Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthetic tracked aperture ultrasound imaging: design, simulation, and experimental evaluation

Abstract. Ultrasonography is a widely used imaging modality to visualize anatomical structures due to its low cost and ease of use; however, it is challenging to acquire acceptable image quality in deep tissue. Synthetic aperture (SA) is a technique used to increase image resolution by synthesizing information from multiple subapertures, but the resolution improvement is limited by the physical size of the array transducer. With a large F-number, it is difficult to achieve high resolution in deep regions without extending the effective aperture size. We propose a method to extend the available aperture size for SA—called synthetic tracked aperture ultrasound (STRATUS) imaging—by sweeping an ultrasound transducer while tracking its orientation and location. Tracking information of the ultrasound probe is used to synthesize the signals received at different positions. Considering the practical implementation, we estimated the effect of tracking and ultrasound calibration error to the quality of the final beamformed image through simulation. In addition, to experimentally validate this approach, a 6 degree-of-freedom robot arm was used as a mechanical tracker to hold an ultrasound transducer and to apply in-plane lateral translational motion. Results indicate that STRATUS imaging with robotic tracking has the potential to improve ultrasound image quality.
Video Concept Detection Using Support Vector Machine with Augmented Features

In this paper, we present a direct application of Support Vector Machine with Augmented Features (AFSVM) for video concept detection. For each visual concept, we learn an adapted classifier by leveraging the pre-learnt SVM classifiers of other concepts. The solution of AFSVM is to re-train the SVM classifier using augmented feature, which concatenates the original feature vector with the decision value vector obtained from the pre-learnt SVM classifiers in the Reproducing Kernel Hilbert Space (RKHS). The experiments on the challenging TRECVID 2005 dataset demonstrate the effectiveness of AFSVM for video concept detection.
The Role of Reduced Humanity in Producing Linguistic Discrimination

This article addresses the role of perceived (reduced) humanity and group membership of others in producing linguistic discrimination. Study 1 assessed the effects of these factors on a subtle measure of linguistic discrimination, namely, linguistic abstraction. Study 2 considered the explicit level of verbal abuse. Results highlighted that target’s reduced humanity led to enhanced linguistic discrimination toward the target, while group membership moderated this effect in specific conditions. Overall, the evidence of this set of studies sheds light on the role of humanity and its interplay with social categorization on discrimination outcomes.
Membrane inlet laser spectroscopy to measure H and O stable isotope compositions of soil and sediment pore water with high sample throughput.

RATIONALE The fast and accurate measurement of H and O stable isotope compositions (δ2 H and δ18 O values) of soil and sediment pore water remains an impediment to scaling-up the application of these isotopes in soil and vadose hydrology. Here we describe a method and its calibration to measuring soil and sediment pore water δ2 H and δ18 O values using a water vapor-permeable probe coupled to an isotope ratio infrared spectroscopy analyzer. METHODS We compare the water vapor probe method with a vapor direct equilibration method, and vacuum extraction with liquid water analysis. At a series of four study sites in a managed desert agroecosystem in the eastern Great Basin of North America, we use the water vapor probe to measure soil depth profiles of δ2 H and δ18 O values. RESULTS We demonstrate the accuracy of the method to be equivalent to direct headspace equilibration and vacuum extraction techniques, with increased ease of use in its application, and with analysis throughput rates greater than 7 h-1 . The soil depth H and O stable isotope profiles show that soil properties such as contrasting soil texture and pedogenic soil horizons control the shape of the isotope profiles, which are reflective of local evaporation conditions within the soils. CONCLUSIONS We conclude that this water vapor probe method has potential to yield large numbers of H and O stable isotope analyses of soil and sediment waters within shorter timeframes and with increased ease than with currently existing methods. Copyright © 2016 John Wiley & Sons, Ltd.
Optimizing the general linear model for functional near-infrared spectroscopy: an adaptive hemodynamic response function approach

