Miracle-dz/UniFAR-FTUs huggingface dataset:
Anxiety before dental surgery under local anesthesia: reducing the items on state anxiety in the State-Trait Anxiety Inventory-form X

Background It is important to evaluate preoperative anxiety and prepare sedation when performing dental surgery under local anesthesia. Spielberger's State-Trait Anxiety Inventory (STAI) is useful for predicting preoperative anxiety. State anxiety is defined as a subjective feeling of nervousness. Reduction in the number of the state anxiety items (questions) will be clinically important in allowing us to predict anxiety more easily. Methods We analyzed the STAI responses from 1,252 patients who visited our institution to undergo dental surgery under local anesthesia. Multiple linear regression analysis was conducted for 9 groups comprising anxiety level determinations using the STAI; we then developed a coefficient of determination and a regression formula. We searched for a group satisfying the largest number of requirements for regression expression while setting any necessary conditions for accurately predicting anxiety before dental surgery under local anesthesia. Results The regression expression from the group determined as normal for preoperative state anxiety was deemed the most suitable for predicting preoperative anxiety. Conclusions It was possible to reduce the number of items in the STAI by focusing on “Preoperative anxiety before dental surgery. ”
Cycle spaces in topological spaces

We develop a general model of edge spaces in order to generalize, unify, and simplify previous work on cycle spaces of infinite graphs. We give simple topological criteria to show that the fundamental cycles of a (generalization of a) spanning tree generate the cycle space in a connected, compact, weakly Hausdorff edge space. Furthermore, in such a space, the orthogonal complement of the bond space is the cycle space. This work unifies the two different notions of cycle space as introduced by Diestel and Kühn [Combinatorica 24 (2004), 68–89 and Eur J Combin 25 (2004), 835–862] and by Bonnington and Richter [J Graph Theory 44 (2003), 132–147]. © 2008 Wiley Periodicals, Inc. J Graph Theory 59: 115–144, 2008
Number of parallel fiber synapses on an individual Purkinje cell in the cerebellum of the rat

In the present study, stereological techniques applied to electron micrographs of the molecular layer of the rat cerebellum have been used to estimate the number of parallel fiber synapses on the dendritic tree of a single Purkinje cell. Quantitative features of the parallel fiber to Purkinje cell dendritic spine synapses and of the parallel fibers were investigated as a preliminary to estimating the number of synapses. Parallel fiber to Purkinje cell synapses are flattened disclike structures with a mean axial ratio of 1.47 and a mean diameter of 319 μm in fixed tissue. The density of synapses in our fixed material was 8.17 × 108 per μl of molecular layer. Determination of the length density of the synapses per unit area of micrograph indicated a synapse density of 8.03 × 108 per μl. These densities give a total number of synapses per Purkinje cell of 1.74 × 105 and 1.71 × 105, respectively. Estimation of the number of parallel fiber varicosities and of varicosity length gave a density of 9.31 × 108 varicosities per μl of molecular layer and determining the mean number of parallel fiber to Purkinje cell synapses per varicosity gave a synapse density of 9.82 × 108 per μl, equivalent to 2.09 × 105 per Purkinje cell. The reasons why this estimate is likely to be too high are discussed. We conclude that there are some 175,000 parallel fiber synapses on an individual Purkinje cell dendritic tree in the cerebellar cortex of the rat, considerably more than previously reported.
Study of Joint MMSE Consensus and Relay Selection Algorithms for Distributed Beamforming

This work presents joint minimum mean-square error (MMSE) consensus algorithm and relay selection algorithms for distributed beamforming. We propose joint MMSE consensus relay and selection schemes with a total power constraint and local communications among the relays for a network with cooperating sensors. We also devise greedy relay selection algorithms based on the MMSE consensus approach that optimize the network performance. Simulation results show that the proposed scheme and algorithms outperform existing techniques for distributed beamforming.
Enhancing scatterplots with smoothed densities

