Miracle-dz/UniFAR-FTUs huggingface dataset:
Alterations in Memory Networks in Mild Cognitive Impairment and Alzheimer's Disease: An Independent Component Analysis

Memory function is likely subserved by multiple distributed neural networks, which are disrupted by the pathophysiological process of Alzheimer's disease (AD). In this study, we used multivariate analytic techniques to investigate memory-related functional magnetic resonance imaging (fMRI) activity in 52 individuals across the continuum of normal aging, mild cognitive impairment (MCI), and mild AD. Independent component analyses revealed specific memory-related networks that activated or deactivated during an associative memory paradigm. Across all subjects, hippocampal activation and parietal deactivation demonstrated a strong reciprocal relationship. Furthermore, we found evidence of a nonlinear trajectory of fMRI activation across the continuum of impairment. Less impaired MCI subjects showed paradoxical hyperactivation in the hippocampus compared with controls, whereas more impaired MCI subjects demonstrated significant hypoactivation, similar to the levels observed in the mild AD subjects. We found a remarkably parallel curve in the pattern of memory-related deactivation in medial and lateral parietal regions with greater deactivation in less-impaired MCI and loss of deactivation in more impaired MCI and mild AD subjects. Interestingly, the failure of deactivation in these regions was also associated with increased positive activity in a neocortical attentional network in MCI and AD. Our findings suggest that loss of functional integrity of the hippocampal-based memory systems is directly related to alterations of neural activity in parietal regions seen over the course of MCI and AD. These data may also provide functional evidence of the interaction between neocortical and medial temporal lobe pathology in early AD.
Journal of Quality and Technology Management Patterns of Leadership for Effective Project Management

Organizations are shifting towards project organizations thus creating a need to understand the factors that lead to effective project management. The present study explores effective project management in the context of leadership behaviour (concern for task and people) in more and less global projects. We identify factors based on leadership behaviour and propose a model for effective project management. We use t test to test our hypotheses. Results show that both concern for task and concern for people are equally important for both more global and less global projects. The findings of this study have significant implications for leadership behavior at project management workplace.
Hybrid Metric-Palatini Gravity

Recently, the phenomenology of f(R) gravity has been scrutinized motivated by the possibility to account for the self-accelerated cosmic expansion without invoking dark energy sources. Besides, this kind of modified gravity is capable of addressing the dynamics of several self-gravitating systems alternatively to the presence of dark matter. It has been established that both metric and Palatini versions of these theories have interesting features but also manifest severe and different downsides. A hybrid combination of theories, containing elements from both these two formalisms, turns out to be also very successful accounting for the observed phenomenology and is able to avoid some drawbacks of the original approaches. This article reviews the formulation of this hybrid metric-Palatini approach and its main achievements in passing the local tests and in applications to astrophysical and cosmological scenarios, where it provides a unified approach to the problems of dark energy and dark matter.
Pathfinder: Robust path reconstruction in large scale sensor networks with lossy links

In wireless sensor networks, sensor nodes are usually self-organized, delivering data to a central sink in a multi-hop manner. Reconstructing the per-packet routing path enables fine-grained diagnostic analysis and performance optimizations of the network. The performances of existing path reconstruction approaches, however, degrade rapidly in large scale networks with lossy links. In this paper, we propose Pathfinder, a robust path reconstruction method against packet losses as well as routing dynamics. At the node side, Pathfinder exploits temporal correlation between a set of packet paths and efficiently compresses the path information using path difference. At the PC side, Pathfinder infers packet paths from the compressed information and employs intelligent path speculation to reconstruct the packet paths with high reconstruction ratio. We evaluate several variations of Pathfinder as well as two most related approaches using traces from a large scale deployment and extensive simulations. Results show that Pathfinder outperforms existing approaches, achieving both high reconstruction ratio and low transmission overhead.
The impact of socio-demographic characteristics and cognitive transformation on desistance from high risk behaviors

