Image Analysis Procedure Research Articles

Curved passive mixing structures: a robust design to obtain efficient mixing and mass transfer in microfluidic channels

Analyte mixing and delivery to a functionalized sensor surface are important to realize several advantages associated with biosensors integrated with microfluidic channels. Here, we present a comparison between a herringbone structure (HBS) and a curved passive mixing structure of their efficiency at facilitating mixing and surface saturation using fluorescein included in one of the inlets of a Y-channel microfluidic device. We performed a large parametric study to assess the effects of varying the height of the microfluidic channel as well as the height, width, and spacing of the passive mixing structures. Scanning confocal microscopy combined with a custom-designed image-analysis procedure were utilized to visualize and quantify the observed changes in efficiency in inducing solute mixing by the different designs. The flow patterns within the channels were found to vary significantly with changes in the geometry of the passive mixing structures, which in turn affected the efficiency of the channel at mixing the fluid and saturating the surface opposite the mixing structures. The solute mixing as a function of the channel length was also determined; an initial slow mixing rate does not always coincide with a low mixing index (MI). We found that the range of MIs for the curved mixing structure 1 cm downstream from the inlet was 0.85–0.99 whilst for our HBS it was 0.74–0.98, depending on the design parameters of the passive mixing structures. Overall, this study shows that the curved passive mixing structure family is more robust in inducing efficient mixing than the HBSs.

Impact of the Analytical Approach on the Reliability of MRI-Based Assessment of Hepatic Fat Content.

ABSTRACTMRI is a popular noninvasive method for the assessment of liver fat content. After MRI scan acquisition, there is currently no standardized image analysis procedure for the most accurate estimate of liver fat content. We determined intraindividual reliability of MRI-based liver fat measurement using 10 different MRI slice analysis methods in normal-weight, overweight, and obese individuals who underwent 2 same-day abdominal MRI scans. We also compared the agreement in liver fat content between analytical methods and assessed the variability in fat content across the entire liver. Our results indicate that liver fat content varies across the liver, with some slices averaging 54% lower and others 75% higher fat content than the mean of all slices (gold standard). Our data suggest that the entire liver should be contoured on at least every 10th slice to achieve close agreement with the gold standard.

Impact of the Binder Nature on the Morphological Change of Sulfur Electrodes upon Cycling Investigated By in Situ Characterization Methods