Abstract. An increasing number of functional near-infrared spectroscopy (fNIRS) studies utilize a general linear model (GLM) approach, which serves as a standard statistical method for functional magnetic resonance imaging (fMRI) data analysis. While fMRI solely measures the blood oxygen level dependent (BOLD) signal, fNIRS measures the changes of oxy-hemoglobin (oxy-Hb) and deoxy-hemoglobin (deoxy-Hb) signals at a temporal resolution severalfold higher. This suggests the necessity of adjusting the temporal parameters of a GLM for fNIRS signals. Thus, we devised a GLM-based method utilizing an adaptive hemodynamic response function (HRF). We sought the optimum temporal parameters to best explain the observed time series data during verbal fluency and naming tasks. The peak delay of the HRF was systematically changed to achieve the best-fit model for the observed oxy- and deoxy-Hb time series data. The optimized peak delay showed different values for each Hb signal and task. When the optimized peak delays were adopted, the deoxy-Hb data yielded comparable activations with similar statistical power and spatial patterns to oxy-Hb data. The adaptive HRF method could suitably explain the behaviors of both Hb parameters during tasks with the different cognitive loads during a time course, and thus would serve as an objective method to fully utilize the temporal structures of all fNIRS data.
Anatomical guidance for functional near-infrared spectroscopy: AtlasViewer tutorial

Abstract. Functional near-infrared spectroscopy (fNIRS) is an optical imaging method that is used to noninvasively measure cerebral hemoglobin concentration changes induced by brain activation. Using structural guidance in fNIRS research enhances interpretation of results and facilitates making comparisons between studies. AtlasViewer is an open-source software package we have developed that incorporates multiple spatial registration tools to enable structural guidance in the interpretation of fNIRS studies. We introduce the reader to the layout of the AtlasViewer graphical user interface, the folder structure, and user files required in the creation of fNIRS probes containing sources and detectors registered to desired locations on the head, evaluating probe fabrication error and intersubject probe placement variability, and different procedures for estimating measurement sensitivity to different brain regions as well as image reconstruction performance. Further, we detail how AtlasViewer provides a generic head atlas for guiding interpretation of fNIRS results, but also permits users to provide subject-specific head anatomies to interpret their results. We anticipate that AtlasViewer will be a valuable tool in improving the anatomical interpretation of fNIRS studies.
Artifact reduction in long-term monitoring of cerebral hemodynamics using near-infrared spectroscopy

Abstract. Near-infrared spectroscopy (NIRS) is a noninvasive neuroimaging technique used to assess cerebral hemodynamics. Its portability, ease of use, and relatively low operational cost lend itself well to the long-term monitoring of hemodynamic changes, such as those in epilepsy, where events are unpredictable. Long-term monitoring is associated with challenges including alterations in behaviors and motion that can result in artifacts. Five patients with epilepsy were assessed for interictal hemodynamic changes and alterations in behavior or motion. Based on this work, visual inspection was used to identify NIRS artifacts during a period of interest, specifically prior to seizures, in four patients. A motion artifact reduction algorithm (MARA, also known as the spline interpolation method) was tested on these data. Alterations in the NIRS measurements often occurred simultaneously with changes in motion and behavior. Occasionally, sharp shift artifacts were observed in the data. When artifacts appeared as sustained baseline shifts in the data, MARA reduced the standard deviation of the data and the appearance improved. We discussed motion and artifacts as challenges associated with long-term monitoring of cerebral hemodynamics in patients with epilepsy and our group’s approach to circumvent these challenges and improve the quality of the data collected.
Red fluorescent proteins (RFPs) and RFP-based biosensors for neuronal imaging applications

