Miracle-dz/UniFAR-FTUs huggingface dataset:
Visualization of intravenously administered contrast material in the CSF on fluid-attenuated inversion-recovery MR images: an in vitro and animal-model investigation.

BACKGROUND AND PURPOSE The FLAIR (fluid-attenuated inversion-recovery) pulse sequence has been shown to be sensitive to abnormalities of the subarachnoid space. Our clinical experience led us to investigate whether intravenously injected contrast material can affect the appearance of the subarachnoid space on FLAIR MR images. METHODS After noting unexplained high signal in the subarachnoid space on FLAIR images in a patient, we studied two dogs with sequential FLAIR MR imaging after i.v. administration of contrast material. A third dog was studied with a 6-hour delayed FLAIR sequence after triple-dose (0.3 mmol/kg) i.v. contrast administration. CSF was obtained from two animals for measurement of gadolinium concentration. A phantom was developed to determine the lowest concentration at which the effects of gadolinium were evident on FLAIR images in vitro. RESULTS In all three animals, the appearance of the CSF in the ventricles or subarachnoid space was modified after administration of i.v. contrast. This was most evident on delayed images. The CSF samples showed a gadolinium concentration of 0.007 mmol/L in the dog who received the 0.1 mmol/kg dose and 0.02 mmol/L in the dog who received a triple dose. In our in vitro phantom experiments, gadolinium effects were evident on FLAIR images at a concentration four times lower than those on T1-weighted images. CONCLUSION I.v. contrast material can cross into the CSF in sufficient concentration to alter the appearance of the subarachnoid space on FLAIR images in normal dogs. Although we encountered two patients with CNS disease in whom enhancement of the CSF was seen on postcontrast FLAIR images, additional investigation is needed in humans to determine whether enhancement may occur at triple dose in healthy subjects.
Adaptive Array Thinning for Enhanced DOA Estimation

Antenna array configurations play an important role in direction of arrival (DOA) estimation. In this letter, performance enhancement of DOA estimation is achieved by reconfiguring the multi-antenna receiver through an antenna selection strategy. We derive the Cramer-Rao Bound (CRB) in terms of the selected antennas and associated subarray for both peak sidelobe level (PSL) constrained isotropic and directional arrays in single source cases. Since directional arrays are angle dependent, a Dinklebach type algorithm and convex relaxation are introduced to maintain the optimum selection by adaptively reconfiguring the directional subarrays using semi-definite programming. Simulation results validate the effectiveness of the proposed antenna selection strategy.
Bilateral Renal Denervation Ameliorates Isoproterenol-Induced Heart Failure through Downregulation of the Brain Renin-Angiotensin System and Inflammation in Rat

Heart failure (HF) is characterized by cardiac dysfunction along with autonomic unbalance that is associated with increased renin-angiotensin system (RAS) activity and elevated levels of proinflammatory cytokines (PICs). Renal denervation (RD) has been shown to improve cardiac function in HF, but the protective mechanisms remain unclear. The present study tested the hypothesis that RD ameliorates isoproterenol- (ISO-) induced HF through regulation of brain RAS and PICs. Chronic ISO infusion resulted in remarked decrease in blood pressure (BP) and increase in heart rate and cardiac dysfunction, which was accompanied by increased BP variability and decreased baroreflex sensitivity and HR variability. Most of these adverse effects of ISO on cardiac and autonomic function were reversed by RD. Furthermore, ISO upregulated mRNA and protein expressions of several components of the RAS and PICs in the lamina terminalis and hypothalamic paraventricular nucleus, two forebrain nuclei involved in cardiovascular regulations. RD significantly inhibited the upregulation of these genes. Either intracerebroventricular AT1-R antagonist, irbesartan, or TNF-α inhibitor, etanercept, mimicked the beneficial actions of RD in the ISO-induced HF. The results suggest that the RD restores autonomic balance and ameliorates ISO-induced HF and that the downregulated RAS and PICs in the brain contribute to these beneficial effects of RD.
Deep Neural Networks Under Stress

In recent years, deep architectures have been used for transfer learning with state-of-the-art performance in many datasets. The properties of their features remain, however, largely unstudied under the transfer perspective. In this work, we present an extensive analysis of the resiliency of feature vectors extracted from deep models, with special focus on the trade-off between performance and compression rate. By introducing perturbations to image descriptions extracted from a deep convolutional neural network, we change their precision and number of dimensions, measuring how it affects the final score. We show that deep features are more robust to these disturbances when compared to classical approaches, achieving a compression rate of 98.4%, while losing only 0.88% of their original score for Pascal VOC 2007.
Nonlinear inversion applied to acoustic tomography

