Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of a Dual-Polarized Stacked Patch Antenna for Wide-Angle Scanning Reflectarrays

A novel dual-polarized stacked patch antenna element for wide-angle scanning satcom on the move applications at Ka-band is presented. The proposed highly integrated multilayer unit cell element operates from 27.8 to 30.8 GHz with excellent scan performance up to ±60° in both E- and H-planes. High port-to-port isolation in the entire scan volume evidences the antenna's distinguished suitability for integration into an active folded reflectarray transceiver architecture. Parasitic effects in planar array antennas degrading the intended scan volume are investigated using the infinite array analysis, and measures are introduced to suppress them efficiently. To validate the proposed antenna design, several configurations were fabricated and measured successfully. The experimental results show close agreement with the simulations and indicate its excellent scanning capabilities.
Effects of a rapeseed oil-enriched hypoenergetic diet with a high content of α-linolenic acid on body weight and cardiovascular risk profile in patients with the metabolic syndrome

In therapy of the metabolic syndrome, the optimal dietary approach with regard to its macronutrient composition and metabolically favourable food components, such as the plant-derived n-3 fatty acid α-linolenic acid (ALA), is still a matter of debate. We investigated the effects of a hypoenergetic diet with low energy density (ED) enriched in rapeseed oil, resulting in high MUFA content and an ALA intake of 3·5 g/d on body weight and cardiovascular risk profile in eighty-one patients with the metabolic syndrome in comparison with an olive oil diet rich in MUFA, but with a low ALA content. After a 6-month dietary intervention, body weight was significantly reduced in the rapeseed oil and olive oil groups ( − 7·8 v. − 6·0 kg; P < 0·05). There were significant decreases in systolic blood pressure, total cholesterol and LDL-cholesterol, and insulin levels in both groups (P < 0·05). For all of these changes, no inter-group differences were observed. After the rapeseed oil diet, diastolic blood pressure declined more than after the olive oil diet (P < 0·05 for time × group interaction). Furthermore, concentrations of serum TAG were significantly reduced after the high ALA intake, but not in the low ALA group (P < 0·05 for time × group interaction). In conclusion, our dietary food pattern with a low ED and high intakes of MUFA and ALA may be a practical approach for long-term dietary treatment in patients with the metabolic syndrome, leading to weight reduction and an improvement in the overall cardiovascular risk profile.
Assistive technology and robotic control using motor cortex ensemble‐based neural interface systems in humans with tetraplegia

This review describes the rationale, early stage development, and initial human application of neural interface systems (NISs) for humans with paralysis. NISs are emerging medical devices designed to allow persons with paralysis to operate assistive technologies or to reanimate muscles based upon a command signal that is obtained directly from the brain. Such systems require the development of sensors to detect brain signals, decoders to transform neural activity signals into a useful command, and an interface for the user. We review initial pilot trial results of an NIS that is based on an intracortical microelectrode sensor that derives control signals from the motor cortex. We review recent findings showing, first, that neurons engaged by movement intentions persist in motor cortex years after injury or disease to the motor system, and second, that signals derived from motor cortex can be used by persons with paralysis to operate a range of devices. We suggest that, with further development, this form of NIS holds promise as a useful new neurotechnology for those with limited motor function or communication. We also discuss the additional potential for neural sensors to be used in the diagnosis and management of various neurological conditions and as a new way to learn about human brain function.
Yggdrasil: An Optimized System for Training Deep Decision Trees at Scale

Deep distributed decision trees and tree ensembles have grown in importance due to the need to model increasingly large datasets. However, PLANET, the standard distributed tree learning algorithm implemented in systems such as \xgboost and Spark MLlib, scales poorly as data dimensionality and tree depths grow. We present Yggdrasil, a new distributed tree learning method that outperforms existing methods by up to 24x. Unlike PLANET, Yggdrasil is based on vertical partitioning of the data (i.e., partitioning by feature), along with a set of optimized data structures to reduce the CPU and communication costs of training. Yggdrasil (1) trains directly on compressed data for compressible features and labels; (2) introduces efficient data structures for training on uncompressed data; and (3) minimizes communication between nodes by using sparse bitvectors. Moreover, while PLANET approximates split points through feature binning, Yggdrasil does not require binning, and we analytically characterize the impact of this approximation. We evaluate Yggdrasil against the MNIST 8M dataset and a high-dimensional dataset at Yahoo; for both, Yggdrasil is faster by up to an order of magnitude.
Dynamic Trust Evaluation of Wireless Sensor Networks Based on Multi-factor

