Miracle-dz/UniFAR-FTUs huggingface dataset:
The Primary Process: Freud’s Profound Yet Neglected Contribution to the Psychology of Consciousness

ABSTRACT The primary process model is part of Freud’s struggle to define and distinguish conscious and unconscious mental activity. He created two embryonic models of unconscious mind. One he derived from studying symptoms of dynamic repression or sequestration of content already capable of symbolic mental representation. The other, the primary process, is his landmark effort to define a mental activity different from reflective representational thought, derived from studying dreaming. He could not clearly separate the repression model, as it is also based on the primary process. He vacillated as to whether the primary process is qualitatively different from representational symbolic thought. His efforts to articulate preconscious mentation suggest an ambiguous gray area between conscious thought and the primary process. Although he concluded that the primary process is unconscious because it is not intrinsically reflective, its manifestations are psychologically conscious and directly evident except in the physiologically unconscious state of dreaming. Similar problems color the efforts of others including Klein, Matte-Blanco, and theorists of attachment and implicit learning to separate conscious and unconscious mind and to articulate a model of mental function different from reflective consciousness. A model of conscious mental activity different from reflective representational consciousness, called primordial consciousness, is proposed to account for a wide spectrum of human phenomena both normal and pathological that share characteristics of immediacy and belief. They include, in addition to dreaming, psychosis, creativity, spirituality, and mental process in non-western cultures.
Heart failure with preserved ejection fraction

Abstract Heart failure with preserved ejection fraction (HFpEF) has recently emerged as a major cause of cardiovascular morbidity and mortality. Contrary to initial beliefs, HFpEF is now known to be as common as heart failure with reduced ejection fraction (HFrEF) and carries an unacceptably high mortality rate. With a prevalence that has been steadily rising over the past two decades, it is very likely that HFpEF will represent the dominant heart failure phenotype over the coming few years. The scarcity of trials in this semi-discrete form of heart failure and lack of unified enrolment criteria in the studies conducted to date might have contributed to the current absence of specific therapies. Understanding the epidemiological, pathophysiological and molecular differences (and similarities) between these two forms of heart failure is cornerstone to the development of targeted therapies. Carefully designed studies that adhere to unified diagnostic criteria with the recruitment of appropriate controls and adoption of practical end-points are urgently needed to help identify effective treatment strategies.
User centric QoS management framework and its implementation

There have been numerous proposals for managing the end-to-end Quality of Service of multimedia applications. These approaches can be categorised into two groups, namely schemes that attempt to provide service guarantees, and schemes that provide best effort service. The schemes that attempt to provide service guarantees, only have limited applicability as they require apriori knowledge of all resource requirements. In contrast, the approaches, which provide best effort service cannot provide predictable services, and use application adpativity to deal with variation in service levels. However, neither of these approaches facilitate user participation in the decision making process except at the start of the session. In this paper, we present a new QoS management framework, which is user centric, and integrates the adaptability of the application and the resource management of the system. It presents the architecture of the proposed framework, and describes the design requirements of each of these architectural components. Then the viability of the proposed framework is demonstrated through a prototype implementation of the QoS management architecture under Linux, and the use of an adaptive MPEG based video on demand application.
Context Awareness through Cross-Layer Network Architecture

Layered architectures are not sufficiently flexible to cope with the dynamics of wireless-dominated next generation communications. Cross-layer approaches may provide a better solution: allowing interactions between two or more non-adjacent layers in the protocol stack. Cross-layer architectures based on purely local information will not be able to support system-wide cross-layer performance optimization, context-awareness, etc. A new cross-layer architecture which provides a hybrid local and global view, using gossiping to maintain consistency has been proposed in [1]. This paper studies the possibilities of context-awareness in communications through this architecture by two examples. The first example uses user-centric context to control the available link-bandwidth and satisfy user accordingly. The second uses contextual information to control the transmission power of a mobile node.
Comparative Study of Malaria Prevalence among Travellers in Nigeria (West Africa) Using Slide Microscopy and a Rapid Diagnosis Test

