Typical Acquisition Research Articles

Phase unwrapping with a rapid opensource minimum spanning tree algorithm (ROMEO).

PurposeTo develop a rapid and accurate MRI phase‐unwrapping technique for challenging phase topographies encountered at high magnetic fields, around metal implants, or postoperative cavities, which is sufficiently fast to be applied to large‐group studies including Quantitative Susceptibility Mapping and functional MRI (with phase‐based distortion correction).MethodsThe proposed path‐following phase‐unwrapping algorithm, ROMEO, estimates the coherence of the signal both in space—using MRI magnitude and phase information—and over time, assuming approximately linear temporal phase evolution. This information is combined to form a quality map that guides the unwrapping along a 3D path through the object using a computationally efficient minimum spanning tree algorithm. ROMEO was tested against the two most commonly used exact phase‐unwrapping methods, PRELUDE and BEST PATH, in simulated topographies and at several field strengths: in 3T and 7T in vivo human head images and 9.4T ex vivo rat head images.ResultsROMEO was more reliable than PRELUDE and BEST PATH, yielding unwrapping results with excellent temporal stability for multi‐echo or multi‐time‐point data. It does not require image masking and delivers results within seconds, even in large, highly wrapped multi‐echo data sets (eg, 9 seconds for a 7T head data set with 31 echoes and a 208 × 208 × 96 matrix size).ConclusionOverall, ROMEO was both faster and more accurate than PRELUDE and BEST PATH, delivering exact results within seconds, which is well below typical image acquisition times, enabling potential on‐console application.

Accelerating Fourier Transform-Ion Cyclotron Resonance Mass Spectrometry Imaging Using a Subspace Approach

We present a subspace method that accelerates data acquisition using Fourier transform-ion cyclotron resonance (FT-ICR) mass spectrometry imaging (MSI). For MSI of biological tissue samples, there is a finite number of heterogeneous tissue types with distinct chemical profiles that introduce redundancy in the high-dimensional measurements. Our subspace model exploits the redundancy in data measured from whole-slice tissue samples by decomposing the transient signals into linear combinations of a set of basis transients with the desired spectral resolution. This decomposition allowed us to design a strategy that acquires a subset of long transients for basis determination and short transients for the remaining pixels, drastically reducing the acquisition time. The computational reconstruction strategy can maintain high-mass-resolution and spatial-resolution MSI while providing a 10-fold improvement in throughput. We validated the capability of the subspace model using a rat sagittal brain slice imaging data set. Comprehensive evaluation of the quality of the mass spectral and ion images demonstrated that the reconstructed data produced by the reported method required only 15% of the typical acquisition time and exhibited both qualitative and quantitative consistency when compared to the original data. Our method enables either higher sample throughput or higher-resolution images at similar acquisition lengths, providing greater flexibility in obtaining FT-ICR MSI measurements.

Advances in Specific Language Impairment Research and Intervention: An Overview of Five Research Symposium Papers.

PurposeThis article provides an overview of five papers appearing together on the topic of “Advances in Specific Language Impairment Research and Intervention,” which was the 2019 program in an ongoing series of research symposia presented at the Annual Convention of the American Speech-Language-Hearing Association.MethodThe article provides a historical context for the set of papers, then a short summation of each paper's content, followed by the identification of overarching themes and working conclusions.ResultsEach paper provides summations of empirical results, and some papers provide new empirical evidence.ConclusionThe papers collectively highlight six points: (a) Children with specific language impairment (SLI) are likely to be unidentified among their age peers. (b) There is great need for better identification of children with SLI across developmental levels. (c) Progress is evident toward a better understanding of causal pathways, as examined across different research designs involving comparison of children with typical language acquisition to children with SLI and other possibly co-occurring atypical conditions. (d) Measuring multiple dimensions of language brings enhanced informativeness, with differing outcomes for differing dimensions. (e) Replicated research findings require precision of methods in order to reduce unexplained error variance especially when defining groups. (f) Accurate identification of children with SLI is the first step toward a sound treatment plan for SLI and reading disorders as well.Presentation Video https://doi.org/10.23641/asha.13063721

Recording and analyzing kinematic data in children and adults with SOLLAR: Sonographic & Optical Linguo-Labial Articulation Recording system

Understanding the development of spoken language in young children has become increasingly important for advancing basic theories of language acquisition and for clinical practice. However, such a goal requires refined measurements of speech articulation (e.g., from the tongue), which are difficult to obtain from young children. In recent years though, technological advances have allowed developmental researchers to make significant steps in that direction. For instance, movements of the tongue, an articulator that is essential for spoken language, can now be tracked and recorded in children with ultrasound imaging. This technique has opened novel research avenues in (a)typical language acquisition, enabling researchers to reliably capture what has long remained invisible in the speech of young children. Within this context, we have designed an experimental platform for the recording and the processing of kinematic data: SOLLAR (Sonographic and Optical Linguo-Labial Articulatory Recording system). The method has been tailored for children, but it is suitable for adults. In the present article, we introduce the recording environment developed to record over 100 children and 30 adults within SOLLAR. We then describe SOLLAR’s data processing framework, providing examples of data visualization and a summary of strengths and limitations.