Abstract. The inherent advantages of red-shifted fluorescent proteins and fluorescent protein-based biosensors for the study of signaling processes in neurons and other tissues have motivated the development of a plethora of new tools. Relative to green fluorescent proteins (GFPs) and other blue-shifted alternatives, red fluorescent proteins (RFPs) provide the inherent advantages of lower phototoxicity, lower autofluorescence, and deeper tissue penetration associated with longer wavelength excitation light. All other factors being the same, the multiple benefits of using RFPs make these tools seemingly ideal candidates for use in neurons and, ultimately, the brain. However, for many applications, the practical utility of RFPs still falls short of the preferred GFPs. We present an overview of RFPs and RFP-based biosensors, with an emphasis on their reported applications in neuroscience.
Newer contributions to the neuropsychological assessment of executive functions

Although the need for tests sensitive to executive dysfunction is great, and getting greater as the number of survivors of serious motor vehicle accidents increases, relatively few examination techniques are available. This article reviews a number of the tests developed recently and tests involving new applications of older examination techniques. It is hoped that this review will stimulate further test development in this area
Establishing the diffuse correlation spectroscopy signal relationship with blood flow

Abstract. Diffuse correlation spectroscopy (DCS) measurements of blood flow rely on the sensitivity of the temporal autocorrelation function of diffusively scattered light to red blood cell (RBC) mean square displacement (MSD). For RBCs flowing with convective velocity vRBC, the autocorrelation is expected to decay exponentially with (vRBCτ)2, where τ is the delay time. RBCs also experience shear-induced diffusion with a diffusion coefficient Dshear and an MSD of 6Dshearτ. Surprisingly, experimental data primarily reflect diffusive behavior. To provide quantitative estimates of the relative contributions of convective and diffusive movements, we performed Monte Carlo simulations of light scattering through tissue of varying vessel densities. We assumed laminar vessel flow profiles and accounted for shear-induced diffusion effects. In agreement with experimental data, we found that diffusive motion dominates the correlation decay for typical DCS measurement parameters. Furthermore, our model offers a quantitative relationship between the RBC diffusion coefficient and absolute tissue blood flow. We thus offer, for the first time, theoretical support for the empirically accepted ability of the DCS blood flow index (BFi) to quantify tissue perfusion. We find BFi to be linearly proportional to blood flow, but with a proportionality modulated by the hemoglobin concentration and the average blood vessel diameter.
Comparison of species classification models of mass spectrometry data: Kernel Discriminant Analysis vs Random Forest; A case study of Afrormosia (Pericopsis elata (Harms) Meeuwen).

RATIONALE The genus Pericopsis includes four tree species of which only Pericopsis elata (Harms) Meeuwen is of commercial interest. Enforcement officers might have difficulties discerning this CITES-listed species from some other tropical African timber species. Therefore, we tested several methods to separate and identify these species rapidly in order to enable customs officials to uncover illegal trade. In this study, two classification methods using Direct Analysis in Real Time (DART™) ionization coupled with Time-of-Flight Mass Spectrometry (DART-TOFMS) data to discern between several species are presented. METHODS Metabolome profiles were collected using DART™ ionization coupled with TOFMS analysis of heartwood specimens of all four Pericopsis species and Haplormosia monophylla (Harms) Harms, Dalbergia melanoxylon Guill. & Perr. Harms, and Milicia excelsa (Welw.) C.C. Berg. In total, 95 specimens were analysed and the spectra evaluated. Kernel Discriminant Analysis (KDA) and Random Forest classification were used to discern the species. RESULTS DART-TOFMS spectra obtained from wood slivers and post-processing analysis using KDA and Random Forest classification separated Pericopsis elata from the other Pericopsis taxa and its lookalike timbers Haplormosia monophylla, Milicia excelsa, and Dalbergia melanoxylon. Only 50 ions were needed to achieve the highest accuracy. CONCLUSIONS DART-TOFMS spectra of the taxa were reproducible and the results of the chemometric analysis provided comparable accuracy. Haplormosia monophylla was visually distinguished based on the heatmap and was excluded from further analysis. Both classification methods, KDA and Random Forest, were capable of distinguishing Pericopsis elata from the other Pericopsis taxa, Milicia excelsa, and Dalbergia melanoxylon, timbers that are commonly traded.
Is Education a Fundamental Right? People’s Lay Theories About Intellectual Potential Drive Their Positions on Education