Malaria is a major disease in Africa and leads to various public health problems. A study was carried out at the Aviation Medical Clinic Laboratory, Murtala Mohammed Airport, Ikeja, Lagos State, Nigeria, in 2014. The work aimed to determine the prevalence of malaria among patients attending the laboratory. Blood samples were therefore collected from 51 patients and subjected to both blood smear microscopy and a rapid immunochromatographic diagnostic test (SD BIOLINE Malaria Ag) for detection of, respectively, malaria parasites and antigens. At the end of the study, 22% of the patients were detected positive by the microscopic examination while 9.8% were tested positive when using SD BIOLINE Malaria Ag. The outcomes of the study show a high prevalence of malaria at the airport. This represents a serious risk factor leading to a high likelihood of spread and occurrence of malaria in other countries including Western countries whereby the disease is nonendemic. It also pointed out that the blood smear microscopy seems to be better than Rapid Diagnosis Test (RDT) for malaria diagnosis.
The Financial Burden of Non-Communicable Chronic Diseases in Rural Nigeria: Wealth and Gender Heterogeneity in Health Care Utilization and Health Expenditures

Objectives Better insights into health care utilization and out-of-pocket expenditures for non-communicable chronic diseases (NCCD) are needed to develop accessible health care and limit the increasing financial burden of NCCDs in Sub-Saharan Africa. Methods A household survey was conducted in rural Kwara State, Nigeria, among 5,761 individuals. Data were obtained using biomedical and socio-economic questionnaires. Health care utilization, NCCD-related health expenditures and distances to health care providers were compared by sex and by wealth quintile, and a Heckman regression model was used to estimate health expenditures taking selection bias in health care utilization into account. Results The prevalence of NCCDs in our sample was 6.2%. NCCD-affected individuals from the wealthiest quintile utilized formal health care nearly twice as often as those from the lowest quintile (87.8% vs 46.2%, p = 0.002). Women reported foregone formal care more often than men (43.5% vs. 27.0%, p = 0.058). Health expenditures relative to annual consumption of the poorest quintile exceeded those of the highest quintile 2.2-fold, and the poorest quintile exhibited a higher rate of catastrophic health spending (10.8% among NCCD-affected households) than the three upper quintiles (4.2% to 6.7%). Long travel distances to the nearest provider, highest for the poorest quintile, were a significant deterrent to seeking care. Using distance to the nearest facility as instrument to account for selection into health care utilization, we estimated out-of-pocket health care expenditures for NCCDs to be significantly higher in the lowest wealth quintile compared to the three upper quintiles. Conclusions Facing potentially high health care costs and poor accessibility of health care facilities, many individuals suffering from NCCDs—particularly women and the poor—forego formal care, thereby increasing the risk of more severe illness in the future. When seeking care, the poor spend less on treatment than the rich, suggestive of lower quality care, while their expenditures represent a higher share of their annual household consumption. This calls for targeted interventions that enhance health care accessibility and provide financial protection from the consequences of NCCDs, especially for vulnerable populations.
Small Interfering RNA Effectively Inhibits the Expression of SARS Coronavirus Membrane Gene at Two Novel Targeting Sites

