Miracle-dz/UniFAR-FTUs huggingface dataset:
Susceptibility-weighted MRI of extrapyramidal brain structures in Parkinsonian disorders

AbstractSusceptibility-weighted MRI (SWI) is sensitive to T2* effects and mineralization.We investigated differences in the extrapyramidal brain structures on SWI between Parkinson disease (PD) and postural instability gait disorder (PIGD) patients and correlated the SWI values with the degree of gait dysfunction.Forty patients diagnosed with PD and PIGD underwent 3 Tesla magnetic resonance imaging (MRI) brain study. An SWI sequence (TE/TR/FA 20/33/15) was used. Ten regions of interest were placed in the midbrain and basal ganglia by 2 independent raters blinded to subject data and quantitatively evaluated.The inter-rater reliability between the raters was excellent (interclass correlation coefficient >0.8). The SWI intensity values in all regions were on average lower in PIGD than in PD patients, with the lowest results found in globus pallidus.Multivariate analysis showed a lower SWI hypointensity in the putamen and globus pallidus in PIGD compared with PD patients, with a similar trend for the other basal ganglia nuclei. Pearson correlation analysis showed a statistically significant positive correlation between SWI putaminal hypointensity and the Tinetti total score (r = 0.39, P = 0.01) in both PD and PIGD.SWI putaminal hypointensity may be a useful imaging marker in prospective evaluation for clinical progression for Parkinsonian disorders.
An Identity-Based Matching Theory Approach to Integration

Abstract This paper aims to explain immigration and integration behavior in complex economic system using a framework that emphasizes social identity mechanisms. Immigration concerns individuals’ move from one society to another. Integration concerns the evolution of migrants’ identities and of consequent behaviors in the matching processes between immigrants and social groups in host countries. I suggest that we switch the basis for motivation to form matching from price to social identities and explain migrants’ interactions in host countries in individual-to-group types of interactions rather than the individual-to-individual types of interactions that standard approach employs. Thus, I propose a shift from an isolated individual economic approach through the market mechanism to an identity-based matching theory approach to integration.
Physical properties of palm fruits processed with tools by wild bearded capuchins (Cebus libidinosus)

Habitually, capuchin monkeys access encased hard foods by using their canines and premolars and/or by pounding the food on hard surfaces. Instead, the wild bearded capuchins (Cebus libidinosus) of Boa Vista (Brazil) routinely crack palm fruits with tools. We measured size, weight, structure, and peak‐force‐at‐failure of the four palm fruit species most frequently processed with tools by wild capuchin monkeys living in Boa Vista. Moreover, for each nut species we identify whether peak‐force‐at‐failure was consistently associated with greater weight/volume, endocarp thickness, and structural complexity. The goals of this study were (a) to investigate whether these palm fruits are difficult, or impossible, to access other than with tools and (b) to collect data on the physical properties of palm fruits that are comparable to those available for the nuts cracked open with tools by wild chimpanzees. Results showed that the four nut species differ in terms of peak‐force‐at‐failure and that peak‐force‐at‐failure is positively associated with greater weight (and consequently volume) and apparently with structural complexity (i.e. more kernels and thus more partitions); finally for three out of four nut species shell thickness is also positively associated with greater volume. The finding that the nuts exploited by capuchins with tools have very high resistance values support the idea that tool use is indeed mandatory to crack them open. Finally, the peak‐force‐at‐failure of the piassava nuts is similar to that reported for the very tough panda nuts cracked open by wild chimpanzees; this highlights the ecological importance of tool use for exploiting high resistance foods in this capuchin species. Am. J. Primatol. 70:884–891, 2008. © 2008 Wiley‐Liss, Inc.
Reparameterization trick for discrete variables

Low-variance gradient estimation is crucial for learning directed graphical models parameterized by neural networks, where the reparameterization trick is widely used for those with continuous variables. While this technique gives low-variance gradient estimates, it has not been directly applicable to discrete variables, the sampling of which inherently requires discontinuous operations. We argue that the discontinuity can be bypassed by marginalizing out the variable of interest, which results in a new reparameterization trick for discrete variables. This reparameterization greatly reduces the variance, which is understood by regarding the method as an application of common random numbers to the estimation. The resulting estimator is theoretically guaranteed to have a variance not larger than that of the likelihood-ratio method with the optimal input-dependent baseline. We give empirical results for variational learning of sigmoid belief networks.
From Living Space to Cultural Space: How a Modern University Academy System is Possible