The propagation of waves through heterogeneous media is described via wave equations. For the electromagnetic case, they follow from Maxwell equations, for the acoustic case from the acoustic field equations. The fields scattering of the contrasts may be recorded and used for imaging the unknown internal structure of the object. Ideally, these imaging algorithms obey the physics as formulated via the wave equations. However, as these imaging algorithms are often computationally demanding, inverse Radon transformations based on optical ray theory may be employed. In this paper, both a approaches are tested on simulated tomo-graphic measurements. Results show that for the considered test case, phenomena such as multiple scattering and refraction should not be neglected.
PTHMM: Beyond Single Specific Behavior Prediction

Existing works on user behavior analysis mainly focus on modeling a single behavior and predicting whether a user will take an action or not. However, users' behaviors do not always happen in isolation, sometimes, different behaviors may happen simultaneously. Therefore, in this paper, we try to analyze the combination of basic behaviors, called behavioral state here, which can describes users' complex behaviors comprehensively. We propose a model, called Personal Timed Hidden Markov Model (PTHMM), to settle the problem by considering time-interval information of users' behaviors and users' personalization. The experimental result on sina-weibo demonstrates the effectiveness of the model. It also shows that users' behavioral state is affected by their historical behaviors, and the influence of historical behaviors declines with the increasing of historical time.
Intelligent beamforming to improve the spectral efficiency in MIMO system

Cognitive radio assents the secondary users to access the spectrum of the primary user only when there is a spectrum hole is detected. Hence the looked-for spectral competence cannot be achieved. To improve the spectral efficiency the synchronicity of the primary and secondary users are required and it is achieved by beamforming. Two main problems are existing while beamforming are to achieve the throughput required by the secondary user and to maintain the interference level below the threshold value. The problems are solved by using convex optimization technique and SVD. By using the SVD single channel can be spliced into orthonormal channels; because of that coexistence of primary and secondary users can be implemented and the steering vector is used to improve the directionality of the signal. MIMO system with four antenna is considered for simulation. Using the new proposed scheme it is sure that the MIMO cognitive radio performance will be enhanced.
Moving-object detection, association, and selection in home videos

Due to the prevalence of digital video camcorders, home videos have become an important part of life-logs of personal experiences. To enable efficient video parsing, a critical step is to automatically extract objects, events and scene characteristics present in videos. This paper addresses the problem of extracting objects from home videos. Automatic detection of objects is a classical yet difficult vision problem, particularly for videos with complex scenes and unrestricted domains. Compared with edited and surveillant videos, home videos captured in uncontrolled environment are usually coupled with several notable features such as shaking artifacts, irregular motions, and arbitrary settings. These characteristics have actually prohibited the effective parsing of semantic video content using conventional vision analysis. In this paper, we propose a new approach to automatically locate multiple objects in home videos, by taking into account of how and when to initialize objects. Previous approaches mostly consider the problem of how but not when due to the efficiency or real-time requirements. In home-video indexing, online processing is optional. By considering when, some difficult problems can be alleviated, and most importantly, enlightens the possibility of parsing semantic video objects. In our proposed approach, the how part is formulated as an object detection and association problem, while the when part is a saliency measurement to determine the best few locations to start multiple object initialization
Chromosomal Distribution of PcG Proteins during Drosophila Development

Polycomb group (PcG) proteins are able to maintain the memory of silent transcriptional states of homeotic genes throughout development. In Drosophila, they form multimeric complexes that bind to specific DNA regulatory elements named PcG response elements (PREs). To date, few PREs have been identified and the chromosomal distribution of PcG proteins during development is unknown. We used chromatin immunoprecipitation (ChIP) with genomic tiling path microarrays to analyze the binding profile of the PcG proteins Polycomb (PC) and Polyhomeotic (PH) across 10 Mb of euchromatin. We also analyzed the distribution of GAGA factor (GAF), a sequence-specific DNA binding protein that is found at most previously identified PREs. Our data show that PC and PH often bind to clustered regions within large loci that encode transcription factors which play multiple roles in developmental patterning and in the regulation of cell proliferation. GAF co-localizes with PC and PH to a limited extent, suggesting that GAF is not a necessary component of chromatin at PREs. Finally, the chromosome-association profile of PC and PH changes during development, suggesting that the function of these proteins in the regulation of some of their target genes might be more dynamic than previously anticipated.
Chosen-Ciphertext Secure Multi-use Unidirectional Attribute-Based Proxy Re-Encryptions

