Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy-Efficient Resource Allocation for Heterogeneous Cognitive Radio Networks with Femtocells

Both cognitive radio and femtocell have been considered as promising techniques in wireless networks. However, most of previous works are focused on spectrum sharing and interference avoidance, and the energy efficiency aspect is largely ignored. In this paper, we study the energy efficiency aspect of spectrum sharing and power allocation in heterogeneous cognitive radio networks with femtocells. To fully exploit the cognitive capability, we consider a wireless network architecture in which both the macrocell and the femtocell have the cognitive capability. We formulate the energy-efficient resource allocation problem in heterogeneous cognitive radio networks with femtocells as a Stackelberg game. A gradient based iteration algorithm is proposed to obtain the Stackelberg equilibrium solution to the energy-efficient resource allocation problem. Simulation results are presented to demonstrate the Stackelberg equilibrium is obtained by the proposed iteration algorithm and energy efficiency can be improved significantly in the proposed scheme.
Artwork Identification method and database construction

For identification an image, there are some researches published. Through the experiments, we have learned that there are some limitations in achieving a high matching rate. In this paper, we propose an effective data construction for identification artworks to improve the identification rate and reliability. Some image identification methods based on feature points have the limitations like large-scale size conversion, geometric distortion, camera angle distortion and so on. For overcoming the limitation, we construct the image database with several images for an artwork. We attach labels to image. The images are made up of the original image file of artwork, size conversion of various scales, various kinds of geometrical distortion, and camera shots at multiple angles. To eliminate unnecessary feature inclusion, we remove the boundary of image that included information of non-artwork. We matching the feature and get the ranking with these database. Through analyzing the ranking, we can get the result of artwork identification finally. The experiments shows the better identification rates, especially in the high-scale attacks.
Subclinical Atherosclerosis Among Young and Middle-Aged Adults Using Carotid Intima-Media Thickness Measurements

Objectives The presence of atherosclerotic plaque in the carotid arteries is a strong predictor of cardiovascular disease (CVD). Research and data on CVD risk have been derived primarily from individuals aged 55 years or older, and assessment of CVD risk among young and middle-aged adults seldom has been studied. The use of ultrasonography to measure carotid intima-media thickness (IMT) and carotid plaque appears to have utility to detect subclinical atherosclerosis in asymptomatic adults. This study evaluated the presence of carotid plaque using ultrasonography among healthy young and middle-aged adults. Methods Participants were men and women recruited in Miami, Florida, and were 18 to 50 years old with no history of CVD. Participants underwent a general physical examination and carotid artery ultrasonography to evaluate carotid IMT and carotid plaque. Results From a total of 173 participants with a mean age of 34 years (standard deviation 8.9), 21.0% (95% confidence interval [CI] 15.0–27.2) were identified as having carotid plaque. IMT values ranged from 0.49 to 1.03 mm, with a mean value of 0.70 mm (standard deviation 0.09). In multivariable logistic regression older age (adjusted odds ratio [AOR] 1.08, 95% CI 1.01–1.16, P = 0.024) and cigarette smoking (AOR 2.67, 95% CI 1.02–7.00, P = 0.045) were associated with plaque, after controlling for IMT (AOR 2.55, 95% CI 1.40–4.65, P = 0.002). Conclusions Traditional CVD risk factors such as those evaluated in this study may fail to provide adequate predictive value of carotid atherosclerosis in younger populations with no history of CVD, because the majority of traditional risk factors identified in previous research were not associated with carotid plaque in this young sample. Further research assessing nontraditional risk factors among asymptomatic individuals is required, and the evaluation of IMT as an intervention tool to detect CVD risk in these asymptomatic populations is warranted.
Test-case generator for nonlinear continuous parameter optimization techniques

The experimental results reported in many papers suggest that making an appropriate a priori choice of an evolutionary method for a nonlinear parameter optimization problem remains an open question. It seems that the most promising approach at this stage of research is experimental, involving the design of a scalable test suite of constrained optimization problems, in which many features could be tuned easily. It would then be possible to evaluate the merits and drawbacks of the available methods, as well as to test new methods efficiently. In this paper, we propose such a test-case generator for constrained parameter optimization techniques. This generator is capable of creating various test problems with different characteristics including: 1) problems with different relative sizes of the feasible region in the search space; 2) problems with different numbers and types of constraints; 3) problems with convex or nonconvex evaluation functions, possibly with multiple optima; and 4) problems with highly nonconvex constraints consisting of (possibly) disjoint regions. Such a test-case generator is very useful for analyzing and comparing different constraint-handling techniques.
Belief in free will affects causal attributions when judging others’ behavior

