Miracle-dz/UniFAR-FTUs huggingface dataset:
Spectrum sensing for cognitive radio: A signal-processing perspective on signal-statistics exploitation

Future cognitive radios will require use of both established emitter databases and local spectrum sensing to optimize their performance. We view these techniques as ways of estimating an RF environment map (RFEM), which characterizes the position, directivity, power, and modulation type of all relevant RF emitters in a geographical region of interest. Cognitive radios will make their best decisions when they have the best RFEM information available. Good RFEM estimates are facilitated by spectrum-sensing algorithms that exploit the complex statistics of modern communication signals rather than relying on energy detection. We illustrate some of the ways that such statistics can be exploited using collected modern communications signals.
Optimal Bartlett Detector Based SPRT for Spectrum Sensing in Multi-antenna Cognitive Radio Systems

This letter presents the optimal Bartlett detector based sequential probability ratio test (SPRT) for spectrum sensing in multi-antenna array cognitive radio networks. The optimal Wald test based sequential Bartlett spectral detector (S-BSD) is derived for a single/multiple primary user scenario, considering a fading wireless channel. Further, this is also extended to a scenario with multiple-input multiple-output (MIMO) wireless systems. Closed form expressions are derived for the average number of blocks required for the sequential detector in terms of the desired probability of false alarm and mis-detection. The S-BSD framework is also subsequently extended to an AWGN channel scenario. Simulation results are presented to illustrate the performance of the proposed detection schemes and verify the derived analytical results. The proposed S-BSD scheme is seen to significantly reduce the average number of symbols/blocks required to achieve the desired detection performance in comparison to the fixed block size BSD (F-BSD).
Code Growth Is Not Caused by Introns

Genetic programming trees have a strong tendency to grow rapidly and relatively independent of fitness, a serious flaw which has received considerable attention in the genetic programming literature. Much of this literature has implicated introns, subtree structures with no effect on the an individual’s fitness assessment. The propagation of inviable code, a certain kind of intron, has been especially linked to tree growth. However this paper presents evidence which shows that denying inviable code the opportunity to propagate actually increases tree growth. The paper argues that rather than causing tree growth, a rise in inviable code is in fact an expected result of tree growth. Lastly, this paper proposes a more general theory of growth for which introns are merely a symptom.
Systemic Administration of a Nerve Growth Factor Conjugate Reverses Age-Related Cognitive Dysfunction and Prevents Cholinergic Neuron Atrophy

Intraventricular administration of nerve growth factor (NGF) in rats has been shown to reduce age-related atrophy of central cholinergic neurons and the accompanying memory impairment. Intraventricular administration of NGF is necessary because NGF will not cross the blood–brain barrier (BBB). Here we have used a novel carrier system, consisting of NGF covalently linked to an anti-transferrin receptor antibody (OX-26), to transport biologically active NGF across the BBB. In our experiment, aged (24 months old) Fischer 344 rats received intravenous injections of the OX-26-NGF conjugate or a control solution (a mixture of unconjugated OX-26 and NGF) twice weekly for 6 weeks. The OX-26-NGF injections resulted in a significant improvement in spatial learning in previously impaired rats but disrupted the learning ability of previously unimpaired rats. Neuroanatomical analyses showed that OX-26-NGF conjugate treatment resulted in a significant increase in cholinergic cell size in the medial septal region of rats initially impaired in spatial learning. These results indicate the potential use of the transferrin receptor antibody delivery system for treatment of CNS disorders with neurotrophic proteins.
Measurement of auditory hemodynamic response function due to different temporal patterns of imaging acoustic noise using functional magnetic resonance imaging

