Fast Data Acquisition Research Articles

An analytical system for evaluating academia units based on metrics provided by academic social network

Social networks are becoming more and more popular, not only among young people looking for entertainment, but also among specialists, experts and researchers who wish to establish professional networks, develop business or research projects. They may be useful also for the comparison and evaluation of scientists and research organizations.This study aims to show how to build a framework of an analytical system for evaluation of researchers and research units using the data retrieved from an academic social network. Acquired data are used to find out the main differences between ResarchGate (RG) usage and values of metrics owned by scientists of different gender, scientific title and field of study to find out if various groups of employees can be directly compared.The authors apply web scraping technique for collecting data from university web page (2847 employees) and use R scripts to acquire the metrics form RG portal. Also, data of 1497 researchers and teaching workers from 11 faculties at Polish university were explored.The descriptive statistics, Chi square test, ANOVA and logistic regression were used to analyse the main RG metrics: RG Score, number of publications, reads and citations.Analysis shows the significant differences both in terms of popularity of ResearchGate and values of its main metrics. The research confirmed that 1) the rvest package allows for fast data acquisition from RG, 2) RG metrics can be used by university managers to compare achievements and progress of single researchers, research labs, departments or faculties, 3) Researchers employed at the faculties of formal and natural sciences use RG portal more frequently, possess higher values of RG metrics, therefore different types of workers and various branches of science shouldn’t be compared directly.

Automated crop plant counting from very high-resolution aerial imagery

Knowing before harvesting how many plants have emerged and how they are growing is key in optimizing labour and efficient use of resources. Unmanned aerial vehicles (UAV) are a useful tool for fast and cost efficient data acquisition. However, imagery need to be converted into operational spatial products that can be further used by crop producers to have insight in the spatial distribution of the number of plants in the field. In this research, an automated method for counting plants from very high-resolution UAV imagery is addressed. The proposed method uses machine vision—Excess Green Index and Otsu’s method—and transfer learning using convolutional neural networks to identify and count plants. The integrated methods have been implemented to count 10 weeks old spinach plants in an experimental field with a surface area of 3.2 ha. Validation data of plant counts were available for 1/8 of the surface area. The results showed that the proposed methodology can count plants with an accuracy of 95% for a spatial resolution of 8 mm/pixel in an area up to 172 m2. Moreover, when the spatial resolution decreases with 50%, the maximum additional counting error achieved is 0.7%. Finally, a total amount of 170 000 plants in an area of 3.5 ha with an error of 42.5% was computed. The study shows that it is feasible to count individual plants using UAV-based off-the-shelf products and that via machine vision/learning algorithms it is possible to translate image data in non-expert practical information.

EKSPLORASI AKUIFER AIR BAWAH TANAH MENGGUNAKAN METODE TAHANAN JENIS 2D DI DESA SELARU KABUPATEN KOTABARU, KALIMANTAN SELATAN

Geoelectric resistivity method is one method that can be used to characterize water-bearing rock layers (aquifers). This method is based on the existence of differences in type resistivity in the layers of rock that are flowed electrically. The use of this method is based on easy application, faster data acquisition with broad data coverage (lateral and vertical), and lower costs. Data acquisition uses two configurations or electrode arrangement, namely sclumberger and wenner-schlumberger configurations. The number of trajectories for data acquisition uses one path with a total of 28 electrodes and the spacing between the electrodes is 20 meters. The data obtained in the form of data resistivity type of each underground layer and its depth will be further analyzed using AGISSAdmin software. The results are obtained in the form of a 2-dimensional (2D) cross-sectional value of underground layers laterally and vertically. The low resistivity value will be interpreted as a layer containing ground water, which was previously corrected against the geological and hydrological data of the area. From the cross section of the type resistors, values of 20 - 317 Ωm were obtained for the wenner and wenner-schlumberger arrangements. Selaru Village consists of two rocks unit, the first rock (≤ 120 Ohm.m) in the form of Tanjung Formation rocks, with large porosity and small permeability and groundwater potential in this unit is small (0 - 40 m depth). The second rock (≥ 120 Ohm.m) is Pre Tertiary, with very little porosity and permeability, except secondary porosity in rock fractures.

