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Purpose : To investigate the ability of simultaneous multislice triple-echo steady-state (SMS- TESS) imaging to provide quantitative maps of multiple tissue parameters, i.e., longitudinal and transverse relaxation times (T 1 and T 2 ), proton density (PD), and off-resonance ( ∆ B 0 ), in the human brain at 3 T from a single scan. Methods : TESS acquisitions were performed in 2D mode to reduce motion sensitivity and accelerated by a simultaneous multislice excitation scheme (CAIPIRINHA) with SENSE reconstruction. SMS-acceleration factors (R) of 2 and 4 were evaluated. The in vitro and in vivo validation process included standard reference scans to analyze the accuracy of T 1 , T 2 , and  B 0 estimates, as well as single-slice TESS measurements. Results : For R=2, the quantification of T 1 , T 2 , PD, and ∆ B 0 was overall reliable with marginal noise enhancement. T 1 and T 2 values were in good agreement with the reference measurements and single-slice TESS. For R=4, the agreement of  B 0 with the standard reference was excellent and the determination of T 1 , T 2 , and PD was reproducible, however, increased variations in T 1 and T 2 values with respect to single-slice TESS were observed. Conclusion : SMS-TESS has shown potential to offer rapid simultaneous T 1 , T 2 , PD, and ∆ B 0 mapping of human brain tissues.

We report on a new method to achieve the single-scan polarization-resolved degenerate four-wave mixing (DFWM) spectroscopy in a Rb atomic medium using a vector optical field, in which two pump beams are kept linearly polarized and a vector beam is employed as the probe beam. As the polarization and intensity of the DFWM signal are closely dependent on the polarization state of the probe beam, a vector probe beam with space-variant states of polarization is able to generate a DFWM signal with space-variant states of polarization and intensity across the DFWM image. Accordingly, the polarization-resolved spectra can be retrieved from a single DFWM image. To the best of our knowledge, this is the first time that the single-scan polarization-resolved spectrum detection has been realized experimentally with a vector beam. This work provides a simple but efficient single-scan polarization-resolved spectroscopic method, which would be of great utility for the samples of poor light stability and fast optical processes.

The agriculture industry experiences severe economic losses each year due to infection of cereal crops with Fusarium, often leading to contamination with the secondary metabolite mycotoxin Deoxynivalenol (DON). Timely detection of Fusarium Damaged Kernels (FDK) could provide producers with an opportunity to develop and implement mitigation strategies and minimize corresponding losses, and also to avoid health risks to humans and animals. Given the slow, labor-intensive, and often destructive current FDK and DON detection methods, the agriculture industry is in dire need of fast, non-invasive, and non-destructive alternative screening techniques. Recent research efforts have introduced hyperspectral imaging (HSI) as a promising non-destructive tool for FDK and DON risk management in cereals. However, a simple single scan for both FDK and DON identification is highly desired due to its ease of use and resulting commercial acceptance. To this end, the present research investigated the feasibility of using NIR HSI in the 960–1700 nm wavelength range to detect the presence of FDK and its secondary metabolite DON in Canadian Western Red Spring (CWRS) wheat. The two k-nearest neighbour (kNN)-based classifiers were developed by identifying 0.2% of the classified spectra that identify their classes. These were identified through their consistent categorization using faster 1NN classifiers from samples of spectra. The resulting 3NN classifiers, one for identifying the presence of FDK and the other for determining the presence of DON, gave good results in classification. The FDK classifier obtained 85% accuracy and 92% sensitivity, and the DON classifier achieved 80% accuracy and 77% sensitivity. Our results indicate that a single HSI scan can be used to rapidly identify the presence of both FDK and DON in CWRS wheat samples. The developed model can be used as a pre-screening technique by the wheat industry to reduce the time and labor currently expended in FDK and DON identification.

We propose and experimentally demonstrate single-scan vectorial frequency-resolved optical gating (FROG) which characterizes the amplitude, phase and polarization of ultrashort laser pulses using a single measured spectrogram. It is carried out by rotating the polarization of the incoming pulse (using a half-wavelength waveplate), in parallel to scanning the delay between the pulse and its replica in an otherwise ordinary FROG apparatus. A ptychography-based phase retrieval algorithm extracts the full pulse information from the recorded spectrogram. We numerically show that this method is reliable and use it to experimentally reconstruct a pulse with intricate time-dependent polarization. We also show that this method can be used to remove time-reversal ambiguity of second harmonic generation FROG.

In many 3-D perception applications, ground segmentation is a necessary preprocessing phase together with point cloud cleaning and outlier removal. This letter presents a method for ground segmentation in large-scale point clouds of industrial environments acquired using a terrestrial laser scanner (TLS). TLSs provide high-precision, dense 3-D measurements, and therefore, such instruments are becoming the state of the art technology for surveying tasks. In contrast to many previous works, where ground segmentation has been investigated using a single scan (e.g., in LiDAR-equipped vehicles), experiments have been performed in large-scale point clouds that contain over $10^{10}$ points measured from multiple scan stations. The proposed solution is based on a robust estimation of points belonging to the ground below each scan station and it can be applied even in challenging scenarios with nonplanar regions.