MOTIVATION Scatterplots of microarray data generally contain a very large number of dots, making it difficult to get a good impression of their distribution in dense areas. RESULTS We present a fast and simple algorithm for two-dimensional histogram smoothing, to visually enhance scatterplots. AVAILABILITY Functions for Matlab and R are available from the corresponding author.
Effects of Aging Stereotype Threat on Working Self-Concepts: An Event-Related Potentials Approach

Although the influence of stereotype threat (ST) on working self-concepts has been highlighted in recent years, its neural underpinnings are unclear. Notably, the aging ST, which largely influences older adults’ cognitive ability, mental and physical health, did not receive much attention. In order to investigate these issues, electroencephalogram (EEG) data were obtained from older adults during a modified Stroop task using neutral words, positive and negative self-concept words in aging ST vs. neutral control conditions. Results showed longer reaction times (RTs) for identifying colors of words under the aging ST compared to the neutral condition. More importantly, the negative self-concept elicited more positive late P300 amplitudes and enhanced theta band activities compared to the positive self-concept or neutral words under the aging ST condition, whereas no difference was found between these self-concepts and neutral words in the control condition. Furthermore, the aging ST induced smaller theta band synchronization and enhanced alpha band synchronization compared to the control condition. Moreover, we also observed valence differences in self-concepts where the negative self-concept words reduced early P150/N170 complex relative to neutral words. These findings suggest that priming ST could activate negative self-concepts as current working self-concept, and that this influence occurred during a late neural time course.
Fabrication of micro structures on curve surface by X-ray lithography

We demonstrate experimentally the x-ray lithography techniques to fabricate micro structures on curved surfaces such as convex and cylinder surfaces. In order to realize fabricate micro structures on curved surface, two x-ray lithography methods are described. One method is double x-ray exposures method with moving resist stage, the other is flexible mask on curved surface with rotating the resist stage. We also describe two new methods for fabricating a curved surface. One is direct x-ray exposure and the curved surface was obtained by using x-ray Gaussian intensity distribution without LIGA mask. The other one is to produce the concave surface by PCT (Plane Cross section Transfer) method. We believed that the two techniques can also transfer large area submicron size patterns, with a continuous surface relief, onto a curved surface. Research Organization of Science and Engineering, Ritsumeikan University, Kusatsu, Shiga
Real-Time Animation of Objects Modelled using Constructive Solid Geometry

Computer graphics have long been used to help people visualise complex entities such as machine components and assemblies. Systems such as Computer-Aided Design (CAD) applications allow the creation of models and designs for objects by providing interactive tools that can be manipulated by designers. An important facet of interactive design is that it should be possible to see the effects of changes made on models immediately, i.e. in real-time. In this paper we are interested in applications where renderings of complex objects, modelled using Constructive Solid Geometry (CSG), can be updated quickly enough to allow interactive use. The algorithms developed in this paper to allow real-time rendering of CSG-based objects require no specialised hardware or software to perform their tasks. They merely need a display adapter with stencil buffer support, and a graphics language capable of manipulating the colour, depth and stencil buffers provided by the display hardware. They can be implemented on low-cost PClevel systems and still prove capable of generating the required number of frames per second to allow real-time screen updates of CSG-modelled objects. Through empirical studies and observation we have identified that the algorithms developed here provide better performance than equivalent algorithms.
Demo: Platform for Collecting Data From Urban Sensors Using Vehicular Networking

A large-scale urban sensing platform, composed of multiple Data Collection Units (DCUs) equipped with sensor hardware scattered accross the city, allows pervasive monitoring of environmental parameters. Gathering sensor data from a number of disparate locations at a backend server can be supported by delay-tolerant services provided by existing vehicular networks. Our real-world sensing platform takes advantage of an existing vehicular network with more than 400 vehicles equipped with On-Board Units (OBUs). A purposely-developed implementation of a delay tolerant service is installed in all elements involved in the communication flow, from DCUs to the backend server. In this demo, we showcase the full end-to-end data flow with the actual equipment being used in our real-world deployment. Data produced at a DCU is collected by an OBU installed in a vehicle and delivered to a Road-Side Unit (RSU), which then forwards the data to the backend server.
Fatal complications of endoscopic ultrasonography: a look at 18 cases