Does every child have a fundamental right to receive a high-quality education? We propose that people’s beliefs about whether “nearly everyone” or “only some people” have high intellectual potential drive their positions on education. Three studies found that the more people believed that nearly everyone has high potential, the more they viewed education as a fundamental human right. Furthermore, people who viewed education as a fundamental right, in turn (a) were more likely to support the institution of free public education, (b) were more concerned upon learning that students in the country were not performing well academically compared with students in peer nations, and (c) were more likely to support redistributing educational funds more equitably across wealthier and poorer school districts. The studies show that people’s beliefs about intellectual potential can influence their positions on education, which can affect the future quality of life for countless students.
Liquid chromatography/mass spectrometry based detection and semi‐quantitative analysis of INSL5 in human and murine tissues

Rationale Insulin‐like peptide 5 (INSL5) is a hormone produced by enteroendocrine L‐cells in the colon that has recently been implicated in the control of metabolic homeostasis. However, research into its physiology has been hindered by the reported unreliability of commercially available immunoassays and additional detection assays would benefit this emerging field. Methods Peptides from purified murine L‐cells and homogenates from both human and mouse colonic tissues were extracted by precipitating larger proteins with acetonitrile. Untargeted liquid chromatography/tandem mass spectrometry (LC/MS/MS) analyses, followed by database searching, were used to detect and identify various INSL5 gene derived peptides and characterise their precise sequence. A similar approach was developed to quantify INSL5 levels in primary intestinal culture supernatants after purification and concentration by solid‐phase extraction. Results Mass spectral analysis of purified enteroendocrine cells and tissue homogenates identified the exact sequence of A and B chains of INSL5 endogenously expressed in L‐cells. Differences in the endogenously processed peptide and the Swissprot database entry were observed for murine INSL5, whereas the human sequence matched previous predictions from heterologous expression experiments. INSL5 was detected in the supernatant of human and mouse primary colonic cultures and concentrations increased after treatment with a known L‐cell stimulus. Conclusions The first LC/MS/MS‐based method capable of the detection and semi‐quantitative analysis of endogenous INSL5 using MS‐based techniques has been demonstrated. The methodology will enable the identification of stimulants for INSL5 secretion from murine and human primary colonic epithelial cultures.
Review of functional and clinical relevance of intrinsic signal optical imaging in human brain mapping

Abstract. Intrinsic signal optical imaging (ISOI) within the first decade of its use in humans showed its capacity as a precise functional mapping tool. It is a powerful tool that can be used intraoperatively to help a surgeon to directly identify functional areas of the cerebral cortex. Its use is limited to the intraoperative setting as it requires a craniotomy and durotomy for direct visualization of the brain. It has been applied in humans to study language, somatosensory and visual cortices, cortical hemodynamics, epileptiform activity, and lesion delineation. Despite studies showing clear evidence of its usefulness in clinical care, its clinical use in humans has not grown. Impediments imposed by imaging in a human operating room setting have hindered such work. However, recent studies have been aimed at overcoming obstacles in clinical studies establishing the benefits of its use to patients. This review provides a description of ISOI and its use in human studies with an emphasis on the challenges that have hindered its widespread use and the recent studies that aim to overcome these hurdles. Clinical studies establishing the benefits of its use to patients would serve as the impetus for continued development and use in humans.
Review Article: Barriers within the health care system to dealing with sexualized violence: a literature review