Cartilage injuries may be detected using contrast-enhanced computed tomography (CECT) by observing variations in distribution of anionic contrast agent within cartilage. Currently, clinical CECT enables detection of injuries and related post-traumatic degeneration based on two subsequent CT scans. The first scan allows segmentation of articular surfaces and lesions while the latter scan allows evaluation of tissue properties. Segmentation of articular surfaces from the latter scan is difficult since the contrast agent diffusion diminishes the image contrast at surfaces. We hypothesize that this can be overcome by mixing anionic contrast agent (ioxaglate) with bismuth oxide nanoparticles (BINPs) too large to diffuse into cartilage, inducing a high contrast at the surfaces. Here, a dual contrast method employing this mixture is evaluated by determining the depth-wise X-ray attenuation profiles in intact, enzymatically degraded, and mechanically injured osteochondral samples (n = 3 × 10) using a microCT immediately and at 45 min after immersion in contrast agent. BiNPs were unable to diffuse into cartilage, producing high contrast at articular surfaces. Ioxaglate enabled the detection of enzymatic and mechanical degeneration. In conclusion, the dual contrast method allowed detection of injuries and degeneration simultaneously with accurate cartilage segmentation using a single scan conducted at 45 min after contrast agent administration.

Point 1: In this study we introduce metaproperty analysis of Terrestrial Laser Scanner (TLS) data, and demonstrate its application through several ecological classification problems. Metaproperty analysis considers pulselevel and spatial metrics derived from the hundreds of thousands to millions of lidar pulses present in a single scan from a typical contemporary instrument. In such large aggregations, properties of the populations of lidar data reflect attributes of the underlying ecological conditions of the ecosystems. Point 2: In this study we provide the Metaproperty Classification Model to employ TLS metaproperty analysis for classification problems in ecology. We applied this to a proof-of-concept study, which classified 88 scans from rooms and forests with 100% accuracy, to serve as template. Point 3: We then applied the Metaproperty Classification Model in earnest, to separate scans from temperate and tropical forests with 97.09% accuracy (N = 224), and to classify scans from inland and coastal tropical rainforests with 84.07% accuracy (N = 270). Point 4: The results demonstrate the potential for metaproperty analysis to identify subtle and important ecosystem conditions, including diseases and anthropogenic disturbances. Metaproperty analysis serves as an augmentation to contemporary object reconstruction applications of TLS in ecology, and can characterize regional heterogeneity in ecosystems to improve efforts using TLS to validate airborne and satellite estimations of ecosystem properties. Equivalent metrics to the metaproperties used in this study could easily be extracted from most TLS instruments currently utilized in ecology, making the principles and methods widely applicable. The lightweight format of metaproperty data encourages large-scale and collaborative ecosystem studies. This article is protected by copyright. All rights reserved.

In enhanced oil recovery, not only the low-tension performance, but also the robustness at optimum formulation is an important issue. The fourth part of our review series is dedicated to robustness, defined as the width of the zone exhibiting three-phase behavior around the optimum formulation, whatever the scanned variable. It is first corroborated from a screening of the available data in the literature that the tension minimum is inversely proportional to the square of the three-phase range in the HLD scale. However, since there is still an inaccuracy of about a factor 10 in the tension minimum, some significant improvement can be attained in some cases by increasing the three-phase behavior width in two ways. The first approach consists of finding systems that are insensitive to some formulation variable such as temperature, surfactant mixture composition or concentration, and water-to-oil ratio. The second way is to produce an artifact through which the optimum formulation is produced twice in a scan. If the distance between the two events in the scan is reduced down to be zero, their corresponding three-phase behavior zones merge and result in a wider WIII region with a low tension. Several cases of such events are reported: alkaline scans, anionic-nonionic and anionic-cationic mixture changes, linear change in composition in three-surfactant mixture, partial precipitation from a surfactant mixture in a salinity scan, and excessive partitioning of polyethoxylated nonionics. More complex transitions with three effects in a single scan or three concomitantly scanned variables show even more possibilities in practice.

18F-labeled myocardial flow agents are becoming available for clinical application but the ∼2 hour half-life of 18F complicates their clinical application for rest-stress measurements. The goal of this work is to evaluate in a pig model a single-scan method which provides quantitative rest-stress blood flow in less than 15 minutes. Single-scan rest-stress measurements were made using 18F-Flurpiridaz. Nine scans were performed in healthy pigs and seven scans were performed in injured pigs. A two-injection, single-scan protocol was used in which an adenosine infusion was started 4 minutes after the first injection of 18F-Flurpiridaz and followed either 3 or 6 minutes later by a second radiotracer injection. In two pigs, microsphere flow measurements were made at rest and during stress. Dynamic images were reoriented into the short axis view, and regions of interest (ROIs) for the 17 myocardial segments were defined in bull’s eye fashion. PET data were fitted with MGH2, a kinetic model with time varying kinetic parameters, in which blood flow changes abruptly with the introduction of adenosine. Rest and stress myocardial blood flow (MBF) were estimated simultaneously. The first 12–14 minutes of rest-stress PET data were fitted in detail by the MGH2 model, yielding MBF measurement with a mean precision of 0.035 ml/min/cc. Mean myocardial blood flow across pigs was 0.61 ± 0.11 mL/min/cc at rest and 1.06 ± 0.19 mL/min/cc at stress in healthy pigs and 0.36 ± 0.20 mL/min/cc at rest and 0.62 ± 0.24 mL/min/cc at stress in the ischemic area. Good agreement was obtained with microsphere flow measurement (slope = 1.061 ± 0.017, intercept = 0.051 ± 0.017, mean difference 0.096 ± 0.18 ml/min/cc). Accurate rest and stress blood flow estimation can be obtained in less than 15 min of PET acquisition. The method is practical and easy to implement suggesting the possibility of clinical translation.