Even though the lithium-sulfur (Li/S) battery system is one of the most promising candidates to become the successor of the current Li-ion battery, its insufficient cycle life needs to be resolved before envisioning their commercial use. Several phenomena are reported to be involved in the capacity fading of the Li/S cells upon cycling, among which important structural changes in the sulfur electrode. The binder material plays a crucial role in maintaining the integrity of the electrode through cycling, and the use of innovative in situ characterization techniques enables to get a better understanding of its complex mechanisms. In the present study, operando acoustic emission (AE) and dilatometry techniques, and in situ synchrotron X-ray tomography are used to study the degradation mechanism of sulfur-based electrodes depending on their binder formulation [1-3]. In particular, the impact of using a polyelectrolyte binder (poly(diallyldimethylammonium) bis(trifluromethane sulfonyl)imide), previously known for its polysulfide-retaining and ionic conductive abilities [4], on the morphological degradation of the sulfur electrode is evaluated and compared to more conventional binders (poly(vinylidene difluoride) (PVdF) and carboxymethyl cellulose (CMC)) in the present studyTo date, AE technique has been used to characterize the degradation mechanisms (crack growth, friction, delamination, matrix cracking, corrosion, etc) of various materials subjected to a stress by mechanical, pressure or thermal means, and has been used in our previous work to monitor the mechanical degradation (e.g. cracking, collapsing) of electrodes upon cycling. The operando electrochemical dilatometry technique allows to measure thickness variation of an electrode material undergoing electrochemical reactions and has been used to study various battery electrode materials such as graphite or Si anodes. Finally, X-Ray computed tomography (XRCT) is certainly one of the most powerful analytical tools enabling non-destructive 3D imaging of objects with complex and porous morphologies such as S-based electrodes. Using appropriate image processing, segmentation and analysis procedures, quantitative parameters can be extracted such as the volume fraction, the size distribution, the connectivity and the geometrical tortuosity of the constitutive phases of the sulfur electrodes. A spatial resolution of a few tens of nm can be reached with a synchrotron X-ray source. Operando dilatometry is used for one the very first times on sulfur-based electrodes and shows that during the initial sulfur dissolution process, the polyelectrolyte-based electrode displays a lower irreversible thickness contraction of ~16% compared to ~22% and ~31% for CMC and PVdF, respectively. This is confirmed by the XRT measurements showing a reduced thickness variation for the polyelectrolyte electrode compared to the CMC electrode. The same trend is found in the AE results, where a lower acoustic activity attributed to the rupture of the binder/carbon/sulfur network is detected during the 1st discharge plateau for the polyelectrolyte electrode. All these results confirm the major role of the binder for the Li/S system as well as the highly promising performance of the present polyelectrolyte binder. Thanks to its multifunctionality, it impacts both the diffusion of the active material outside the electrode and the electrode integrity and therefore the conduction paths and accessible active surface for electrochemical processes.[1] Q. Lemarié, H. Idrissi,E. Maire, P.X. Thivel, F. Alloin, L. Roué. Impact of the binder nature on the morphological change of sulfur electrodes upon cycling investigated by in-situ characterization methods, J. Power Sources 477 (2020) 228374.[2] Q. Lemarié, E. Maire, H. Idrissi, P.X. Thivel, F. Alloin, L. Roué,Sulfur-based electrode using a polyelectrolyte binder studied via coupled in situ synchrotron X-ray diffraction and tomography, ACS-Applied Energy Materials 3 (2020) 2422-2431.[3] Q. Lemarié, F. Alloin, P.X. Thivel, H. Idrissi, L. Roué, Study of sulfur-based electrodes by operando acoustic emission, Electrochim. Acta 299 (2019) 415-422[4] L. Li, T.A. Pascal, J.G. Connell, F.Y. Fan, S.M. Meckler, L. Ma, Y.-M. Chiang, D. Prendergast, B.A. Helms, Molecular understanding of polyelectrolyte binders that actively regulate ion transport in sulfur cathodes, Nat. Commun. 8 (2017) 1–10. Figure 1

Reliability in ultrasound measurements of plantar aponeurosis thickness

PurposeGiven the increasing research interest in ultrasound plantar aponeurosis (PA) thickness measurements, this study aimed to analyze the inter and intra-rater reliability of independent sonograms and to identify the error related to the image analysis procedure. MethodsTwenty-one healthy men participated in this study. Imaging of PA consisted of two independent sonograms per subject. Two raters (R1 and R2) evaluated each sonogram twice using standardized steps. Precision of the image analysis procedure was analyzed using the Bland and Altman plot and Intraclass Correlation Coefficient (ICC). Agreement estimates and ICC were used to assess absolute and relative inter and intra-rater reliability. ResultsReliability of PA thickness was found to depend strongly on the number of images acquired per subject. Intra-rater agreement for single measurements were 0.696 (R1) and 0.495 (R2), whereas average measurements yielded values of 0.821 (R1) and 0.662 (R2), respectively. Precision within a sonogram varied from ICC values of 0.873 to 0.960 (intra-rater) and 0.670 to 0.822 (inter-rater). ConclusionMost part of the error in PA thickness measurements seems to be related to the sonogram acquisition process and not to the visual inspection of the image. To minimize error, average values of a minimum of two images per subject should be used. The moderate agreement between raters found in this study ratifies the need of all measurements being made by the same rater or group of raters. If a single rater evaluates all subjects, performing multiple measurements over one image does not seem to affect ICC as much as acquiring multiple images.