Imaging acoustic noise (IAN) is a confounding factor that undermines the usefulness of functional magnetic resonance imaging (fMRI), especially in auditory related experiments. This paper presents the methods and results of measuring auditory hemodynamic responses (HDR) due to different temporal patterns of IAN using fMRI. Six different temporal patterns of IAN corresponding to acoustic noise generated while using different numbers of imaging slices and effective repetition times (TR) were used as stimuli in the current study. Hemodynamic responses were measured using a stroboscopic event related paradigm with extra long TRs to minimize the effects due to previous IAN segments. The shape of the HDR and the extent of activation due to each of the above stimuli are reported here and are in agreement with those reported in previous studies. In addition to the responses due to IAN patterns reported in previous studies, responses to several new temporal patterns are also reported here. The results of this study will be used in developing a model-based correction algorithm to account for IAN in auditory fMRI.
Do We Know the First Impressions We Make? Evidence for Idiographic Meta-Accuracy and Calibration of First Impressions

Can we trust our beliefs about the first impressions we make? The current article addresses this question by assessing “idiographic” meta-accuracy, or people’s ability to detect how another person views their characteristic pattern of traits, and people’s awareness of their level of meta-accuracy. Results from two samples suggest that people do achieve idiographic meta-accuracy (i.e., they know which traits a new acquaintance perceives as particularly characteristic of them) and that people’s beliefs about the first impression they make are well calibrated (i.e., the people who are relatively more confident in the accuracy of their metaperceptions are in fact more accurate). Implications of idiographic meta-accuracy and the calibration of meta-accuracy are discussed, as are the ways in which future research can improve our understanding of the process of metaperception formation and the interpersonal consequences of meta-accuracy.
Packet flow histograms to improve firewall efficiency

This paper presents a novel mechanism based on the histograms of packet filtering, which are able to effectively monitor firewall performance in real-time and to predict the patterns of packet filtering in terms of rules order and rule-fields order. Furthermore, the mechanism becomes even more significant when firewall is heavily loaded with burst traffic. A comparison of the proposed approach and the other conventional approaches, including static rule order approach and dynamic rule order approach is presented.
Long-term trends of mono-carboxylic acids in Antarctica: comparison of changes in sources and transport processes at the two EPICA deep drilling sites

Abstract We present here the first profiles of acetate and formate concentrations in Antarctic ice for time periods that include the great climatic changes of the past. Data are from two Antarctic deep ice cores recovered on the central East Antarctic Plateau (EDC) and in the Dronning Maud Land (EDML) facing the Atlantic Ocean (European EPICA Project). Except the sporadic arrival of diluted continental plumes during glacial extrema, the main source of acetate deposited over the EDC does not seem to have changed significantly over the past 300 kyr and is related to marine biogenic activity. A more detailed study of the past 55 kyr leads to the conclusion that acetate reaching the EDML during a large part of the last glacial maximum was emitted by the Patagonian continental biomass and was uptaken along with nitric acid at the surface of mineral dust. Changes in formate concentrations are characterised by less scattered and lower values at both sites during glacial periods. We propose that the present marine source of formic acid (Legrand et al., 2004) drastically decreased but did not completely vanish under cold climate conditions, whereas the share of methane oxidation in formic acid production became prominent.
A METHOD ON MODELING AND VISUALIZATION OF 3 D OBJECT

Three-dimensional (3D) digital modeling of object through optical scanners has been demonstrated in recent years with results of exceptional interest. However, the routine application of 3D modeling and visualization still requires the systematic investigation of a number of technical problems. In this paper, a 3D modeling and visualization techniques is proposed. Using a 3D shape acquisition system we introduced and this modeling method, users can reconstruct accurate models in appropriate date amount. In this paper, triangulated irregular network (TIN) model is utilized and taken as basis in modelling of 3D object, making use of the polygonal structure and vertex coordinates for the visualization of 3D models. In this paper, TIN mesh simplification algorithm, using unified stencil and based on multi-resolution adjustment, is also proposed to utilize data amount adjustable 3D modeling and reduce the difference between low and high resolution models so that model resolution and transmitted data amount can be regulated according to visitor’s requirement. Finally, some experimental results are illustrated and further analyses are discussed. The work described in this paper was fully supported by the National Natural Science Foundation of China (Project No.: 40301040)
Research on knowledge-sharing mechanism in enterprise group