by Annika Yvette Anderson, Ph.D. Washington State University August 2015 Chair: Jennifer Schwartz According to social control theorists, high-risk adolescents who find stable jobs and spouses may be less likely to engage in future criminal behaviors. Although there are several socio-demographic variables that are likely to predict desistance, social support (or the lack thereof) and individual efforts are also instrumental in the desistance process. There is a growing awareness among scholars that life course criminology has largely ignored the role of human agency and the choices people make about whether or not to desist from crime. Yet, only a few studies have examined the effect of social-psychological variables or individual-level identity changes on desistance. This study explores the conduits and barriers to identity transformation and successful desistance for a sample of high-risk adolescents transitioning into adulthood in the United States. I use multivariate analyses of data drawn from the National Longitudinal Survey of Youth 1997– 2011 (rounds 1–15), to answer several research questions: 1) Who among high-risk youth are most likely to undergo a cognitive transformation? 2) Who is most likely to desist? 3) What impact does cognitive transformation have on chances of desistance? 4) What are the similar/different factors relevant for racial/ethnic groups in the cognitive transformation and
A SIMPLE TEST FOR PLANAR GRAPHS

Given an undirected graph, the planarity testing problem is to determine whether the graph can be drawn in the plane without any crossing edges. Linear time planarity testing algorithms have previously been designed by Hopcroft and Tarjan, and by Booth and Lueker. However, their approaches are quite involved. We develop a very simple linear time testing algorithm based only on a depth-first search tree. Our algorithm uses Kuratowski's theorem very explicitly. A graphreduction technique is adopted so that the embeddings for the planar biconnected components constructed at each iteration never have to be changed.
CONSTRAINTS ON HIGH-SPEED SOLAR WIND STRUCTURE NEAR ITS CORONAL BASE : A ULYSSES PERSPECTIVE

Ulysses plasma data at high heliographic latitudes were studied to develop constraints on the structure of the corona at the base of the high-speed solar wind. Salient features of the flow poleward of ±60◦ revealed: 1) low variances of all bulk flow parameters, 2) parameter values that agree with those measured during high-speed conditions in the ecliptic plane when all are scaled to 1 AU, 3) the continuous presence of two interpenetrating proton streams that are not resolved in velocity space, 4) a single alpha-particle beam that travels at a speed that is close to the local Alfvén speed faster than the primary proton beam, 5) a proton temperature that is a factor of 2.4 times that of the electrons, and 6) a constant helium abundance that averages 4.4% , about half that inferred from helioseismic data in the solar convection zone. These data are combined with a host of other remote-sensing solar data and solar wind data to develop support for a model of a well-mixed solar atmosphere that is driven by reconnection-generated plasma-jet transients. In this model, acceleration of the solar wind to its terminal speed is complete within a heliocentric distance of about 5 Rs.
Observer-based measurement of facial expression with the Facial Action Coding System.

to name a few. Because of its importance to the study of emotion, a number of observer-based systems of facial expression measurement have been developed Using FACS and viewing video-recorded facial behavior at frame rate and slow motion, coders can manually code nearly all possible facial expressions, which are decomposed into action units (AUs). Action units, with some qualifications , are the smallest visually discriminable facial movements. By comparison, other systems are less thorough (Malatesta et al., 1989), fail to differentiate between some anatomically distinct movements (Oster, Hegley, & Nagel, 1992), consider movements that are not anatomically distinct as separable (Oster et al., 1992), and often assume a one-to-one mapping between facial expression and emotion (for a review of these systems, see Cohn & Ekman, in press). Unlike systems that use emotion labels to describe expression , FACS explicitly distinguishes between facial actions and inferences about what they mean. FACS itself is descriptive and includes no emotion-specified descriptors. Hypotheses and inferences about the emotional meaning of facial actions are extrinsic to FACS. If one wishes to make emotion based inferences from FACS codes, a variety of related resources exist. These include the FACS Investigators' Guide These resources suggest combination rules for defining emotion-specified expressions from FACS action units, but this inferential step remains extrinsic to FACS. Because of its descriptive power, FACS is regarded by many as the standard measure for facial behavior and is used widely in diverse fields. Beyond emotion science, these include facial neuromuscular disorders
Efficacy of standard rehabilitation in COPD outpatients with comorbidities