Small interfering RNA (siRNA) is a class of duplex RNA molecules of 21-25 nt nucleotides in length functioning post-transcriptionally to downregulate targeted gene expression. The membrane (M) protein of severe acute respiratory syndrome-associated coronavirus (SARS-CoV) is highly abundant during viral infections and is a critical element for viral assembly. Nucleotide substitution in the viral genome occurs frequently during SARS-CoV infection. In the current study, we analyzed the M gene sequences derived from 15 SARS-CoV isolates and uncovered six nucleotide substitutions among these isolates. Interestingly, these nucleotide substitutions are all located at the 5’ half of the M gene. Based on this information and previous reports, we created two novel siRNAs targeting two unexplored and well conserved regions in the M gene. The effects of these two siRNAs were tested by semi-quantitative RT-PCR and EGFP-M fusion gene expression. The results demonstrated that both siRNAs effectively and specifically blocked the targeted gene expression. Real time quantitative RT-PCR (qRT-PCR) revealed that siRNA targeting the 3’ half of the M gene (si-M2) induced more potent inhibition than that targeting the 5’ half (si-M1). Both si-M1 and si-M2 significantly downregulated M gene mediated upregulation of interferon β expression. Thus, our results indicate that SARS-CoV M gene specific siRNA might function in a sequence-dependent manner.
The Neon Abundance of Galactic Wolf-Rayet Stars

The fast, dense winds that characterize Wolf-Rayet (W-R) stars obscure their underlying cores and complicate the verification of evolving core and nucleosynthesis models. Core evolution can be probed by measuring abundances of wind-borne nuclear-processed elements, partially overcoming this limitation. Using ground-based mid-infrared spectroscopy and the 12.81 μm [Ne II] emission line measured in four Galactic W-R stars, we estimate neon abundances and compare them to long-standing predictions from evolved-core models. For the WC star WR 121, this abundance is found to be ≳11 times the cosmic value, in good agreement with predictions. For the three less-evolved WN stars, little neon enhancement above cosmic values is measured, as expected. We discuss the impact of clumping in W-R winds on this measurement and the promise of using metal abundance ratios to eliminate sensitivity to wind density and ionization structure.
Virtual Infrastructures in Future Internet

Virtualization in both computer systems and network elements is becoming increasingly part of the Internet. Apart from posing new challenges, virtualization enables new functionalities, and hints at a future Internet architecture, which contains a physical, but polymorphic, substrate on which various parallel infrastructures can be created on demand. This article explores such a new “architecture of virtual infrastructures”. The FEDERICA project and the recent evolution trends in the National Research and Education networks are taken as examples of this new type of network infrastructure, which is an evolution of the
Machine Learning Approach for Intrusion Detection on Cloud Virtual Machines

Development of the cloud computing in recent years is increasing rapidly and gained great success, its security issues have got more and more attention. Many challenges in cloud computation increase the threat of data and service availability. There is need of many security services in order to improve cloud security for users as well as providers. In this paper, we propose a Anomaly Intrusion Detection System using machine learning approach for virtual machines on cloud computing. Our proposal is feature selection over events from Virtual Machine Monitor to detect anomaly in parallel to training the system so it will learn new threats and update the model. The experiment has been carried out on NSL-KDD’99 datasets using Naive Bayes Tree (NB Tree) Classifier and hybrid approach of NB Tree and Random Forest.
Viewpoint-aware object detection and pose estimation

We describe an approach to category-level detection and viewpoint estimation for rigid 3D objects from single 2D images. In contrast to many existing methods, we directly integrate 3D reasoning with an appearance-based voting architecture. Our method relies on a nonparametric representation of a joint distribution of shape and appearance of the object class. Our voting method employs a novel parametrization of joint detection and viewpoint hypothesis space, allowing efficient accumulation of evidence. We combine this with a re-scoring and refinement mechanism, using an ensemble of view-specific Support Vector Machines. We evaluate the performance of our approach in detection and pose estimation of cars on a number of benchmark datasets.
How Homophily Affects Diffusion and Learning in Networks

We examine how three different communication processes operating through social networks are affected by homophily -- the tendency of individuals to associate with others similar to themselves. Homophily has no effect if messages are broadcast or sent via shortest paths; only connection density matters. In contrast, homophily substantially slows learning based on repeated averaging of neighbors' information and Markovian diffusion processes such as the Google random surfer model. Indeed, the latter processes are strongly affected by homophily but completely independent of connection density, provided this density exceeds a low threshold. We obtain these results by establishing new results on the spectra of large random graphs and relating the spectra to homophily. We conclude by checking the theoretical predictions using observed high school friendship networks from the Adolescent Health dataset.
A Latent Concept Topic Model for Robust Topic Inference Using Word Embeddings