Abstract The reforms on the modern university academy system that preserve certain elements of China’s ancient traditional academies have currently encountered a series of difficulties. The crux of the problem is that living and educational spaces were integrated in the traditional academy, while modern school education institution has separated the two. So the modern university academy system only inherits the spatial form of the traditional academy. To resolve these difficulties requires creatively preserving the spirit rather than the form of the traditional academy, systemically innovating in institutions such as the advisor system, general education curriculum, and association activities, and also exploring mechanisms for academies to coordinate with professional schools and university student affairs.
Exploring the function of discussion forums in MOOCs: comparing data mining and graph-based approaches

In this paper we present an analysis (in progress) of a dataset containing forum exchanges from three different MOOCs. The forum data is enhanced because together with the exchanges and the full text, we have a description of the design and pedagogical function of forums in these courses and a certain level of detail about the users, which includes achievement, completion, and in some instances more details such as: education; employment; age; and prior MOOC exposure. Although a direct comparison between the datasets is not possible because the nature of the participants and the courses are different, what we hope to identify using graph-based techniques is a characterization of the patterns in the nature and development of communication between students and the impact of the ‘teacher presence’ in the forums. With the awareness of the differences, we hope to demonstrate that student engagement can be directed ‘bydesign’ in MOOCs: teacher presence should therefore be planned carefully in the design of large-scale courses.
Modelling Language for Tabletop Hybrid Videogames

This work presents ToyVision TUIML, a Tangible User Interface Modeling Language that enables interaction designers to ideate and express hybrid games for tabletop devices (computer games based on the physical manipulation of playing pieces over an active horizontal surface). This language is based on a hierarchical visual representation of all the playing pieces involved in the game, the meaning of the physical manipulations, and the relationships between playing pieces that players will establish during the game. This representation is used as a bridge between the design and the implementation processes, as it can be automatically translated into a computer understandable language such as XML. This paper also details a user test with interaction designers, who ideated and prototyped innovative playing pieces for tabletop hybrid games, with the support of ToyVision TUIML.
Integrated baby-care recommender platform based on hybrid commonsense reasoning and case-based reasoning algorithms

To get baby care and medical-relative information via search engine from website is becoming a trend. However, nowadays, search engine for such information retrieve is almost “single-shot” searching process. Users are only allowed to input target queries at beginning which is inconsistent with human decision process in reality practice. This work proposed an integrated Baby Care (iBC) platform based on commonsense reasoning (CR) and cased base reasoning (CBR) algorithms. iBC enables users to retrieve baby-care information and share baby-care experience and knowledge. Additionally, iBC provide user with babysitter matching mechanism. For both babysitter information and medical treatment recommendation, iBC can actually replicate real world decision making interactive process. Finally, to validate the feasibility and effectiveness of the proposed iBC platform, a demonstrated scenario is presented. iBC can deal with 10 usual infant diseases and provide four treatments recommendation from traditional Chinese medical, modern medical and experienced treatment aspects. iBC is an integrative baby care knowledge platform that enables newbie mothers to share baby-care experience and information that improve baby-care quality.
CESNET Technical Report 9 / 2002 Overview of Data Structures in IP Lookups

This report sums up various available methods to find the best matching prefix (BMP) of a string especially for the purpose of IP address lookup in routers. The router decides what to do with an incoming packet according to the longest matching prefix in its routing table. This report does not contain any original methods nor results, it is intended purely as an overview. The method to be used in a router to achieve high performance should satisfy several conceptual conditions (adapted from (Crescenzi et al., 1999)): • it should work for any placement of the router in the Internet, both edge and backbone routers, • it should be useful for a long period of time, as hardware implementation is much more difficult and expensive than software one, • the most important cost is the number of memory accesses, • it should be easily implemented in hardware.
Exploring fact-focused relevance and novelty detection

Purpose – Automated sentence‐level relevance and novelty detection would be of direct benefit to many information retrieval systems. However, the low level of agreement between human judges performing the task is an issue of concern. In previous approaches, annotators were asked to identify sentences in a document set that are relevant to a given topic, and then to eliminate sentences that do not provide novel information. This paper aims to explore a new approach in which relevance and novelty judgments are made within the context of specific, factual information needs, rather than with respect to a broad topic.Design/methodology/approach – An experiment is conducted in which annotators perform the novelty detection task in both the topic‐focused and fact‐focused settings.Findings – Higher levels of agreement between judges are found on the task of identifying relevant sentences in the fact‐focused approach. However, the new approach does not improve agreement on novelty judgments.Originality/value – The.
Robust DTW-based recognition algorithm for hand-held consumer devices [speech recognition]

