Miracle-dz/UniFAR-FTUs huggingface dataset:
Poincaré sections for pitch mark determination in dysphonic speech

An approach to pitch mark determination using Poincar(cid:19)e sections is presented. While speech has been interpreted in terms of non-linear systems theory for quite some time, not much e(cid:11)ort has been made to exploit this knowledge in the problem of pitch mark detection. This algorithm uses nonlinear state space embedding and calculates the Poincar(cid:19)e section at a chosen point in state space. Pitch marks are then found at the crossing of the trajectories with the Poincar(cid:19)e plane in a certain neighborhood of the initial point. The procedure is performed frame-wise to account for the changing dynamics of the speech production system. First results show promising performance, comparable to the pitch marking algorithm used in Praat.
Gossip-based asynchronous and robust aggregation protocol — A pessimistic approach

Gossip-based protocols are one of the popular approaches to estimate aggregates in large scale distributed systems. In this paper, we propose a gossip-based asynchronous and robust protocol to compute aggregates. In our protocol, each node employs the proposed pessimistic approach to exchange its local estimate with one of its neighbors and also uses the proposed recovery scheme which conserves the system mass in the presence of asynchrony and churn. The simulation results presented in this paper show that our protocol yields accurate aggregates in comparatively lesser time.
Pixel bar charts: a new technique for visualizing large multi-attribute data sets without aggregation

Simple presentation graphics are intuitive and easy-to-use, but show only highly aggregated data and present only a very limited number of data values (as in the case of bar charts). In addition, these graphics may have a high degree of overlap which may occlude a significant portion of the data values (as in the case of the x-y plots). In this paper, we therefore propose a generalization of traditional bar charts and x-y-plots which allows the visualization of large amounts of data. The basic idea is to use the pixels within the bars to present the detailed information of the data records. Our so-called pixel bar charts retain the intuitiveness of traditional bar charts while allowing very large data sets to be visualized in an effective way. We show that, for an effective pixel placement, we have to solve complex optimization problems, and present an algorithm which efficiently solves the problem. Our application using real-world e-commerce data shows the wide applicability and usefulness of our new idea.
The Ultimate in Cancer Chemoprevention: Cancer Vaccines

This perspective on Beatty et al. (beginning on page 438 in this issue of the journal) discusses the role of the immune system as nature's ultimate chemoprevention agent. A successful immune response to vaccination results in immunologic memory. In the case of a successful cancer-related response, antigen-specific T cells will be poised to destroy an aberrantly expressed protein even if the host is not exposed until years after the end of immunizations. After the abnormal cell is eradicated, T cells will lie in wait for the next exposure. The ability to develop effective cancer vaccines for prevention is fast becoming a reality as immunogenic aberrant proteins that drive malignant transformation are identified. Cancer Prev Res; 3(4); 406–9. ©2010 AACR.
Benchmark heat transfer data for microstructured surfaces for immersion-cooled microelectronics

Pool boiling from a surface featuring micropyramidal reentrant cavities (mouth size 40 /spl mu/m) etched in silicon, bonded to a glass substrate, was studied. All experiments were conducted in the dielectric fluid FC-72 at 1 atm. The heat sink is designed to eliminate spreading through the substrate, and back heat loss. Experimentation showed that the critical heat flux was 12.8 W/cm/sup 2/. A high speed camera (400 frames/s) was used to record and quantify the effect of heat flux on departure diameter and bubble emission frequency. Both departure diameter and frequency showed an increasing trend with heat flux. Comparisons with existing literature are also presented.
Geometric Optics-Based Propagation Prediction Model in Urban Street Canyon Environments

