High-resolution Data Collection Research Articles

URBAN MORPHOLOGICAL DYNAMICS IN SANTIAGO (CHILE): PROPOSING SUSTAINABLE INDICATORS FROM REMOTE SENSING

Abstract. Latin America is one of the world’s most urbanised regions, with more than 80% of inhabitants living in urban areas and over 50 cities with at least 1 million inhabitants. The concept of urban structure types (UST) allows the dynamics of a growing urban environment to be captured in its quantity and quality. They are defined as areas of homogenous appearance in the urban matrix with a recognisable mixture of built-up areas and open spaces. We used the vegetation-impervious-soil (V-I-S) model approach to classify and monitor different types of USTs in Santiago (~800 km2), Chile between 1985 and 2015. The V-I-S model is based on a simplification of the large diversity of urban land cover types in three general categories: vegetation, impervious surfaces and soil. These categories were obtained by processing Landsat-5 TM and Landsat-8 OLI images. First, we applied standard radiometric calibration and co-registration methods to all datasets. Second, using a linear spectral unmixing algorithm we performed a soft classification of urban land cover types (end members): trees, shrubs, herbaceous plants, soils, buildings, roads and water bodies. All end members were validated using a combination of photointerpretation on high-resolution images (~1 m) and field data collection (only for 2015). In each pixel we used the resulting probability scores, logically grouped, to obtain final values for each V-I-S component. Third, we used statistical clustering of V-I-S values to create a set of eight pixel groups, which we interpreted as USTs and mapped them for each date. The overall accuracy for V-I-S components in 1985 and 2015 were 78% and 82%, respectively, and errors did not exhibit any spatial correlation. The main sources of differentiation between USTs were the trade-off proportions between vegetation and impervious components, whereas soil proportions remained near 5% across the city in both dates. To analyse the change in UST spatial configuration between dates, we used a set of selected landscape metrics and discussed their use as indicators for sustainable urban development. These indicators relate to the dispersion pattern of urban growth, the connectivity of open green space and the complexity in the composition of the UST types within the different sectors of the city. We were able to identify, using the dynamics exhibited by the USTs, three main zones: (1) city centre, where USTs of high-intensity development predominate, (2) eastern high-income areas whose spatial structure is marked by a relatively high urbanisation intensity with a very large proportion of vegetated spaces, and (3) peripheral areas, with significant changes in composition and configuration of USTs, in recent decades, showing high rates of urbanisation, shifting from low-medium to high densities. We concluded that these patterns and their dynamics are mainly determined by the spatial socio-economic stratification of the population.

A sensor package for mapping pH and oxygen from mobile platforms

A novel chemical sensor package named “WavepHOx” was developed in order to facilitate measurement of surface ocean pH, dissolved oxygen, and temperature from mobile platforms. The system comprises a Honeywell Durafet pH sensor, Aanderaa optode oxygen sensor, and chloride ion selective electrode, packaged into a hydrodynamic, lightweight housing. The WavepHOx has been deployed on a stand-up paddleboard and a Liquid Robotics Wave Glider in multiple near-shore settings in the Southern California Bight. Integration of the WavepHOx into these mobile platforms has enabled high spatiotemporal resolution pH and dissolved oxygen data collection. It is a particularly valuable tool for mapping shallow, fragile, or densely vegetated ecosystems which cannot be easily accessed by other platforms. Results from three surveys in San Diego, California, are reported. We show pH and dissolved oxygen variability >0.3 and >50% saturation, respectively, over tens to hundreds of meters to highlight the degree of natural spatial variability in these vegetated ecosystems. When deployed during an extensive discrete sampling program, the WavepHOx pH had a root mean squared error of 0.028 relative to pH calculated from fifty six measurements of total alkalinity and dissolved inorganic carbon, confirming its capacity for accurate, high spatiotemporal resolution data collection.

