Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-organizing maps for multi-objective pareto frontiers

Decision makers often need to take into account multiple conflicting objectives when selecting a solution for their problem. This can result in a potentially large number of candidate solutions to be considered. Visualizing a Pareto Frontier, the optimal set of solutions to a multi-objective problem, is considered a difficult task when the problem at hand spans more than three objective functions. We introduce a novel visual-interactive approach to facilitate coping with multi-objective problems. We propose a characterization of the Pareto Frontier data and the tasks decision makers face as they reach their decisions. Following a comprehensive analysis of the design alternatives, we show how a semantically-enhanced Self-Organizing Map, can be utilized to meet the identified tasks. We argue that our newly proposed design provides both consistent orientation of the 2D mapping as well as an appropriate visual representation of individual solutions. We then demonstrate its applicability with two real-world multi-objective case studies. We conclude with a preliminary empirical evaluation and a qualitative usefulness assessment.
Does Dairy Food Intake Predict Arterial Stiffness and Blood Pressure in Men?: Evidence from the Caerphilly Prospective Study

Arterial stiffness is an independent predictor of cardiovascular disease events and mortality, and like blood pressure, may be influenced by dairy food intake. Few studies have investigated the effects of consumption of these foods on prospective measures of arterial stiffness. The present analysis aimed to investigate the prospective relationship between milk, cheese, cream, and butter consumption and aortic pulse wave velocity, augmentation index, systolic and diastolic blood pressure, as well as cross-sectional relationships between these foods and systolic and diastolic blood pressure and metabolic markers using data from the Caerphilly Prospective Study. Included in this cohort were 2512 men, aged 45 to 59 years, who were followed up at 5-year intervals for a mean of 22.8 years (number follow-up 787). Augmentation index was 1.8% lower in subjects in the highest quartiles of dairy product intake compared with the lowest (P trend=0.021), whereas in the highest group of milk consumption systolic blood pressure was 10.4 mm Hg lower (P trend=0.033) than in nonmilk consumers after a 22.8-year follow-up. Cross-sectional analyses indicated that across increasing quartiles of butter intake, insulin (P trend=0.011), triacylglycerol (P trend=0.023), total cholesterol (P trend=0.002), and diastolic blood pressure (P trend=0.027) were higher. Across increasing groups of milk intake and quartiles of dairy product intake, glucose (P trend=0.032) and triglyceride concentrations (P trend=0.031) were lower, respectively. The present results confirm that consumption of milk predicts prospective blood pressure, whereas dairy product consumption, excluding butter, is not detrimental to arterial stiffness and metabolic markers. Further research is needed to better understand the mechanisms that underpin these relationships.
Validation of Chinese Version of Self-perceived Employability Scale

Objective:To examine the reliabilities and validities of Chinese version of Self-perceived Employability Scale on employees in our country.Methods:More than 500 employees were selected and surveyed in the research.Results:There were 11 items in Chinese version of Self-perceived Employability Scale,including two subscales:internal employability and external employability.Confirmatory factor analysis showed a good fit to the data.Cronbach's α of the whole scale and its subscales were 0.80,0.66 and 0.74 respectively;Test-retest reliabilities of them were 0.85,0.83 and 0.79 respectively.Conclusion:With acceptable psychometric quality,the Chinese version of Self-perceived Employability Scale can be used to measure the self-perceived employability of employees in China.
Improved Fuzzy C-Means Algorithm for MR Brain Image Segmentation

Segmentation is an important aspect of medical image processing, where Clustering approach is widely used in biomedical applications particularly for brain tumor detection in abnormal Magnetic Resonance Images (MRI). Fuzzy clustering using Fuzzy C- Means (FCM) algorithm proved to be superior over the other clustering approaches in terms of segmentation efficiency. But the major drawback of the FCM algorithm is the huge computational time required for convergence. The effectiveness of the FCM algorithm in terms of computational rate is improved by modifying the cluster center and membership value updation criterion. In this paper, convergence rate is compared between the conventional FCM and the Improved FCM.
Experiencing ASP with Real World Applications