Simultaneous BOLD-fMRI and constant infusion FDG-PET data of the resting human brain

Simultaneous [18 F]-fluorodeoxyglucose positron emission tomography and functional magnetic resonance imaging (FDG-PET/fMRI) provides the capability to image two sources of energetic dynamics in the brain – cerebral glucose uptake and the cerebrovascular haemodynamic response. Resting-state fMRI connectivity has been enormously useful for characterising interactions between distributed brain regions in humans. Metabolic connectivity has recently emerged as a complementary measure to investigate brain network dynamics. Functional PET (fPET) is a new approach for measuring FDG uptake with high temporal resolution and has recently shown promise for assessing the dynamics of neural metabolism. Simultaneous fMRI/fPET is a relatively new hybrid imaging modality, with only a few biomedical imaging research facilities able to acquire FDG PET and BOLD fMRI data simultaneously. We present data for n = 27 healthy young adults (18–20 yrs) who underwent a 95-min simultaneous fMRI/fPET scan while resting with their eyes open. This dataset provides significant re-use value to understand the neural dynamics of glucose metabolism and the haemodynamic response, the synchrony, and interaction between these measures, and the development of new single- and multi-modality image preparation and analysis procedures.

A new method for gridding passive microwave data with mixed measurements and spatial correlation

In this article we develop a new method to grid passive microwave data in the presence of spatial correlation patterns. Our proposal combines a Tychonov inverse method with a generalized cross validation procedure to grid the observations over a discrete retrieval grid. To build this grid, the study region is partitioned into objects following an object-based image analysis procedure. Then, this partition is refined into small cells of similar size. Two cells from the same object are considered of the same type. The procedure to estimate the brightness temperature of each cell is based on a least-squares estimation with a cell-type aware Tychonov regularization method. This method assumes that the brightness temperature heterogeneity within each cell can be neglected and that adjacent cells of the same type have similar brightness temperature. In other words, spatial correlations are considered within each object in the scene. The Tychonov regularization parameter is found using a fast generalized cross validation procedure that makes it possible to solve the inverse problem when the observational error variance is not known. We evaluate the proposed method using different synthetic scenarios and compare it with other methods. The evaluation shows an excellent performance of the proposed method when the brightness temperature field varies smoothly over each object in the scene. But it also shows that the method is competitive when the brightness temperature field does not present spatial correlations. We conclude that the proposed algorithm provides a fast and robust method to solve the original inverse problem.

Detection and Quantification of Cracking in Concrete Aggregate through Virtual Data Fusion of X-ray Computed Tomography Images.

In this work, which is part of a larger research program, a framework called “virtual data fusion” was developed to provide an automated and consistent crack detection method that allows for the cross-comparison of results from large quantities of X-ray computed tomography (CT) data. A partial implementation of this method in a custom program was developed for use in research focused on crack quantification in alkali-silica reaction (ASR)-sensitive concrete aggregates. During the CT image processing, a series of image analyses tailored for detecting specific, individual crack-like characteristics were completed. The results of these analyses were then “fused” in order to identify crack-like objects within the images with much higher accuracy than that yielded by any individual image analysis procedure. The results of this strategy demonstrated the success of the program in effectively identifying crack-like structures and quantifying characteristics, such as surface area and volume. The results demonstrated that the source of aggregate has a very significant impact on the amount of internal cracking, even when the mineralogical characteristics remain very similar. River gravels, for instance, were found to contain significantly higher levels of internal cracking than quarried stone aggregates of the same mineralogical type.

Peritumoral immune infiltrates in primary tumours are not associated with the presence of axillary lymph node metastasis in breast cancer: a retrospective cohort study.