Endoscopic ultrasonography (EUS) is perceived and reported to be a very safe procedure, at least in expert hands. Biennial assessment of all EUS procedures done in Israel since 1999 shows 8 cases of fatal EUS complications out of a total of 20000 procedures. In seven of the eight cases tears of the duodenum were involved (all occur− ring with linear−type echoendoscopes); none in− volved fine−needle aspiration biopsy (FNA). Duo− denal diverticuli were noted in four of the eight cases. Limited experience with linear echoendo− scopes on the part of the operator (around 100 procedures or fewer) was common (five of the eight cases).
Exploring Knowledge Bases for Similarity

Graph-based similarity over WordNet has been previously shown to perform very well on word similarity. This paper presents a study of the performance of such a graph-based algorithm when using different relations and versions of Wordnet. The graph algorithm is based on Personalized PageRank, a random-walk based algorithm which computes the probability of a random-walk initiated in the target word to reach any synset following the relations in WordNet (Haveliwala, 2002). Similarity is computed as the cosine of the probability distributions for each word over WordNet. The best combination of relations includes all relations in WordNet 3.0, included disambiguated glosses, and automatically disambiguated topic signatures called KnowNets. All relations are part of the official release of WordNet, except KnowNets, which have been derived automatically. The results over the WordSim 353 dataset show that using the adequate relations the performance improves over previously published WordNet-based results on the WordSim353 dataset (Finkelstein et al., 2002). The similarity software and some graphs used in this paper are publicly available at http://ixa2.si. ehu.es/ukb.
Exploiting human anatomical variability as a link between genome and cognome

Although talents and disabilities appear to run in families, direct links between genes and cognitive ability are difficult to establish. Investigators are currently searching for intermediate phenotypes with plausible links to both genome and cognome (the cognitive phenotype). Cortical anatomy could provide one such intermediate phenotype. Variation in cortical size, asymmetry and sulcal pattern is influenced by genetic variation in neurotrophic factors and can predict variation in verbal and mathematical talent. Anecdotal evidence suggests that individuals with a rare morphological variant of Sylvian fissure sometimes have superior visualization ability combined with verbal deficits. Documentation of such ‘cognitive cortical syndromes’ might prove as genetically informative as the identification of dysmorphic syndromes associated with mental retardation. A necessary prerequisite for the establishment of such syndromes is a reliable technique for the identification of cortical patterns. Recent technical advances in software for automatically labeling and measuring cortical sulci now provide the possibility of establishing standard measures for their shape, size and location. Such measures are a prerequisite for genetic studies of cortical patterns that could illuminate the neurodevelopmental pathways by which genes affect cognitive ability.
An agent-based electronic market simulator enhanced with ontology matching services and emergent social networks

AEMOS is a simulator which aims to support the development of agent-based electronic markets capable of dealing with the natural semantic heterogeneity existent in this kind of environment. AEMOS simulates a marketplace which provides ontology matching services, enhanced with the exploitation of emergent social networks, enabling an efficient and transparent communication between agents, even when they use different ontologies. The system recommends possible alignments between the agents' ontologies, and lets them negotiate and decide which alignment should be used to translate the exchanged messages. In this paper we propose a new ontology alignment negotiation process, which promotes the reutilisation and combination of already existing alignments, as well as the involvement of business agents in the alignment composition process. With this new model, we aim to achieve a higher adequacy of the used alignments, as well as a more accurate and trustful evaluation of the alignments.
Allergic Airway Inflammation Decreases Lung Bacterial Burden following Acute Klebsiella pneumoniae Infection in a Neutrophil- and CCL8-Dependent Manner

