectors, resulting in a compact, low-power, and low-cost NDIR CO2 sensor.