BackgroundThe axillary lymph nodes (ALNs) in breast cancer patients are the body regions to where tumoral cells most often first disseminate. The tumour immune response is important for breast cancer patient outcome, and some studies have evaluated its involvement in ALN metastasis development. Most studies have focused on the intratumoral immune response, but very few have evaluated the peritumoral immune response. The aim of the present article is to evaluate the immune infiltrates of the peritumoral area and their association with the presence of ALN metastases.MethodsThe concentration of 11 immune markers in the peritumoral areas was studied in 149 patients diagnosed with invasive breast carcinoma of no special type (half of whom had ALN metastasis at diagnosis) using tissue microarrays, immunohistochemistry and digital image analysis procedures. The differences in the concentration of the immune response of peritumoral areas between patients diagnosed with and without metastasis in their ALNs were evaluated. A multivariate logistic regression model was developed to identify the clinical-pathological variables and the peritumoral immune markers independently associated with having or not having ALN metastases at diagnosis.ResultsNo statistically significant differences were found in the concentrations of the 11 immune markers between patients diagnosed with or without ALN metastases. Patients with metastases in their ALNs had a higher histological grade, more lymphovascular and perineural invasion and larger-diameter tumours. The multivariate analysis, after validation by bootstrap simulation, revealed that only tumour diameter (OR = 1.04; 95% CI [1.00–1.07]; p = 0.026), lymphovascular invasion (OR = 25.42; 95% CI [9.57–67.55]; p < 0.001) and histological grades 2 (OR = 3.84; 95% CI [1.11–13.28]; p = 0.033) and 3 (OR = 5.18; 95% CI [1.40–19.17]; p = 0.014) were associated with the presence of ALN metastases at diagnosis. This study is one of the first to study the association of the peritumoral immune response with ALN metastasis. We did not find any association of peritumoral immune infiltrates with the presence of ALN metastasis. Nevertheless, this does not rule out the possibility that other peritumoral immune populations are associated with ALN metastasis. This matter needs to be examined in greater depth, broadening the types of peritumoral immune cells studied, and including new peritumoral areas, such as the germinal centres of the peritumoral tertiary lymphoid structures found in extensively infiltrated neoplastic lesions.

Imagens do corpo: superfícies reversíveis e marcas de resistências no brinquedo de miriti

O objetivo é refletir sobre as representações do corpo nas imagens do brinquedo de miriti, um bem cultural da cidade de Abaetetuba/Pará. Neste sentido, buscamos apoio no Estudos Culturais pós-críticos, contando, entre outros, com Hall (2016), Kellner (1995), Foucault (1987) e Silva (1999). A decisão metodológica é pelo alfabetismo crítico, um procedimento emergente para a análise de imagens. Ao ser intensamente disseminada em blogs, livros, camisetas e bolsas, as imagens da peça casal de namorados representam o corpo e o casal ideal e afetam a todos, particularmente jovens do ensino médio. Por constituir não apenas a cultura contemporânea, mas as subjetividades juvenis no cotidiano escolar, as imagens merecem a atenção, pois mesmo representando corpos, gêneros e sexualidades hegemônicas, sendo a representação reversível, é capaz de constituir outros modos de ser e de viver.

Experimental and numerical investigation of saltwater intrusion dynamics on sloping sandy beach under static seaside boundary condition

Two-dimensional sandbox experiments were conducted to investigate the variable-density circulation and flow patterns in sloping beach configurations. The experiments provide new benchmark results for validating the sandbox models based on quantitative and qualitative measurements. Previous studies have considered density dependent flow in porous media, vertical beach face saltwater boundary, and multilayered hydrogeology ignoring a sloping beach face, which is a much more common phenomenon in real world. The present study considers sloping beach face under both homogeneous and low-permeability strata configurations. The geohydraulic processes encountered were quantified through pore-water pressure measurements and image analysis techniques. Moreover, validations were performed with numerical simulations (FEFLOW). A simple image analysis procedure is proposed with respect to two-dimensional laboratory scale benchmark experiments. Experimental results provided a detailed circulation flow path within and outside the saltwater wedge with sloping beach face. Fingering effect in porous media was also observed for both the experiments during initial time periods. Stability analysis shows the existence of a stationary convective flow pattern followed by gravitational instabilities under the quasi-steady state condition.

Descriptive Image Analysis: Part III. Multilevel Model for Algorithms and Initial Data Combining in Pattern Recognition

