Miracle-dz/UniFAR-FTUs huggingface dataset:
Shrink-Wrapped Isosurface from Cross Sectional Images

This paper addresses a new surface reconstruction scheme for approximating the isosurface from a set of tomographic cross sectional images. Differently from the novel Marching Cubes (MC) algorithm, our method does not extract the iso-density surface (isosurface) directly from the voxel data but calculates the iso-density point (isopoint) first. After building a coarse initial mesh approximating the ideal isosurface by the cell-boundary representation, it metamorphoses the mesh into the final isosurface by a relaxation scheme, called shrink-wrapping process. Compared with the MC algorithm, our method is robust and does not make any cracks on surface. Furthermore, since it is possible to utilize lots of additional isopoints during the surface reconstruction process by extending the adjacency definition, theoretically the resulting surface can be better in quality than the MC algorithm. According to experiments, it is proved to be very robust and efficient for isosurface reconstruction from cross sectional images.
Emotion primitives estimation from EEG signals using Hilbert Huang Transform

This paper addresses the problem of emotion primitives estimation using information obtained from EEG signals. The EEG data were collected from 18 subjects, 9 male and 9 female, aged from 19 to 26 years old. We used audio clips from International Affective Digital Sounds (IADS) as stimuli for emotion elicitation. Hilbert-Huang Transform, a proper method for non-linear and non-stationary signal processing, was used for feature extraction. EEG signals were first decomposed into their Intrinsic Mode Functions (IMFs). Then 990 features were computed from the first five IMFs. To identify the most salient features and eliminate the redundant and irrelevant ones, we performed correlation based feature selection (CFS). This feature selection process reduced the number of features dramatically while increasing the performance remarkably. In this work, we used support vector regression for estimation of each emotion primitive value. Regression mean absolute error values and their standard deviations over all subjects for valence, activation, and dominance were obtained as 1.11 (0.13), 0.65 (0.09) and 0.38 (0.06) respectively.
Rga6 is a fission yeast Rho GAP involved in Cdc42 regulation of polarized growth

Spatial regulation of Cdc42 activity is essential to maintain polarized growth. Fission yeast Rga6 is a new Cdc42 GAP that collaborates with Rga4, the only known Cdc42 GAP, in the spatial restriction of active Cdc42 at the cell tip. Both GAPs localize preferentially at the nongrowing areas of the membrane in different clusters.
Real-Time Estimation Method of the Number of Pedestrians in Video Sequences

In a ubiquitous network society, information on mobile nodes such as pedestrians with cell phones in a target region is useful for network configuration, communication control, and so on. In this paper, we propose a novel method to estimate in real time the number of pedestrians in video sequences using a stationary camera. The proposed method extracts moving regions from video frame grabs using background difference and frame difference, and estimates the number of pedestrians based on the size of the moving region using a conversion function constructed based on prior learning. We evaluate the effectiveness of the proposed method by comparing the estimated values with the actual values, and show that the estimation error of the number of pedestrians is smaller than 0.1 in approximately 50% of frames, and that the mean absolute error is 0.37.
Aggregated metrics guided software restructuring

Software restructuring is of major importance in improving the reusability of a software system, being a form of perfective maintenance that modifies the structure of the system, without affecting the external behavior of the code. We are investigating in this paper how multiple software metrics defined for the application classes from a software system can be aggregated and used in order to improve the system's internal structure. Computational experiments are provided showing the effectiveness of using the aggregated software metric for restructuring a software system. The obtained results are promising, and illustrate that the research direction started in this paper has potential and it is worth being further investigated and extended.
A Probabilistic Model of MOSAIC