Lipid-nanodiscs formed by paramagnetic metal chelated polymer for fast NMR data acquisition

Lipid-nanodiscs have been shown to be an exciting innovation as a membrane-mimicking system for studies on membrane proteins by a variety of biophysical techniques, including NMR spectroscopy. Although NMR spectroscopy is unique in enabling the atomic-resolution investigation of dynamic structures of membrane-associated molecules, it, unfortunately, suffers from intrinsically low sensitivity. The long data acquisition often used to enhance the sensitivity is not desirable for sensitive membrane proteins. Instead, paramagnetic relaxation enhancement (PRE) has been used to reduce NMR data acquisition time or to reduce the amount of sample required to acquire an NMR spectra. However, the PRE approach involves the introduction of external paramagnetic probes in the system, which can induce undesired changes in the sample and on the observed NMR spectra. For example, the addition of paramagnetic ions, as frequently used, can denature the protein via direct interaction and also through sample heating. In this study, we show how the introduction of paramagnetic tags on the outer belt of polymer-nanodiscs can be used to speed-up data acquisition by significantly reducing the spin-lattice relaxation (T1) times with minimum-to-no alteration of the spectral quality. Our results also demonstrate the feasibility of using different types of paramagnetic ions (Eu3+, Gd3+, Dy3+, Er3+, Yb3+) for NMR studies on lipid-nanodiscs. Experimental results characterizing the formation of lipid-nanodiscs by the metal-chelated polymer, and their increased tolerance toward metal ions are also reported.

Femtosecond imbalanced time-stretch spectroscopy for ultrafast gas detection

Dual-comb spectroscopy is a promising method for precise optical spectrum analysis with fast data acquisition speed. Here, avoiding using a dual-comb source, femtosecond imbalanced time-stretch spectroscopy with a simple optical layout is proposed and demonstrated. Time-stretch interferometry from one femtosecond laser builds mapping from the optical frequency domain to the radio frequency regime. In experiment, the absorption line of a hydrogen cyanide cell is encoded in the probing arm of a Mach–Zehnder interferometer (MZI). The down-converted radio frequency comb is transformed from a periodically chirped waveform, which is the interferogram of the MZI with different dispersion values on two arms. In a single measurement, the optical frequency comb with a span of 112.5 GHz is down-converted to a range of about 20.8 GHz in the radio frequency domain with a comb spacing equal to the laser repetition frequency of 100 MHz. By turning the optical filter, a spectrum range around 2 THz is analyzed. The acquired optical spectrum resolution is 540 MHz.

Evaluation of multi-shell diffusion MRI acquisition strategy on quantitative analysis using multi-compartment models.

Multi-compartment diffusion models such as Neurite Orientation Dispersion and Density Imaging (NODDI) have been increasingly used for diffusion MRI (dMRI) data processing in biomedical research. However, those models usually require multiple HARDI shells that may increase scanning duration substantially, and their application can be hindered in uncooperative patients (like infants) accordingly. Also, it is highly expected that the same dataset can be explored with multiple diffusion models for retrieving complementary information. Multiple gradient-encoding schemes which consisted of 4-6 shells, moderate b-values (bmax =1,500 or 2,000 s/mm2), and 32-80 gradient directions were explored. The corresponding time of acquisition (TA) for a single scan ranged from 3 to 8 minutes respectively. The dMRI protocols were tested on macaque monkeys using a 3T clinical setting. The data were analysed using both NODDI and diffusion basic spectrum imaging (DBSI) models. The maps of orientation dispersion index (ODI) and CSF were consistent across the 4-6 shell sampling schemes. However, the corresponding intra-cellular volume fraction (ICVF) maps showed reduced pixel counts [1,100±98 (80 directions) vs. 806±70 (32 directions), one slice] in white matter when fewer gradient directions or lower b-value was applied. The hindered diffusion and CSF ratio maps were comparable across these sampling schemes. The maps of restricted diffusion ratio varied across the schemes. However, its mean ratios (0.23±0.02 vs. 0.22±0.01) and pixel counts (1,540±70 vs. 1,510±38, one slice) between the schemes of 80 and 32 directions with b=2,000 s/mm2 were comparable. The present study reports a fast multi-shell dMRI data acquisition and processing strategy which allows for obtaining complementary information about microstructural alteration and inflammation from a single dMRI data set with both NODDI and DBSI models. The proposed approach may be particularly useful for characterizing the neurodegenerative disorders in uncooperative patients like children or acute stroke patients in which brain injury is associated with inflammation.

2019 APHRS expert consensus statement on three-dimensional mapping systems for tachycardia developed in collaboration with HRS, EHRA, and LAHRS.

2019 APHRS expert consensus statement on three-dimensional mapping systems for tachycardia developed in collaboration with HRS, EHRA, and LAHRS.