Disjunctive logic programming under answer set semantics (DLP, ASP) is a powerful formalism for knowledge representation and reasoning. The language of DLP is very expressive, and allows for modelling complex combinatorial problems. However, despite the high expressiveness of this language, the success of DLP systems is still dimmed when the applications of interest become data intensive (current DLP systems work only in main memory) or they involve some inherently procedural sub-tasks or the handling of complex data structures. The main goal of this paper is precisely to improve efficiency and usability of DLP systems in these contexts, and verify these improvements by a benchmarking activity on real-world applications. We present a DLP system which: (i) carries out as much as possible of the reasoning tasks in mass memory without degrading performances, thus allowing to deal with data-intensive applications; (ii) extends the expressiveness of DLP with external function calls, yet improving efficiency (at least for procedural sub-tasks) and knowledge-modelling power; (iii) extends the expressiveness of DLP for supporting also the management of recursive data structures (lists). We test the system on four main areas: data-integration, combinatorial problems, data transformation, and string similarity computation. The experimental results are very encouraging: the proposed system can handle significantly larger amounts of data than competitor systems, and it is also faster in response time.
Sharing and Analyzing Presence Experiments Data

Presence research heavily relies on empirical experiments involving subjects in mediated environments. Such experiments can be extremely resource intensive and produce very large amounts of data. As the presence community matures, we would like to suggest that data collected in experiments will be publicly available to the community. This will allow the verification of experimental results, comparing results of experiments carried out in different laboratories, and evaluating new data-analysis methods. In this paper we present the complete data set from a large-scale experiment that we have carried out in highly-immersive virtual reality. We describe the data we have gathered and give examples of the types of analysis that can be made based on that data.
Sparse representation of human auditory system

In this paper, three sparse models for the human auditory system are proposed. Biological studies shows that the haircells in the inner ear of the auditory system generate sparse codes from the output of cochlea filterbank. Here, we employ two mathematical sparse representation methods, which are Orthogonal Matching Pursuit (OMP) and K Singular Value Decomposition (K-SVD), in three different strategies for sparse representation of the output of cochlea filterbank that is modeled by a Gammatone filterbank. Although, we use nearly 5 to 10 percent of the original signal's dimension for sparse representation, experimental results by evaluating reconstruction error and PESQ measures demonstrate good performance of these models in both clean and noisy conditions.
Pedestrian detection for intelligent vehicle based on bilayer difference features algorithm

In this paper, a new powerful pedestrian feature extraction algorithm named bilayer difference feature is proposed. In this new feature, two different features are used for detecting pedestrians and eliminating false alarms respectively. The upper layer of bilayer difference feature is constituted by improved accumulate binary Haar (ABH) feature. ABH feature could enhance the ability of illumination invariance and keep high real-time performance, which is used for fast pedestrian detection and location; while, Edgelet feature could be used for the lower layer of the bilayer difference feature and check the validity of pedestrian detected by ABH feature, reduce the influence of false alarms and occlusion to detection. The experiment carried out on videos from three famous datasets illustrates that the proposed method is real-time and feasible enough for pedestrian detection in intelligent vehicle environment.
Dynamics of User Experience (UX)

User experience (UX) is not a static phenomenon; the way we interact with the technologies is dynamic which evolves over time. Ignoring this temporal nature of UX we cannot fully understand user experience. A longitudinal experiment was conducted over four weeks following 15 individuals using one of four medial players in their daily lives to examine users’ behavior in prolonged use case and to investigate which factors have what type of impact on users’ overall judgments at different point of time. Our analysis suggests that even if non-instrumental (e.g. Aesthetics of interface) quality plays an important role to form users overall judgments during the initial interaction, in prolonged use cage instrumental qualities (i.e. usability, functionality) become more influential. General Terms Human Computer Interaction
Perron-Frobenius spectrum for random maps and its approximation

To study the convergence to equilibrium in random maps we developed the spectral theory of the corresponding transfer (Perron-Frobenius) operators acting in a certain Banach space of generalized functions. The random maps under study in a sense fill the gap between expanding and hyperbolic systems since among their (deterministic) components there are both expanding and contracting ones. We prove stochastic stability of the Perron-Frobenius spectrum and developed its finite rank operator approximations by means of a "stochastically smoothed" Ulam approximation scheme. A counterexample to the original Ulam conjecture about the approximation of the SBR measure and the discussion of the instability of spectral approximations by means of the original Ulam scheme are presented as well.
Chapter 1 SORTING AND SELECTION ON PARALLEL DISK MODELS

Data explosion is an increasingly prevalent problem in every field of science. Traditional out-of-core models that assume a single disk have been found inadequate to handle voluminous data. As a result, models that employ multiple disks have been proposed in the literature. For example, the Parallel Disk Systems (PDS) model assumes D disks and a single computer. It is also assumed that a block of data from each of the D disks can be fetched into the main memory in one parallel I/O operation. In this article, we survey sorting and selection algorithms that have been devised for out-of-core models assuming multiple disks. We also consider practical implementations of parallel disk models.
Large eddy simulation study of scalar transport in fully developed wind-turbine array boundary layers