Notable changes in the next-generation wireless communication system include the fact that the nominal height of base-station antennas becomes lower than the height of typical rooftops. In this scenario, reflection and scattering of waves become more dominant than diffraction in short-range propagation. We first analyze the reflection and scattering loss of propagation by using ray-tracing simulation, and on the basis of the analysis, we propose a propagation prediction model based on geometric optics in the urban street canyon scenario. The proposed model is defined by geometrical parameters such as the street width and the distance to a corner, such that the model can be applied to various environmental scenarios. It can also simultaneously predict propagation losses in many corners. The proposed model is justified with measurement data.
Outlier detection on uncertain data: Objects, instances, and inferences

This paper studies the problem of outlier detection on uncertain data. We start with a comprehensive model considering both uncertain objects and their instances. An uncertain object has some inherent attributes and consists of a set of instances which are modeled by a probability density distribution. We detect outliers at both the instance level and the object level. To detect outlier instances, it is a prerequisite to know normal instances. By assuming that uncertain objects with similar properties tend to have similar instances, we learn the normal instances for each uncertain object using the instances of objects with similar properties. Consequently, outlier instances can be detected by comparing against normal ones. Furthermore, we can detect outlier objects most of whose instances are outliers. Technically, we use a Bayesian inference algorithm to solve the problem, and develop an approximation algorithm and a filtering algorithm to speed up the computation. An extensive empirical study on both real data and synthetic data verifies the effectiveness and efficiency of our algorithms.
Rule-based modeling: precision and transparency

This article is a reaction to recent publications on rule-based modeling using fuzzy set theory and fuzzy logic. The interest in fuzzy systems has recently shifted from the seminal ideas about complexity reduction toward data-driven construction of fuzzy systems. Many algorithms have been introduced that aim at numerical approximation of functions by rules, but pay little attention to the interpretability of the resulting rule base. We show that fuzzy rule-based models acquired from measurements can be both accurate and transparent by using a low number of rules. The rules are generated by product-space clustering and describe the system in terms of the characteristic local behavior of the system in regions identified by the clustering algorithm. The fuzzy transition between rules makes it possible to achieve precision along with a good qualitative description in linguistic terms. The latter is useful for expert evaluation, rule-base maintenance, operator training, control systems design, user interfacing, etc. We demonstrate the approach on a modeling problem from a recently published article.
A network security monitor

This study concentrates on the security-related issues in a single broadcast LAN (local area network) such as Ethernet. The authors formalize various possible network attacks. Their basic strategy is to develop profiles of usage of network resources and then compare current usage patterns with the historical profile to determine possible security violations. Thus, the work is similar to the host-based intrusion-detection systems. Different from such systems, however, is the use of a hierarchical model to refine the focus of the intrusion-detection mechanism. The authors also report on the development of an experimental LAN monitor currently under implementation. Several network attacks have been simulated, and results on how the monitor has been able to detect these attacks are analyzed. Initial results demonstrate that many network attacks are detectable with the authors' monitor, although it can be defeated. <<ETX>>
Derivatives in Financial Markets with Stochastic Volatility

1. The Black-Scholes theory of derivative pricing 2. Introduction to stochastic volatility models 3. Scales in mean-reverting stochastic volatility 4. Tools for estimating the rate of mean-reversion 5. Symptotics for pricing European derivatives 6. Implementation and stability 7. Hedging strategies 8. Application to exotic derivatives 9. Application to American derivatives 10. Generalizations 11. Applications to interest rates models.
Commentary on ‘ The Three-Dimensional Current and Surface Wave Equations ’ by

The lowest order sigma-transformed momentum equation give n by Mellor (J. Phys. Oceangr. 2003) takes into account a phase-averaged wave forcing based on Ai ry wave theory. This equation is shown to be generally inconsistent due to inadequate approximation s of the wave motion. Indeed the evaluation of the vertical flux of momentum requires an estimation of the pressurep and coordinate transformation functions to first order in parameters that define the large scale evolut ion of the wave field, such as the bottom slope. Unfortunately there is no analytical express ion for p ands at that order. A numerical correction method is thus proposed and verified. Alternativ e coordinate transforms that allow a separation of wave and mean flow momenta do not suffer from this inc onsistency nor require a numerical estimation of the wave forcing. Indeed, the problematic ver tical flux is part of the wave momentum flux, thus distinct from the mean flow momentum flux, and not directl y re evant to the mean flow evolution.
Gene-expression profiling of CD34 cells from various hematopoietic stem-cell sources reveals functional differences in stem-cell activity