This is the third article in a series of publications devoted to the current state and future prospects of Descriptive Image Analysis (DIA), one of the leading and intensively developing branches of modern mathematical theory of image analysis. The fundamental problem of computer science touched by the article is the automation of extracting from images of information necessary for intellectual decision-making. A new class of models for the image analysis and recognition process and its constituent procedures is introduced and described – a multilevel model of image analysis and recognition procedures (MMCAI) – which is based on the joint use of methods of combining algorithms and methods of combining fragmentary initial data – partial descriptions of the object of analysis and recognition – an image. The architecture, functionality, limitations, and characteristics of the MMCAI are justified and defined. The main properties of the MMCAI class are as follows: (a) combining the fragments of the initial data and their representations and combining algorithms at all levels of image analysis and recognition processes; (b) the use of multialgorithmic schemes in the image analysis and recognition process; and (c) the use of dual representations of images as input data for the analysis and recognition algorithms. The problems arising in the development of the MMCAI are closely related to the development of the following areas of the modern mathematical theory of image analysis: (a) algebraization of image analysis; (b) image recognition algorithms accepting spatial information as input data; (c) multiple classifiers (MACs). A new class of models for image analysis is introduced in order to provide the following possibilities: (a) standardization, modeling, and optimization of Descriptive Algorithmic Schemes (DAS) that form the brainware of the MMCAI and processing heterogeneous ill-structured information – dual representations – spatial, symbolic, and numerical representations of the initial data; (b) comparative analysis, standardization, modeling, and optimization of different algorithms for the analysis and recognition of spatial information. The fundamental importance of the results of these studies for the development of the mathematical theory of image analysis and their scientific novelty are associated with the statement of problems and the development of methods for modeling the processes of automation of image analysis when ill structured representations of images, including spatial data proper – images and their fragments, image models, incompletely formalized representations, and subsets of combinations of these representations – are used as the initial data. The introduction of the MMCAI as a standard structure for representing algorithms for the analysis and recognition of two-dimensional information and dual representations of images allow one to generalize and substantiate well-known heuristic recognition algorithms and assess their mathematical properties and applied utility.

Flame analysis for prediction of thermocouple temperature and quality of sponge iron at TATA steel long products limited

The temperature profiles of the gas and charge in a coal-fired rotary sponge iron kiln affect both the iron ore reduction process and accretion formation. The temperature profile of charge is estimated from the eleven thermocouples (TC1-TC11) placed along the 80 m length of the kiln. The quality prediction models are heavily dependent upon the accuracy of the measurement of TC10. However, slowly, as the kiln’s campaign life increases TC10, and other thermocouples too, get corrupted due to deposition of material (accretions) on the thermocouples. At the beginning of the campaign, however, there is no accretion on TC10. In the present work, an attempt is made to directly correlate flame characteristics with TC10 and with quality of iron produced so that when TC10 is corrupted due to accretion or breakdown, we can still survive by using flame characteristics as a guide to control quality. The flame inside the rotary kiln has been analysed by using image analysis procedures for the first time in a sponge iron plant. The flame’s estimated average temperature and pixel intensity information are correlated with (a) the temperature measured by the thermocouple TC10 (which is installed at a distance of 20 m from the rotary kiln outlet hood) and (b) with quality of iron produced. It is found that use of average flame temperature for quality prediction has several advantages in terms of increased accuracy of prediction and quicker response time of flame to short-time changes in coal quality (particle size, moisture, ash content, etc) whereas TC10 thermocouple takes much longer to reflect these changes due to slow process of heat transfer to charge. In addition, the adverse effect of accretion formation on TC10 for quality prediction has been overcome.

Polarimetric Semivariogram-Based Spatial Scale Selection for PolSAR Image Segmentation With Mean-Shift Algorithm

Image segmentation has been an important procedure in object-based image analysis (OBIA), which takes image object as a processing unit. The spatial scale in image segmentation has great importance in OBIA. Due to the high heterogeneity and large dynamic range of polarimetric synthetic aperture radar (PolSAR) images, it is often difficult to choose optimal spatial scales. This letter proposes a polarimetric semivariogram-based spatial scale selection method for PolSAR image segmentation. The optimal spatial bandwidth parameter in the mean-shift algorithm is pre-estimated based on the combined polarimetric and statistical analysis of PolSAR images. By implementing a quantitative evaluation of segmentation result, the effectiveness of the proposed method in optimal spatial bandwidth selection for PolSAR image segmentation is verified. Experiments on both the EMISAR and UAVSAR L-band PolSAR data sets testify the validity of the proposed adaptive optimal bandwidth selection strategy for PolSAR images.