A full stack data acquisition, archive and access solution for J-TEXT based on web technologies

Abstract Flexible and fast deployable data acquisition system has always been demanded by tokamak facilities. This work proposes a full stack data acquisition, archive and access solution for J-TEXT based on Web technologies. This solution is based on a single unified control system framework, and all of the above systems are using the same communication interface: HTTP RESTful API that unifies the status monitoring, command sending even diagnostic data accessing and so on, which is called the unified data access. A working system on J-TEXT is built using this full stack solution. It consists of a data acquisition system for ECEI, an archiving system built on HDF5 files, a data management system and a set of unified data access interface to access the experiment data. This working system is integrated into J-TEXT CODAC system which is based on EPICS CA and MDSplus. Flexible and modular design makes it easy to apply this solution to different systems, even using only a part of it. Some diagnostic systems other than ECEI also use this solution to upload their data to the MDSplus database just with different configurations. Users can access data without noticing which data source is providing to them. All the user interface in this system are built as web pages which can be accessed using web browser on various devices.

Microfluidic Mixer with Automated Electrode Switching for Sensing Applications

An electronic tongue (e-tongue) is a multisensory system usually applied to complex liquid media that uses computational/statistical tools to group information generated by sensing units into recognition patterns, which allow the identification/distinction of samples. Different types of e-tongues have been previously reported, including microfluidic devices. In this context, the integration of passive mixers inside microchannels is of great interest for the study of suppression/enhancement of sensorial/chemical effects in the pharmaceutical, food, and beverage industries. In this study, we present developments using a stereolithography technique to fabricate microfluidic devices using 3D-printed molds for elastomers exploring the staggered herringbone passive mixer geometry. The fabricated devices (microchannels plus mixer) are then integrated into an e-tongue system composed of four sensing units assembled on a single printed circuit board (PCB). Gold-plated electrodes are designed as an integral part of the PCB electronic circuitry for a highly automated platform by enabling faster analysis and increasing the potential for future use in commercial applications. Following previous work, the e-tongue sensing units are built functionalizing gold electrodes with layer-by-layer (LbL) films. Our results show that the system is capable of (i) covering basic tastes below the human gustative perception and (ii) distinguishing different suppression effects coming from the mixture of both strong and weak electrolytes. This setup allows for triplicate measurements in 12 electrodes, which represents four complete sensing units, by automatically switching all electrodes without any physical interaction with the sensor. The result is a fast and reliable data acquisition system, which comprises a suitable solution for monitoring, sequential measurements, and database formation, being less susceptible to human errors.

Evaluating phone camera and cloud service-based 3D imaging and printing of human bones for anatomical education

ObjectiveTo evaluate the feasibility of a phone camera and cloud service-based workflow to image bone specimens and print their three-dimensional (3D) models for anatomical education.DesignThe images of four typical human...

Top-down proteomics-a near-future technique for clinical diagnosis?

We thank Dr. Laszlo Prokai, Dr. Jae-Seok Kim, and Dr. Hyun Sik Kim for their insightful editorial commentaries on our recent publication “ Diagnosis of hemoglobinopathy and β-thalassemia by 21 Tesla Fourier transform ion cyclotron resonance mass spectrometry and tandem mass spectrometry of hemoglobin from blood ” (1-3). As described by the editorial authors, 21 Tesla Fourier transform ion cyclotron resonance mass spectrometry (21 T FT-ICR MS) and top-down MS/MS set a new benchmark for precision diagnosis of hemoglobinopathies and thalassemia with fast sample preparation (dilute and infuse) and data acquisition (3 min).

High Coherence at f and 2f of Mid-Infrared Supercontinuum Generation in Silicon Germanium Waveguides

Absorption spectroscopy based on supercontinuum generation in the mid-infrared is a powerful technique to analyze the chemical composition of samples. Furthermore, phase-coherent supercontinuum sources can enable fast data acquisition with coherent, stable pulses that allow single-shot measurements. We report here a numerical study of the coherence of an octave-spanning mid-infrared supercontinuum source that was experimentally obtained in an air-clad SiGe/Si waveguide. We show that engineering two closely spaced zero-dispersion wavelengths that enclose an anomalous dispersion band centered around a fixed pump wavelength can produce supercontinuum pulses with high spectral density and full coherence at the extreme ends of the spectrum. This work is important for absorption spectroscopy, on-chip optical frequency metrology, and f -to-2 f interferometry applications.

High-Resolution Dynamic 31P-MR Spectroscopic Imaging for Mapping Mitochondrial Function.