Most of the existing trust evaluation methods of wireless sensor networks focus on communication behaviors in building paths without considering transmission behaviors in sensing environment. Therefore, a potential threat tothe network security exists in wireless sensor networks. Wepropose a dynamic trust evaluation method based on multi-factor including direct trust factor and indirect trust factor in this paper. Firstly, direct trust factor is composed of communication trust factor and transmission trust factor, both of which can be got from observing the interaction process. Secondly, indirect trust factorcomes from other nodes' recommendations, which are classified into certainand uncertain ones. Such two kinds of recommendation trust values are computed respectively. Finally, nodes' trustworthinessis measured by combining direct trust with indirect trust dynamically. Besides, both the involved classification standard and dynamic weight assignment are dependent on the interaction times between nodes, which are put forward under the background of Hoeffding's Inequality in Probability Theory. Experiments on NS-2 platform show that the proposed method is effective in increasing the network throughput and the network packet delivery ratio.
Truncated Prediction Output Feedback Control of a Class of Lipschitz Nonlinear Systems With Input Delay

This brief addresses an output feedback control design for Lipschitz nonlinear systems in the presence of input delay. A nonlinear observer is introduced to estimate the system states. A truncated predictor state feedback, which is the conventional predictor state feedback law with the distributed term dropped, is implemented with the estimated states. Lyapunov-Krasovskii functionals are constructed to establish conditions under which this observer-based truncated predictor feedback law asymptotically stabilizes the system at the origin. The effectiveness of the proposed method is demonstrated on Chua's circuit.
Measuring Security Risk of Networks Using Attack Graphs

Today’s computer systems face sophisticated attackers who combine multiple vulnerabilities to penetrate networks with devastating impact. The overall security of a network cannot be determined by simply counting the number of vulnerabilities. To accurately assess the security of networked systems, one must understand how vulnerabilities can be combined to stage an attack. We model such composition of vulnerabilities through attack graphs. By simulating incremental network penetration, and propagating attack likelihoods, we measure the overall security of a networked system. From this, we score risk mitigation options in terms of maximizing security and minimizing cost. We populate our attack graph models from live network scans and databases that have knowledge about properties such as vulnerability likelihood, impact, severity, and ease of exploitation. Our exible model can be used to quantify overall security of networked systems, and to study cost/benet tradeos for analyzing return on security investment.
Automated Eye-Movement Protocol Analysis

This article describes and evaluates a class of methods for performing automated analysis of eye-movement protocols. Although eye movements have become increasingly popular as a tool for investigating user behavior, they can be extremely difficult and tedious to analyze. In this article we propose an approach to automating eye-movement protocol analysis by means of tracing-relating observed eye movements to the sequential predictions of a process model. We present three tracing methods that provide fast and robust analysis and alleviate the equipment noise and individual variability prevalent in typical eye-movement protocols. We also describe three applications of the tracing methods that demonstrate how the methods facilitate the use of eye movements in the study of user behavior and the inference of user intentions.
Nitric Oxide Plays a Key Role in Myelination in the Developing Brain

Inhaled nitric oxide (iNO) is one of the most promising therapies used in neonates, but there is little information available about its effect on the developing brain. We explored the effects of both iNO and endogenous NO on developing white matter in rodents. Rat or mouse pups and their mothers were placed in a chamber containing 5 to 20 ppm of NO for 7 days after birth. Neonatal exposure to iNO was associated with a transient increase in central nervous system myelination in rats and C57BL/6 mice without any deleterious effects at low doses (5 ppm) or behavioral consequences in adulthood. Exposure to iNO was associated with a proliferative effect on immature oligodendrocytes and a subsequent promaturational effect. The role of endogenous NO in myelination was investigated in animals treated with the nitric oxides synthase inhibitor N(G)-nitro-L-arginine methyl ester (L-NAME) in the neonatal period; this led to protracted myelination defects and subsequent behavioral deficits in adulthood. These effects were reversed by rescuing L-NAME-treated animals with iNO. Thus, we demonstrate considerable effect of both exogenous and endogenous NO on myelination in rodents. These data point to potential new avenues for neuroprotection in human perinatal brain damage.
A Survey and Classification of Storage Deduplication Systems

The automatic elimination of duplicate data in a storage system, commonly known as deduplication, is increasingly accepted as an effective technique to reduce storage costs. Thus, it has been applied to different storage types, including archives and backups, primary storage, within solid-state drives, and even to random access memory. Although the general approach to deduplication is shared by all storage types, each poses specific challenges and leads to different trade-offs and solutions. This diversity is often misunderstood, thus underestimating the relevance of new research and development. The first contribution of this article is a classification of deduplication systems according to six criteria that correspond to key design decisions: granularity, locality, timing, indexing, technique, and scope. This classification identifies and describes the different approaches used for each of them. As a second contribution, we describe which combinations of these design decisions have been proposed and found more useful for challenges in each storage type. Finally, outstanding research challenges and unexplored design points are identified and discussed.
Automated web based system for bone age assessment using historam technique