Miniature particulate matter counter and analyzer based on lens-free imaging of light scattering signatures with a holed image sensor

We report our latest developments on a novel miniature particulate matter (PM) sensor for personal air quality monitoring. This optical sensor combines a visible fibered light source and a vertical air channel drilled out of a holed retina. The fabrication of such retina features an unconventional design of a CMOS image sensor and a specific drilling post process at wafer level. The scattering of light by a single particle generates a distinctive pattern. By using a compact optical set-up, we measure a lens-free projection of the scattering signature on the image sensor. We present the design and fabrication of such sensor as well as experimental signatures that are consistent with our in-house analytical model. We demonstrate counting and differentiation between calibrated particles of different sizes. Our current setup allows for the detection of single 320 nm polystyrene particles. Finally, we describe our image analysis procedure that fits a measured signature with a modelled one in order to retrieve particle's size and refractive index.

Batch leaching testing of stabilized dredged bottom-sea sediments

This study aims to define the long-term leaching of metals from structural fills composed of quarry byproduct-amended marine-dredged material under the influence of pH and to study the geochemical behavior of the species likely to form. Compaction and shear tests, image analysis, and pHstat and toxicity characteristic leaching procedure tests were undertaken to study the metal leaching behavior of raw dredged sediments and their blends prepared with three different quarry fines. Geochemical analysis was conducted to determine the predominant oxidation states from the analyzed metals, the aqueous concentrations of metal species, and the dominant leaching control mechanisms in the leachates. The quarry fine-amended dredged sediments satisfied the local compaction specifications for highway embankment construction while the raw sediments did not. The effective friction angle of the blends was also higher than that of raw sediments due to differences in soil structure and shape parameters. Leaching of As during the pHstat leaching tests followed an amphoteric pattern for raw sediments and a cationic pattern for the blends. Al, Cu, Fe, Ni, and Zn concentrations leached from the blends were below the EPA water quality limits at near-neutral pH. The concentrations of all metals released during the batch leach tests from the treated dredged materials are below the water quality limits under varying pH conditions. Geochemical modeling results indicated that release of all elements except arsenic from the treated dredged sediments was controlled by the dissolution and precipitation of oxide, hydroxide, and carbonate solids containing the elements.

In vivo large-scale analysis of Drosophila neuronal calcium traces by automated tracking of single somata

How does the concerted activity of neuronal populations shape behavior? Impediments to address this question are primarily due to critical experimental barriers. An integrated perspective on large scale neural information processing requires an in vivo approach that can combine the advantages of exhaustively observing all neurons dedicated to a given type of stimulus, and simultaneously achieve a resolution that is precise enough to capture individual neuron activity. Current experimental data from in vivo observations are either restricted to a small fraction of the total number of neurons, or are based on larger brain volumes but at a low spatial and temporal resolution. Consequently, fundamental questions as to how sensory information is represented on a population scale remain unanswered. In Drosophila melanogaster, the mushroom body (MB) represents an excellent model to analyze sensory coding and memory plasticity. In this work, we present an experimental setup coupled with a dedicated computational method that provides in vivo measurements of the activity of hundreds of densely packed somata uniformly spread in the MB. We exploit spinning-disk confocal 3D imaging over time of the whole MB cell body layer in vivo while it is exposed to olfactory stimulation. Importantly, to derive individual signal from densely packed somata, we have developed a fully automated image analysis procedure that takes advantage of the specificities of our data. After anisotropy correction, our approach operates a dedicated spot detection and registration over the entire time sequence to transform trajectories to identifiable clusters. This enabled us to discard spurious detections and reconstruct missing ones in a robust way. We demonstrate that this approach outperformed existing methods in this specific context and made possible high-throughput analysis of approximately 500 single somata uniformly spread over the MB in various conditions. Applying this approach, we find that learned experiences change the population code of odor representations in the MB. After long-term memory (LTM) formation, we quantified an increase in responsive somata count and a stable single neuron signal. We predict that this method, which should further enable studying the population pattern of neuronal activity, has the potential to uncover fine details of sensory processing and memory plasticity.