Time-gated Raman system has been assembled using a pulsed laser and high-resolution echelle spectrograph. Echelle spectrograph provides broad spectral band-pass of 0–8500 cm�1 in a single scan with a resolution of 1.75 cm�1 for 532 nm at an extremely small slit width of 10 μm. Advantages of gated mode detection over continuous-wave mode detection are improved signal-to-noise ratio, reduced background signal, and unwanted fluorescent emission. Feasibility of echelle spectrograph for Raman measurements has been tested for both conventional and standoff distance of 5 m with all the external illumination sources on. The echelle system provides high-quality Raman signals with an extremely low inherent bandwidth in solid and liquid samples, (~8 cm�1 ) for 478 cm�1 fundamental band of sulfur. Intensity ratio of e2 fundamental to a1 fundamental of conventional and remote Raman measurements indicates that the spectral features remain the same in both measurements. The advantages of ‘time-gated’ Raman compared with continuous-wave mode detection, like low background even under extraneous illumination and lowered fluorescence, are also illustrated with spectrum of sulfur taken in the two modes.

To overcome the effects of static field inhomogeneities, single-scan hybrid imaging techniques that use k-space encoding in one direction and spatial encoding in the other have been shown to be superior to traditional imaging techniques based on full k-space encoding. Like traditional imaging methods, hybrid methods can be implemented in different ways that favor different sources of contrast. So far, little attention appears to have been paid to these aspects. By modifying an established hybrid imaging sequence called Rapid Acquisition by Sequential Excitation and Refocusing (RASER) so as to obtain Echo-Shifted RASER sequences, we show that by shifting spin echoes one can tune the contrast due to inhomogeneous T decay.

This paper presents database security approach for complete hiding of sensitive association rules by using six novel algorithms. These algorithms utilize three new weights to reduce the needed database modifications and support complete hiding, as well as they reduce the knowledge distortion and the data distortions. Complete weighted hiding algorithms enhance the hiding failure by 100%; these algorithms have the advantage of performing only a single scan for the database to gather the required information to form the hiding process. These proposed algorithms are built within the database structure which enables the sanitized database to be generated on run time as needed.

Macrophages are excellent imaging targets for detecting atherosclerotic plaques as they are involved in all the developmental stages of atherosclerosis. However, no imaging technique is currently capable of visualizing macrophages inside blood vessel walls. The current study develops an intravascular ultrasonic-photoacoustic (IVUP) imaging system combined with indocyanine green (ICG) as a contrast agent to provide morphological and compositional information about the targeted samples. Both tissue-mimicking vessel phantoms and atherosclerotic plaque-mimicking porcine arterial tissues are used to demonstrate the feasibility of mapping macrophages labeled with ICG by endoscopically applying the proposed hybrid technique. A delay pulse triggering technique is able to sequentially acquire photoacoustic (PA) and ultrasound (US) signals from a single scan without using any external devices. The acquired PA and US signals are used to reconstruct 2D cross-sectional and 3D volumetric images of the entire tissue with the ICG-loaded macrophages injected. Due to high imaging contrast and sensitivity, the IVUP imaging vividly reveals structural information and detects the spatial distribution of the ICG-labeled macrophages inside the samples. ICG-assisted IVUP imaging can be a feasible imaging modality for the endoscopic detection of atherosclerotic plaques.

Efficient quantification of the three-dimensional forest structure is of increasing importance for our understanding of forest functions and services, but it remains challenging with conventional methods. We used a single-scan ground-based laser approach in stands with a known difference in management history and associated differences in structures. The data were used to test whether the measurement approach could distinguish various structural measures among the stands, including overall density, vertical structure, competitive conditions for regeneration, horizontal visibility, and three-dimensional structural variability. In general, our data reflected known differences in stand structure. However, in some cases the different measures showed contradicting results, highlighting the limited information represented in each measure when considered in isolation. At the same time, our results suggested that all components of stand structure do not develop in sync. The variability of horizontal and vertical structural heterogeneity appears to be a good indicator of structural elements typically found in old-growth forests, i.e., spatially homogenous (scale independent) horizontal structural variability in combination with a scale-dependent vertical structural variability. In addition, our results provided information with direct management implications. For example, gap creation, a prominent practice in restoration treatments in the region, increased spatial variability, but the hard edges and removal of all trees inside the gap, are not reflecting structural conditions found in our old-growth stand. In summary, our results suggest that this new technology can efficiently provide objective and holistic inventories of stand structures. However, more work is needed to fully understand the implications of the novel structural measures for ecosystem processes and services.

