Miracle-dz/UniFAR-FTUs huggingface dataset:
A method of detecting driver drowsiness state based on multi-features of face

A real-time method for monitoring driver drowsiness is presented in this paper to prevent potential vehicle accidents. Instead of based on the eye states alone in previous studies, we combined it with the state of driver's mouth to judge whether the driver fatigues, thus solving the traditional challenge of wearing glasses. AdaBoost algorithm is used to detect face region due to its high correct rate. Then the exact positions of driver's eyes and mouth are located according to their geometric features respectively. The method of PATECP (Percentage And Time that Eyelids Cover the Pupils) and PATMIO (Percentage And Time that Mouth Is Open) as well as the new judge rule is used to estimate whether the driver is drowsy. The tests with actual driving video shows that our approach based on eye and mouth features makes the conditions of recognizing the driver's drowsy state wider accurate.
Title Towards opportunistic fair scheduling in wireless networks

Opportunistic transmission scheduling schemes improve system capacity by taking advantage of independent time varying channels in wireless networks. In the design of such scheduling schemes, the fairness criterion plays an important role in the tradeoff of total system capacity and the achievable throughput of individual users. To meet different fairness demands with a unified opportunistic scheduling scheme, in this paper, we have extended the well known opportunistic scheduling scheme PFS into αPFS, which satisfies arbitrary fairness demands, varying from proportional fairness to maxmin fairness, through adjusting the parameter α. To further improve the achievable diversity gains of αPFS, we extend the αPFS scheme into an αPFS-P scheme. Performances of αPFS and αPFS-P are studied and compared. As demonstrated in the simulation results, both αPFS and αPFS-P can achieve adjustable fairness criteria, varying from proportional fairness to max-min fairness. Compared with αPFS, αPFS-P achieves higher diversity gains with degraded short term performance, which is still better than the performance of PFS.
A limit relation for entropy and channel capacity per unit cost

In a thermodynamic model, Diosi et al. [Int. J. Quantum Inf. 4, 99–104 (2006)] arrived at a conjecture stating that certain differences of von Neumann entropies converge to relative entropy as system size goes to infinity. The conjecture is proven in this paper for density matrices. The analytic proof uses the quantum law of large numbers and the inequality between the Belavkin-Staszewski and Umegaki relative entropies. Moreover, the concept of channel capacity per unit cost is introduced for classical-quantum channels. For channels with binary input alphabet, this capacity is shown to equal the relative entropy. The result provides a second proof of the conjecture and a new interpretation. Both approaches lead to generalizations of the conjecture.
Comparison of 3 Diffusion Models to Track the Hand Motor Fibers within the Corticospinal Tract Using Functional, Anatomical and Diffusion MRI

In this paper, we propose to compare three diffusion models to track the portion of the corticospinal tract dedicated to the hand motor function (called hand motor fibers hereafter), using diffusion, functional and anatomical MRI. The clinical diffusion data have few gradient directions and low b-values. In this context, we show that a newly introduced model, called diffusion directions imaging (DDI) outperforms both the DTI and the ODF models. This new model allows to capture several diffusion directions within a voxel, with only a low number of parameters. Two important results are that i) the DDI model is the only one allowing consistent tracking from the mesencephalon to the most lateral part of the cortical motor hand area, and that ii) the DDI model is the only model able to show that the number of hand motor fibers in the left hemisphere is larger than in the contralateral hemisphere for right-handed subjects; the DDI model, as the other two models, fails to find such a difference for left-handed subjects. To the best of our knowledge, this is the first time such results are reported, at least on clinical data.
Automated aperture filter design by stochastic optimization

Aperture filters are a relatively new class of image operators, where in addition to the domain constraint, imposed by windowing, the range constraint is defined, effectively condensing probability mass to improve filter output estimates. In this paper the automatic design methodology by means of stochastic optimisation is proposed, which can generate an aperture filter to suit a specific application. Usability of presented method was verified experimentally, and the results are presented in the paper.
Sentiment dispersion of individual investors in stock market