Efficient multiple constraint acquisition

Constraint acquisition systems such as QuAcq and MultiAcq can assist non-expert users to model their problems as constraint networks by classifying (partial) examples as positive or negative. For each negative example, the former focuses on one constraint of the target network, while the latter can learn a maximum number of constraints. Two bottlenecks of the acquisition process where both these algorithms encounter problems are the large number of queries required to reach convergence, and the high cpu times needed to generate queries, especially near convergence. In this paper we propose algorithmic and heuristic methods to deal with both these issues. We first describe an algorithm, called MQuAcq, that blends the main idea of MultiAcq into QuAcq resulting in a method that learns as many constraints as MultiAcq does after a negative example, but with a lower complexity. A detailed theoretical analysis of the proposed algorithm is also presented. %We also present a technique that boosts the performance of constraint acquisition by reducing the number of queries significantly. Then we turn our attention to query generation which is a significant but rather overlooked part of the acquisition process. We describe %in detail how query generation in a typical constraint acquisition system operates, and we propose heuristics for improving its efficiency. Experiments from various domains demonstrate that our resulting algorithm that integrates all the new techniques does not only generate considerably fewer queries than QuAcq and MultiAcq, but it is also by far faster than both of them, in average query generation time as well as in total run time, and also largely alleviates the premature convergence problem.

Numerical Model of SPAD-Based Direct Time-of-Flight Flash LIDAR CMOS Image Sensors.

We present a Montecarlo simulator developed in Matlab® for the analysis of a Single Photon Avalanche Diode (SPAD)-based Complementary Metal-Oxide Semiconductor (CMOS) flash Light Detection and Ranging (LIDAR) system. The simulation environment has been developed to accurately model the components of a flash LIDAR system, such as illumination source, optics, and the architecture of the designated SPAD-based CMOS image sensor. Together with the modeling of the background noise and target topology, all of the fundamental factors that are involved in a typical LIDAR acquisition system have been included in order to predict the achievable system performance and verified with an existing sensor.

Relationship between the visuo-spatial cognition and the linguistic domain in Williams syndrome

O estudo piloto descrito investiga o domínio de verbos de movimento na aquisição típica e atípica, com indivíduos com Síndrome de Williams. Consideram-se diferentes tipos de verbos de movimento em relação aos primitivos semânticos movimento, modo e trajetória e sua lexicalização na raiz verbal (SILVA JÚNIOR, 2015). Avalia-se a compreensão a partir de uma tarefa de julgamento de verificação de compatibilidade entre codificação linguística e eventos ocorridos. Os participantes foram apresentados a sentenças, seguidas de pequenos vídeos e deveriam responder se as frases eram ou não compatíveis com o evento exibido no vídeo. Testaram-se (i) verbos de movimento e modo, (ii) verbos de movimento e trajetória, (iii) verbos de movimento, modo e trajetória com foco na meta e (iv) verbos de movimento, modo e trajetória com trajetória delimitada. Reportam-se os dados de quinze crianças com desenvolvimento típico, quinze adultos, como grupo controle, além de um estudo de caso com um indivíduo com SW, com 10 anos de idade. Os resultados indicam efeitos de grupo e tipo de verbo. As crianças apresentam maior dificuldade nos verbos do tipo (iv). Já o indivíduo com SW, apesar de mais velho, evidencia dificuldade ainda maior nessa condição, indicando uma dificuldade não-linguística stricto sensu.

Comparison of parameter optimization methods for quantitative susceptibility mapping.