A prospective study was performed to confirm the prevalence pattern of the most frequent co-morbidities and to evaluate whether characteristics of patients, specific comorbidities and increasing number of comorbidities are independently associated with poorer outcomes in a population with complex chronic obstructive pulmonary disease (COPD) submitted for pulmonary rehabilitation (PR). 316 outpatients (mean±sd age 68±7 yrs) were studied. The outcomes recorded were comorbidities and proportion of patients with a pre-defined minimally significant change in exercise tolerance (6-min walk distance (6MWD) +54 m), breathlessness (Medical Research Council (MRC) score -1 point) and quality of life (St George’s Respiratory Questionnaire -4 points). 62% of patients reported comorbidities; systemic hypertension (35%), dyslipidaemia (13%), diabetes (12%) and coronary disease (11%) were the most frequent. Of these patients, >45% improved over the minimum clinically important difference in all the outcomes. In a logistic regression model, baseline 6MWD (OR 0.99, 95% CI 0.98–0.99; p = 0.001), MRC score (OR 12.88, 95% CI 6.89–24.00; p = 0.001) and arterial carbon dioxide tension (OR 1.08, 95% CI 1.00–1.15; p = 0.034) correlated with the proportion of patients who improved 6MWD and MRC, respectively. Presence of osteoporosis reduced the success rate in 6MWD (OR 0.28, 95% CI 0.11–0.70; p = 0.006). A substantial prevalence of comorbidities in COPD outpatients referred for PR was confirmed. Only the individual's disability and the presence of osteoporosis were independently associated with poorer rehabilitation outcomes.
Local Sparse Approximation for Image Restoration with Adaptive Block Size Selection

In this paper the problem of image restoration (denoising and inpainting) is approached using sparse approximation of local image blocks. The local image blocks are extracted by sliding square windows over the image. An adaptive block size selection procedure for local sparse approximation is proposed, which affects the global recovery of underlying image. Ideally the adaptive local block selection yields the minimum mean square error (MMSE) in recovered image. This framework gives us a clustered image based on the selected block size, then each cluster is restored separately using sparse approximation. The results obtained using the proposed framework are very much comparable with the recently proposed image restoration techniques.
Graph Processing on an "almost" Relational Database

It would be hard to disagree with the contention that graph processing (whether it be of connections between people, shopping habits,.) allows the creation of valuable data-driven products and insights. There is less consensus on the systems that make it easy to analyze these graphs. In this paper, we argue that a relational database (actually, a close approximation to one) is well suited for many graph processing applications. We restrict our claims to the following case, which, we believe, dominates the nature of much data analyses --- the data does not change during the analysis in response to external events. We present representative examples from our work at LinkedIn, the world's largest professional network. We present performance results for these examples using Q, a single-node, analytical database.
Pandemics in the Age of Twitter: Content Analysis of Tweets during the 2009 H1N1 Outbreak