This paper presents a novel cipher text-policy attribute-based multi-use unidirectional proxy re-encryption scheme. In the proposed scheme, the tree access policy can be used to handle and (¡Ä), or (¡Å) and threshold (of) operators. We first formalize the security definition against chosen cipher text attack for cipher text-policy attribute-based multi-use unidirectional proxy re-encryption schemes, and then prove the proposed scheme to be secure under ADBDH assumption in the standard model. Furthermore, compared with other cipher text policy attribute-based proxy re-encryption schemes, our scheme is more efficient and allows the encryptor to control whether the cipher text need to be re-encrypted.
Genetic Algorithms for Air Traac Control Systems

The Air Traac Control system of a country manages all the aircraft that y in its airspace, designs control sectors, manages the ows between the diier-ent airports and beacons, ensures separation between aircraft during their ight, take oo and landing. Thus, it operates at diierent levels, each one of them designed to provide control, ensure safety, and limit the traac passed to the following level. In this paper we show how Genetic Algorithms can improve some of the tasks manually done by the ATC system. After a brief description of GAs, some of the improvements used (simulated annealing, sharing), we study three applications of GAs to ATC. We rst show an application of GAs to en-route connict resolution. Then we give an example on GAs used to optimize air space sec-toring. The last part gives an application of GAs to traac assignment.
Scenario-Based Requirement Analysis

A method for scenario based requirements engineering is described. The method uses two types of scenario, structure models of the system context and scripts of system usage. A modelling language is reported for describing scenarios, and heuristics are given to cross check dependencies between scenario models and the requirements specification. Heuristics are grouped into several analytic treatments that investigate correspondences between users’ goals and system functions; input events and system processes to deal with them; system output and its destination in the scenario model, and acceptability analysis of system output for different stakeholders. The method is illustrated with a case study taken from the London Ambulance Service report. The prospects for scenario based RE and related work are discussed.
A Real Time Object Detection Approach Applied to Reliable Pedestrian Detection

This paper presents a robust real time obstacle and pedestrian detection algorithm, which is capable of handling the challenges of stationary as well as moving objects, utilizing a single car mounted monochrome camera. First, the system detects obstacles above the ground plane by obtaining a "virtual stereo system" through the usage of inverse perspective mapping. A fast digital image stabilization algorithm is used to compensate erroneous detections whenever the flat ground plane assumption is an inaccurate model of the road surface. Finally, a low level pedestrian segmentation algorithm is developed to extract bounding boxes of potential pedestrians. Furthermore a novel approach called the pedestrian detection strip is used to improve the calculation time by a factor of six compared to previous attempts. Experiments have been carried out by applying the proposed algorithm on prerecorded sequences as well as within a test vehicle and thus in a closed loop environment. The experimental results indicate a promising detection performance. Obstacles and pedestrians up to 50 meters away from the vehicle have been detected reliably at 64 frames per second on a 3 GHz PC.
Overview of Power-Efficient MAC and Routing Protocols for Wireless Sensor Networks

Energy conservation is a primary concern in sensor networks. Firstly, we introduce the necessary of power saving in wireless sensor network. Then we analyze and summarize the main MAC protocols and routing protocols that are designed specially for energy conservation. Further, the methods for reducing energy consumption of node and increasing lifetime of networks are highlighted. Moreover, we make a comprehensive comparison between every protocol in performance of networks. Finally, we point out the future research directions and challenges that must be overcome on this topic
Parallel Type-checking with Saturating LVars

Given the sophistication of recent type systems, unification-based type-checking and inference can be a time-consuming phase of compilation—especially when union types are combined with subtyping. It is natural to consider improving performance through parallelism, but these algorithms are challenging to parallelize due to complicated control structure and difficulties representing data in a way that is both efficient and supports concurrency. We provide a solution to these problems based on the LVish approach to deterministic-by-default parallel programming. We extend LVish with a novel class of concurrent data structures: Saturating LVars, which are the first LVars to safely release memory during the object’s lifetime. Our new design allows us to achieve a parallel speedup on worst-case (exponential) inputs of traditional HindleyMilner inference, and on the Typed-Racket type-checking algorithm, which yields up an 8.46× parallel speedup on type-checking examples drawn from the Racket repository.
Optimizing Pattern Matching for Intrusion Detection