Significance The question whether free will exists or not has been a matter of debate in philosophy for centuries. Recently, researchers claimed that free will is nothing more than a myth. Although the validity of this claim is debatable, it attracted much attention in the general public. This raises the crucial question whether it matters if people believe in free will or not. In six studies, we tested whether believing in free will is related to the correspondence bias—that is, people’s automatic tendency to overestimate the influence of internal as compared to external factors when interpreting others’ behavior. Overall, we demonstrate that believing in free will increases the correspondence bias and predicts prescribed punishment and reward behavior. Free will is a cornerstone of our society, and psychological research demonstrates that questioning its existence impacts social behavior. In six studies, we tested whether believing in free will is related to the correspondence bias, which reflects people’s automatic tendency to overestimate the influence of internal as compared to external factors when interpreting others’ behavior. All studies demonstrate a positive relationship between the strength of the belief in free will and the correspondence bias. Moreover, in two experimental studies, we showed that weakening participants’ belief in free will leads to a reduction of the correspondence bias. Finally, the last study demonstrates that believing in free will predicts prescribed punishment and reward behavior, and that this relation is mediated by the correspondence bias. Overall, these studies show that believing in free will impacts fundamental social-cognitive processes that are involved in the understanding of others’ behavior.
Applications of dynamic high pressure micro-fluidization technology in maize pollen polysaccharides extraction

The effects of dynamic high pressure micro-fluidization(DHPM) treatment on maize pollen wall-breaking rate and yield of pollen polysaccharides were studied in this paper.The optimum conditions of micro-fluidization homogenizing wall-breaking and polysaccharides extraction were obtained by single factor tests and orthogonal experiment.The wall - breaking and extraction conditions were as follows:homogenization pressure 120MPa,homogenizing one time,ratio of solid-liquid 1:20,extraction temperature 70℃for 2.5h,extracting two times.The yield of maize pollen polysaccharides was 7.545%under the optimum conditions.Compared with dry comminution wall-breaking extraction,the polysaccharides yield of micro-fluidization wall-breaking extraction was higher and the wall-breaking effect was more remarkable.
Exacerbation risk and characterisation of the UK’s asthma population from infants to old age

Background Few studies have examined the characteristics of a general asthma population; most have focused on more severe patients or severe exacerbations. Methods This population-based cohort study, from April 2007 to September 2015, used linked primary and secondary care electronic healthcare records (Clinical Practice Research Datalink, Hospital Episode Statistics). Characteristics of four age cohorts, ‘Under 5s’, ‘5 to 17s’, ‘18 to 54s’, ‘55+’, were described. Exacerbation risk factors, including asthma severity (measured by the British Thoracic Society (BTS) stepwise approach), were assessed using Poisson regression. Results 424 326 patients with current asthma were eligible (n, median follow-up: ‘Under 5s’=17 320, 1 year; ‘5 to 17s’=82 707, 3.3 years; ‘18 to 54s’=210 724, 4 years; ‘55+’=113 575, 5.1 years). Over 60% of the total study population had mild asthma (BTS steps 1/2). There were differences between the cohort’s characteristics, including by gender, disease severity and exacerbation pattern. The rate of exacerbations was highest in the oldest cohort and lowest in the ‘5 to 17s’ cohort (rate per 10 person-years (95% CI), ‘Under 5s’=4.27 (4.18 to 4.38), ‘5 to 17s’=1.48 (1.47 to 1.50), ‘18 to 54s’=3.22 (3.21 to 3.24), ‘55+’=9.40 (9.37 to 9.42)). In all cohorts, exacerbation rates increased with increasing asthma severity, after adjusting for confounders including gender, socioeconomic status, smoking, body mass index, atopy, rhinitis, gastro-oesophageal reflux, anxiety, depression and COPD. Conclusion The majority of UK patients with asthma had mild asthma and did not experience an exacerbation during follow-up. Patients aged ≥55 years had the lowest proportion with mild asthma and highest rate of exacerbations; the opposite was found in patients aged between 5 and 18 years.
Power dependence on the nonlinear interaction enhancement in a coherently excited microcavity

The enhanced nonlinear interaction in a silicon microcavity under coherent excitation is studied under different conditions. By controlling the pulse frequency drift, we guarantee, at every instant, the coincidence with the frequency resonance of the cavity that in the nonlinear regime suffers from a blue shift in time. This limiting shift effect is caused by the free carriers generated by the strong silicon two-photon absorption. Owing to the linear time-frequency relation of the pulse, the coupling efficiency to the drifted resonance can be maintained, further increasing the blue-shift. We study the input power effect after using different pulse durations.
Robust Low-Dose CT Sinogram Preprocessing via Exploiting Noise-Generating Mechanism

