Cryo-EM image alignment based on nonuniform fast Fourier transform

In single particle analysis, two-dimensional (2-D) alignment is a fundamental step intended to put into register various particle projections of biological macromolecules collected at the electron microscope. The efficiency and quality of three-dimensional (3-D) structure reconstruction largely depends on the computational speed and alignment accuracy of this crucial step. In order to improve the performance of alignment, we introduce a new method that takes advantage of the highly accurate interpolation scheme based on the gridding method, a version of the nonuniform fast Fourier transform, and utilizes a multi-dimensional optimization algorithm for the refinement of the orientation parameters. Using simulated data, we demonstrate that by using less than half of the sample points and taking twice the runtime, our new 2-D alignment method achieves dramatically better alignment accuracy than that based on quadratic interpolation. We also apply our method to image to volume registration, the key step in the single particle EM structure refinement protocol. We find that in this case the accuracy of the method not only surpasses the accuracy of the commonly used real-space implementation, but results are achieved in much shorter time, making gridding-based alignment a perfect candidate for efficient structure determination in single particle analysis.     

Integrated Data Management for a Fleet of Search‐and‐rescue Robots

Search‐and‐rescue operations have recently been confronted with the introduction of robotic tools that assist the human search‐and‐rescue workers in their dangerous but life‐saving job of searching for human survivors after major catastrophes. However, the world of search and rescue is highly reliant on strict procedures for the transfer of messages, alarms, data, and command and control over the deployed assets. The introduction of robotic tools into this world causes an important structural change in this procedural toolchain. Moreover, the introduction of search‐and‐rescue robots acting as data gatherers could potentially lead to an information overload toward the human search‐and‐rescue workers, if the data acquired by these robotic tools are not managed in an intelligent way. With that in mind, we present in this paper an integrated data combination and data management architecture that is able to accommodate real‐time data gathered by a fleet of robotic vehicles on a crisis site, and we present and publish these data in a way that is easy to understand by end‐users. In the scope of this paper, a fleet of unmanned ground and aerial search‐and‐rescue vehicles is considered, developed within the scope of the European ICARUS project. As a first step toward the integrated data‐management methodology, the different robotic systems require an interoperable framework in order to pass data from one to another and toward the unified command and control station. As a second step, a data fusion methodology will be presented, combining the data acquired by the different heterogenic robotic systems. The computation needed for this process is done in a novel mobile data center and then (as a third step) published in a software as a service (SaaS) model. The SaaS model helps in providing access to robotic data over ubiquitous Ethernet connections. As a final step, we show how the presented data‐management architecture allows for reusing recorded exercises with real robots and rescue teams for training purposes and teaching search‐and‐rescue personnel how to handle the different robotic tools. The system was validated in two experiments. First, in the controlled environment of a military testing base, a fleet of unmanned ground and aerial vehicles was deployed in an earthquake‐response scenario. The data gathered by the different interoperable robotic systems were combined by a novel mobile data center and presented to the end‐user public. Second, an unmanned aerial system was deployed on an actual mission with an international relief team to help with the relief operations after major flooding in Bosnia in the spring of 2014. Due to the nature of the event (floods), no ground vehicles were deployed here, but all data acquired by the aerial system (mainly three‐dimensional maps) were stored in the ICARUS data center, where they were securely published for authorized personnel all over the world. This mission (which is, to our knowledge, the first recorded deployment of an unmanned aerial system by an official governmental international search‐and‐rescue team in another country) proved also the concept of the procedural integration of the ICARUS data management system into the existing procedural toolchain of the search and rescue workers, and this in an international context (deployment from Belgium to Bosnia). The feedback received from the search‐and‐rescue personnel on both validation exercises was highly positive, proving that the ICARUS data management system can efficiently increase the situational awareness of the search‐and‐rescue personnel.     

Segmentation of microscope images of living cells

This paper describes a segmentation method combining a texture based technique with a contour based method. The technique is designed to enable the study of cell behaviour over time by segmenting brightfield microscope image sequences. The technique was tested on artificial images, based on images of living cells and on real sequences acquired from microscope observations of neutrophils and lymphocytes as well as on a sequence of MRI images. The results of the segmentation are compared with the results of the watershed and snake segmentation methods. The results show that the method is both effective and practical.

An empirical analysis of heuristics for solving the two-machine flow shop problem with job release times

The theoretical analysis of heuristics for solving intractable optimization problems has many well-known drawbacks. Constructed instances demonstrating an exceptionally poor worst-case performance of heuristics are typically too peculiar to occur in practice. Theoretical results on the average-case performance of most heuristics could not be established due to the difficulty with the use of probabilistic analysis. Moreover, the heuristics for which some type of asymptotic optimality has been proven are likely to perform questionably in practice. The purpose of this paper is to confront known theoretical results with our empirical results concerning heuristics for solving the strongly NP-hard problem of minimizing the makespan in a two-machine flow shop with job release times. The heuristics' performance is examined with respect to their average and maximum relative errors, as well as their optimality rate, that is, the probability of being optimal. In particular, this allows us to observe that the asymptotic optimality rate of so called “almost surely asymptotically optimal” heuristic can be zero. We also present a new heuristic with short worst-case running time and statistically prove that it outperforms all heuristics known so far. However, our empirical experiments reveal that the heuristic is on average slower that its competitors with much longer worst-case running times.     