The DIERS formetric 4D provides a safe method to monitor and track the progression of postural deformities over time. However, further evaluation of reliability is necessary. Reference values are also needed to indicate postural change. The current study examined the reliability of spine shape parameters produced by the formetric 4D in adults without postural abnormalities and established reference values to determine when real change occurs. Thirty participants were scanned during 1 week. Intraclass correlation coefficients (ICCs) were calculated for 40 spine shape parameters for scans with participants stationary between scans, scans with repositioning between scans, and between days. Within-day and between-day standard error of measurement (SEM), absolute relative SEM, and smallest detectable change (SDC) were reported. ICC for stationary scans was excellent for 29 parameters, good for 10 parameters, and fair for 1 parameter. With repositioning, ICC was excellent for 27 parameters, good for 12 parameters, and fair for 1 parameter. Between days, ICC was excellent for 26 parameters, good for 10 parameters, and fair for 4 parameters. Within-day SEM% was greater than 10% for 6 parameters. Within-day SDC ranged from 1.80 to 25.03 units for a single scan and from 0.97 to 17.93 units for 6 scans. Between-day SEM% was greater than 10% for 9 parameters. Between-day SDC ranged from 1.44 to 28.24 units for a single scan and from 1.05 to 22.2 units for 6 scans. Thirty-six of the 40 spine shape parameters from the DIERS formetric 4D reliably distinguished between participants over time. Reference values were established that can be used to track patient postural change over time. Future research should investigate the clinical relevance of these 40 spine shape parameters and determine when a clinically important change in posture occurs.

Background The stem curve of standing trees is an essential parameter for accurate estimation of stem volume. This study aims to directly quantify the occlusions within the single-scan terrestrial laser scanning (TLS) data, evaluate its correlation with the accuracy of the retrieved stem curves, and subsequently, to assess the capacity of single-scan TLS to estimate stem curves. Methods We proposed an index, occlusion rate, to quantify the occlusion level in TLS data. We then analyzed three influencing factors for the occlusion rate: the percentage of basal area near the scanning center, the scanning distance and the source of occlusions. Finally, we evaluated the effects of occlusions on stem curve estimates from single-scan TLS data. Results The results showed that the correlations between the occlusion rate and the stem curve estimation accuracies were strong (r = 0.60–0.83), so was the correlations between the occlusion rate and its influencing factors (r = 0.84–0.99). It also showed that the occlusions from tree stems were the main factor of the low detection rate of stems, while the non-stem components mainly influenced the completeness of the retrieved stem curves. Conclusions Our study demonstrates that the occlusions significantly affect the accuracy of stem curve retrieval from the single-scan TLS data in a typical-size (32 m × 32 m) forest plot. However, the single-scan mode has the capacity to accurately estimate the stem curve in a small forest plot (

Tissue biopsy evaluation in the clinic is in need of quantitative disease markers for diagnosis and, most importantly, prognosis. Among the new technologies, quantitative phase imaging (QPI) has demonstrated promise for histopathology because it reveals intrinsic tissue nanoarchitecture through the refractive index. However, a vast majority of past QPI investigations have relied on imaging unstained tissues, which disrupts the established specimen processing. Here we present color spatial light interference microscopy (cSLIM) as a new whole-slide imaging modality that performs interferometric imaging on stained tissue, with a color detector array. As a result, cSLIM yields in a single scan both the intrinsic tissue phase map and the standard color bright-field image, familiar to the pathologist. Our results on 196 breast cancer patients indicate that cSLIM can provide stain-independent prognostic information from the alignment of collagen fibers in the tumor microenvironment. The effects of staining on the tissue phase maps were corrected by a mathematical normalization. These characteristics are likely to reduce barriers to clinical translation for the new cSLIM technology.

The inspection of particles plays an important role in quality control of smooth surfaces, such as optics and silicon wafers. The difficulty of inspection lies not only in the high-resolution detectivity for small-size particles, but also in the need to distinguish among different types of particles due to their different damages and re-work processes. This paper proposes a detection and discrimination method of the particles on (surface particles) and below smooth surfaces (subsurface particles) by laser scattering with polarization measurement. The incident laser beam passes through a polarization state generator (PSG) to illuminate the smooth surface. A large proportion of the particle-induced scattered light is detected after collected by an ellipsoidal mirror. Meanwhile, in the blind area of the ellipsoidal mirror, a small amount of scattered light enters the polarization measurement channel, where a polarization state analyzer (PSA) is used to finally obtain a two-dimensional polarization signal for discriminating the two types of particles. Then, by a nonlinear global search combined with the theoretical models for polarized light scattering from particles, the optimal polarization measurement state of the PSG and the PSA is obtained to maximize the separability between the surface particles and subsurface particles on the acquired polarization signals. This method takes full advantage of the polarization of scattered light, and with one single scan the inspection for the whole surface can be accomplished. Finally, experimental results demonstrate the effectiveness and accuracy of the method.