Quantitative Susceptibility Mapping (QSM) is usually performed by minimizing a functional with data fidelity and regularization terms. A weighting parameter controls the balance between these terms. There is a need for techniques to find the proper balance that avoids artifact propagation and loss of details. Finding the point of maximum curvature in the L-curve is a popular choice, although it is slow, often unreliable when using variational penalties, and has a tendency to yield overregularized results. We propose 2 alternative approaches to control the balance between the data fidelity and regularization terms: 1) searching for an inflection point in the log-log domain of the L-curve, and 2) comparing frequency components of QSM reconstructions. We compare these methods against the conventional L-curve and U-curve approaches. Our methods achieve predicted parameters that are better correlated with RMS error, high-frequency error norm, and structural similarity metric-based parameter optimizations than those obtained with traditional methods. The inflection point yields less overregularization and lower errors than traditional alternatives. The frequency analysis yields more visually appealing results, although with larger RMS error. Our methods provide a robust parameter optimization framework for variational penalties in QSM reconstruction. The L-curve-based zero-curvature search produced almost optimal results for typical QSM acquisition settings. The frequency analysis method may use a 1.5 to 2.0 correction factor to apply it as a stand-alone method for a wider range of signal-to-noise-ratio settings. This approach may also benefit from fast search algorithms such as the binary search to speed up the process.

Follow the Money: The Funding Acquisition Process of Nascent Ventures

This paper integrates the largely separate literatures of financial bootstrapping and pecking-order theory (POT) in order to explore how funding acquisition processes evolve at the firm level. Based on novel optimal matching techniques combined with binary logistic regressions, we identify how the most typical funding acquisition processes of nascent ventures evolve in specific circumstances. In accordance with financial bootstrapping theory, the majority of nascent ventures rely on bootstrapped finance. Importantly, we are additionally able to theorize – in line with pecking order theory – under which circumstances the minority of nascent ventures transition from founder and insider equity towards market-based (debt and equity) finance. As a result we offer a novel theoretical approach to understand how funding acquisition processes evolve in nascent venture.

Point ahead angle prediction based on Kalman filtering of optical axis pointing angle in satellite laser communication

Point ahead angle (PAA) prediction is important in space laser communication, but the existing methods have low accuracy and complicated calculation processes. In this paper, a new PAA prediction method is proposed based on Kalman filtering of the optical axis pointing trajectory. The proposed method uses the high precision of fine tracking to improve the accuracy of predictive filtering. Taking ground-satellite laser communication as the research background, the beam transmission process in a typical acquisition, pointing, and tracking (APT) system is derived, then the Kalman filter model is established, and a simulation of the model is performed. The results show that the PAA can be predicted accurately and the error of the PAA can be reduced effectively the maximum prediction error is 3.8 μrad only, and the method does not need to take the complex satellite perturbations into consideration. The proposed approach improves the accuracy of PAA prediction and contributes to the design of space laser communication systems.

Studying Acquisition Strategy Formulation of Incremental Development Approaches

This is a study of the challenges that acquisition professionals confront in formulating the Department of Defense’s preferred acquisition–incremental development. The research surveys acquisition professionals to recommend the components of an acquisition strategy associated with a typical acquisition program undergoing program/project milestone review and approval. This work provides insights into how program managers use typical programmatic decision inputs (requirements, technology maturity, risk, urgency, and funding) to formulate the components of an acquisition strategy. The results suggest that acquisition policy should perhaps require a justification for most programs of record if an incremental development approach is not planned. Adoption of the recommended acquisition policy changes would make the defense acquisition system more responsive to the warfighter by fielding improved capability as quickly as possible and reducing risk of the eventual delivery of the full required capability.

M&A Activity and the Capital Structure of Target Firms

Using a large sample of European acquisitions, we find that acquired firms substantially close the gap between their actual and optimal leverage ratios. The bulk of this adjustment occurs quite rapidly â?? within a year of the acquisition. The typical over-levered firm adjusts its debt-to-assets ratio from 34.4% in the year before acquisition to 20% in the year after. (The adjustment is smaller, but still quite rapid, for targets that had been under-leveraged.) These adjustments occur primarily through debt issuances or retirements. We also investigate whether target firms' pre-merger leverage contributes to the probability of them being acquired. We find that firms further away from their optimal leverage are more likely to be acquired: for an average firm, an increase in the absolute leverage deviation from 1% to 10% of total assets increases the probability of being acquired by 4.1% to 5.6% (The larger effect applies to over-leveraged firms.) Overall, our results provide support for the trade-off theory of capital structure and suggest that financial synergies have a significant role in the typical European acquisition decision.

Automatic labeling of respiratory phases and detection of abnormal respiratory signals in free-breathing thoracic dynamic MR image acquisitions based on deep learning.