Computed tomography (CT) image recovery from low-mAs acquisitions without adequate treatment is always severely degraded due to a number of physical factors. In this paper, we formulate the low-dose CT sinogram preprocessing as a standard maximum a posteriori (MAP) estimation, which takes full consideration of the statistical properties of the two intrinsic noise sources in low-dose CT, i.e., the X-ray photon statistics and the electronic noise background. In addition, instead of using a general image prior as found in the traditional sinogram recovery models, we design a new prior formulation to more rationally encode the piecewise-linear configurations underlying a sinogram than previously used ones, like the TV prior term. As compared with the previous methods, especially the MAP-based ones, both the likelihood/loss and prior/regularization terms in the proposed model are ameliorated in a more accurate manner and better comply with the statistical essence of the generation mechanism of a practical sinogram. We further construct an efficient alternating direction method of multipliers algorithm to solve the proposed MAP framework. Experiments on simulated and real low-dose CT data demonstrate the superiority of the proposed method according to both visual inspection and comprehensive quantitative performance evaluation.
Differential Privacy for Growing Databases

We study the design of differentially private algorithms for adaptive analysis of dynamically growing databases, where a database accumulates new data entries while the analysis is ongoing. We provide a collection of tools for machine learning and other types of data analysis that guarantee differential privacy and accuracy as the underlying databases grow arbitrarily large. We give both a general technique and a specific algorithm for adaptive analysis of dynamically growing databases. Our general technique is illustrated by two algorithms that schedule black box access to some algorithm that operates on a fixed database to generically transform private and accurate algorithms for static databases into private and accurate algorithms for dynamically growing databases. These results show that almost any private and accurate algorithm can be rerun at appropriate points of data growth with minimal loss of accuracy, even when data growth is unbounded. Our specific algorithm directly adapts the private multiplicative weights algorithm to the dynamic setting, maintaining the accuracy guarantee of the static setting through unbounded data growth. Along the way, we develop extensions of several other differentially private algorithms to the dynamic setting, which may be of independent interest for future work on the design of differentially private algorithms for growing databases.
A Fundamental Study on the Correlationship between Hydration Heat and Autogenous Shrinkage of High Strength Concrete at an Early Age

In this study, to analyze the correlation between hydration heat and autogenous shrinkage of high strength concrete at an early age, hydration heating velocity and autogenous shrinking velocity as quantitative coefficients which represent the main properties of hydration heat and autogenous shrinkage were proposed. Two coefficients were calculated by statistical analysis and were equal with the regression coefficient. The complemented semi-adiabatic temperature rise test as test method to evaluate the hydration heat and autogenous shrinkage of concrete were proposed. In results of proposed test and analysis method, it was possible that early age properties of hydration heat and autogenous shrinkage of concrete were expressed numerically, and autogenous shrinkage was represented by equation with coefficients of hydration heat.
Minimax lower bounds for function estimation on graphs.

We study minimax lower bounds for function estimation problems on large graph when the target function is smoothly varying over the graph. We derive minimax rates in the context of regression and classification problems on graphs that satisfy an asymptotic shape assumption and with a smoothness condition on the target function, both formulated in terms of the graph Laplacian.
Oligodendrocyte lineage and the motor neuron connection

One of the more surprising recent discoveries in glial biology has been that oligodendrocytes (OLs) originate from very restricted regions of the embryonic neural tube. This was surprising because myelinating OLs are widespread in the mature central nervous system, so there was no reason to suspect that their precursors should be restricted. What we now know about early OL development suggests that they might have as much (or more) in common with ventral neurons—specifically motor neurons (MNs)—as with other types of glia. This has implications for the way we think about glial development, function, and evolution. In this article we review the evidence for a shared MN‐OL lineage and debate whether this is the only lineage that generates OLs. We decide in favour of a single embryonic lineage with regional variations along the anterior‐posterior neuraxis. GLIA 29:136–142, 2000. © 2000 Wiley‐Liss, Inc.
Concept Drift Mining of Fundamental Variables in China Stock Market

We adopt the classical Fama and French (1992) [E.F. Fama, K.R. French, The Cross-Section of Expected Stock Returns, The Journal of Finance, 47 (1992) 427 - 465. ] approach to investigate the effect of Beta, size, leverage, book value to market value (B/P), and earnings to price (E/P) ratio on the average monthly returns in the China Stock Market (CSM) from July 1998 to June 2011. The phenomenon of concept drift was found in this research. Our results indicate that the B/P has a significant negative correlation with the monthly average returns during this period, in contrast to the positive correlation found by a previous study by Wang and Di Iorio (2007) [Y. Wang, A. Di Iorio, The cross section of expected stock returns in the Chinese A-share market, Global Finance Journal, 17 (2007) 335 - 349. ] that covered from July 1996 to June 2002. Meanwhile the small-firm effect remains significant. Thus, while the behavioral or institutional factors may account for the counter-intuitive finding of the effect of value in the transitional economy, the relationship between fundamental characteristics and stock returns is more complex in China and warrants more rigorous investigation. Further, we suggest that autonomic and cloud computing system has a number of potential applications in stock market concept drift mining.
Sparse Reduced Rank Regression with Nonconvex Regularization