In the era of knowledge economy, knowledge becomes not only the primary factor that leads enterprises to success, but also the motivation that enterprises carry out innovation. Effective knowledge-sharing mechanism can help the member in an enterprise group learn from itself and others so as to achieve an ideal goal of the organization. Basing on exploring the knowledge-sharing process in the enterprise groups and analyzing the problems existing in knowledge-sharing mechanism, this paper puts forward suggestions for enterprise groups to build up knowledge-sharing mechanism.
Principal Component Analysis in Linear Discriminant Analysis Space for Face Recognition

Principal component analysis (PCA) is an effective statistical technique for face recognition because it can reduce the dimensions of a given unlabeled high-dimensional dataset while keeping its spatial characteristics as much as possible. However, since PCA only explains the covariance structure of all the data its most expressive components, it cannot represent the most important discriminant directions to separate sample groups. To solve this problem, in this paper we propose a new PCA method based on the linear discriminant analysis (LDA) space. From our theoretic analysis and numerical experiments, our new PCA method (we call it PCA-LDA) can work effectively and efficiently.
Delaunay Mesh Reconstruction from 3D Medical Images Based on Centroidal Voronoi Tessellations

Reconstructing meshes from 3D medical images is an important but complicated task, which provides a fundamental data structure for Bio-medical applications. In this paper, a novel and easily implemental solution is proposed. Instead of following the popular methods, we sample on the medical images with centroidal Voronoi tessellations, and then build the Delaunay mesh from the sampled points directly. By applying the algorithm on the CT images and evaluating the mesh quality metrics, the solution presents to be good at reconstructing complicated objects and generates optimized meshes, which shows that it is suitable for anatomical structure modeling.
An Investigation of Likelihoods and Priors for Bayesian Endmember Estimation

A Gibbs sampler for piece‐wise convex hyperspectral unmixing and endmember detection is presented. The standard linear mixing model used for hyperspectral unmixing assumes that hyperspectral data reside in a single convex region. However, hyperspectral data is often non‐convex. Furthermore, in standard unmixing methods, endmembers are generally represented as a single point in the high dimensional space. However, the spectral signature for a material varies as a function of the inherent variability of the material or environmental conditions. Therefore, it is more appropriate to represent each endmember as a full distribution to incorporate the variability and utilize this information during spectral unmixing. A Gibbs sampler that searches for several sets of endmember distributions, i.e. a piece‐wise convex representation, is presented. The hyperspectral data is partitioned among the sets of endmember distributions using a Dirichlet process prior that also estimates the number of needed sets. The propose.
Differentiating Integration Testing and unit testing

Software testing plays a vital role in the affirmation of the software quality and reliability. It is a never ending process which starts with the very initial stage of software development and continues with Software Development Life Cycle. Testing may be in any form depending on the type of software under consideration. This paper furnishes the basics of Software Testing and steps involved in the testing procedure. We will review two significant approaches for testing software which are Unit testing and Integration Testing. We will study the brief overview of the both the approaches and also compare them on the basis of various parameters like modules, problem discovery and techniques involved.
Donepezil treatment and Alzheimer disease: can the results of randomized clinical trials be applied to Alzheimer disease patients in clinical practice?