Bone age assessment (BAA) is often used to evaluate the growth status of children as part of the detection of hormonal problems and genetic disorders. The determination of skeletal maturity is done based on a radiological examination of the hand-wrist skeletal area.This paper introduces a novel approach for BAA that utilizes a histogram based comparison technique. This approach is executed as a web based system that uses an image repository and similarity measures based on content-based image retrieval. This study aims to overcome to the limitations of traditional methods utilized to estimate human age which were often imprecise.The system provides age prediction for hand and wrist x-ray images up till age of 18 years. The results of the system evaluation indicate this method as a reliable method for BAA with the error rates of -0.170625 years compared with BoneXpert system that have returned error rate of between ±0.46 to ±0.37 years.
The Relationship between Arousal, Personality, and Perception of Control in a Gambling Task

iii ACKNOWLEDGEMENTS I would first like to thank Heather Richardson for co-sponsoring me during my senior year. Without her sponsorship into the Masters NSB program, I would have been unable to even pursue a Masters and for that as well as her constant support, I am eternally grateful. I would also like to thank Rebecca Spencer for the use of the BIOPAC system, Rebecca Ready for training on that system, Jesse McClure for his help on the data analysis, the Cognitive second year cohort for their statistical consulting, Tina Chen for her expertise in E-Prime, Madeline Parsons for help running participants, and the UMass BDIC office and University of Massachusetts Commonwealth Honors College for providing funding. I would also like to thank my committee members, David Moorman and Paula Pietromonaco who provided immensely helpful feedback throughout my defense. I am also eternally grateful to my parents who supported me throughout my years in academia. Merci pour tout. Lastly, I would like to thank Andrew Cohen for the countless hours he was willing to put into my work. Without three years of his guidance, support, and willingness to patiently answer my questions, this would not have been possible. Thank you. The somatic marker hypothesis posits that physiological arousal is partially responsible for decision-making behavior. Arousal, measured by skin conductance responses (SCR), increases before deck choice in the Iowa Gambling Task (IGT). These markers co-vary with performance-pathological gamblers lack these markers and perform poorly. Personality also modulates IGT behavior – high-novelty-seeking (NS) individuals tend to perform worse. In the IGT, participants decide which deck to select, creating a potential confound between personality, performance, and arousal. For example, high-NS individuals select the bad decks more often, potentially causing habituation and a muted SCR. The first goal of this research was to replicate the finding that personality modulates arousal in a task which removes these confounds. Participants selected a series of cards from two decks. Each card was either a win or loss. Real money was used. To remove the potential confound between choice and outcome, all participants experienced the same outcomes regardless of choice. SCR was measured during the task. Personality characteristics previously shown to modulate gambling behavior, such as sensation seeking (SS), were measured. Arousal may also occur during other phases of gambling, for example, before or after the outcome is revealed. To date, few studies have examined the relationship between arousal …
Current evidence on diagnostic accuracy of commercially based nucleic acid amplification tests for the diagnosis of pulmonary tuberculosis

Background: Even though commercial nucleic acid amplification tests (NAATs) have become the most frequently used molecular tests for laboratory diagnosis of pulmonary tuberculosis (TB), published studies report variable estimates of their diagnostic accuracy. We analysed the accuracy of commercial NAATs for the diagnosis of pulmonary TB in smear positive and smear negative respiratory samples using culture as a reference standard. Methods: English language studies reporting data sufficient for calculating sensitivity and specificity of commercial NAATs on smear positive and/or smear negative respiratory samples were included. Meta-regression was used to analyse associations with reference test quality, the prevalence of TB, sample and test type. Predictive values for different levels of pre-test probability were quantified using Bayes’ approach. Results: Sixty three journal articles published between 1995 and 2004 met the inclusion criteria. Pooled sensitivity and specificity were 0.96 and 0.85 among smear positive samples and 0.66 and 0.98 among smear negative samples. The number of culture media used as reference test, the inclusion of bronchial samples, and the TB prevalence were found to influence the reported accuracy. The test type had no effect on the diagnostic odds ratio but seemed to be correlated with sensitivity or specificity, probably via a threshold effect. Conclusions: Commercial NAATs can be confidently used to exclude TB in patients with smear positive samples in which environmental mycobacteria infection is suspected and to confirm TB in a proportion of smear negative cases. The methodological characteristics of primary studies have a considerable effect on the reported diagnostic accuracy.
A spoken language understanding approach using successive learners

In this paper, we describe a novel spoken language understanding approach using two successive learners. The first learner is used to identify the topic of an input utterance. With the restriction of the recognized target topic, the second learner is trained to extract the corresponding slot-value pairs. The advantage of the proposed approach is that it is mainly data-driven and requires only minimally annotated corpus for training whilst retaining the understanding robustness and deepness for spoken language. Experiments have been conducted in the context of Chinese public transportation information inquiry domain. The good performance demonstrates the viability of the proposed approach.
Perception, Attention, and Resources: A Decision-Theoretic Approach to Graphics Rendering