4D thoracic images constructed from free-breathing 2D slice acquisitions based on dynamic magnetic resonance imaging (dMRI) provide clinicians the capability of examining the dynamic function of the left and right lungs, left and right hemi-diaphragms, and left and right chest wall separately for thoracic insufficiency syndrome (TIS) treatment [1]. There are two shortcomings of the existing 4D construction methods [2]: a) the respiratory phase corresponding to end expiration (EE) and end inspiration (EI) need to be manually identified in the dMRI sequence; b) abnormal breathing signals due to non-tidal breathing cannot be detected automatically which affects the construction process. Since the typical 2D dynamic MRI acquisition contains ~3000 slices per patient, handling these tasks manually is very labor intensive. In this study, we propose a deep-learning-based framework for addressing both problems via convolutional neural networks (CNNs) [3] and Long Short-Term Memory (LSTM) [4] models. A CNN is used to extract the motion characteristics from the respiratory dMRI sequences to automatically identify contiguous sequences of slices representing exhalation and inhalation processes. EE and EI annotations are subsequently completed by comparing the changes in the direction of motion of the diaphragm. A LSTM network is used for detecting abnormal respiratory signals by exploiting the non-uniform motion feature sequence of abnormal breathing motions. Experimental results show the mean error of labeling EE and EI is ~0.3 dMRI time point unit (much less than one time point). The accuracy of abnormal cycle detection reaches 80.0%. The proposed approach achieves results highly comparable to manual labeling in accuracy but with close to full automation of the whole process. The framework proposed here can be readily adapted to other modalities and dynamic imaging applications.

On bells, saliva, and abdominal pain or discomfort: Early aversive visceral conditioning and vulnerability for anorexia nervosa.

Gastrointestinal (GI) symptoms are common in anorexia nervosa (AN), can predate illness onset, complicate renourishment, and persist after recovery. We explore how, through processes of aversive visceral conditioning, early GI pain and discomfort may increase vulnerability to AN in some individuals. Processes include enhanced preoccupation with the gut resulting from aversive visceral memories and disruptions in the typical acquisition of self-attunement when children learn to map and interpret interoceptive sensations and develop adaptive actions. We question whether a fear of weight gain, in some cases, may be an epiphenomenon of the recapitulation of actual or perceived GI symptoms that is especially relevant during puberty, especially in girls. This conceptualization has immediate clinical implications and offers ideas for future research. We propose that GI discomfort associated with renourishment may reignite prior aversive visceral experiences. We encourage development of a formulation that organizes the individual's current experience of the body with respect to these prior aversive experiences. Our conceptualization underscores the importance of assessment of GI experiences in individuals with AN; the examination of dietary strategies that minimize GI symptoms and enhance renourishment efficacy; and strategies that attempt to alter this aversive visceral conditioning by mapping sensations to meanings and adaptive actions.

Speed of sound ultrasound transmission tomography image reconstruction based on Bézier curves

Speed of Sound (SoS) maps from ultrasound tomography (UST) provide valuable quantitative information for soft tissue characterization and identification of lesions, making this technique interesting for breast cancer detection. However, due to the complexity of the processes that characterize the interaction of ultrasonic waves with matter, classic and fast tomographic algorithms such as back-projection are not suitable. Consequently, the image reconstruction process in UST is generally slow compared to other more conventional medical tomography modalities. With the aim of facilitating the translation of this technique into real clinical practice, several reconstruction algorithms are being proposed to make image reconstruction in UST to be a fast and accurate process. The geometrical acoustic approximation is often used to reconstruct SoS with less computational burden in comparison with full-wave inversion methods. In this work, we propose a simple formulation to perform on-the-flight reconstruction for UST using geometrical acoustics with refraction correction based on quadratic Bézier polynomials. Here we demonstrate that the trajectories created with these polynomials are an accurate approximation to reproduce the refracted acoustic paths connecting the emitter and receiver transducers. The method is faster than typical acquisition times in UST. Thus, it can be considered a step towards real-time reconstructions, which may contribute to its future clinical translation.

M&A Activity and the Capital Structure of Target Firms

Using a large sample of European acquisitions, we find that acquired firms substantially close the gap between their actual and optimal leverage ratios. The bulk of this adjustment occurs quite rapidly â?? within a year of the acquisition. The typical over-levered firm adjusts its debt-to-assets ratio from 34.4% in the year before acquisition to 20% in the year after. (The adjustment is smaller, but still quite rapid, for targets that had been under-leveraged.) These adjustments occur primarily through debt issuances or retirements. We also investigate whether target firms' pre-merger leverage contributes to the probability of them being acquired. We find that firms further away from their optimal leverage are more likely to be acquired: for an average firm, an increase in the absolute leverage deviation from 1% to 10% of total assets increases the probability of being acquired by 4.1% to 5.6% (The larger effect applies to over-leveraged firms.) Overall, our results provide support for the trade-off theory of capital structure and suggest that financial synergies have a significant role in the typical European acquisition decision.