Risk assessment for a video surveillance system based on Fuzzy Cognitive Maps

For various IT systems security is considered a key quality factor. In particular, it might be crucial for video surveillance systems, as their goal is to provide continuous protection of critical infrastructure and other facilities. Risk assessment is an important activity in security management; it aims at identifying assets, threats and vulnerabilities, analysis of implemented countermeasures and their effectiveness in mitigating risks. This paper discusses an application of a new risk assessment method, in which risk calculation is based on Fuzzy Cognitive Maps (FCMs) to a complex automated video surveillance system. FCMs are used to capture dependencies between assets and FCM based reasoning is applied to aggregate risks assigned to lower-level assets (e.g. cameras, hardware, software modules, communications, people) to such high level assets as services, maintained data and processes. Lessons learned indicate, that the proposed method is an efficient and low-cost approach, giving instantaneous feedback and enabling reasoning on effectiveness of security system.     

Surfactant free fractions of metallic and semiconducting single-walled carbon nanotubes via optimised gel chromatography

We report the procedure of sorting/purification of carbon nanotubes by electronic type using chromatographic column with sodium dodecylsulfate (SDS) and sodium deoxycholate (DOC) solutions as the eluents. The non-commercial agarose gel in different concentrations has been tested in the process. It was found that in optimal gel concentration the fractionation resulted in ～96.2% yield of semiconducting species. Importantly, to get surfactant-free fractions the post-separation purification procedure has been carried out. The UV–vis–NIR and Raman spectroscopy have been utilised for the samples analysis. High resolution transmission microscopy and thermogravimetric analysis allowed to study the sample morphology and purity, respectively.     

Characterizing sources and emissions of volatile organic compounds in a northern California residence using space‐ and time‐resolved measurements

We investigate source characteristics and emission dynamics of volatile organic compounds (VOCs) in a single‐family house in California utilizing time‐ and space‐resolved measurements. About 200 VOC signals, corresponding to more than 200 species, were measured during 8 weeks in summer and five in winter. Spatially resolved measurements, along with tracer data, reveal that VOCs in the living space were mainly emitted directly into that space, with minor contributions from the crawlspace, attic, or outdoors. Time‐resolved measurements in the living space exhibited baseline levels far above outdoor levels for most VOCs; many compounds also displayed patterns of intermittent short‐term enhancements (spikes) well above the indoor baseline. Compounds were categorized as “high‐baseline” or “spike‐dominated” based on indoor‐to‐outdoor concentration ratio and indoor mean‐to‐median ratio. Short‐term spikes were associated with occupants and their activities, especially cooking. High‐baseline compounds indicate continuous indoor emissions from building materials and furnishings. Indoor emission rates for high‐baseline species, quantified with 2‐hour resolution, exhibited strong temperature dependence and were affected by air‐change rates. Decomposition of wooden building materials is suggested as a major source for acetic acid, formic acid, and methanol, which together accounted for ~75% of the total continuous indoor emissions of high‐baseline species.     

Indoor emissions of total and fluorescent supermicron particles during HOMEChem

Inhalation of particulate matter is associated with adverse health outcomes. The fluorescent portion of supermicron particulate matter has been used as a proxy for bioaerosols. The sources and emission rates of fluorescent particles in residential environments are not well-understood. Using an ultraviolet aerodynamic particle sizer (UVAPS), emissions of total and fluorescent supermicron particles from common human activities were investigated during the HOMEChem campaign, a test-house investigation of the chemistry of indoor environments. Human occupancy and activities, including cooking and mopping, were found to be considerable sources of indoor supermicron fluorescent particles, which enhanced the indoor particle concentrations by two orders of magnitude above baseline levels. The estimated total (fluorescent) mass emission rates for the activities tested were in the range of 4-30 (1-11) mg per person meal for cooking and 0.1-4.9 (0.05-4.7) mg/h for occupancy and mopping. Model calculations indicate that, once released, the dominant fate of coarse particles (2.5-10 micrometer in diameter) was deposition onto indoor surfaces, allowing for the possibility of subsequent resuspension and consequent exposures over durations much longer than the ventilation time scale. Indoor coarse particle deposition would also contribute to soiling of indoor surfaces.     

Characterization and properties of PVD coatings applied to extrusion dies

The paper presents the research results on the microstructure, mechanical and tribological properties of coatings deposited by cathodic arc evaporation methods on the X40CrMoV5-1 hot work tool steel substrates as well as the possibility to employ the finite element method for evaluation of stresses in the investigated coatings. The tests were carried out on CrAlSiN and CrN coatings. The coatings demonstrated a dense cross-sectional morphology as well as good adhesion to the substrate. The critical load L_C2 lies within the range 54-55 N, depending on the coating type. The investigated coatings have the potential to increase the service life of an extrusion die by orders of magnitude as compared with uncoated steel.     

Self-phase Modulation in Quadratically Nonlinear Media

Abstract

We discuss self-phase modulations and related transverse effects accompanying interaction of a light beam with a second harmonic radiation generated by it. Some experimental observations are explained by a simple perturbative approach. Numerical simulations provide a further insight into the nature of transverse self-effects in quadratically nonlinear media. An effective x ⁽³⁾-like behaviour of dispersive quadratically nonlinear media is discussed. Such feature may lead to important consequences for measurements of the x ⁽³⁾ tensor in complex nonlinear media.