Uncovering thematic structures of SNS and blog posts is a crucial yet challenging task, because of the severe data sparsity induced by the short length of texts and diverse use of vocabulary. This hinders effective topic inference of traditional LDA because it infers topics based on document-level co-occurrence of words. To robustly infer topics in such contexts, we propose a latent concept topic model (LCTM). Unlike LDA, LCTM reveals topics via co-occurrence of latent concepts , which we introduce as latent variables to capture conceptual similarity of words. More speciﬁcally, LCTM models each topic as a distribution over the latent concepts , where each latent concept is a localized Gaussian distribution over the word embedding space. Since the number of unique concepts in a corpus is often much smaller than the number of unique words, LCTM is less susceptible to the data sparsity. Experiments on the 20Newsgroups show the effectiveness of LCTM in dealing with short texts as well as the capability of the model in handling held-out documents with a high degree of OOV words.
Recognition of Sarcasms in Tweets Based on Concept Level Sentiment Analysis and Supervised Learning Approaches

Sarcasm is a form of communication that is intended to mock or harass someone by us- ing words with the opposite of their literal meaning. However, identification of sarcasm is somewhat difficult due to the gap between its literal and intended meaning. Recognition of sarcasm is a task that can potentially pro- vide a lot of benefits to other areas of nat- ural language processing. In this research, we propose a new method to identify sarcasm in tweets that focuses on several approaches: 1) sentiment analysis, 2) concept level and common-sense knowledge 3) coherence and 4) machine learning classification. We will use support vector machine (SVM) to classify sarcastic tweet based on our proposed features as well as ordinary N-grams. Our proposed classifier is an ensemble of two SVMs with two different feature sets. The results of the experiment show our method outperforms the baseline method and achieves 80% accuracy.
Structure and clumping in the fast wind of NGC 6543

Far-ultraviolet spectroscopy from the FUSE satellite is analysed to uniquely probe spatial structure and clumping in the fast wind of the central star of the H- rich planetary nebula NGC 6543 (HD 164963). Time-series data of the unsaturated Pv lambda lambda 1118, 1128 resonance line P Cygni profiles provide a very sensitive diagnostic of variable wind conditions in the outflow. We report on the discovery of episodic and recurrent optical depth enhancements in the Pv absorption troughs, with some evidence for a similar to 0.17-d modulation time-scale. Empirical line-synthesis modelling is used to derive physical properties, including the optical depth evolution of individual 'events'. The characteristics of these features are essentially identical to the ` discrete absorption components' (DACs) commonly seen in the ultraviolet lines of massive OB stars. We have also employed the unified model atmosphere code CMFGEN to explore spectroscopic signatures of clumping, and report, in particular, on the clear sensitivity of the Pv lines to the clump volume filling factor. The results presented here have implications for the downward revision of mass-loss rates in planetary nebula central stars. We conclude that the temporal structures seen in the Pv lines of NGC 6543 likely have a physical origin that is similar to that operating in massive, luminous stars, and may be related to near-surface perturbations caused by stellar pulsation and/or magnetic fields.
Topology of energy surfaces and existence of transversal Poincare sections

Two questions on the topology of compact energy surfaces of natural two degrees of freedom Hamiltonian systems in a magnetic field are discussed. We show that the topology of this 3-manifold (if it is not a unit tangent bundle) is uniquely determined by the Euler characteristic of the accessible region in configuration space. In this class of 3-manifolds for most cases there does not
Selective Attention to Auditory Memory Neurally Enhances Perceptual Precision