Local description of foam flow, deformation and pressure drop in narrow constricted channels

We study in extensive detail the flow of dry and wet gas-liquid foams through a narrow two-dimensional channel comprising a complex constriction. The effects of constriction profile and size of aperture, foam flowrate, liquid holdup and liquid viscosity are experimentally investigated and a sophisticated image analysis procedure is developed to extract local fields of foam flow and deformation. Foam dynamics are scrutinised and interpreted in terms of local velocity distribution, elastic strain (texture tensor), plastic deformation (T1 events) and pressure drop. Important foam transformations occur in the vicinity of the constriction. For the first time, the relationship between pressure drop, flowrate and size of constriction aperture is investigated.

Morphological characterization of crushed coal gangue by micro X-ray computed tomography scanning

ABSTRACT To accurately estimate the separation effects and breakage characteristics of coal and gangue particles (CGPs), it is of great significance to understand the meso-morphologies of CGPs and their correlations with different crushing conditions. In the present work, the impact crushing tests were conducted to obtain the effects of sizes, gangue mixture ratios, and crushing velocities on the fractal characteristics of the crushed PSD characteristics, using an in-house designed device. Then, X-ray computed tomography (XCT) scanning with different resolutions was conducted on uncrushed and crushed CGPs, followed by a series of image processing and analysis procedures. Finally, the effects of different impact velocities on the evolution of morphological parameters, the fracture ratios, and the fractal fragmentation characteristics were investigated using different image processing algorithms. Results show that many factors such as the energy consumption, the source of raw ores, the impact velocity, and the feeding particle size should be considered to design an optimal crushing scheme for best crushing effects.

Direct Assessment of Separator Strain in Li-Ion Batteries at the Onset of Mechanically Induced Short Circuit

In the literature, mechanical deformation of Li-ion batteries (LIB) is characterized in terms of global or volumetric strain of the entire cell to develop load vs. strain plots. In characterizing the mechano-electrical–thermal–chemical interaction of the battery in relation to internal short circuit (ISC) due to mechanical load, these estimated strains are “indirect strains” at best. Direct evaluation of “internal local strains” between the layers, particularly, in the first separator layer should be a critical material parameter as it relates to separator rupture and should be the key link in ISC in LIBs. We make an effort to assess “internal local strains” which is not reported elsewhere, first by using the Oak Ridge National Laboratory (ORNL) approach to use plastic deformation of aluminum casing to “freeze” deformation states of the LIBs followed by microscopy to image undeformed and deformed cells. An image analysis procedure is developed to estimate transverse compression strains in the cells, e.g., in Cu anode, Al cathode, and the polymeric separator. The local strain experienced by the polymeric separator nearest to ball indentation is found to be close to 65–70% and this strain level is much higher than 40–50% maximum average strains estimated for the same sample.

A novel approach to estimating the competitive ability of Cirsium arvense in cereals using unmanned aerial vehicle imagery

SummaryEight experiments were carried out in Denmark to determine the yield loss of spring barley due to Cirsium arvense in farmers' fields and to suggest and evaluate a novel approach for quantifying C. arvense infestation in large plots. Literature about the competitive ability of C. arvense is old, scattered and inconclusive, and existing models for estimating crop yield loss are based on data from North America. This study showed that C. arvense coverage could be quantified from unmanned aerial vehicle imagery using a manual image analysis procedure. This gave similar results as scoring the coverage. Yield loss of spring barley due to C. arvense infestation assessed at harvest was given by Y = 100·(1−exp(−0.00170·X)) where Y is the percentage of crop yield loss and X is the percentage of C. arvense coverage. The yield loss was much lower than estimates from models that have been developed in North America. It is speculated that the main reason for this is the later emergence of C. arvense than the crop due to lower soil temperatures in spring. Grain moisture increased linearly with C. arvense coverage: M = 0.0310·X where M is the proportional (%) increase in grain moisture and X is the proportion (%) of C. arvense coverage. Automated image analysis procedures are needed to estimate C. arvense coverage on field scales, and further experiments are needed to reveal whether the low competitive ability of C. arvense found in this study is representative for Northern Europe.