OBJECTIVE To determine if results from randomized clinical trials of donepezil in Alzheimer disease (AD) patients can be applied to AD patients in clinical practice by comparing the findings from a Nordic one-year randomized AD donepezil trial with data from a one-year prospective, observational study of AD patients. METHODS AD patients from a consortium of California sites were systematically followed for at least one year. Their treatment regimens, including prescription of donepezil, were determined by their individual physician according to his or her usual criteria. RESULTS The 148 California patients treated with donepezil had a one-year decline of 1.3 (3.5 SD) points on the Mini-Mental State Exam compared to a decline of 3.3 (4.4 SD) in the 158 AD patients who received no anti-Alzheimer drugs. The Mini-Mental State Exam decline in Nordic sample was approximately 0.25 points for the 91 patients receiving donepezil and approximately 2.2 for the 98 placebo patients. The overall effect sizes were estimated at about 0.49 in both studies. The California data were further analyzed using propensity methods; after taking into account differences that could bias prescribing decisions, benefits associated with taking donepezil remained. CONCLUSION A comparison of a randomized clinical trial of donepezil in AD patients and this observational study indicates that if appropriate methodological and statistical precautions are undertaken, then results from randomized clinical trials can be predictive with AD patients in clinical practice. This California study supports the modest effectiveness of donepezil in AD patients having clinical characteristics similar to those of the Nordic study.
Culturally Embedded Measurement of Latino Caregivers’ Engagement in Head Start: A Tale of Two Forms of Engagement

ABSTRACT Practice and Policy: The preschool years represent a critical time to foster family engagement in education for children growing up in poverty. Yet the ways in which Latino families with lower levels of income engage with their children’s education at home and at school might look different from how middle-income parents from the dominant U.S. culture do, depending on cultural values and beliefs about best ways to support children’s learning as well as on socioeconomic realities that present barriers for traditional forms of engagement. This study sought to examine further the psychometric functioning of a promising new measure of family engagement, developed with and for Latino Head Start families. Research Findings: Results of this study supported continued use of this measure, with clear caveats and directions for future research. Findings suggested that the ways Latino Head Start parents engage with children’s learning and development at home (e.g., supporting children’s social awareness and behavior, connection to cultural heritage, academic skills) might be a more culturally nuanced and salient form of engagement, while school-based engagement (e.g., volunteering at school, communicating with teachers) might be a more universal form. Findings contribute to understandings of Latino family engagement as well as to methodological considerations for culture-specific measurement development efforts, with relevance for early education researchers and professionals.
Fingerprinting methods for RFID tag indoor localization

Different approaches based on various wireless have been proposed so far for indoor localization. Radio frequency Identification (RFID) indoor localization seems to be a promising way of research. The identification capability of this technology combined to localization methods improves the results obtained by other wireless technologies such as Wifi, GPS, Zigbee. This paper details some localization techniques used for RFID Tags localization in Indoor environment. In particular, Fingerprinting methods are compared to Distance estimation methods. We will show through several simulation experiments, using NS2 and Matlab software, that fingerprinting techniques outperform Distance estimation techniques for localization and tracking tasks.
The Influence of Confessions on Guilty Pleas and Plea Discounts

The influence on confession evidence in trials is quite strong; triers of fact who hear confession evidence find these self-incriminating statements hard to ignore and in turn, vote to convict more often. However, most cases do not see the inside of a courtroom, but rather are resolved via plea bargains. In the present study, we examined how confessions, whether partial or full, influence guilty plea rates and plea discounts (the difference between sentence received at trial if convicted and sentence received as part of the plea). We coded more than 500 district attorney case files for defendant statement type (i.e., not questioned by police, questioned but denied guilt, questioned and partially confessed, questioned and fully confessed), case disposition (guilty plea, trial, dismissal), and other pertinent information (e.g., initial charges, perceived strength of evidence). We found that whereas those who denied guilt were the least likely to plead guilty, when they did plead, they enjoyed the largest plea discounts. In addition, partial and full confessors were found to be equally likely to plead guilty (both at near-ceiling levels), but partial confessors received the smallest plea discounts by far. Our findings have implications for theories of remorse and punishment, and plea decision-making.
Biochemical Inhibition of the Acetyltransferases ATase1 and ATase2 Reduces β-Secretase (BACE1) Levels and Aβ Generation*