We describe work to control graphics rendering under limited computational resources by taking a decision-theoretic perspective on perceptual costs and computational savings of approximations. The work extends earlier work on the control of rendering by introducing methods and models for computing the expected cost associated with degradations of scene components. The expected cost is computed by considering the perceptual cost of degradations and a probability distribution over the attentional focus of viewers. We review the critical literature describing findings on visual search and attention, discuss the implications of the findings, and introduce models of expected perceptual cost. Finally, we discuss policies that harness information about the expected cost of scene components.
Efficient Two-Dimensional Filters for Doubly-Dispersive Channel Estimation in Time-Frequency Signal Processing

We consider minimum mean squared error (MSE) channel estimators operating on the basis of time-frequency signal observations comprising mixtures of known pilot and unknown data signals. These estimators are useful for a general class of receivers resorting to a time-frequency signal representation of the received signal - obtained by, e.g., a filter bank - which have recently been considered in the context of reconfigurable radio. Taking advantage of the Kronecker product properties we derive two-dimensional filter formulations for doubly-dispersive channel estimation, which afford implementations with moderate complexities. Rank reduction and the use of fast Fourier transform methods are shown to offer further complexity reductions. The different estimator variants are compared in terms of MSE performance and complexity.
Community discovery algorithm based on potential energy in complex network

In recent years, our understanding of complex networks has improved. Community structure as a common characteristic of complex networks has become an important direction in the study of complex networks. Meanwhile, people put forward many community detection algorithms. To original Largest Fitness Measure algorithm, the selection of seed node is random, community division needs to be improved, and it is difficult to achieve its end condition. Based on above problems, we propose a kind of Weight Largest Fitness Measure algorithm. According to the thought of potential energy, the new algorithm optimizes and handles initial node, simplify node fitness function and expand community according to potential queue. Finally, through two groups of experimental validate the performance of the algorithm. The experimental results show that, compared with Largest Fitness Measure algorithm, the new algorithm has higher accuracy and shorter run time.
Clinical and Genetic Investigation of a Multi-generational Chinese Family Afflicted with Von Hippel-Lindau Disease

Background: Von Hippel-Lindau (VHL) disease is a hereditary tumor disorder caused by mutations or deletions of the VHL gene. Few studies have documented the clinical phenotype and genetic basis of the occurrence of VHL disease in China. This study armed to present clinical and genetic analyses of VHL within a five-generation VHL family from Northwestern China, and summarize the VHL mutations and clinical characteristics of Chinese families with VHL according to previous studies. Methods: An epidemiological investigation of family members was done to collect the general information. A retrospective study of clinical VHL cases was launched to collect the relative clinical data. Genetic linkage and haplotype analysis were used to make sure the linkage of VHL to disease in this family. The VHL gene screening was performed by directly analyzing DNA sequence output. At last, we summarized the VHL gene mutation in China by the literature review. Results: A five-generation North-western Chinese family afflicted with VHL disease was traced in this research. The family consisted of 38 living family members, of whom nine were affected. The individuals afflicted with VHL exhibited multi-organ tumors that included pheochromocytomas (8), central nervous system hemangioblastomas (3), pancreatic endocrine tumors (2), pancreatic cysts (3), renal cysts (4), and paragangliomas (2). A linkage analysis resulted in a high maximal LOD score of 8.26 (theta = 0.0) for the marker D3S1263, which is in the same chromosome region as VHL. Sequence analysis resulted in the identification of a functional C>T transition mutation (c. 499 C>T, p.R167W) located in exon 3 of the 167th codon of VHL. All affected individuals shared this mutation, whereas the unaffected family members and an additional 100 unrelated healthy individuals did not. To date, 49 mutations have been associated with this disease in Chinese populations. The most frequent VHL mutations in China are p.S65 W, p.N78 S, p.R161Q and p.R167 W. Conclusions: The results supported the notion that the genomic sequence that corresponds to the 167th residue of VHL is a mutational hotspot. Further research is needed to clarify the molecular role of VHL in the development of organ-specific tumors.
Electron Back Scattering in CNTFETs

A new nonballistic analytical model for the intrinsic channel region of MOSFET-like single-walled carbon-nanotube FETs (CNTFETs) with ohmic contacts has been developed which overcomes the limitations of existing models and extends their applicability toward high bias voltages needed for analog applications. The new model comprises an improved description of the electron-phonon scattering mechanism, considering the accumulation of electrons at the bottom of conduction subband due to back scattering by optical phonons. The model has been justified by a Boltzmann transport equation solver. The simulation results are found to be in agreement with the experimental data for highly doped CNTFETs.