ABSTRACT The Th17 cytokines interleukin-17A (IL-17A), IL-17F, and IL-22 are critical for the lung immune response to a variety of bacterial pathogens, including Klebsiella pneumoniae. Th2 cytokine expression in the airways is a characteristic feature of asthma and allergic airway inflammation. The Th2 cytokines IL-4 and IL-13 diminish ex vivo and in vivo IL-17A protein expression by Th17 cells. To determine the effect of IL-4 and IL-13 on IL-17-dependent lung immune responses to acute bacterial infection, we developed a combined model in which allergic airway inflammation and lung IL-4 and IL-13 expression were induced by ovalbumin sensitization and challenge prior to acute lung infection with K. pneumoniae. We hypothesized that preexisting allergic airway inflammation decreases lung IL-17A expression and airway neutrophil recruitment in response to acute K. pneumoniae infection and thereby increases the lung K. pneumoniae burden. As hypothesized, we found that allergic airway inflammation decreased the number of K. pneumoniae-induced airway neutrophils and lung IL-17A, IL-17F, and IL-22 expression. Despite the marked reduction in postinfection airway neutrophilia and lung expression of Th17 cytokines, allergic airway inflammation significantly decreased the lung K. pneumoniae burden and postinfection mortality. We showed that the decreased lung K. pneumoniae burden was independent of IL-4, IL-5, and IL-17A and partially dependent on IL-13 and STAT6. Additionally, we demonstrated that the decreased lung K. pneumoniae burden associated with allergic airway inflammation was both neutrophil and CCL8 dependent. These findings suggest a novel role for CCL8 in lung antibacterial immunity against K. pneumoniae and suggest new mechanisms of orchestrating lung antibacterial immunity.
An Evaluation of Alternative Feature Selection Strategies and Ensemble Techniques for Classifying Music

Automatic annotation of music files is a key problem in multimedia information retrieval. In this paper we present a solution to this problem that addresses the issues of feature extraction, feature selection and design of classifier. We outline a process for feature extraction based on the discrete wavelet packet transform and we evaluate a variety of wrapper-based feature subset selection strategies that use feature ranking based on information gain , gain ratio and principle components analysis. We evaluate four alternative classifiers; simple k -nearest neighbour and o ne-against-all , round-robin and feature-subspace based ensembles of nearest neighbour classifiers. The best classification accuracy is achieved by the feature subspace-based ensemble with the round-robin ensemble also showing considerable promise.
Weakly Supervised Approaches for Ontology Population

We present a weakly supervised approach to automatic ontology population from text and compare it with two other unsupervised approaches. In our experiments we populate a part of our ontology of Named Entities. We considered two high level categories-geographical locations and person names and ten sub-classes for each category. For each sub-class we automatically learn a syntactic model from a list of training examples and a parsed corpus. A novel syntactic indexing method allowed us to use large quantities of syntactically annotated data. The syntactic model for each named entity sub-class is a set of weighted syntactic features, i.e. words which typically co-occur with the members of the class in the corpus. The method is weakly supervised, since no manually annotated corpus is used in the learning process. The syntactic models are used to classify the unknown Named Entities in the test set. The method achieved promising results, i.e. 65% accuracy, and outperforms significantly the other two approaches.
Social Network Analysis of Tweets on Typhoon during Haiyan and Hagupit

Social media sites have become a platform for interaction during disaster and emergency situations. Twitter, for instance, is found to be one of the top preferred for sharing and seeking information. To reveal more information about the interaction of users regarding a specific event or topic, Social Network Analysis (SNA) is utilized. Content analysis and SNA have been implemented on the tweets regarding different situations to be able to understand and depict a visual representation of interaction between users. In this study, SNA was employed to reveal the user interaction of the Filipino community between two major typhoons that hit the Philippines. Similarities and differences were revealed by the social networks that were derived. Results also revealed that users tend to seek and share information from reliable sources such as news websites and verified Twitter users. Determining the interaction of Twitter users in an online community plays a vital role in information dissemination and allows appropriate response during disaster and emergency situations.
The Research on the Detection of Noteworthy Symptom Descriptions