A new perspective of storm bite on sandy beaches using Unmanned Aerial Vehicles

Aerial imagery collected before and after major storm events is ideal for the assessment of coastal landscape change driven by individual high-magnitude events. Using traditional satellite sensors and manned aerial systems can be challenging due to issues related to cloud cover, mobilization expenses and resolution. Rapid advances in unmanned aerial vehicle (UAV) technology allow for the cost-effective collection of aerial imagery and topography at centimetre resolution suitable for assessing change in coastal ecosystems. In this study we demonstrate the utility of UAV-based photogrammetry to quantify storm-driven sediment dynamics on a sandy beach on the open-coast shoreline of Victoria, Australia. UAV-based aerial photography was collected before and after a major storm event. High-resolution (< 5 cm) aerial imagery and digital surface models were acquired and change-detection techniques were applied to quantify changes in the beachface. An average beach erosion of 12.24 m3/m with a maximum of 28.05 m3/m was observed, and the volume of sand cut from the beachface and retreat of the foredune are clearly illustrated. Following the storm event, erosion was estimated at 7259.94 ± 503.69 m3 along 550 m of beach. By combining the aerial imagery and derived topographic datasets we demonstrate the advantage of UAV-based photogrammetry techniques for rapid high-resolution data collection in semi-remote locations. Its utility in setting unlimited virtual vantage points is also illustrated and the valuable perspective it provides for tracking landscape change discussed.

A High-Resolution Imaging Technique using a Whole-body, Research Photon Counting Detector CT System.

A high-resolution (HR) data collection mode has been introduced to the whole-body, research photon-counting-detector CT system installed in our laboratory. In this mode, 64 rows of 0.45 mm × 0.45 mm detectors pixels were used, which corresponded to a pixel size of 0.225 mm × 0.225 mm at the iso-center. Spatial resolution of this HR mode was quantified by measuring the MTF from a scan of a 50 micron wire phantom. An anthropomorphic lung phantom, cadaveric swine lung, temporal bone and heart specimens were scanned using the HR mode, and image quality was subjectively assessed by two experienced radiologists. Comparison of the HR mode images against their energy integrating system (EID) equivalents using comb filters was also performed. High spatial resolution of the HR mode was evidenced by the MTF measurement, with 15 lp/cm and 20 lp/cm at 10% and 2% MTF. Images from anthropomorphic phantom and cadaveric specimens showed clear delineation of small structures, such as lung vessels, lung nodules, temporal bone structures, and coronary arteries. Temporal bone images showed critical anatomy (i.e. stapes superstructure) that was clearly visible in the PCD system but hardly visible with the EID system. These results demonstrated the potential application of this imaging mode in lung, temporal bone, and vascular imaging. Other clinical applications that require high spatial resolution, such as musculoskeletal imaging, may also benefit from this high resolution mode.

Neutron and high-resolution room-temperature X-ray data collection from crystallized lytic polysaccharide monooxygenase.

Bacteria and fungi express lytic polysaccharide monooxgyenase (LPMO) enzymes that act in conjunction with canonical hydrolytic sugar-processing enzymes to rapidly convert polysaccharides such as chitin, cellulose and starch to single monosaccharide products. In order to gain a better understanding of the structure and oxidative mechanism of these enzymes, large crystals (1-3 mm(3)) of a chitin-processing LPMO from the Gram-positive soil bacterium Jonesia denitrificans were grown and screened for their ability to diffract neutrons. In addition to the collection of neutron diffraction data, which were processed to 2.1 Å resolution, a high-resolution room-temperature X-ray diffraction data set was collected and processed to 1.1 Å resolution in space group P212121. To our knowledge, this work marks the first successful neutron crystallographic experiment on an LPMO. Joint X-ray/neutron refinement of the resulting data will reveal new details of the structure and mechanism of this recently discovered class of enzymes.

An isomorphous replacement method for efficient de novo phasing for serial femtosecond crystallography.

Serial femtosecond crystallography (SFX) with X-ray free electron lasers (XFELs) holds great potential for structure determination of challenging proteins that are not amenable to producing large well diffracting crystals. Efficient de novo phasing methods are highly demanding and as such most SFX structures have been determined by molecular replacement methods. Here we employed single isomorphous replacement with anomalous scattering (SIRAS) for phasing and demonstrate successful application to SFX de novo phasing. Only about 20,000 patterns in total were needed for SIRAS phasing while single wavelength anomalous dispersion (SAD) phasing was unsuccessful with more than 80,000 patterns of derivative crystals. We employed high energy X-rays from SACLA (12.6 keV) to take advantage of the large anomalous enhancement near the LIII absorption edge of Hg, which is one of the most widely used heavy atoms for phasing in conventional protein crystallography. Hard XFEL is of benefit for de novo phasing in the use of routinely used heavy atoms and high resolution data collection.

Advances in membrane protein crystallography: in situ and in meso data collection.

Advances in membrane protein crystallography: in situ and in meso data collection.

Goniometer-based femtosecond X-ray diffraction of mutant 30S ribosomal subunit crystals.