Selective attention to a task-relevant stimulus facilitates encoding of that stimulus into a working memory representation. It is less clear whether selective attention also improves the precision of a stimulus already represented in memory. Here, we investigate the behavioral and neural dynamics of selective attention to representations in auditory working memory (i.e., auditory objects) using psychophysical modeling and model-based analysis of electroencephalographic signals. Human listeners performed a syllable pitch discrimination task where two syllables served as to-be-encoded auditory objects. Valid (vs neutral) retroactive cues were presented during retention to allow listeners to selectively attend to the to-be-probed auditory object in memory. Behaviorally, listeners represented auditory objects in memory more precisely (expressed by steeper slopes of a psychometric curve) and made faster perceptual decisions when valid compared to neutral retrocues were presented. Neurally, valid compared to neutral retrocues elicited a larger frontocentral sustained negativity in the evoked potential as well as enhanced parietal alpha/low-beta oscillatory power (9–18 Hz) during memory retention. Critically, individual magnitudes of alpha oscillatory power (7–11 Hz) modulation predicted the degree to which valid retrocues benefitted individuals' behavior. Our results indicate that selective attention to a specific object in auditory memory does benefit human performance not by simply reducing memory load, but by actively engaging complementary neural resources to sharpen the precision of the task-relevant object in memory. SIGNIFICANCE STATEMENT Can selective attention improve the representational precision with which objects are held in memory? And if so, what are the neural mechanisms that support such improvement? These issues have been rarely examined within the auditory modality, in which acoustic signals change and vanish on a milliseconds time scale. Introducing a new auditory memory paradigm and using model-based electroencephalography analyses in humans, we thus bridge this gap and reveal behavioral and neural signatures of increased, attention-mediated working memory precision. We further show that the extent of alpha power modulation predicts the degree to which individuals' memory performance benefits from selective attention.
Intermediate to low-mass stellar content of Westerlund 1

We have analysed near-infrared NTT/SofI observations of the starburst cluster Westerlund 1, which is among the most massive young clusters in the Milky Way. A comparison of colour-magnitude diagrams with theoretical main-sequence and pre-main sequence evolutionary tracks yields improved extinction and distance estimates of AKs = 1.13 ± 0.03 mag and d = 3.55 ± 0.17 kpc (DM = 12.75 ± 0.10 mag). The pre-main sequence population is best fit by a Palla & Stahler isochrone for an age of 3.2 Myr, while the main sequence population is in agreement with a cluster age of 3 to 5 Myr. An analysis of the structural parameters of the cluster yields that the half-mass radius of the cluster population increases towards lower mass, indicative of the presence of mass segregation. The cluster is clearly elongated with an eccentricity of 0.20 for stars with masses between 10 and 32 M� , and 0.15 for stars with masses in the range 3 to 10 M� . We derive the slope of the stellar mass function for stars with masses between 3.4 and 27 M� . In an annulus with radii between 0.75 and 1.5 pc from the cluster centre, we obtain a slope of Γ= −1.3. Closer in, the mass function of Westerlund #[
Transformations of nonlinear dynamical systems to jerky motion and its application to minimal chaotic flows

Third-order explicit autonomous differential equations in one scalar variable or, mechanically interpreted, jerky dynamics constitute an interesting subclass of dynamical systems that can exhibit many major features of regular and irregular or chaotic dynamical behavior. In this paper, we investigate the circumstances under which three dimensional autonomous dynamical systems possess at least one equivalent jerky dynamics. In particular, we determine a wide class of three-dimensional vector fields with polynomial and non-polynomial nonlinearities that possess this property. Taking advantage of this general result, we focus on the jerky dynamics of Sprott’s minimal chaotic dynamical systems and Ro ̈ssler’s toroidal chaos model. Based on the interrelation between the jerky dynamics of these models, we classify them according to their increasing polynomial complexity. Finally, we also provide a simple criterion that excludes chaotic dynamics for some classes of jerky dynamics and, therefore, also for some classes of three-dimensional dynamical systems. @S1063-651X~98! 09710-4#