Background: The acetyltransferases ATase1 and ATase2 regulate the levels of BACE1, which is involved in the pathogenesis of Alzheimer disease (AD). Results: Both ATases are up-regulated in the brain of AD patients. ATase1/ATase2 inhibitors were identified. Structure-activity relationship, mechanisms of action, and biological effects were determined. Conclusion: ATase1/ATase2 inhibitors down-regulate levels and activity of BACE1. Significance: ATase1/ATase2 are potential targets to prevent AD. The cellular levels of β-site APP cleaving enzyme 1 (BACE1), the rate-limiting enzyme for the generation of the Alzheimer disease (AD) amyloid β-peptide (Aβ), are tightly regulated by two ER-based acetyl-CoA:lysine acetyltransferases, ATase1 and ATase2. Here we report that both acetyltransferases are expressed in neurons and glial cells, and are up-regulated in the brain of AD patients. We also report the identification of first and second generation compounds that inhibit ATase1/ATase2 and down-regulate the expression levels as well as activity of BACE1. The mechanism of action involves competitive and non-competitive inhibition as well as generation of unstable intermediates of the ATases that undergo degradation.
V/V_max_ statistics and neo-classic cosmological tests.

A new cosmological test is derived, based on the distribution of individual V/V max in a complete redshift– limited sample of distant objects. The fundamental assumption is that, in any range of absolute luminosity, individual V/V max are required to be uniformly spread over the [0 , 1] range. Under the assumption of Pure Luminosity Evolution, this gives rise to a natural partition of the sample into high luminosity, redshift-limited and low luminosity magnitude–limited quasars. The behavior of V/V max versus evolution and cosmology diﬀers substantially in the two subsamples. This condition of uniformity is probed in any absolute magnitude bin, allowing a likelihood function to be computed from the Kolmogorov–Smirnov probabilities of each bin. Monte–Carlo simulations show that the test is mostly sensitive to the density parameter, but, under certain conditions, it also sets constraints on the space curvature and, to a lower extent, on the cosmological constant. The eﬃciency of this test applied to two kinds of simulated quasar samples is examined: large number QSO sample, but limited to redshifts z < 2 . 2 or smaller in QSO number, but with higher a redshift limit. Power law and exponential luminosity evolution laws are compared, and cross–tests show that the functional form of luminosity evolution does not aﬀect substantially the probabilities in the parameter space (Ω mat , Λ). The test is then applied to the UVX sample of Boyle et al. (1990). A low matter density, and a ﬂat Universe without cosmological constant, are rejected: 0 . 2 < Ω < 0 . 8 within the 95 % conﬁdence level.
A Fast Nonparametric Noncausal MRF-Based Texture Synthesis Scheme Using a Novel FKDE Algorithm

In this paper, a new algorithm is proposed for fast kernel density estimation (FKDE), based on principal direction divisive partitioning (PDDP) of the data space. A new framework is also developed to apply FKDE algorithms (both proposed and existing), within nonparametric noncausal Markov random field (NNMRF) based texture synthesis algorithm. The goal of the proposed FKDE algorithm is to use the finite support property of kernels for fast estimation of density. It has been shown that hyperplane boundaries for partitioning the data space and principal component vectors of the data space are two requirements for efficient FKDE. The proposed algorithm is compared with the earlier algorithms, with a number of high-dimensional data sets. The error and time complexity analysis, proves the efficiency of the proposed FKDE algorithm compared to the earlier algorithms. Due to the local simulated annealing, direct incorporation of the FKDE algorithms within the NNMRF-based texture synthesis algorithm, is not possible. This work proposes a new methodology to incorporate the effect of local simulated annealing within the FKDE framework. Afterward, the developed texture synthesis algorithms have been tested with a number of different natural textures, taken from a standard database. The comparison in terms of visual similarity and time complexity, between the proposed FKDE based texture synthesis algorithm with the earlier algorithms, show the efficiency.