To enable non-invasive dynamic metabolic mapping in rodent model studies of mitochondrial function using 31P-MR spectroscopic imaging (MRSI). We developed a novel method for high-resolution dynamic 31P-MRSI. The method synergistically integrates physics-based models of spectral structures, biochemical modeling of molecular dynamics, and subspace learning to capture spatiospectral variations. Fast data acquisition was achieved using rapid spiral trajectories and sparse sampling of (k, t, T)-space; image reconstruction was accomplished using a low-rank tensor-based framework. The proposed method provided high-resolution dynamic metabolic mapping in rat hindlimb at spatial and temporal resolutions of 4[Formula: see text]2mm3 and 1.28s, respectively. This allowed for in vivo mapping of the time-constant of phosphocreatine resynthesis, a well established index of mitochondrial oxidative capacity. Multiple rounds of in vivo experiments were performed to demonstrate reproducibility, and in vitro experiments were used to validate the accuracy of the estimated metabolite maps. A new model-based method is proposed to achieve high-resolution dynamic 31P-MRSI. The proposed method's ability to delineate metabolic heterogeneity was demonstrated in rat hindlimb. Abnormal mitochondrial metabolism is a key cellular dysfunction in many prevalent diseases such as diabetes and heart disease; however, current understanding of mitochondrial function is mostly gained from studies on isolated mitochondria under nonphysiological conditions. The proposed method has the potential to open new avenues of research by allowing in vivo and longitudinal studies of mitochondrial dysfunction in disease development and progression.

Elemental assessment of the leaf and seed of Rauwolfia serpentina (Sarpagandha) by direct current arc optical emission spectroscopy

Rauwolfia serpentina is an important medicinal plant widely used in formulating various drugs and medicines in the pharmacological industries. The efficacy of the medicinal plants mainly depends upon its constituents like nutrients and trace metals that require their detection with sophisticated techniques having cost-effective, fast data acquisition and multi-elemental detection capability. Therefore, the aim of this study is to investigate the elemental profile of the leaf and seed of the Rauwolfia serpentina plant using direct current arc optical emission spectroscopy. The emission spectrum of the powder of the leaves and seeds of the Rauwolfia serpentina has been acquired in the spectral region 300–900 nm at a resolution of 0.3 nm. The spectrum shows the persistent lines of the calcium, potassium, sodium, iron, magnesium, manganese, molybdenum, nickel, chromium, cadmium, aluminum, titanium, bismuth, mercury, lead, tin, barium, vanadium, silicon and strontium, which confirms the occurrence of these elements in the leaf and seed. Area of the spectral profile evaluated by curve fitting has been used for comparing the content of elements present in leaf and seed of Rauwolfia serpentina. The role of the detected elements has been described with reference to human health.

Research progress of terahertz semiconductor optical frequency combs

Optical frequency comb consists of a series of equally spaced and highly stable frequency lines. Due to the advantages of the ultra-high frequency stability and ultra-low phase noise, the optical frequency combs have important applications in high precision spectroscopy, imaging, communications, etc. In the terahertz frequency range, semiconductor-based electrically pumped terahertz quantum cascade lasers have the characteristics of high output power and wide frequency coverage, and are the ideal candidates for generating terahertz optical frequency combs. In this article, we first briefly introduce the research progress of the optical frequency comb in the communication and the mid-infrared bands. Then we mainly review the research progress of the optical frequency combs based on the terahertz semiconductor quantum cascade laser (QCL) operating in free-running, active frequency stabilization and passive frequency stabilization modes. In free running mode, the terahertz QCL frequency comb is mainly limited by the large group velocity dispersion which results in a small comb bandwidth. Therefore, the dispersion compensation is one of the important methods to stabilize the optical frequency comb and broaden the spectral bandwidth. At present, the active frequency stabilization mode is a relatively matured method to realize the optical frequency combs in terahertz QCLs. In this article, we also detail the methods and applications of terahertz QCL dual-comb operations, including on-chip dual-comb and dual-comb spectroscopy. Compared with the Fourier transform infrared spectroscopy and time domain spectroscopy, the terahertz dual-comb spectroscopy has advantages in fast data acquisition (real-time) and high spectral resolution. The emergence of the dual-comb technique not only verifies the concept of optical frequency combs, but also further promotes the applications of frequency combs.

Fast Small-Scale Membrane Protein Purification and Grid Preparation for Single-Particle Electron Microscopy.