Wind harvesting is fast becoming an important alternative source of energy. As wind farms become larger, they begin to attain scales at which two-way interactions with the atmospheric boundary layer (ABL) must be taken into account. Several studies have shown that there is a quantifiable effect of wind farms on the local meteorology, mainly through changes in the land-atmosphere fluxes of heat and moisture. In particular, the observed trends suggest that wind farms increase fluxes at the surface and this could be due to increased turbulence in the wakes. Conversely, simulations and laboratory experiments show that underneath wind farms, the friction velocity is decreased due to extraction of momentum by the wind turbines, a factor that could decrease scalar fluxes at the surface. In order to study this issue in more detail, a suite of large eddy simulations of an infinite (fully developed) wind turbine array boundary layer, including scalar transport from the ground surface without stratification, is perf.
GString: A Novel Approach for Efficient Search in Graph Databases

Graphs are widely used for modeling complicated data, including chemical compounds, protein interactions, XML documents, and multimedia. Information retrieval against such data can be formulated as a graph search problem, and finding an efficient solution to the problem is essential for many applications. A popular approach is to represent both graphs and queries on graphs by sequences, thus converting graph search to subsequence matching. State-of-the-art sequencing methods work at the finest granularity - each node (or edge) in the graph will appear as an element in the resulting sequence. Clearly, such methods are not semantic conscious, and the resulting sequences are not only bulky but also prone to complexities arising from graph isomorphism and other problems in searching. In this paper, we introduce a novel sequencing method to capture the semantics of the underlying graph data. We find meaningful components in graph structures and use them as the most basic units in sequencing. It not only reduces the size of resulting sequences, but also enables semantic-based searching. In this paper, we base our approach on chemical compound databases, although it can be applied to searching other complicated graphs, such as protein structures. Experiments demonstrate that our approach outperforms state-of-the-art graph search methods.
Characterization of protein redox dynamics induced during light-to-dark transitions and nutrient limitation in cyanobacteria

Protein redox chemistry constitutes a major void in knowledge pertaining to photoautotrophic system regulation and signaling processes. We have employed a chemical biology approach to analyze redox sensitive proteins in live Synechococcus sp. PCC 7002 cells in both light and dark periods, and to understand how cellular redox balance is disrupted during nutrient perturbation. The present work identified 300 putative redox-sensitive proteins that are involved in the generation of reductant, macromolecule synthesis, and carbon flux through central metabolic pathways, and may be involved in cell signaling and response mechanisms. Furthermore, our research suggests that dynamic redox changes in response to specific nutrient limitations, including carbon and nitrogen limitations, contribute to the regulatory changes driven by a shift from light to dark. Taken together, these results contribute to a high-level understanding of post-translational mechanisms regulating flux distributions and suggest potential metabolic engineering targets for redirecting carbon toward biofuel precursors.
Concurrent ontology and the extensional conception of attribute

By analogy with the extension of a type as the set of individuals of that type, we define the extension of an attribute as the set of states of an idealized observer of that attribute, observing concurrently with observers of other attributes. The attribute-theoretic counterpart of an operation mapping individuals of one type to individuals of another is a dependency mapping states of one attribute to states of another. We integrate attributes with types via a symmetric but not self-dual framework of dipolar algebras or disheaves amounting to a type-theoretic notion of Chu space over a family of sets of qualia doubly indexed by type and attribute, for example the set of possible colors of a ball or heights of buildings. We extend the sheaf-theoretic basis for type theory to a notion of disheaf on a profunctor. Applications for this framework include the Web Ontology Language OWL, UML, relational databases, medical information systems, geographic databases, encyclopedias, and other data-intensive areas standing to benefit from a precise ontological framework coherently accommodating types and attributes.
Radical Resection of Adult Low Grade Oligodendroglioma without Adjuvant Therapy: Results of a Prospective Treatment Protocol —Surgical Treatment of Low-Grade Oligodendroglioma