This paper aims to study the role of sentiment dispersion in stock market. We extract the investor sentiment from tweets that are specifically about opinions on stocks. Naïve Bayes is then used to assign each tweet a conditional probability representing how positive each tweet is. We did not discretize the probability so as to reduce the information loss. Sentiment dispersion is then measured by standard deviation. The resulting sentiment dispersion is then correlate with future stock returns and realized volatility. This research is able to show whether sentiment dispersion contains information about future return and volatility, which are helpful in formulating investment strategy.
Epistatic Rescue of Nkx2.5 Adult Cardiac Conduction Disease Phenotypes by Prospero-Related Homeobox Protein 1 and HDAC3

Rationale: Nkx2.5 is one of the most widely studied cardiac-specific transcription factors, conserved from flies to man, with multiple essential roles in both the developing and adult heart. Specific dominant mutations in NKX2.5 have been identified in adult congenital heart disease patients presenting with conduction system anomalies and recent genome-wide association studies implicate the NKX2.5 locus, as causative for lethal arrhythmias (“sudden cardiac death”) that occur at a frequency in the population of 1 in 1000 per annum worldwide. Haploinsufficiency for Nkx2.5 in the mouse phenocopies human conduction disease pathology yet the phenotypes, described in both mouse and man, are highly pleiotropic, implicit of unknown modifiers and/or factors acting in epistasis with Nkx2.5/NKX2.5. Objective: To identify bone fide upstream genetic modifier(s) of Nkx2.5/NKX2.5 function and to determine epistatic effects relevant to the manifestation of NKX2.5-dependent adult congenital heart disease. Methods and Results: A study of cardiac function in prospero-related homeobox protein 1 (Prox1) heterozygous mice, using pressure-volume loop and micromannometry, revealed rescue of hemodynamic parameters in Nkx2.5Cre/+; Prox1loxP/+ animals versus Nkx2.5Cre/+ controls. Anatomic studies, on a Cx40EGFP background, revealed Cre-mediated knock-down of Prox1 restored the anatomy of the atrioventricular node and His-Purkinje network both of which were severely hypoplastic in Nkx2.5Cre/+ littermates. Steady state surface electrocardiography recordings and high-speed multiphoton imaging, to assess Ca2+ handling, revealed atrioventricular conduction and excitation-contraction were also normalized by Prox1 haploinsufficiency, as was expression of conduction genes thought to act downstream of Nkx2.5. Chromatin immunoprecipitation on adult hearts, in combination with both gain and loss-of-function reporter assays in vitro, revealed that Prox1 recruits the corepressor HDAC3 to directly repress Nkx2.5 via a proximal upstream enhancer as a mechanism for regulating Nkx2.5 function in adult cardiac conduction. Conclusions: Here we identify Prox1 as a direct upstream modifier of Nkx2.5 in the maintenance of the adult conduction system and rescue of Nkx2.5 conduction disease phenotypes. This study is the first example of rescue of Nkx2.5 function and establishes a model for ensuring electrophysiological function within the adult heart alongside insight into a novel Prox1-HDAC3-Nkx2.5 signaling pathway for therapeutic targeting in conduction disease.
Recommendation and Usage in the Digital Library LANCASTER UNIVERSITY Computing Department

The movement from the physical to the digital library offers both dangers and opportunities. Alongside the greater quantity of online material goes the problem of quality assurance: how can be the information searcher be sure of the status of a document. We suggest that this be addressed by supporting recommendations and that the key feature that links these recommendations together i s that of usage. The main use of usage data within information science is currently that of a research tool in the form of transaction log analysis. In a digital library this data, together with other evaluations and recommendations, can enrich the existing information structure. Several approaches t o the integration of usage data are described together with their respective costs and benefits. The social implications of these possibilities are discussed with particular reference to the privacy of usage data. CSEG, Computing Department, Lancaster University, Lancaster, LA1 4YR, UK Tel: +44-1524-65201 Ext 93799; Fax: +44-1524-593608; E-Mail: julie@comp.lancs.ac.uk http://www.comp.lancs.ac.uk/computing/research/cseg/
Rate-Based Active Queue Management for Congestion Control Over Wired and Wireless Links