Purpose of Review Magnetic resonance imaging (MRI) has enabled non-invasive myocardial tissue characterization in a wide range of cardiovascular diseases by quantifying several tissue specific parameters such as T1, T2, and T2* relaxation times. Simultaneous assessment of these parameters has recently gained interest to potentially improve diagnostic accuracy and enable further understanding of the underlying disease. However, these quantitative maps are usually acquired sequentially and are not necessarily co-registered, making multi-parametric analysis challenging. Magnetic resonance fingerprinting (MRF) has been recently introduced to unify and streamline parametric mapping into a single simultaneous, multi-parametric, fully co-registered, and efficient scan. Feasibility of cardiac MRF has been demonstrated and initial clinical validation studies are ongoing. Provide an overview of the cardiac MRF framework, recent technical developments and initial undergoing clinical validation. Recent Findings Cardiac MRF has enabled the acquisition of co-registered T1 and T2 maps in a single, efficient scan. Initial results demonstrate feasibility of cardiac MRF in healthy subjects and small patient cohorts. Current in vivo results show a small bias and comparable precision in T1 and T2 with respect to conventional clinical parametric mapping approaches. This bias may be explained by several confounding factors such as magnetization transfer and field inhomogeneities, which are currently not included in the cardiac MRF model. Initial clinical validation for cardiac MRF has demonstrated good reproducibility in healthy subjects and heart transplant patients, reduced artifacts in inflammatory cardiomyopathy patients and good differentiation between hypertrophic cardiomyopathy and healthy controls. Summary Cardiac MRF has emerged as a novel technique for simultaneous, multi-parametric, and co-registered mapping of different tissue parameters. Initial efforts have focused on enabling T1, T2, and fat quantification; however this approach has the potential of enabling quantification of several other parameters (such as T2*, diffusion, perfusion, and flow) from a single scan. Initial results in healthy subjects and patients are promising, thus further clinical validation is now warranted.

In real-world databases, high utility itemset (HUI) is an important class of regularities. Most previous studies have focused on mining HUIs in transactional databases and did not consider the spatiotemporal characteristics of items. In this study, a more flexible model of spatial HUIs (SHUIs) that exist in spatiotemporal databases is proposed. In a spatiotemporal database (STD), an itemset is said to be an SHUI if its utility is not less than a user-specified minimum utility and the distance between any two of its items is not more than a user-specified maximum distance. Identifying SHUIs is very challenging because the generated itemsets do not satisfy the anti-monotonic property. In this study, we present two novel pruning techniques for reducing computational costs. Moreover, a fast single scan algorithm is presented for effectively evaluating all SHUIs in a STD. Furthermore, two case studies are presented, in which the proposed model is used to identify useful information in traffic congestion data and air pollution data.

Polarization sensitive second harmonic generation (pSHG) microscopy is an imaging technique able to provide, in a non-invasive manner, information related to the molecular structure of second harmonic generation (SHG) active structures, many of which are commonly found in biological tissue. The process of acquiring this information by means of pSHG microscopy requires a scan of the sample using different polarizations of the excitation beam. This process can take considerable time in comparison with the dynamics of in vivo processes. Fortunately, single scan polarization sensitive second harmonic generation (SS-pSHG) microscopy has also been reported, and is able to generate the same information at a faster speed compared to pSHG. In this paper, the orientation of second harmonic active supramolecular assemblies in starch granules is obtained on by means of pSHG and SS-pSHG. These results are compared in the forward and backward directions, showing a good agreement in both techniques. This paper shows for the first time, to the best of the authors’ knowledge, data acquired using both techniques over the exact same sample and image plane, so that they can be compared pixel-to-pixel.

This paper considers frequent itemset mining in big transactional databases. It first introduces a novel approach (Bio-SS) that combines the bio-inspired algorithms with the single scan algorithm (SSFIM). The proposed approach addresses the limitations of SSFIM by utilizing the bio-inspired operators in the generation process. This reduces the time complexity of SSFIM from exponential to polynomial, while taking advantage of the capacity to derive the frequent itemsets by performing a single database scan, independently from the minimum support value. This allows to considerably accelerate the scan procedure compared to existing approaches, especially when dealing with large scale databases. The numerical results show that the designed Bio-SS outperforms both accurate and metaheuristics baseline FIM approaches when dealing with big databases.

Ice caves can be considered as an indicator of the long-term changes in the landscape. Dynamics in ice volume in the caves are common throughout the year, but the inter-seasonal comparison of ice dynamics indicates a change in the hydrological-climatic regime of the landscape. However, evaluating cave ice volume changes is a challenging task that requires continuous monitoring based on detailed mapping. Nowadays, laser scanning technology is used for cryomorphology mapping to record a status of the ice at an ultra-high resolution. In order to evaluate the dynamics of cave ice, it is necessary to place individual measurements in an unified coordinate system. In the presented paper, we propose a selective cloud-to-cloud approach that addresses the issue of registration of single scan missions into unified coordinate system. We present the results of the ice dynamics monitoring in the Silická ľadnica cave situated in the Slovak Karst, which started in summer of 2016. Based on the results we can conclude that the change in ice volume during the year is continuous and we can observe repeated processes of degradation and ice formation in the cave. Presented analysis of the inter-seasonal dynamics of the ice volume demonstrates that there has been a significant decrement of ice in the monitored period.

Semiconductor yield improvement and stability is becoming increasingly more difficult to achieve with decreasing technology nodes. There are many new sources, types, and mechanisms of process induced systematic defects, with a growing demand to identify and control those sources of hotspots that impact yield with the most comprehensive results, fastest time, and lowest cost. Previously there has been extensive characterization and publications on the techniques used for hotspot discovery, with little overall improvement to the flow and time to results needed to keep up with today’s fast paced development process which requires rapid results. We propose implementing new inspection and binning algorithms to the process window discovery methodology, to achieve improvements in time to results, process window qualification, and hotspot identification. These systematic defect discovery improvements enable lithography processes to be controlled and monitored more accurately and more precisely than ever before.