The goal of this work was to demonstrate prospectively that maximal surgical resection of low grade oligodendrogliomas without adjuvant therapy does not reduce life expectancy over that of historical controls. All patients with surgically accessible grade II oligodendrogliomas underwent maximal resection using stereotactic guidance and/or cortical mapping and were followed with serial MRI scans without adjuvant therapy until either progression or spread into brain regions deemed not surgically resectable. Nineteen patients were treated between 1993 and 2006. Ten patients required reoperation an average of 55 months after their first surgery. Nine patients progressed to anaplastic tumors an average of 42 months after their first surgery: six patients died from their tumors an average of 73 months after diagnosis, two are still alive 76 and 18 months after progression, and one was lost to follow up. Ten patients are alive and progression-free an average of 116 months after diagnosis, one of whom was lost to follow up at 106 months from diagnosis. Four patients are alive and event-free an average of 125 months after diagnosis. All are male and three had tumors in the superior frontal gyrus. The event-free survival, progression-free survival, and overall survival of our patients are not worse than those of patients treated with postoperative adjuvant therapy. Withholding adjuvant therapy at diagnosis appears to be safe. It will be important to establish the molecular differences between the patients who did very well and those who progressed so that adjuvant therapy could be offered to the latter.
The response of eye-movement and pupil size to audio instruction while viewing a moving target

Eye movement reflects a viewer's visual information process. This study examines whether eye-movement responds to the viewer's cognitive load. It is already known that pupil size and blink can use as an indicator of mental workload. Saccades are rapid eye movements to turn a fovea to a focusing target. For this process, saccade was extracted to observe viewing process. The ocular-following task was conducted with audio-response task. The moving target was controlled at visual angle 3deg 5deg and 10deg. Audio response task required oral response. Experimental results showed that pupil size and blink rate increased with visual angle and audio response task. Both increased largest when the subject gave incorrect response in audio response task. Eye movement was also controlled by certain factors. Saccadic movement time increased with visual angle and it had negative correlation to blink time. This relationship was observed in larger visual angle, but despite of this negative correlation, saccadic movement time increased in incorrect response. Furthermore saccade length increased with the visual angle and decreased in incorrect response. The saccade is divided into miniature saccade appearing in gaze area, and larger saccade appearing between gazes. In incorrect response, saccade in following targets decreased and saccade inside gazing targets increased. It suggests that saccade occurrence changes not only in following targets but also inside gazing targets. The results of these experiments provide evidence that eye-movement can be an index of mental work-load.
Striatal Neuronal Activity and Responsiveness to Dopamine and Glutamate after Selective Blockade of D1 and D2 Dopamine Receptors in Freely Moving Rats

Although striatal neurons receive continuous dopamine (DA) input, little information is available on the role of such input in regulating normal striatal functions. To clarify this issue, we assessed how systemic administration of selective D1 and D2 receptor blockers or their combination alters striatal neuronal processing in freely moving rats. Single-unit recording was combined with iontophoresis to monitor basal impulse activity of dorsal and ventral striatal neurons and their responses to glutamate (GLU), a major source of excitatory striatal drive, and DA. SCH-23390 (0.2 mg/kg), a D1 antagonist, strongly elevated basal activity and attenuated neuronal responses to DA compared with control conditions, but GLU-induced excitations were enhanced relative to control as indicated by a reduction in response threshold, an increase in response magnitude, and a more frequent appearance of apparent depolarization inactivation. In contrast, the D2 antagonist eticlopride (0.2 mg/kg) had a weak depressing effect on basal activity and was completely ineffective in blocking the neuronal response to DA. Although eticlopride reduced the magnitude of the GLU response, the response threshold was lower, and depolarization inactivation occurred more often relative to control. The combined administration of these drugs resembled the effects of SCH-23390, but whereas the change in basal activity and the GLU response was weaker, the DA blocking effect was stronger than SCH-23390 alone. Our data support evidence for DA as a modulator of striatal function and suggest that under behaviorally relevant conditions tonically released DA acts mainly via D1 receptors to provide a continuous inhibiting or restraining effect on both basal activity and responsiveness of striatal neurons to GLU-mediated excitatory input.
The power of student empowerment: Measuring classroom predictors and individual indicators

ABSTRACT Despite spending more money per student than almost all developed nations, the United States lags behind in educational indicators with persistent disparities between privileged and marginalized students. Most approaches have ignored the role of power dynamics in predicting student performance. Building on the existing literature in school climate and empowering settings, this study explored the construct of student empowerment to identify both environmental factors that predict increased empowerment and outcomes associated with empowerment. A survey was administered to 381 students from five urban high schools. Results suggest that intrapersonal student empowerment is predicted by equitable power use by teachers, positive teacher–student relationships and a sense of community in the classroom. Highly empowered students reported better grades, fewer behavioral incidents, increased extracurricular participation and higher educational aspirations than students who were less empowered. Limitations are discussed alongside implications for educational practice and future research.