The replacement of bone marrow (BM) as a conventional source of stem cell (SC) by umbilical cord blood (UCB) and granulocyte-colony stimulating factor-mobilized peripheral blood SC (PBSC) has brought about clinical advantages. However, several studies have demonstrated that UCB CD34 cells and PBSC significantly differ from BM CD34 cells qualitatively and quantitatively. Here, we quantified the number of SC in purified BM, UCB CD34 cells, and CD34 PBSC using in vitro and in vivo assays for human hematopoietic SC (HSC) activity. A cobblestone area-forming cell (CAFC) assay showed that UCB CD34 cells contained the highest frequency of CAFC (3.6to tenfold higher than BM CD34 cells and PBSC, respectively), and the engraftment capacity in vivo by nonobese diabetic/severe combined immunodeficiency repopulation assay was also significantly greater than BM CD34 , with a higher proportion of CD45 cells detected in the recipients at a lower cell dose. To understand the molecular characteristics underlying these functional differences, we performed several DNA microarray experiments using Affymetrix gene chips, containing 12,600 genes. Comparative analysis of gene-expression profiles showed differential expression of 51 genes between BM and UCB CD34 SC and 64 genes between BM CD34 cells and PBSC. These genes are involved in proliferation, differentiation, apoptosis, and engraftment capacity of SC. Thus, the molecular expression profiles reported here confirmed functional differences observed among the SC sources. Moreover, this report provides new insights to describe the molecular phenotype of CD34 HSC and leads to a better understanding of the discrepancy among the SC sources. J. Leukoc. Biol. 75: 314–323; 2004.
Study of Reputation Based Defense Mechanism in Peer To Peer Live Streaming

Peer-to-peer live video streaming systems are having more popularity as the information technology is advancing fast. Peerto-peer live video streaming systems are like peer-to-peer file sharing system and they are also vulnerable to content pollution attack as file sharing. In this type of attack, the attacker mixes polluted or unnecessary data into the streaming data and forwards the polluted data to normal peers and hence the perceived video quality is decreased. In this paper, a comparative study among three pollution defense mechanisms in peer-to-peer live streaming systems: Blacklisting, Simple Decentralized Reputation System and Bayesian Approach to Reputation System. Finally performance analysis and the derived result has been presented.
Collaborative Dispatching of Commercial Vehicles

Collaborative dispatching allows several dispatchers to view the routing solution as a dynamic model where changes to the vehicle routes can be made in real-time. In this paper we discuss implications of collaborative dispatching on real-time decision support tools for motor carriers. We present a collaborative dispatching system which uses real-time information obtained from a telematics system. Messages sent from the vehicles are automatically analysed and actual data, such as exact arrival and departure times, as well as discrepancies between actual and planned data are identified. The collaborative dispatching system not only allows several dispatchers to concurrently modify the schedule, but also a dynamic optimisation method. The optimisation method is capable of taking into account that input data may change at any time and that dispatchers can concurrently modify the schedule and may add or relax certain constraints relevant to the optimisation model
Computational Photography