In this work, we collected radiation-damage-free data from a set of cryo-cooled crystals for a novel 30S ribosomal subunit mutant using goniometer-based femtosecond crystallography. Crystal quality assessment for these samples was conducted at the X-ray Pump Probe end-station of the Linac Coherent Light Source (LCLS) using recently introduced goniometer-based instrumentation. These 30S subunit crystals were genetically engineered to omit a 26-residue protein, Thx, which is present in the wild-type Thermus thermophilus 30S ribosomal subunit. We are primarily interested in elucidating the contribution of this ribosomal protein to the overall 30S subunit structure. To assess the viability of this study, femtosecond X-ray diffraction patterns from these crystals were recorded at the LCLS during a protein crystal screening beam time. During our data collection, we successfully observed diffraction from these difficult-to-grow 30S ribosomal subunit crystals. Most of our crystals were found to diffract to low resolution, while one crystal diffracted to 3.2 Å resolution. These data suggest the feasibility of pursuing high-resolution data collection as well as the need to improve sample preparation and handling in order to collect a complete radiation-damage-free data set using an X-ray Free Electron Laser.

Raster-scanning serial protein crystallography using micro- and nano-focused synchrotron beams.

High-resolution structural information was obtained from lysozyme microcrystals (20 µm in the largest dimension) using raster-scanning serial protein crystallography on micro- and nano-focused beamlines at the ESRF. Data were collected at room temperature (RT) from crystals sandwiched between two silicon nitride wafers, thereby preventing their drying, while limiting background scattering and sample consumption. In order to identify crystal hits, new multi-processing and GUI-driven Python-based pre-analysis software was developed, named NanoPeakCell, that was able to read data from a variety of crystallographic image formats. Further data processing was carried out using CrystFEL, and the resultant structures were refined to 1.7 Å resolution. The data demonstrate the feasibility of RT raster-scanning serial micro- and nano-protein crystallography at synchrotrons and validate it as an alternative approach for the collection of high-resolution structural data from micro-sized crystals. Advantages of the proposed approach are its thriftiness, its handling-free nature, the reduced amount of sample required, the adjustable hit rate, the high indexing rate and the minimization of background scattering.

Automated high-resolution GPR data collection for monitoring dynamic hydrologic processes in two and three dimensions

An automated GPR data-collection system was constructed to monitor dynamic hydrologic processes with high spatiotemporal resolution. The design of the system allows for fast acquisition of constant-offset profiles (COP) and common-midpoint surveys (CMP) to monitor unsaturated flow at multiple locations. A fast and accurate motion-control system enables the high-resolution monitoring of spatial patterns of reflectors through time while preserving important information about the normal moveout of reflectors for velocity analysis. In two experiments, infiltration was monitored using time-lapse ground-penetrating radar (GPR) measurements in two and three dimensions. The data from both experiments provide substantial qualitative insight about the dynamics of hydrologic events and a path forward for quantitative analysis of surface-based GPR monitoring data. Analysis shows (1) the advantages of collecting high-resolution time-lapse data, (2) the complexities of patterns associated with the wetting of the soil, and (3) evidence of nonuniform propagation of a wetting front through the soil column.

Combining high-resolution contact data with virological data to investigate influenza transmission in a tertiary care hospital.

Contact patterns and microbiological data contribute to a detailed understanding of infectious disease transmission. We explored the automated collection of high-resolution contact data by wearable sensors combined with virological data to investigate influenza transmission among patients and healthcare workers in a geriatric unit. Proof-of-concept observational study. Detailed information on contact patterns were collected by wearable sensors over 12 days. Systematic nasopharyngeal swabs were taken, analyzed for influenza A and B viruses by real-time polymerase chain reaction, and cultured for phylogenetic analysis. An acute-care geriatric unit in a tertiary care hospital. Patients, nurses, and medical doctors. A total of 18,765 contacts were recorded among 37 patients, 32 nurses, and 15 medical doctors. Most contacts occurred between nurses or between a nurse and a patient. Fifteen individuals had influenza A (H3N2). Among these, 11 study participants were positive at the beginning of the study or at admission, and 3 patients and 1 nurse acquired laboratory-confirmed influenza during the study. Infectious medical doctors and nurses were identified as potential sources of hospital-acquired influenza (HA-Flu) for patients, and infectious patients were identified as likely sources for nurses. Only 1 potential transmission between nurses was observed. Combining high-resolution contact data and virological data allowed us to identify a potential transmission route in each possible case of HA-Flu. This promising method should be applied for longer periods in larger populations, with more complete use of phylogenetic analyses, for a better understanding of influenza transmission dynamics in a hospital setting.