Background Surveys are popular methods to measure public perceptions in emergencies but can be costly and time consuming. We suggest and evaluate a complementary “infoveillance” approach using Twitter during the 2009 H1N1 pandemic. Our study aimed to: 1) monitor the use of the terms “H1N1” versus “swine flu” over time; 2) conduct a content analysis of “tweets”; and 3) validate Twitter as a real-time content, sentiment, and public attention trend-tracking tool. Methodology/Principal Findings Between May 1 and December 31, 2009, we archived over 2 million Twitter posts containing keywords “swine flu,” “swineflu,” and/or “H1N1. ” using Infovigil, an infoveillance system. Tweets using “H1N1” increased from 8.8% to 40.5% (R 2 = .788; p<.001), indicating a gradual adoption of World Health Organization-recommended terminology. 5,395 tweets were randomly selected from 9 days, 4 weeks apart and coded using a tri-axial coding scheme. To track tweet content and to test the feasibility of automated coding, we created database queries for keywords and correlated these results with manual coding. Content analysis indicated resource-related posts were most commonly shared (52.6%). 4.5% of cases were identified as misinformation. News websites were the most popular sources (23.2%), while government and health agencies were linked only 1.5% of the time. 7/10 automated queries correlated with manual coding. Several Twitter activity peaks coincided with major news stories. Our results correlated well with H1N1 incidence data. Conclusions This study illustrates the potential of using social media to conduct “infodemiology” studies for public health. 2009 H1N1-related tweets were primarily used to disseminate information from credible sources, but were also a source of opinions and experiences. Tweets can be used for real-time content analysis and knowledge translation research, allowing health authorities to respond to public concerns.
Dynamics of large-scale circulation of turbulent thermal convection in a horizontal cylinder

Abstract A systematic study of the effects of cell geometry on the dynamics of large-scale flows in turbulent thermal convection is carried out in horizontal cylindrical cells of different lengths filled with water. Four different flow modes are identified with increasing aspect ratio $\Gamma $. For small aspect ratios ($\Gamma \leq 0.16$), the flow is highly confined in a thin disc-like cell with a quasi-two-dimensional (quasi-2D) large-scale circulation (LSC) in the circular plane of the cell. For larger aspect ratios ($\Gamma >0.16$), we observe periodic switching of the angular orientation $\theta $ of the rotation plane of LSC between the two longest diagonals of the cell. The sides of the container along which the LSC oscillates changes at a critical aspect ratio $\Gamma _{c}\simeq 0.82$. The measured switching period is equal to the LSC turnover time for $\Gamma \leq \Gamma _c$, shows a sharp increase at $\Gamma _{c}$ and decays exponentially to the LSC turnover time with increasing $\Gamma $. For $\Gamma \geq 1.3$, a periodic rocking of LSC along the long axis of the cylinder is also observed. The measured probability density function $P(\theta )$ of the LSC orientation $\theta $ peaks at the two diagonal positions, and its shape is described by a phenomenological model proposed by Brown & Ahlers (Phys. Fluids, vol. 20, 2008b, 075101; J. Fluid Mech., vol. 638, 2009, pp. 383–400). Using this model, we describe the dynamics of the LSC orientation $\theta $ by stochastic motion in a double-well potential. The potential is predicted from a model in which the sidewall shape produces an orientation-dependent pressure on the LSC. This model also captures key features of the four flow modes. The experiment reveals an interesting array of rich dynamics of LSC in the horizontal cylinders, which are very different from those observed in the upright cylindrical convection cells. The success of the model for both upright and horizontal cylinders suggests that it can be applied to different geometries.
Graph-based diagnosis in software-defined infrastructure

Performing system diagnosis is a critical task in modern datacenters. Investigating individual resource behavior may not be efficient in detecting abnormal behavior in large and complex datacenters. In this paper, we propose a scalable graph based diagnosis framework to detect system anomalies in Software-Defined Infrastructure running in SAVI testbed. We have leveraged Graph Mining and Machine Learning techniques in our approach in order to detect different kinds of anomalies. We have experimentally tested our framework on several use cases: Webserver-Database workload pattern, bandwidth throttling between a pair of VMs, denial-of-service (DoS) attack on a webserver and Spark Job failure. Our framework was able to detect the aforementioned anomalies accurately.
COMPLEX EVALUATION OF FENCERS PREDISPOSITION IN THREE STAGES OF SPORT DEVELOPMENT