The aim of this study was to review the literature about possible barriers to recognition and intervention regarding women exposed to sexualized violence, in their interactions with the health care system. The barriers, as reported by the health care staff, were: lack of education; the stereotype of a ``typical battered woman''; too close identification with the victim/abuser; time constraints; fear of offending the victim/abuser; and feelings of hopelessness and non-responsibility. The barriers, as reported by the victims, were: negative experiences of and structural limitations within the health care system; fear of retaliation from the abusive partner; and psychological effects of the normalization process. We conclude that the barriers within the health care sector have to be dealt with on three different levels: the structural level in order to diminish male power in society; the organizational level in order to initiate screening and to allow the staff time for dealing with the victims; and on the individual level, health care staff need to acquire the knowledge and skills to enable them to address sexualized violence.
Power allocation and control for multicarrier systems with soft decoding

We consider the application of multicarrier modulation in a wireless cellular network in order to enable high-data rate communication and alleviate the multipath induced intersymbol interference (ISI). In this scenario, power control becomes crucial in enhancing the spectral and power efficiency. A conventional approach of maintaining the same link quality for all the subchannels, in other words, disregarding any possible post-demodulation processing, is considered first. This approach appears to have increasing power consumption as the number of subchannels increases. It also deteriorates the power control stability and convergence properties in a multicell network. We attribute this phenomenon to lack of frequency diversity exploitation, and thus, we propose to use channel coding and soft decoding as vehicles to profit from the (frequency) diversity advantage in addition to the coding advantage. Based on the soft decoding performance bound, a power allocation and control algorithm is proposed. It is shown through simulations that the proposed algorithm improves the power efficiency as the number of subchannels increases. It also provides a better convergence property and is able to "detect" and eliminate ill-conditioned subchannels. The advantages of using multicarrier modulation are thus reassured. Besides these enhancements, the proposed algorithm is simple and feasible in that it consists of only the traditional closed-loop power control algorithm and a target signal-to-interference ratio (SIR) reassignment at the receiver. Detailed channel information feedback from receiver to transmitter is not required.
Denial of Service in Sensor Networks

Sensor networks hold the promise of facilitating large-scale, real-time data processing in complex environments, helping to protect and monitor military, environmental, safety-critical, or domestic infrastructures and resources, Denial-of-service attacks against such networks, however, may permit real world damage to public health and safety. Without proper security mechanisms, networks will be confined to limited, controlled environments, negating much of the promise they hold. The limited ability of individual sensor nodes to thwart failure or attack makes ensuring network availability more difficult. To identify denial-of-service vulnerabilities, the authors analyzed two effective sensor network protocols that did not initially consider security. These examples demonstrate that consideration of security at design time is the best way to ensure successful network deployment.
Ontology-Based Knowledge Management

The Web's very popularity is making it more difficult to find, present, and maintain the data that users with a wide range of tasks and computer skills need. Existing document management systems use keyword matching as a search method, combined with information retrieval rather than query answering. In addition, these systems offer limited information-sharing facilities, and they do not support different views on documents or information maintenance. To address these weaknesses, a European consortium formed the On-to-Knowledge Project to build an ontology-based tool suite that efficiently processes the many heterogeneous, distributed, and semistructured documents typically found in intranets and on the Web. The consortium's approach integrates Semantic Web search technology, document exchange via transformation operators, automated information extraction, and systematic support for information maintenance and user-specific views. The paper considers how On-to-Knowledge's tools exploit the power of ontologies to provide automated support for acquiring, maintaining, and accessing weakly structured information sources.
Comparison of Three Vertical Search Spiders

The Web's dynamic, unstructured nature makes locating resources difficult. Vertical search engines solve part of the problem by keeping indexes only in specific domains. They also offer more opportunity to apply domain knowledge in the spider applications that collect content for their databases. The authors used three approaches to investigate algorithms for improving the performance of vertical search engine spiders: a breadth-first graph-traversal algorithm with no heuristics to refine the search process, a best-first traversal algorithm that uses a hyperlink-analysis heuristic, and a spreading-activation algorithm based on modeling the Web as a neural network.