The ongoing development of single-particle cryo-electron microscopy (cryo-EM) is leading to fast data acquisition, data processing, and protein structure elucidation. Quick and reliable methods to go from protein purification and optimization to grid preparation will significantly improve the reach and power of cryo-EM. Such methods would particularly constitute a tremendous advantage in structural biology of membrane proteins, whose published structures stay still far behind the number of soluble protein structures. Here we describe a fast, low-cost, and user-friendly method for the purification and cryo-EM analysis of a recombinant membrane protein. This method minimizes the amount of starting material and manipulation steps needed to go from purification to grid preparation, and could potentially be expanded to other membrane protein purification systems for its direct application in structure determination by single-particle cryo-EM.

Geometric Partitioning of Complex Surface Measurements

Dimensional inspection of microparts is challenging. Optimized processes, such as microdeep-drawing with tailored tools, even increase the requirements. While the development of fast and precise data acquisition techniques is in progress and various solutions already exist, the geometrical evaluation of measuring data still shows open questions: 1) the evaluation methods for freeform surfaces do not provide information in a form that can be directly used to assess dimensional tolerances; 2) manual association of approximating geometric elements to points is not suited for high inspection rates; and 3) partitioning based on the nominal workpiece coordinate system is affected by alignment uncertainties. An algorithm was developed for the automated evaluation of surface measuring data composed of geometric primitives, such as planes, cylinders, and tori, which combines and optimizes the estimation of geometric parameters together with the automatic partitioning of the measured points. This article presents the extension of this holistic approximation (HA) with root point iteration in order to evaluate more complex geometric elements. The verification of the extended HA for a 2-D combination of lines and an ellipse shows no systematic error and achievable uncertainties below 0.8 μm for the approximated shape parameters of an ellipse for simulated surface data with uniformly distributed noise in the range of 1.0 μm. The validation in comparison with commercial metrology software finally exhibits the full potential of the extended HA. As a result, a fully automatic dimensional evaluation is possible, providing geometric parameters that can directly be compared to nominal specifications and tolerances.

Fiber laser-driven gas plasma-based generation of THz radiation with 50-mW average power

We present on THz generation in the two-color gas plasma scheme driven by a high-power, ultrafast fiber laser system. The applied scheme is a promising approach for scaling the THz average power but it has been limited so far by the driving lasers to repetition rates up to 1 kHz. Here, we demonstrate recent results of THz generation operating at a two orders of magnitude higher repetition rate. This results in a unprecedented THz average power of 50 mW. The development of compact, table-top THz sources with high repetition rate and high field strength is crucial for studying nonlinear responses of materials, particle acceleration or faster data acquisition in imaging and spectroscopy.

CPEM: Accurate cancer type classification based on somatic alterations using an ensemble of a\xa0random forest and a deep neural network

With recent advances in DNA sequencing technologies, fast acquisition of large-scale genomic data has become commonplace. For cancer studies, in particular, there is an increasing need for the classification of cancer type based on somatic alterations detected from sequencing analyses. However, the ever-increasing size and complexity of the data make the classification task extremely challenging. In this study, we evaluate the contributions of various input features, such as mutation profiles, mutation rates, mutation spectra and signatures, and somatic copy number alterations that can be derived from genomic data, and further utilize them for accurate cancer type classification. We introduce a novel ensemble of machine learning classifiers, called CPEM (Cancer Predictor using an Ensemble Model), which is tested on 7,002 samples representing over 31 different cancer types collected from The Cancer Genome Atlas (TCGA) database. We first systematically examined the impact of the input features. Features known to be associated with specific cancers had relatively high importance in our initial prediction model. We further investigated various machine learning classifiers and feature selection methods to derive the ensemble-based cancer type prediction model achieving up to 84% classification accuracy in the nested 10-fold cross-validation. Finally, we narrowed down the target cancers to the six most common types and achieved up to 94% accuracy.

Performance Tests of Smart City IoT Data Repositories for Universal Linear Infrastructure Data and Graph Databases

The infrastructure managed by Smart City systems includes mainly linear structures, such as pipelines, electric power lines, railway lines, etc.. In this paper, we propose the transcription of linear infrastructure to graph representation and storing needed meta-data in a graph database, merged with the traditional relational database used for device management. Such an approach enables fast acquisition of data about infrastructure’s properties and allows merging information about the structure of the managed infrastructure with information devices’ properties and statistics. We develop a graph generator that generates virtual network basing on representative examples of linear infrastructure, incorporation of a data from existing metering systems with the generated structure, which automates the deployment and allows to evaluate the performance of Smart City monitoring and management system. We present results of performance tests that show and the creation time of graph database structures in Neo4j and the difference between the performance of the Microsoft SQL Server database and the Neo4j database in a few Smart City use cases. The results show that the use of the graph database to execute queries related to linear infrastructure allows decreasing the response time up to 9 times.