The paper deals with the multi-frequency characterization of antennas by using Near-Field measurements collected over one optimized grid common to all the frequencies. In this way the frequency measurements are carried out with a single scan. The approach provides a drastic reduction of the number of measurement points and uses a raster scan grid to take advantage of the classical continuous scan or of the new scanning capabilities shown in [6].

It is vital to assess the performance of emission computed tomography (ECT) systems prior to their use for clinical examinations. Generally, performance tests of ECT systems are time-consuming, expensive and require more than one phantom to scan and then analyse the data. There is nonavailability of such type of phantoms that can provide all necessary data for performance of some quality control (QC) tests from a single scan data. In this paper, commercially available emission computed tomography (ECT) phantoms are thoroughly reviewed. It is concluded that, there is a need of designing and construction of a time-saving and cost-effective new compact ECT phantom.

The development of precise and reliable near infrared spectroscopy (NIRS)-based non-destructive tools to assess physicochemical properties of fleshy fruit has been challenging. A novel crop load × fruit developmental stage protocol for multivariate NIRS-based prediction models calibration to non-destructively assess peach internal quality and maturity was followed. Regression statistics of the prediction models highlighted that dry matter content (DMC, R2 = 0.98, RMSEP = 0.41%), soluble solids concentration (SSC, R2 = 0.96, RMSEP = 0.58%) and index of absorbance difference (IAD, R2 = 0.96, RMSEP = 0.08) could be estimated accurately with a single scan during fruit growth and development. Thus, the impact of preharvest factors such as crop load and canopy position on peach quality and maturity was evaluated. Large-scale field validation showed that heavier crop loads reduced peach quality (DMC, SSC) and delayed maturity (IAD) and upper canopy position advanced both mainly in the moderate crop loads. This calibration protocol can enhance NIRS adaptation across tree fruit supply chain.

Protein−ligand interactions are frequently screened using nuclear magnetic resonance (NMR) spectroscopy. The dissociation constant (KD) of a ligand of interest can be determined via a spin-spin relaxation measurement of a reporter ligand, in a single scan when using hyperpolarization by means of dissolution dynamic nuclear polarization (D-DNP). Despite nearly instantaneous signal acquisition, a limitation of D-DNP for the screening of protein−ligand interactions is the required polarization time on the order of tens of minutes. Here, we introduce a multiplexed NMR experiment, where a single hyperpolarized ligand sample is rapidly mixed with protein injected into two flow cells. NMR detection is achieved simultaneously on both channels, resulting in a chemical shift resolved spin relaxation measurement. Spectral resolution allows the use of reference compounds for accurate quantification of concentrations. Simultaneous use of two concentration ratios between protein and ligand broadens the range of KD that is accurately measurable in a single experiment to at least an order of magnitude. In a comparison of inhibitors for the protein trypsin, the average KD values of benzamidine and benzylamine were found to be 12.6±1.4 μM and 207±22.3 μM from three measurements, based on KD = 142 μM assumed known for the reporter ligand 4-(trifluoromethyl)benzene-1-carboximidamide. Typical confidence ranges at 95% evaluated for single experiments were (8.3 μM, 20 μM) and (151 μM, 328 μM). The multiplexed detection of two or more hyperpolarized samples increases throughput of D-DNP by the same factor, improving the applicability to most multi-point measurements that would traditionally be achieved using titrations.

We analyzed quantitative maps of T 1 and T 2 relaxation times and muscle fat fraction measurements in magnetic resonance imaging of the upper arm skeletal muscles and heart in ambulatory boys with Duchenne muscular dystrophy and age‐range‐matched healthy volunteer boys. The cardiac‐optimized sequences detected fatty infiltration and edema in the upper arm skeletal muscles but not the myocardium in these Duchenne muscular dystrophy boys who had normal ejection fraction. Imaging the heart and skeletal muscle using the same magnetic resonance imaging methods during a single scan may be useful in assessing relative disease status and therapeutic response in clinical trials of Duchenne muscular dystrophy.

Purpose To develop an individually optimized contrast-enhanced (CE) 4D-computed tomography (CT) for radiotherapy simulation in pancreatic ductal adenocarcinomas (PDA). Methods Ten PDA patients were enrolled. Each underwent three CT scans: a 4D-CT immediately following a CE 3D-CT and an individually optimized CE 4D-CT using test injection. Three physicians contoured the tumor and pancreatic tissues. Image quality scores, tumor volume, motion, tumor-to-pancreas contrast, and contrast-to-noise ratio (CNR) were compared in the three CTs. Interobserver variations were also evaluated in contouring the tumor using simultaneous truth and performance level estimation. Results Average image quality scores for CE 3D-CT and CE 4D-CT were comparable (4.0 and 3.8, respectively; P = 0.082), and both were significantly better than that for 4D-CT (2.6, P < 0.001). Tumor-to-pancreas contrast results were comparable in CE 3D-CT and CE 4D-CT (15.5 and 16.7 Hounsfield units (HU), respectively; P = 0.21), and the latter was significantly higher than in 4D-CT (9.2 HU, P = 0.001). Image noise in CE 3D-CT (12.5 HU) was significantly lower than in CE 4D-CT (22.1 HU, P = 0.013) and 4D-CT (19.4 HU, P = 0.009). CNRs were comparable in CE 3D-CT and CE 4D-CT (1.4 and 0.8, respectively; P = 0.42), and both were significantly better in 4D-CT (0.6, P = 0.008 and 0.014). Mean tumor volumes were significantly smaller in CE 3D-CT (29.8 cm3, P = 0.03) and CE 4D-CT (22.8 cm3, P = 0.01) than in 4D-CT (42.0 cm3). Mean tumor motion was comparable in 4D-CT and CE 4D-CT (7.2 and 6.2 mm, P = 0.17). Interobserver variations were comparable in CE 3D-CT and CE 4D-CT (Jaccard index 66.0% and 61.9%, respectively) and were worse for 4D-CT (55.6%) than CE 3D-CT. Conclusions CE 4D-CT demonstrated characteristics comparable to CE 3D-CT, with high potential for simultaneously delineating the tumor and quantifying tumor motion with a single scan.