Urban soil exploration through multi-receiver electromagnetic induction and stepped-frequency ground penetrating radar.

In environmental assessments, the characterization of urban soils relies heavily on invasive investigation, which is often insufficient to capture their full spatial heterogeneity. Non-invasive geophysical techniques enable rapid collection of high-resolution data and provide a cost-effective alternative to investigate soil in a spatially comprehensive way. This paper presents the results of combining multi-receiver electromagnetic induction and stepped-frequency ground penetrating radar to characterize a former garage site contaminated with petroleum hydrocarbons. The sensor combination showed the ability to identify and accurately locate building remains and a high-density soil layer, thus demonstrating the high potential to investigate anthropogenic disturbances of physical nature. In addition, a correspondence was found between an area of lower electrical conductivity and elevated concentrations of petroleum hydrocarbons, suggesting the potential to detect specific chemical disturbances. We conclude that the sensor combination provides valuable information for preliminary assessment of urban soils.

Epidemiologic Survey of Infantile Cancer in Iran based on the Data of the Largest Pediatric Cancer Referral Center (Ali-Asghar Children Hospital), 1996-2005

Cancer in infants younger than one year of age represents a unique problem with distinct epidemiological, clinical and genetic characteristics compared with older age groups. No report is yet available from Iran regarding epidemiological and survival rate of cancers diagnosed in this age group. The population under study comprised of patients which were diagnosed and admitted to Ali-Asghar hospital between years 1996-2005. In total, 287 infants were included in the retrospective descriptive survey. Patient files were evaluated for age of patient at the time of diagnosis, sex, geographical residence, consanguinity of parents, histological diagnosis, site of cancer involvement, type of therapy, date of last follow-up and cause of death (if applicable). The average age at the time of diagnosis was 7.2 months old. The most frequent malignancy was retinoblastoma (44%), followed by leukemia (19%) and neuroblastoma (10%), with five-year overall survival rates of 77.7%, 41% and 90%, respectively Parents of 40 infants (13.9%) had consanguinity relationships. Although we cannot make any conclusions regarding the incidence of infant cancer subtypes based on this study, survival rates for major types were similar to the developed countries, which signifies strict adherence to standards of care in Ali-Asghar hospital, the main infant cancer care centre in Iran. A Childhood Cancer Registry with high-resolution data collection and also advanced genetic testing is advocated for in-depth analysis of variation in incidence and survival.

Using Flatbed Scanners to Collect High-resolution Time-lapsed Images of the Arabidopsis Root Gravitropic Response

Research efforts in biology increasingly require use of methodologies that enable high-volume collection of high-resolution data. A challenge laboratories can face is the development and attainment of these methods. Observation of phenotypes in a process of interest is a typical objective of research labs studying gene function and this is often achieved through image capture. A particular process that is amenable to observation using imaging approaches is the corrective growth of a seedling root that has been displaced from alignment with the gravity vector. Imaging platforms used to measure the root gravitropic response can be expensive, relatively low in throughput, and/or labor intensive. These issues have been addressed by developing a high-throughput image capture method using inexpensive, yet high-resolution, flatbed scanners. Using this method, images can be captured every few minutes at 4,800 dpi. The current setup enables collection of 216 individual responses per day. The image data collected is of ample quality for image analysis applications.

Using Flatbed Scanners to Collect High-resolution Time-lapsed Images of the Arabidopsis Root Gravitropic Response

Research efforts in biology increasingly require use of methodologies that enable high-volume collection of high-resolution data. A challenge laboratories can face is the development and attainment of these methods. Observation of phenotypes in a process of interest is a typical objective of research labs studying gene function and this is often achieved through image capture. A particular process that is amenable to observation using imaging approaches is the corrective growth of a seedling root that has been displaced from alignment with the gravity vector. Imaging platforms used to measure the root gravitropic response can be expensive, relatively low in throughput, and/or labor intensive. These issues have been addressed by developing a high-throughput image capture method using inexpensive, yet high-resolution, flatbed scanners. Using this method, images can be captured every few minutes at 4,800 dpi. The current setup enables collection of 216 individual responses per day. The image data collected is of ample quality for image analysis applications.