In this paper, the estimation problem for sparse reduced rank regression (SRRR) model is considered. The SRRR model is widely used for dimension reduction and variable selection with applications in signal processing, econometrics, etc. The problem is formulated to minimize the least squares loss with a sparsity-inducing penalty considering an orthogonality constraint. Convex sparsity-inducing functions have been used for SRRR in literature. In this work, a nonconvex function is proposed for better sparsity inducing. An efficient algorithm is developed based on the alternating minimization (or projection) method to solve the nonconvex optimization problem. Numerical simulations show that the proposed algorithm is much more efficient compared to the benchmarks and the nonconvex function can result in a better estimation accuracy.
Robust image/video super-resolution display

This paper describes a new method to reconstruct high-resolution video sequences from several observed low-resolution images based on an adaptive Mumford-shah model which is extended by using nonlocal information and low-rank representation. In our regularization framework, joint image restoration and motion estimation are first implemented and then detailed information can be recovered by incorporating new model as a prior term.
Gene Therapy for Parkinson's Disease

Current pharmacological and surgical treatments for Parkinson's disease offer symptomatic improvements to those suffering from this incurable degenerative neurological disorder, but none of these has convincingly shown effects on disease progression. Novel approaches based on gene therapy have several potential advantages over conventional treatment modalities. These could be used to provide more consistent dopamine supplementation, potentially providing superior symptomatic relief with fewer side effects. More radically, gene therapy could be used to correct the imbalances in basal ganglia circuitry associated with the symptoms of Parkinson's disease, or to preserve or restore dopaminergic neurons lost during the disease process itself. The latter neuroprotective approach is the most exciting, as it could theoretically be disease modifying rather than simply symptom alleviating. Gene therapy agents using these approaches are currently making the transition from the laboratory to the bedside. This paper summarises the theoretical approaches to gene therapy for Parkinson's disease and the findings of clinical trials in this rapidly changing field.
Multiscale Superpixels and Supervoxels Based on Hierarchical Edge-Weighted Centroidal Voronoi Tessellation

Superpixels and supervoxels play an important role in many computer vision applications, such as image segmentation, object recognition, and video analysis. In this paper, we propose a new hierarchical edge-weighted centroidal Voronoi tessellation (HEWCVT) method for generating superpixels/supervoxels in multiple scales. In this method, we model the problem as a multilevel clustering process: superpixels/supervoxels in one level are clustered to obtain larger size superpixels/supervoxels in the next level. In the finest scale, the initial clustering is directly conducted on pixels/voxels. The clustering energy involves both color similarities and boundary smoothness of superpixels/supervoxels. The resulting superpixels/supervoxels can be easily represented by a hierarchical tree which describes the nesting relation of superpixels/supervoxels across different scales. We first investigate the performance of obtained superpixels/supervoxels under different parameter settings, then we evaluate and compare the proposed method with several state-of-the-art superpixel/supervoxel methods on standard image and video data sets. Both quantitative and qualitative results show that the proposed HEWCVT method achieves superior or comparable performances with other methods.
Integration of planning and execution in force controlled compliant motion

This paper presents the compliant task generator: a new approach for the automatic conversion of a geometric path generated by a compliant path planner to a force based task specification for a compliant robot controller. Based on the geometric model of a moving object and its environment, a compliant path planner generates a set of six-dimensional positions x/sub 1.m/ and their corresponding contact formations CF/sub 1.n/. The compliant force controller, which executes a planned path under force feedback using the hybrid control paradigm, expects a desired force w/sub d/, velocity t/sub d/ and position x/sub d/ at each time-step, together with their force and velocity controlled subspaces W and T. To specify these controller primitives, we add information about the desired dynamic interaction between the moving object and its environment, in the form of the desired kinetic energy E/sub kin/ of the moving object and the potential energy E/sub pot/ in the contacts with the environment, together with the inertia and stiffness matrix M and S. We fully automated the conversion process of the compliant planner output together with the added information about the dynamic interaction, to a force based task specification. This eliminates the requirement of human intervention between the planning and execution phase. The presented approach applies to all compliant motions between polyhedral objects, and is verified in a real world experiment.