– This paper presents an optimized version of the Aho-Corasick [1] algorithm. This design represents a significant enhancement to the author’s original implementation released in 2002 as part of an update to the Snort Intrusion Detection System. The enhanced design uses an optimized vector implementation of the Aho-Corasick state table that significantly improves performance. A memory efficient variant uses sparse matrix storage to reduce memory requirements and further improve performance on large pattern groups. Intrusion Detection Systems are very specialized applications that require real-time pattern matching capabilities at very high network speeds, and in hostile environments. Several of the major issues that must be considered in pattern matching and Intrusion Detection are discussed to establish a framework for the use of the Aho-Corasick algorithm as implemented in the Snort Intrusion Detection System. The performance results comparing the original, optimized, and sparse storage versions of the authors Aho-Corasick algorithm are presented. Tests were conducted using several dictionary tests and a Snort based Intrusion Detection performance test. The impact of pattern group sizes and compiler selection on performance is also demonstrated using several popular compilers.
A New World of Work Challenging Swedish Unions

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Reconsidering Sex-Based Occupational Segregation and Agency Missions: An Analysis of U.S. State Bureaucracies (1987-2015) Using Two Different Thresholds

We examine Equal Employment Opportunity Commission data (1987-2015) to determine whether sex-based occupational segregation among administrative and professional workforces is related to state agency policy missions. Based on two thresholds, the customary 30% benchmark and the 50% benchmark of parity, the findings indicate segregation is related to policy missions. The 30% benchmark suggests a story of widespread progress across state bureaucracies. The 50% benchmark suggests less progress, especially, in police, fire, corrections, utilities, natural resources, and highways. The authors argue it is important to use multiple indicators to assess the progress of women in the workplace.
Physiological reactivity to mental imagery as a construct relating to somatization and hypnotizability

Previous research has failed to find a consistent relationship between hypnotizability and imagery ability. Common means of assessing imagery ability involve self-report measures of visual imagery vividness. The present study implements a behavioral approach to capture a unique aspect of imagery ability. It was hypothesized that participants' ability to have physiological reactions to their mental images as if those images were real, may be related to hypnotizability. Additionally, previous research has explored links between hypnotizability and a tendency to have psychosomatic difficulties. The present study examines this relationship using a new measure of somatization (Somatization of Emotional Conflict Scale). 70 Undergraduates at the Univeristy of Tennessee (34 Males and 36 females, mean age = 19.59) completed several self-report questionnaires as well as the Waterloo-Stanford Group C scale of hypnotic susceptibility. Their physiological reactivity to imagery of having their hands immersed in an ice bath was also measured. Findings indicate that reactivity to mental imagery was not related to hypnotizability however, scores from the Somatization_ of Emotional Conflict scale significantly predicted hypnotizability over and above all other measures implemented in the study. Implications for further research on the relationship between somatization and hypnotizability are discussed.
Race at the Center: Perspectives on Improving Science and Math Achievement.

This study explored the perspectives of teachers, administrators, and students as they were engaged in a 5-year funded project aimed at improving science and mathematics achievement for African American students in a school district. The study also discusses the obstacles that hindered and the supports that bolstered this project. In this study, race is at the center of the examination of science and mathematics achievement. Interviews were conducted with 27 secondary school teachers, 27 elementary school teachers, and 4 project administrators (also school district administrators) . Twelve African American secondary school students were also interviewed. The perceptions of obstacles and supports were derived from the experiences of the co-principal investigator. As a result of the project, more African American students were enrolled in upper level mathematics and science classes and more received grades of "C" or better than previously. However, the number of these students remained extremely low. In many instances, teachers blamed the students' low achievement on their families or on previous teachers. Administrators were less likely to support this view, but some students agreed with teachers' emphasis on parental influence and responsibility. Those schools in which African Americans showed greater gains in mathematics and science had principals who were risk takers who supported teachers who wanted to alter their pedagogy. Principals of the effective schools were also able to confront and examine the racial disparities within their schools. The teachers in this study were increasing their focus on state standards and testing, a fact that that moved them further away from pedagogy that is relevant to any student, much less those of nondominant groups like African Americans. The school district suffers from many constraints that hamper efforts to increase student achievement, including low teacher salaries and inadequate funding, but it is to be hoped that another grant to improve mathematics and science may make the district able to consider some of the issues raised in this report. (SLD) Reproductions supplied by EDRS are the best that can be made from the original document. Race at the Center: Science and Math Achievement 1 Race at the Center: Perspectives on Improving Science and Math Achievement U.S. DEPARTMENT OF EDUCATION Off ice of Educational Research and Improvement EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) /his document has been reproduced as received from the person or organization originating it. 0 Minor changes have been made to improve reproduction quality. Points of view or opinions stated in this document do not necessarily represent official OERI position or policy. Carol Lloyd, University of Nebraska at Omaha CD CD C's1 Paper presented at the 2001 AERA Annual Meeting ce) Seattle, Washington co) PERMISSION TO REPRODUCE AND DISSEMINATE THIS MATERIAL HAS BEEN GRANTED BY