Current active queue management (AQM) and TCP are designed and tuned to work well for wired networks where packet loss is mainly due to network congestion. In wireless networks, however, communication links suffer from transmission bit errors and handoff failures. As a result, the performance of TCP flows is significantly degraded. To mitigate this problem, we propose a rate-based exponential AQM (REAQM) scheme. REAQM tries to stabilize the system and achieve low delay, low packet loss, and high link utilization regardless the dynamic of network conditions. Simulation results indicate that REAQM is capable of performing well for TCP flows over both wired and wireless links.
FGF21 Requires βklotho to Act In Vivo

FGF21 has gradually become a focal point in metabolic research given its intriguing and complex biology and relevance to drug discovery. Despite the large amount of accumulated data, there remains a dearth of understanding of FGF21 physiology at the molecular/whole organism level. The scaffold protein βklotho (KLB) has previously been demonstrated in vitro to function as a co-factor permitting FGF21 mediated FGF receptor activation. However, the requirement for KLB in the propagation of FGF21 action in living animals has yet to be evaluated. To answer this question, we tested FGF21 in mice with total body ablation of KLB (KLBKO) and found no detectable activity. Firstly, we demonstrate that the disruption of KLB entirely abrogates acute FGF21 signaling in adipose tissue. We go on to show that this signaling defect translates to the absence of FGF21 mediated metabolic improvements in DIO mice. Indeed, KLBKO mice are totally refractory to FGF21-induced normalization of glucose homeostasis, attenuation of dyslipidemia, elevation of energy expenditure and weight loss. The lack of FGF21-driven effects was further substantiated at the transcriptional level with no FGF21 target gene signature detectable in adipose tissue and liver of KLBKO animals. Taken together our data show that KLB is a vital component of the FGF21 in vivo signaling machinery and is critically required for FGF21 action at the whole organism level.
Design methodology for approximate accumulator based on statistical error model

Approximate computing technology has aroused growing interest in circuit and system design for its well-performed trade-off between output quality and performance. Numerous basic circuits and system design methodologies for approximate computing have been proposed. Considering that the existing methodologies for the evaluation of tradeoff between output quality and performance is time-consuming, this paper presents a fast design methodology for approximate accumulator based on statistical error model, in which the inexact multistage speculative adder is adopted and modeled for its advantage of compact error pattern. To validate the proposed methodology, Support Vector Machine(SVM) algorithm is analyzed and mapped to a hardware system composed of inexact and accurate computing circuits. Results show that our time for searching the optimal mapping circuits has been saved by 22.08% than functional-based simulation where the final approximate system design achieves 1.57× speedups with 8.56% accuracy degradation.
Real-time kernel based object tracking using mean shift

In this paper, we improve the real-time object tracking algorithm of Yang [1] which uses a symmetric similarity function between spatially smoothed kernel-density estimates of the model and the target distributions. This spatial smoothed process applied on the centre points of the probability density functions increases not only computational complexity but also noise sensitivity. After reducing background information and using a new simple similarity function between the model and the target distributions, the proposed algorithm successfully coped with camera motion, partial occlusions and clutter with lower computational complexity. For tracking object, the mean shift algorithm is used iteratively. The simplicity of the new similarity function leads to an efficient and robust nonparametric tracking algorithm. The mathematical results obtained about the performance of the proposed algorithm on several image sequences are represented comparatively in a tabular format.
Neural mechanisms of social decision-making in the primate amygdala