The advance of mobile devices and communication technologies enable patients to communicate with their doctors in a more convenient way. We have developed an App that allows patients to record their symptoms and submit them to their doctors. Physicians can keep track of patients’ conditions by looking at the self-report messages. Nevertheless, physicians are usually busy and may be overwhelmed by the large amount of incoming messages. As a result, critical messages may not receive immediate attentions, and patient care is compromised. It is imperative to identify the messages that require physicians’ attention, called noteworthy messages. In this research, we propose an approach that applies text-mining technologies to identify medical symptoms conveyed in the messages and their associated sentiment orientation, as well as other factors. Noteworthy messages are subsequently characterized by symptom sentiment and symptom change features. We then construct a prediction model to identify messages that are noteworthy to the physicians. We show from our experiments using data collected from a teaching hospital in Taiwan that the different features have different degrees of impact on the performance of the prediction model, and our proposed approach can effectively identify noteworthy messages.
Musculo-skeletal shape skinning

A method for use in animation includes establishing a model having a plurality of bones with muscles attached to the bones, binding skin to the muscles when the model is in a first pose with each vertex of the skin being attached at a first attachment point on a muscle, deforming the model into a second pose, and selecting a second attachment point for each vertex of the skin in the second pose. A storage medium stores a computer program for causing a processor based system to execute these steps, and a system for use in animation includes a processing system configured to execute these steps.
The Analysis of Nash Equilibria of the One-Shot Random-Access Game for Wireless Networks and the Behavior of Selfish Nodes

We address the fundamental question of whether or not there exist stable operating points in a network in which selfish nodes share a common channel, and if they exist, how the nodes behave at these stable operating points. We begin with a wireless communication network in which n nodes (agents), which might have different utility functions, contend for access on a common, wireless communication channel. We characterize this distributed multiple-access problem in terms of a one-shot random-access game, and then analyze the behavior of the nodes using the tools of game theory. We give necessary and sufficient conditions on nodes for the complete characterization of the Nash equilibria of this game for all n ges 2. We show that all centrally controlled optimal solutions are a subset of this game theoretic solution, and almost all (w.r.t. Lebesgue measure) transmission probability assignments chosen by a central authority are supported by the game theoretic solution. We analyze the behavior of the network throughput at Nash equilibria as a function of the costs of the transmitters incurred by failed transmissions. Finally, we conclude the paper with the asymptotic analysis of the system as the number of transmitters goes to infinity. We show that the asymptotic distribution of the packet arrivals converges in distribution to a Poisson random variable, and the channel throughput converges to -(c/(1+c))ln(c/(1+c)) with c > 0 being the cost of failed transmissions. We also give the best possible bounds on the rates of convergence of the packet arrival distribution and the channel throughput.
Parameters-tuning of PID controller for automatic voltage regulators using the African buffalo optimization

In this paper, an attempt is made to apply the African Buffalo Optimization (ABO) to tune the parameters of a PID controller for an effective Automatic Voltage Regulator (AVR). Existing metaheuristic tuning methods have been proven to be quite successful but there were observable areas that need improvements especially in terms of the system’s gain overshoot and steady steady state errors. Using the ABO algorithm where each buffalo location in the herd is a candidate solution to the Proportional-Integral-Derivative parameters was very helpful in addressing these two areas of concern. The encouraging results obtained from the simulation of the PID Controller parameters-tuning using the ABO when compared with the performance of Genetic Algorithm PID (GA-PID), Particle-Swarm Optimization PID (PSO-PID), Ant Colony Optimization PID (ACO-PID), PID, Bacteria-Foraging Optimization PID (BFO-PID) etc makes ABO-PID a good addition to solving PID Controller tuning problems using metaheuristics.