The work presents detailed analysis of somatic, psychomotor, special and psychologic parameters of fencers during initial, directed and master stage of the training. Using specific statistical methods (factor and regressive analyses - Hellwig's model) agents determinig the sport fitness were identified (n=65). Averages of height and body mass as well the slender index according to Roeher were calculated basing on age and registered somatic features. Following tests were performed as considering the special fitness predisposition: fencing endurance, precision of weapon movement, speed and special coordination, motorial adaptation and motions frequency capacity (Zuchory's test). As regards the psychomotor abilities the visual-motion coordination test (cross apparatus) and simple and complex computer speed trials with mistakes recording were done. The whole procedure was enriched with the psychological examination through temperamental features measurement - Strelau Temperament Inventory (STI) and personality dimensions - Eysenck Personality Questionnaire (EPQ). The factors analysis was conducted as considering the specific fencing ability. It allowed the evaluation of the fencing abilities factors internal structure. As the most predictive and statistically significant following variables were found: fencing endurance, movements precision and motorial adaptation. Research confirmed the special preparation importance and the role of psychomotor indices, especially the visual- motion coordination and concentration in tests examining the variety of reactions. Contemporary fencers turned to be athletes with strong nervous system what was proved by the temperament and personality tests. Final conclusions of this research focus on the application thoughts, mostly in a sphere of diagnostics and training methods which would take into account the whole exploratory procedure. Comparative analyses of 3 examined groups showed that during the initial stage of training the physical fitness of fencers plays an important role while during the directed and master phase of practice the technical abilities development and psychomotor parameters grow more important. (Biol.Sport 23:41-53, 2006)
Improving student’s performance and writing skills by using photography, autophotography and music

The following study deals with the use of photography, autophotograhy and music when improving the students’ writing skills. The author stipulates that the use of various media as is photography, autophotography and music would not only help students to improve their writings, but will also increase their interest in a free-style and creative writings. Based on his own experiences as a teacher and college instructor and various scholarly publications together with his own research of the gr. 7, 12 and Alternative Studies program students at the School District No.70, Port Alberni, the author confirms previous findings that the use of various media increases students interest in their own writings. The author suggests that due to the positive results of his study the similar approach should be implemented not only in the Language Arts classes but in any program dealing with students writings. In addition, he believes that there are no age limitations for students or any other persons using this method to improve their writing skills and to generate their interest in writing. Furthermore, the author proposes that another positive output of this method is the increase of students’ and other peoples’ selfesteem due to their growing abilities of expressing themselves, dealing with their personal issues and with other people as well. Therefore, the author believes that the use of photography, autophotograpy and music should be incorporated into current curricula at any educational level.
Hierarchical galaxy formation

We describe the GALFORM semi-analytic model for calculating the formation and evolution of galaxies in hierarchical clustering cosmologies. It improves upon, and extends, the earlier scheme developed by Cole et al. (1994). The model employs a new Monte-Carlo algorithm to follow the merging evolution of dark matter halos with arbitrary mass resolution. It incorporates realistic descriptions of the density profiles of dark matter halos and the gas they contain; it follows the chemical evolution of gas and stars, and the associated production of dust; and it includes a detailed calculation of the sizes of disks and spheroids. Wherever possible, our prescriptions for modelling individual physical processes are based on results of numerical simulations. They require a number of adjustable parameters which we fix by reference to a small subset of local galaxy data. This results in a fully specified model of galaxy formation which can be �
Topological structure analysis of the protein-protein interaction network in budding yeast.

Interaction detection methods have led to the discovery of thousands of interactions between proteins, and discerning relevance within large-scale data sets is important to present-day biology. Here, a spectral method derived from graph theory was introduced to uncover hidden topological structures (i.e. quasi-cliques and quasi-bipartites) of complicated protein-protein interaction networks. Our analyses suggest that these hidden topological structures consist of biologically relevant functional groups. This result motivates a new method to predict the function of uncharacterized proteins based on the classification of known proteins within topological structures. Using this spectral analysis method, 48 quasi-cliques and six quasi-bipartites were isolated from a network involving 11,855 interactions among 2617 proteins in budding yeast, and 76 uncharacterized proteins were assigned functions.