The ultrasonographic surface rendered oro-palatal (SROP) view is a 3D reconstructed view of the fetal perioral region, which combines ultrasound insonation in a trans oral, upward directed axial direction and the surface rendered mode. It allows the simultaneous visualization on a single scan of the superior lip, alveolar ridge and secondary palate. It corresponds prenatally to the submental intra oral photography of the palate of neonates. The aim of the study was to demonstrate the benefice of using the SROP view in the management of cleft lip with or without cleft palate, uni- or bi-lateral, diagnosed prenatally (22-28 gestational weeks). The SROP view allowed the representation on a single view of the characteristics of the defect useful to the different members of the orofacial team to exactly evaluate the difformity and to plan the ulterior therapeutic steps (e.g. side, extension of the cleft to the secondary palate, tooth organization). Also, being easier to read by lay people thanks to the use of a surface rendered representation rather than the usual multiplanar reconstructions in the three traditional orthogonal planes, the SROP view makes it easier to bring exact information to the parents about the malformation and its consequences.

Signature-based authentication is used often to authenticate hardware intellectual property (IP) when it is reused on a plug-and-play system-on-chip. A signature embedded in the functional/test component of a hardware IP can easily be verified as it can be generated and observed as functional/scan output of the hardware IP for a certain input key vector. An existing scan-based approach for embedding signature inserts signature through reordering of scan cells in a single scan (SS) chain. However, it is not applicable to the recent reconfigurable scan architectures having reduced test application time. We propose a scheme for embedding two distinct signatures separately in a reconfigurable scan architecture and verifying those without conflict from the packaged chip by using two distinct test modes of the reconfigurable architecture: namely, scan tree mode and SS mode. The two signatures may include one from logic IP source and the other from physical IP source. The overhead in both routing and power has been minimised in our scheme. Experimental results on design overhead and robustness for ISCAS89 benchmarks are very encouraging.

For many non-destructive evaluation (NDE) applications, more information can be obtained by using different techniques, especially when the techniques are sensitive to different types of defects. However separate inspections are not always practical due to time and cost constraints. Therefore, an inspection system combing more than one modalities would have many advantages. A dual modality imaging system is thus proposed which can automatically switch between capacitive imaging and inductive imaging modes. Instead of using a physical combination of two sensors, the proposed system employs a coplanar coil pair as a sensor, and the modality switching is done by changing the wiring schemes through program-controlled switch box. After a single scan over the specimen under test, two types of images, namely capacitive and inductive, can be obtained by the proposed system. For an insulated metallic structure, the capacitive image contains the defect information in the insulation layer and on the top surface of the conducting layer, while the inductive image contains the defect information within the conducting region. The proposed integration of the two imaging modalities in a single system does not introduce any interference between the modes and provides more information on the defects with a reduced testing time and production cost on hardware and software compared to using two NDE techniques separately. A theoretical explanation of the imaging mechanisms for the capacitive and inductive modes are provided. The results of finite element modelling show perturbation of the probing fields due to defects in the two imaging modes. Experimental results from a dual modality imaging system are also presented, demonstrating detection of defects in insulator-metal hybrid structures to verify the effectiveness of this approach.

Part 1: MAKE-Main Track; International audience; Mining association rules is an significant research area in Knowledge Extraction. Although the negative association rules have notable advantages, but they are less explored in comparaison with the positive association rules. In this paper, we propose a new approach allowing the mining of positive and negative rules. We define an efficient method of support counting, called reduction-access-database. Moreover, all the frequent itemsets can be obtained in a single scan over the whole database. As for the generating of interesting association rules, we introduce a new efficient technique, called reduction-rules-space. Therefore, only half of the candidate rules have to be studied. Some experiments will be conducted into such reference databases to complete our study.

This talk goes through the components in generic single-scan target tracking algorithms from filtering to data association, track initiation, and termination. In many areas, reference is made to functions in the open-source copyleft-free Tracker Component Library (available online) so that attendees can rapidly apply the algorithms that are discussed.