Numerical Method for Horizontal and Vertical Spatial Resolutions of Seismic Acquisition Geometries in Complex 3D Media

Spatial sampling, finite bandwidth, and overlying-strata shielding are three key issues to affect the spatial resolution of seismic imaging for deep targets. Some factors have a great impact on the horizontal resolution, whereas others influence the vertical resolution. How to quantify these effects remains controversial for complex media. Most previous studies on seismic acquisition geometries focus on the horizontal resolution for layered media but neglecting to measure the vertical resolution especially in complex media. Conventional criteria for vertical resolution are based on the theory of geometric seismology with the assumption of a simple medium. As a practical alternative for resolution estimation in complex media, numerical methods with wavefield extrapolation for focal-beam analysis can provide comprehensive insight into the combined effect of acquisition geometries, bandlimited frequencies, and complex media on the horizontal and vertical spatial resolutions of acquisition geometries. We incorporate some classic criteria into the focal-beam numerical analysis to measure the spatial resolutions. Four parameters are used to quantify the performance of acquisition geometries. The horizontal (vertical) resolution is defined as the main-lobe width of a focal beam along the horizontal (vertical) direction, whereas the square root of the peak-to-total ratio of energies is referred to as the horizontal (vertical) sharpness. These parameters describe the horizontal and vertical spatial resolution and sharpness to image the target. Numerical examples with typical acquisition geometries demonstrate the performance of numerical resolution analyses in complex media.

Persistent Neurobehavioral Markers of Developmental Morphosyntax Errors in Adults.

Purpose Child language acquisition is marked by an optional infinitive period (ages 2-4 years) during which children use nonfinite (infinitival) verb forms and finite verb forms interchangeably in grammatical contexts that require finite forms. In English, children's errors include omissions of past tense /-ed/ and 3rd-person singular /-s/. This language acquisition period typically ends by the age of 4 years, but it persists in children with language impairments. It is unknown if adults still process optional infinitives differently than other kinds of morphosyntax errors. Method We compared behavior and functional brain activation during grammaticality judgments across sentences with developmental optional infinitive tense/agreement errors ("Yesterday I play the song"), nondevelopmental agreement errors ("He am tall") that do not occur in typical child language acquisition, and grammatically correct sentences. Results Adults (N = 25) were significantly slower and less accurate in judging sentences with developmental errors relative to other sentences. Sentences with developmental errors yielded greater activation in bilateral inferior frontal gyri relative to nondevelopmental error sentences in both auditory and visual modalities. Conclusions These findings suggest that the heightened computational demands for finiteness extend well beyond early childhood and continue to exert their influence on grammatical mental and brain function in adulthood.

Rutile dielectric loop-gap resonator for X-band EPR spectroscopy of small aqueous samples.

The performance of a metallic microwave resonator that contains a dielectric depends on the separation between metallic and dielectric surfaces, which affects radio frequency currents, evanescent waves, and polarization charges. The problem has previously been discussed for an X-band TE011 cylindrical cavity resonator that contains an axial dielectric tube (Hyde and Mett, 2017). Here, a short rutile dielectric tube inserted into a loop-gap resonator (LGR) at X-band, which is called a dielectric LGR (dLGR), is considered. The theory is developed and experimental results are presented. It was found that a central sample loop surrounded by four "flux-return" loops (i.e., 5-loop-4-gap) is preferable to a 3-loop-2-gap configuration. For sufficiently small samples (less than 1 µL), a rutile dLGR is preferred relative to an LGR both at constant Λ (B1/Pl) and at constant incident power. Introduction of LGR technology to X-band EPR was a significant advance for site-directed spin labeling because of small sample size and high Λ. The rutile dLGR introduced in this work offers further extension to samples that can be as small as 50 nL when using typical EPR acquisition times.

A gramática fonológica na aquisição da linguagem

O artigo trata do processo de construção do conhecimento fonológico na aquisição típica da linguagem pelas crianças, evidenciado mais especificamente pela variabilidade no emprego de consoantes até a integralização do inventário fonológico da língua alvo. Uma análise fundamentada em traços distintivos e centrada no comportamento de consoantes líquidas confirma a hipótese de que a variabilidade, entendida como o uso de diferentes formas fonéticas para representar um mesmo segmento fonológico em gramáticas características do gradual processo de aquisição, oferece evidência de que o pertencimento a uma classe antecede a estabilização do segmento como unidade da fonologia da língua. Os dados empíricos de variabilidade, enriquecidos pela observação do preenchimento de lacunas nos estágios mais precoces de aquisição, secundados pelo comportamento de empréstimos linguísticos, conduzem à proposição de uma Escala de Agregação para expressar uma hierarquia relativa à força dos traços no cumprimento do papel de agregar segmentos para a constituição de classes naturais.