This work presents a new dynamic programming (DP)-based recognition algorithm that is quite suitable for menu-driven recognition applications with small vocabulary size (typically less than 50). In terms of computational complexity and parameter file size, the proposed algorithm shows improved results for a command recognition system with small vocabulary size than the conventional hidden Markov model (HMM)-based recognizer. In addition, the proposed algorithm shows much higher recognition accuracy compared to the conventional dynamic time warping (DTW)-based recognizer.
Detailed Investigation of the Effects of Color on Human Overt Attention

Acknowledgements I would like to thank those who made this thesis possible and helped me to get it into its final state: Hans-Peter Frey for his enthusiastic support, helpful comments and his patience. Peter König for providing a great atmosphere at the Neurobiopsychology work group that made working on this thesis possible as well as enjoyable, and for his suggestions on how to analyze my data. Cornell for the great teamwork during data acquisition and for all the additional work he had to do so I could find time to write this. Niklas, above all other things that I am also grateful for, for actually making me finish. My father, Carolin and especially Kai for their comments on the draft. All the others who don't mind me not writing their names here and making the whole thing look ridiculous. I still thank you. Abstract 3 Abstract We investigated the influence of colors on human overt attention. To this end, we acquired eye-tracking data in a paradigm developed by Willenbockel(2006). The colors on images taken in Kibale rainforest in Uganda were systematically altered without affecting any other image properties such as luminance or edges. This was achieved by rotating the hue of each pixel by a certain angle around the luminance axis of DKL color space. Fixation data of 24 subjects was recorded on those images and pooled with Willenbockel's data coming from 12 subjects. Her results suggested that those color changes do not have an influence on fixations, but that subjects look at the same image locations in all conditions. However, there seemed to be some minor deviations from this pattern. For example, clockwise rotation yielded slightly different feature values at fixations than counterclockwise rotation. This asymmetry was to be examined an if possible explained. We did find an asymmetry in our data as well, but were able to explain it as a result of image properties. Therefore, the hypothesis that similar image locations are fixated regardless of condition was not challenged. We also calculated a measure of fixation constancy across subjects and compared the values of our subjects to those from subjects of a different study (Honey, 2006) who had seen the same images without changes in color. Again our hypothesis was supported; fixation constancy was the same for our subjects as for Honey's subjects, although our subjects had seen the images in different conditions. We conclude that absolute …
#Connected: Facebook May Facilitate Face-to-Face Relationships for Introverts

Many fear that social networking sites (SNSs) are disconnecting people from meaningful face-to-face relationships. Nevertheless, previous research suggests that SNS use is related to increased face-to-face communication. The present study was conducted to determine whether personality traits and attachment styles moderate this relationship. Students (n = 855) completed an online survey that included measures of Facebook use, time spent engaging in face-to-face communication, personality traits, and attachment styles. The results revealed that Facebook use was associated with increased face-to-face communication and that this relationship was moderated by extraversion. Specifically, the relationship between Facebook use and face-to-face communication was significant for individuals with low to moderate levels of extraversion (i.e., introverts) only. As extraversion increased, the magnitude of the relationship between Facebook use and face-to-face time decreased. No other personality traits or attachment styles significantly moderated the relationship between Facebook use and face-to-face communication. Facebook (and potentially SNSs more generally) may be especially beneficial for introverts by allowing them to build trust and rapport in a less threatening social environment that, in turn, makes them more comfortable engaging in face-to-face communication. However, research is needed to understand the direction and mechanisms underlying this relationship. Nevertheless, the present study provides novel insights into the beneficial role that Facebook may play in connecting people in the real world.
THE META-METHOD: AN EXPERIMENTAL EVALUATION OF A THREE-SIDED DIDACTICAL APPROACH TO REINFORCE METACOGNITION AMONG SECONDARY SCHOOL STUDENTS

To stimulate learning, both cognitive and metacognitive strategies are believed to be effective. This contribution reports on the experimental evaluation of an approach to develop metacognitive skills among students in secondary school. In the experiment 653 students of two schools and three age levels (14-15-16) participated. They experienced in their math and economics classes the three aspects of the META-method: metacognitive charts, mindmapping and exchanging opinions on metacognitive theory. The method intends to stimulate stepwise metacognitive thinking, by letting students develop mindmaps and metacognitive charts in class. The attention given to metacognitive theory is meant to foster this learning process supplying the students with scientific insights on brain functioning and learning. The experiment shows promising results, clearly improving the self-reported metacognitive practice and skills like self-regulation, elaboration and critical thinking among the intervention students. Yet, regarding the cognitive outcomes (math tests), it reveals statistically significant effects only for students in the second quartile, i.e. students who –in the pretest- performed below average, but not dramatically so. For other students the method does not improve, neither harm the learning outcomes. This result is more modest than earlier, small-scale experiments, which may stem from incomplete adoption of the method by teachers, who report to need more time to incorporate the method in their teaching practice. Future longer term research will be able to confront this issue.
Continuous Pose Normalization for Pose-Robust Face Recognition