International audience; Multidimensional NMR (nD NMR) has become one of the most powerful spectroscopic tools to deliver diverse structural and functional insights into organic and biomolecules as well as on raw materials. A long-standing concern of nD NMR is related to its long experiment duration, arising from the need to sample the indirect dimension(s) in a multistep fashion. For decades, the NMR community has been developing numerous strategies to speed up nD NMR experiments and therefore extend their scope of applications. Among them is the ultrafast (UF) NMR methodology, capable of delivering arbitrary homo-or heteronuclear multidimensional spectra in a single scan. Since the initial concept was published in 2002, the performance of this subsecond 2D NMR approach has been greatly improved so that UF NMR is nowadays a relevant analytical tool used in broad variety of situations whereby the experiment duration is crucial. Following a description of the principles of UF NMR, the present review aims at emphasizing the numerous methodological developments that this approach has undergone so far in 2017. Thereafter, the high versatility of UF NMR is highlighted through the review of the applications that have been reported in a variety of settings and disciplines, in isotropic as well as anisotropic media.

Powder bed additive manufacturing technologies gained much attention in past years not only thanks to design freedom but also because of the peculiar microstructures and mechanical properties that can be obtained thanks to the extremely high cooling rate. However the phenomena that arise during the laser scanning are not yet deeply understood. In this work the effect of the main building parameters and of powder properties on the shape, the microstructure and the properties of Al-based LPBF single scan tracks was evaluated. The experiments were carried out with three different powders in order to understand of the effect of the material thermo-physical properties on the consolidation phenomena.

This paper considers frequent itemsets mining in transactional databases. It introduces a new accurate single scan approach for frequent itemset mining (SSFIM), a heuristic as an alternative approach (EA-SSFIM), as well as a parallel implementation on Hadoop clusters (MR-SSFIM). EA-SSFIM and MR-SSFIM target sparse and big databases, respectively. The proposed approach (in all its variants) requires only one scan to extract the candidate itemsets, and it has the advantage to generate a fixed number of candidate itemsets independently from the value of the minimum support. This accelerates the scan process compared with existing approaches while dealing with sparse and big databases. Numerical results show that SSFIM outperforms the state-of-the-art FIM approaches while dealing with medium and large databases. Moreover, EA-SSFIM provides similar performance as SSFIM while considerably reducing the runtime for large databases. The results also reveal the superiority of MR-SSFIM compared with the existing HPC-based solutions for FIM using sparse and big databases.

Magnetic resonance fingerprinting (MRF) has recently been introduced as a new approach to quantify multiple tissue properties within a single scan [(1,2)][1]. This technique uses a pulse sequence with varying magnetic resonance imaging parameters, which causes tissues with different magnetic

Stem characteristics of plants are of great importance to both ecology study and forest management. Terrestrial laser scanning (TLS) may provide an effective way to characterize the fine-scale structures of vegetation. However, clumping plants, dense foliage and thin structure could intensify the shadowing effect and pose a series of problems in identifying stems, distinguishing neighboring stems, and merging disconnected stem parts in point clouds. This paper presents a new method to automatically detect stems in dense and homogeneous forest using single-scan TLS data. Stem points are first identified with a two-scale classification method. Then a clustering approach is used to group the candidate stem points. Finally, a direction-growing algorithm based on a simple stem curve model is applied to merge stem points. Field experiments were carried out in two different bamboo plots with a stem density of about 7500 stems/ha. Overall accuracy of the stem detection is 88% and the quality of detected stems is mainly affected by the shadowing effect. Results indicate that the proposed method is feasible and effective in detection of bamboo stems using TLS data, and can be applied to other species of single-stem plants in dense forests.

Multidimensional NMR has become one of the most widespread spectroscopic tools available to study diverse structural and functional aspects of organic and biomolecules. A main feature of multidimensional NMR is the relatively long acquisition times that these experiments demand. For decades, scientists have been working on a variety of alternatives that would enable NMR to overcome this limitation, and deliver its data in shorter acquisition times. Counting among these methodologies is the so-called ultrafast (UF) NMR approach, which in principle allows one to collect arbitrary multidimensional correlations in a single sub-second transient. By contrast to conventional acquisitions, a main feature of UF NMR is a spatiotemporal manipulation of the spins that imprints the chemical shift and/or J-coupling evolutions being sought, into a spatial pattern. Subsequent gradient-based manipulations enable the reading out of this information and its multidimensional correlation into patterns that are identical to those afforded by conventional techniques. The current review focuses on the fundamental principles of this spatiotemporal UF NMR manipulation, and on a few of the methodological extensions that this form of spectroscopy has undergone during the years.

Evaluate the usefulness of diffusion-weighted spatiotemporally encoded (SPEN) methods to obtain apparent diffusion coefficient (ADC) maps of fibroglandular human breast tissue, in the presence of silicone implants.Seven healthy volunteers with breast augmentation were scanned at 3 Tesla (T) using customized SPEN sequences yielding separate silicone and water (1) H images in one scan, together with their corresponding diffusion-weightings.SPEN's ability to deliver multiple spectrally resolved images in a single scan, coupled to the method's substantial robustness to magnetic field heterogeneities, served to acquire ADC maps that could be freed from contributions that did not belong to fibroglandular tissue.SPEN-based sequences incorporating spectral discrimination and diffusion-weighting enable the acquisition of reliable ADC maps despite the presence of dominant signals from silicone implants, thereby opening new screening possibilities for the identification of malignancies in breast augmented patients.