The digital camera has brought a revolutionary shift in the nature of photography, sweeping aside more than 150 years of technology based on the weird and wonderful photochemistry of silver halide crystals. Curiously, though, the camera itself has come through this transformation with remarkably little change. A digital camera has a silicon sensor where the film used to go, and there’s a new display screen on the back, but the lens and shutter and the rest of the optical system all work just as they always have, and so do most of the controls. The images that come out of the camera also look much the same—at least until you examine them microscopically. But further changes in the art and science of photography may be coming soon. Imaging laboratories are experimenting with cameras that don’t merely digitize an image but also perform extensive computations on the image data. Some of the experiments seek to improve or augment current photographic practices, for example by boosting the dynamic range of an image (preserving detail in both the brightest and dimmest areas) or by increasing the depth of field (so that both near and far objects remain in focus). Other innovations would give the photographer control over factors such as motion blur. And the wildest ideas challenge the very notion of the photograph as a realistic representation. Future cameras might allow a photographer to record a scene and then alter the lighting or shift the point of view, or even insert fictitious objects. Or a camera might have a setting that would cause it to render images in the style of watercolors or pen-and-ink drawings.
New Algorithm to Determine True Colocalization in Combination with Image Restoration and Time-Lapse Confocal Microscopy to Map Kinases in Mitochondria

The subcellular localization and physiological functions of biomolecules are closely related and thus it is crucial to precisely determine the distribution of different molecules inside the intracellular structures. This is frequently accomplished by fluorescence microscopy with well-characterized markers and posterior evaluation of the signal colocalization. Rigorous study of colocalization requires statistical analysis of the data, albeit yet no single technique has been established as a standard method. Indeed, the few methods currently available are only accurate in images with particular characteristics. Here, we introduce a new algorithm to automatically obtain the true colocalization between images that is suitable for a wide variety of biological situations. To proceed, the algorithm contemplates the individual contribution of each pixel's fluorescence intensity in a pair of images to the overall Pearsońs correlation and Manders' overlap coefficients. The accuracy and reliability of the algorithm was validated on both simulated and real images that reflected the characteristics of a range of biological samples. We used this algorithm in combination with image restoration by deconvolution and time-lapse confocal microscopy to address the localization of MEK1 in the mitochondria of different cell lines. Appraising the previously described behavior of Akt1 corroborated the reliability of the combined use of these techniques. Together, the present work provides a novel statistical approach to accurately and reliably determine the colocalization in a variety of biological images.
Serotonin signaling is associated with lower amyloid-β levels and plaques in transgenic mice and humans

Aggregation of amyloid-β (Aβ) as toxic oligomers and amyloid plaques within the brain appears to be the pathogenic event that initiates Alzheimer's disease (AD) lesions. One therapeutic strategy has been to reduce Aβ levels to limit its accumulation. Activation of certain neurotransmitter receptors can regulate Aβ metabolism. We assessed the ability of serotonin signaling to alter brain Aβ levels and plaques in a mouse model of AD and in humans. In mice, brain interstitial fluid (ISF) Aβ levels were decreased by 25% following administration of several selective serotonin reuptake inhibitor (SSRI) antidepressant drugs. Similarly, direct infusion of serotonin into the hippocampus reduced ISF Aβ levels. Serotonin-dependent reductions in Aβ were reversed if mice were pretreated with inhibitors of the extracellular regulated kinase (ERK) signaling cascade. Chronic treatment with an SSRI, citalopram, caused a 50% reduction in brain plaque load in mice. To test whether serotonin signaling could impact Aβ plaques in humans, we retrospectively compared brain amyloid load in cognitively normal elderly participants who were exposed to antidepressant drugs within the past 5 y to participants who were not. Antidepressant-treated participants had significantly less amyloid load as quantified by positron emission tomography (PET) imaging with Pittsburgh Compound B (PIB). Cumulative time of antidepressant use within the 5-y period preceding the scan correlated with less plaque load. These data suggest that serotonin signaling was associated with less Aβ accumulation in cognitively normal individuals.
Efficient Steganography Scheme based on Logistic Map and DWT-SVD

Steganography is one of the most powerful techniques to conceal the existence of hidden secret message inside a cover medium like image, video, audio, etc. An image is a suitable cover object for steganography because of its great amount of redundant spaces and its abundance. This paper represents a secure steganography scheme which incorporating discrete wavelet transform (DWT) and the stability of the singular values with logistic map-based encryption. In this proposed scheme first of all, the secret image has been encrypted using the logistic map. The encrypted image is added to singular value of original image after two-level DWT to form the stego-image. In this paper the Peak Signal to Noise Ratio (PSNR), correlation coefficient (CR) are used to evaluate the transparency and security of algorithm.
PSYCHOLOGICAL STRUCTURE OF CONSCIOUS SELF-REGULATION OF STUDENTS OF DIFFERENT TYPES OF SPECIALTIES