Significance Making social decisions requires evaluation of benefits and costs to self and others. Long associated with emotion and vigilance, neurons in primate amygdala also signal reward and punishment as well as information about the faces and eyes of others. Here we show that neurons in the basolateral amygdala signal the value of rewards for self and others when monkeys make social decisions. These value-mirroring neurons reflected monkeys’ tendency to make prosocial decisions on a momentary as well as long-term basis. We also found that delivering the social peptide oxytocin into basolateral amygdala enhances both prosocial tendencies and attention to the recipients of prosocial decisions. Our findings endorse the amygdala as a critical neural nexus regulating social decisions. Social decisions require evaluation of costs and benefits to oneself and others. Long associated with emotion and vigilance, the amygdala has recently been implicated in both decision-making and social behavior. The amygdala signals reward and punishment, as well as facial expressions and the gaze of others. Amygdala damage impairs social interactions, and the social neuropeptide oxytocin (OT) influences human social decisions, in part, by altering amygdala function. Here we show in monkeys playing a modified dictator game, in which one individual can donate or withhold rewards from another, that basolateral amygdala (BLA) neurons signaled social preferences both across trials and across days. BLA neurons mirrored the value of rewards delivered to self and others when monkeys were free to choose but not when the computer made choices for them. We also found that focal infusion of OT unilaterally into BLA weakly but significantly increased both the frequency of prosocial decisions and attention to recipients for context-specific prosocial decisions, endorsing the hypothesis that OT regulates social behavior, in part, via amygdala neuromodulation. Our findings demonstrate both neurophysiological and neuroendocrinological connections between primate amygdala and social decisions.
Implementing On-line Sketch-Based Change Detection on a NetFPGA Platform

Sketch-based algorithms are widely applied in various networking applications. In this paper, we present a compact implementation for on-line traffic change detection on a NetFPGA platform. The system utilizes a straight forward scheme to reveal the key of flow with tradeoff on the accuracy for hardware simplicity. It is capable of digesting traffic up to 4Gbps line rate with accuracy needed based on the available memory on-board.
Advection-dominated Accretion: From Sgr A* to other Low-luminosity AGNs

This paper reviews our current understanding of low-luminosity AGNs (LLAGNs) in the context of the advection-dominated accretion flow. The best investigated source, the supermassive black hole in our galactic center, Sgr A*, is emphasized since the physics of accretion should be the same for various LLAGNs except for their different accretion rates. The important role of jets is discussed, but this is less well established.
Image based visual servoing for an autonomous quadrotor with adaptive backstepping control (ICCAS 2011)

This paper proposes a quadrotor control scheme using image-based visual servo integrated with adaptive backstepping control. Image-based visual servo provides the reference velocities by using image-Jacobian matrix and errors of feature positions on the image plane. Adaptive backstepping control generates input signals for propellers to track the reference velocity accurately even under uncertain effects. The integrated system enables a quadrotor robot to fly to the desired place by minimizing the errors of image feature positions. The performance of the overall system is validated by numerical simulation. Also, to demonstrate the superiority of the proposed system, we compare the performance to that of image-based visual servo integrated with PI control.
Tetrahedra Based Volume

Volume Visualization techniques have advanced considerably since the rst international symposium held on this topic eight years ago. This paper brieey reviews the techniques proposed for the visualization of irregular (or scattered) volume datasets. In particular, methods which adopt simplicial de-compositions of E 3 space are considered, and this choice is justiied both in terms of modeling and visualization. Simplicial complexes are powerful and robust geometric structures, and a number of eecient visualization algorithms have been proposed. We show that simplicial cells (or simply tetrahedral cells since our target is 3D space) may be conceived as being the unifying kernel primitive for the visualization of not-regular meshes.
Analysis of Synaptic Weight Distribution in an Izhikevich Network

Izhikevich network is a relatively new neuronal network, which consists of cortical spiking model neurons with axonal conduction delays and spike-timingdependent plasticity (STDP) with hard bound adaptation. In this work, we use uniform and Gaussian distributions respectively to initialize the weights of all excitatory neurons. After the network undergoes a few minutes of STDP adaptation, we can see that the weights of all synapses in the network, for both initial weight distributions, form a bimodal distribution, and numerically the established distribution presents dynamic stability.
Different views on Digital Scholarship: separate worlds or cohesive research field?