Pose variation is a great challenge for robust face recognition. In this paper, we present a fully automatic pose normalization algorithm that can handle continuous pose variations and achieve high face recognition accuracy. First, an automatic method is proposed to find pose-dependent correspondences between 2-D facial feature points and 3-D face model. This method is based on a multi-view random forest embedded active shape model. Then we densely map each pixel in the face image onto the 3-D face model and rotate it to the frontal view. The filling of occluded face regions is guided by facial symmetry. Recognition experiments were conducted on the two western databases CMU-PIE, FERET and one eastern database CAS-PEAL. Currently the algorithm has been trained with pose variation up to ±50° in yaw. Our algorithm not only achieves high recognition accuracy for learnt poses but also shows good generalizability for extreme poses. Furthermore, it suggests the promising application to people of different races.
Recurrent competitive networks can learn locally excitatory topologies

A common form of neural network consists of spatially arranged neurons, with weighted connections between the units providing both local excitation and long-range or global inhibition. Such networks, known as soft-winner-take-all networks or lateral-inhibition type neural fields, have been shown to exhibit desirable information-processing properties including balancing the influence of compatible inputs, deciding between incompatible inputs, signal restoration from noisy, weak, or overly strong input, and the ability to be used as trainable building blocks in larger networks. However, the local excitatory connections in such a network are typically hand-wired based on a fixed spatial arrangement which is chosen using prior knowledge of the dimensionality of the data to be learned by such a network, and neuroanatomical evidence is stubbornly inconsistent with these wiring schemes. Here we present a learning rule that allows networks with completely random internal connectivity to learn the weighted connections necessary for implementing the “local” excitation used by these networks, where the locality is with respect to the inherent topology of the input received by the network, rather than being based on an arbitrarily prescribed spatial arrangement of the cells in the network. We use the Siegert approximation to leaky integrate-and-fire neurons, obtaining networks with consistently sparse activity, to which we apply standard Hebbian learning with weight normalization, plus homeostatic activity regulation to ensure full network utilization. Our results show that such networks learn appropriate excitatory connections from the input, and do not require these connections to be hand-wired with a fixed topology as they traditionally have been for decades.
Prospective Study of the Performance of Vibrational Spectroscopies for Rapid Identification of Bacterial and Fungal Pathogens Recovered from Blood Cultures

ABSTRACT Rapid identification of microbial pathogens reduces infection-related morbidity and mortality of hospitalized patients. Raman spectra and Fourier transform infrared (IR) spectra constitute highly specific spectroscopic fingerprints of microorganisms by which they can be identified. Little biomass is required, so that spectra of microcolonies can be obtained. A prospective clinical study was carried out in which the causative pathogens of bloodstream infections in hospitalized patients were identified. Reference libraries of Raman and IR spectra of bacterial and yeast pathogens highly prevalent in bloodstream infections were created. They were used to develop identification models based on linear discriminant analysis and artificial neural networks. These models were tested by carrying out vibrational spectroscopic identification in parallel with routine diagnostic phenotypic identification. Whereas routine identification has a typical turnaround time of 1 to 2 days, Raman and IR spectra of microcolonies were collected 6 to 8 h after microbial growth was detected by an automated blood culture system. One hundred fifteen samples were analyzed by Raman spectroscopy, of which 109 contained bacteria and 6 contained yeasts. One hundred twenty-one samples were analyzed by IR spectroscopy. Of these, 114 yielded bacteria and 7 were positive for yeasts. High identification accuracy was achieved in both the Raman (92.2%, 106 of 115) and IR (98.3%, 119 of 121) studies. Vibrational spectroscopic techniques enable simple, rapid, and accurate microbial identification. These advantages can be easily transferred to other applications in diagnostic microbiology, e.g., to accelerate identification of fastidious microorganisms.
The Effects of Two Methods on Training EFL University Students in Taiwan to Identify Three Non-Native Phonemic Contrasts

ii Dedication. v Acknoledgements. vi Vita. vii List of Tables. xvi List of Figures. xix Chapter 1: Introduction 1.1. Background. 1 1.2. Statement of the Problem . 3 1.3. Gap statement . 7 1.4. Purposes of the Study. 10 1.5. Research Questions. 11 1.6. Research Hypotheses . 12 1.7. Significance of the Study. 13 1.8. Assumptions of the Study. 14 1.9. Definition of Key Terms. 14