УДК 159.9:37.015. 3 ПСИХОЛОГИЧЕСКАЯ СТРУКТУРА ОСОЗНАННОЙ САМОРЕГУЛЯЦИИ СТУДЕНТОВ РАЗНЫХ ТИПОВ СПЕЦИАЛЬНОСТЕЙ Неверов В. Н. В статье представлен анализ влияния профессиональной принадлежности на особенности строения саморегуляции учебной деятельности студентов. В ходе проведенного исследования было установлено, что группа специальностей типа «человек – человек» и «человек – знаковая система» имеют специфические отличия в уровне развития компонентов саморегуляции. Обнаружено также, что симптомокомплекс качеств личности, влияющих на общий уровень саморегуляции различен в исследуемых специальностях. Выявлена связь показателей академической успеваемости и саморегуляции на третьем курсе обучения. Результаты статьи могут выступить теоретической основой для совершенствования программ обучения в высших учебных заведениях. Ключевые слова: саморегуляция; качества личности; академическая успеваемость; компоненты структуры; тип профессии; функциональные звенья. PSYCHOLOGICAL STRUCTURE OF CONSCIOUS SELF-REGULATION OF STUDENTS OF DIFFERENT TYPES OF SPECIALTIES Neverov V.N. In this article the analysis of influence of professional affiliation to the particular qualities of self-regulation structure of students educational activity. During the studying it was found that the groups of specialties “human-human” and “human-character” have specific differences in the level of development of self-regulation
Microtubule: A Common Target for Parkin and Parkinson’s Disease Toxins

Parkinson’s disease (PD) is characterized by the selective loss of nigral dopaminergic (DA) neurons, which have long axons enriched with microtubules. Depolymerization of microtubules by PD toxins such as rotenone disrupts vesicular transport. The ensuing accumulation of vesicles in the cell body leads to increased cytosolic concentration of dopamine due to leakage of the vesicles. Elevated oxidative stress induced by dopamine oxidation may thus trigger the selective demise of DA neurons. Many strategies have been developed to protect DA neurons by stabilizing microtubules either directly or through intracellular signaling cascades. On the other hand, parkin, one of the most frequently mutated genes in PD, encodes for a protein-ubiquitin E3 ligase that strongly binds to microtubules. Parkin stabilizes microtubules through three domains that provide strong and independent interactions with tubulin and microtubules. These interactions anchor parkin on microtubules and may facilitate its E3 ligase activity on misfolded proteins transported along microtubules. Thus, parkin and rotenone, two prominent genetic and environmental factors linked to PD, act in an opposing manner on the same molecular target in the cell, microtubules, whose destruction underlies the selective vulnerability of dopaminergic neurons.
A phenomenological investigation into cultural factors which may or may not contribute to degree completion among American Indian students in one community college district

This study investigated cultural factors’ contribution to degree completion among American Indian college students. Surveys were sent to 238 currently enrolled and 87 formerly enrolled American Indian students during March 2013. From the survey respondents, a group of ten, all currently enrolled American Indian students, agreed to one-on-one interview sessions with the researcher. Dialoguing sessions were recorded and transcribed; answers were analysed and subjected to close examination through metasynthesis leading to the discovery of themes. Verification of dialogue and transcriptions through triangulation was obtained. The results indicated there were no reported cultural factors that contributed to the retention or attrition of the American Indian college student. For administrators, faculty and staff, the findings affirm practices used to welcome students of various cultures may be effective in preventing attrition of the American Indian student and that cultural factors may not play a role in retention or attrition.