The IMAGINE instrument: first neutron protein structure and new capabilities for neutron macromolecular crystallography

The first high-resolution neutron protein structure of perdeuterated rubredoxin from Pyrococcus furiosus (PfRd) determined using the new IMAGINE macromolecular neutron crystallography instrument at the Oak Ridge National Laboratory is reported. Neutron diffraction data extending to 1.65 Å resolution were collected from a relatively small 0.7 mm(3) PfRd crystal using 2.5 d (60 h) of beam time. The refined structure contains 371 out of 391, or 95%, of the D atoms of the protein and 58 solvent molecules. The IMAGINE instrument is designed to provide neutron data at or near atomic resolution (1.5 Å) from crystals with volume <1.0 mm(3) and with unit-cell edges <100 Å. Beamline features include novel elliptical focusing mirrors that deliver neutrons into a 2.0 × 3.2 mm focal spot at the sample position with full-width vertical and horizontal divergences of 0.5 and 0.6°, respectively. Variable short- and long-wavelength cutoff optics provide automated exchange between multiple-wavelength configurations (λmin = 2.0, 2.8, 3.3 Å to λmax = 3.0, 4.0, 4.5, ∼20 Å). These optics produce a more than 20-fold increase in the flux density at the sample and should help to enable more routine collection of high-resolution data from submillimetre-cubed crystals. Notably, the crystal used to collect these PfRd data was 5-10 times smaller than those previously reported.

Estimating confidence intervals in predicted responses for oscillatory biological models

BackgroundThe dynamics of gene regulation play a crucial role in a cellular control: allowing the cell to express the right proteins to meet changing needs. Some needs, such as correctly anticipating the day-night cycle, require complicated oscillatory features. In the analysis of gene regulatory networks, mathematical models are frequently used to understand how a network’s structure enables it to respond appropriately to external inputs. These models typically consist of a set of ordinary differential equations, describing a network of biochemical reactions, and unknown kinetic parameters, chosen such that the model best captures experimental data. However, since a model’s parameter values are uncertain, and since dynamic responses to inputs are highly parameter-dependent, it is difficult to assess the confidence associated with these in silico predictions. In particular, models with complex dynamics - such as oscillations - must be fit with computationally expensive global optimization routines, and cannot take advantage of existing measures of identifiability. Despite their difficulty to model mathematically, limit cycle oscillations play a key role in many biological processes, including cell cycling, metabolism, neuron firing, and circadian rhythms.ResultsIn this study, we employ an efficient parameter estimation technique to enable a bootstrap uncertainty analysis for limit cycle models. Since the primary role of systems biology models is the insight they provide on responses to rate perturbations, we extend our uncertainty analysis to include first order sensitivity coefficients. Using a literature model of circadian rhythms, we show how predictive precision is degraded with decreasing sample points and increasing relative error. Additionally, we show how this method can be used for model discrimination by comparing the output identifiability of two candidate model structures to published literature data.ConclusionsOur method permits modellers of oscillatory systems to confidently show that a model’s dynamic characteristics follow directly from experimental data and model structure, relaxing assumptions on the particular parameters chosen. Ultimately, this work highlights the importance of continued collection of high-resolution data on gene and protein activity levels, as they allow the development of predictive mathematical models.

A Self-Learning Approach to Single Image Super-Resolution

Learning-based approaches for image super-resolution (SR) have attracted the attention from researchers in the past few years. In this paper, we present a novel self-learning approach for SR. In our proposed framework, we advance support vector regression (SVR) with image sparse representation, which offers excellent generalization in modeling the relationship between images and their associated SR versions. Unlike most prior SR methods, our proposed framework does not require the collection of training low and high-resolution image data in advance, and we do not assume the reoccurrence (or self-similarity) of image patches within an image or across image scales. With theoretical supports of Bayes decision theory, we verify that our SR framework learns and selects the optimal SVR model when producing an SR image, which results in the minimum SR reconstruction error. We evaluate our method on a variety of images, and obtain very promising SR results. In most cases, our method quantitatively and qualitatively outperforms bicubic interpolation and state-of-the-art learning-based SR approaches.

The Development of the Durable Test-Bed of the Hydraulic Pump

An energy recovery method during the durable test is put forward in this essay, and the durable test-bed of the hydraulic pump is developed. The efficiency and accuracy data acquisition is realized by using High-Speed High-Resolution sensor and data collection module. Control automation is come true by using PLC, industrial tablet PC and electric command device. The instrument panel constructed by LabWindows/CVI made the operation more concision, flexible and easy-to-use. This test bed has been put into use for a year and shows that the system can realize duration and efficient test of hydraulic pump easily and reliable.

ChemInform Abstract: Single Cell Analysis at the Nanoscale

AbstractReview: 73 refs.