This article presents a systematic review of the literature on Digital Scholarship, aimed at better understanding the collocation of this research area at the crossroad of several disciplines and strands of research. The authors analysed 45 articlesin order to draw a picture of research in this area. In the first phase, the articles were classified, and relevant quantitative and qualitative data were analysed. Results showed that three clear strands of research do exist: Digital Libraries, Networked Scholarship and Digital Humanities. Moreover, researchers involved in this research area tackle the problems related to technological uptake in the scholar’s profession from different points of view, and define the field in different – often complementary – ways, thus generating the perception of a research area still in need of a unifying vision. In the second phase, authors searched for evidence of the disciplinary contributions and interdisciplinary cohesion of research carried out in this area through the use of bibliometric maps. Results suggest that the area of Digital Scholarship, still in its infancy, is advancing in a rather fragmented way, shaping itself around the above-mentioned strands, each with its own research agenda. However, results from the cross-citation analysis suggest that the Networked Scholarship strand is more cohesive than the others in terms of cross-citations. (Published: 1 December 2016) Citation: Research in Learning Technology 2016, 24 : 32036 - http://dx.doi. org/10.3402/rlt.v24. 32036
3D Registration based on Normalized Mutual Information

Medical image registration is time-consuming but can be sped up employing parallel processing on the GPU. Normalized mutual information (NMI) is a well performing similarity measure for performing multi-modal registration. We present CUDA based solutions for computing NMI on the GPU and compare the results obtained by rigidly registering multi-modal data sets with a CPU based implementation. Our tests with RIRE data sets show a speed-up of factor 5 to 7 for our best
Metabolism of ciclesonide in the upper and lower airways: review of available data

Ciclesonide is a novel corticosteroid (CS) for the treatment of asthma and allergic rhinitis. After administration, the parent compound ciclesonide is converted by intracellular airway esterases to its pharmacologically active metabolite desisobutyryl-ciclesonide (des-CIC). We investigated the in vitro activation of ciclesonide and further esterification of des-CIC to (mainly) des-CIC oleate in several human target organ test systems. Human precision-cut lung slices, alveolar type II epithelial cells (A549), normal bronchial epithelial cells (NHBE), and nasal epithelial cells (HNEC) were incubated with ciclesonide. Enzymes characterization and the determination of the reversibility of fatty acid esterification was investigated in HNEC and NHBE. Ciclesonide was taken up and converted to des-CIC in all cellular test systems. Intracellular concentrations of des-CIC were maintained for up to 24 h. Formation of des-CIC oleate increased over time in HNEC, A549 cells, and lung slices. The formed des-CIC fatty acid conjugates were reconverted to des-CIC. Increasing concentrations of carboxylesterase and cholinesterase inhibitors progressively reduced the formation of metabolites. The results derived from these studies demonstrate the activation of ciclesonide to des-CIC in the upper and lower airways. The reversible formation of des-CIC fatty acid conjugates may prolong the anti-inflammatory activity of des-CIC and may allow for once-daily dosing.
Eigenvalues of Random Power Law Graphs ( DRAFT )

Many graphs arising in various information networks exhibit the “power law” behavior – the number of vertices of degree k is proportional to k−β for some positive β. We show that if β > 2.5, the largest eigenvalue of a random power law graph is almost surely (1+o(1)) √ m where m is the maximum degree. When 2 < β < 2.5, the largest eigenvalue is heavily concentrated at cm3−β for some constant c depending on β and the average degree. This result follows from a more general theorem which shows that the largest eigenvalue of a random graph with a given expected degree sequence is determined by m, the maximum degree, and d̃, the weighted average of the squares of the expected degrees. We show that λ is almost surely (1 + o(1))max{d̃,√m} provided some minor condition is satisfied. Our results have implications on the usage of spectral techniques in many areas related to pattern detection and information retrieval.