Humans can generate accurate and appropriate motor commands in various and even uncertain environments. MOSAIC (MOdular Sellection And Identification for Control) was formerly proposed for describing such human ability, but it includes some complex and heuristic procedures which make the model's understandability hard. In this article, we present an alternative and probabilistic model of MOSAIC (p-MOSAIC) as a mixture of normal distributions, and an online EM-based learning method for its predictors and controllers. Theoretical consideration shows that the learning rule of p-MOSAIC corresponds to that of MOSAIC except for some points mostly related to the controller learning. Experimental studies using synthetic datasets have shown some practical advantages of p-MOSAIC. One is that the learning rule of p-MOSAIC makes the estimation of 'responsibility' stable. Another is that p-MOSAIC realizes accurate control and robust parameter learning in comparison to the original MOSAIC especially in noisy environments, due to the direct incorporation of the noise into the model
Vibrational and thermodynamic properties of forsterite at mantle conditions

[1] We present a first-principle study of the vibrational and thermodynamic properties of Mg2SiO4 forsterite up to 20 GPa. The calculated local density approximation (LDA) frequencies and their pressure dependence are in good agreement with the available Raman and infrared spectroscopy data. We also predict the pressure dependence of the modes which are yet to be measured. Thermodynamic properties are obtained using the quasi-harmonic approximation (QHA) to the free energy in conjunction with these results. The calculated pressure-volume-temperature (P-V-T) relations and thermodynamic properties agree well with the reported experimental data within the regime of validity of the QHA. The only discrepancies with experimental data that point to intrinsic anharmonic effects are the mode Gruneisen parameters of two Raman and one infrared modes. However, their effect on thermodynamic properties appears to be negligible. Citation: Li, L. , R. M. Wentzcovitch, D. J. Weidner, and C. R. S. Da Silva (2007), Vibrational and thermodynamic properties of forsterite at mantle conditions, J. Geophys. Res., 112, B05206, doi:10.1029/2006JB004546.
A LEARNING ALGORITHM FOR FORECASTING ADAPTIVE WAVELET-NEURO-FUZZY NETWORK

The architecture of forecasting adaptive wavelet-neuro-fuzzy-network and its learning algorithm for the solving of nonstationary processes forecasting tasks are proposed. The learning algorithm is optimal on rate of convergence and allows to tune both the synaptic weights and dilations and translations parameters of wavelet activation functions. The simulation of developed wavelet-neuro-fuzzy network architecture and its learning algorithm justifies the effectiveness of proposed approach.
Fourier shape-frequency words for actions

Actions consist of short shape-motion fragments which recur in a seemingly unique sequence. We propose that these short fragments may constitute a concise vocabulary for actions. Models based on such “words” sometimes use the bag of words paradigm, which ignores sequence information. Also, despite the well-known utility of Fourier and similar features for temporal modelling, Fourier models have not received due attention to model action words until recently. Hence, we employ shape-frequency features as a temporally windowed Fourier transform to capture local motion and shape information. Unsupervised clustering discovers the naturally occurring modes (words) of these features. Each labelled video can thus be represented as a sequence of cluster transitions. Though different actions share common words, we observe that the word sequences are different for different actions, enabling easy discrimination. We evaluate the model on the Weizmann action dataset [1] and achieve 96.7% classification accuracy, and show how it compares to other similar algorithms.
Reflecting on the PRET A Rapporter Framework Via a Field Study of Adolescents’ Perceptions of Technology and Exercise

PRET A Rapporter (PRETAR) was developed to explicitly structure user- centered evaluation studies to ensure all necessary elements are individually and independently considered. Its creators see its benefit as twofold: for study design and in retrospective evaluations. We evaluate PRETAR's potential by applying it retrospectively to one of our eHealth field studies in which we investigated the design requirements for mobile technologies that would support and motivate adolescents to exercise opportunistically. We also use PRETAR to evaluate the key literature for this eHealth study. This shows that typically the research methodology is under-reported. Then we document the study in terms of its purpose, resources, ethical concerns, data collection and analysis techniques, and manner of reporting the study. Finally, our reflection on the use of PRETAR leads us to propose that four different modes of the framework should be applied during the course of a study, that is, when reviewing, planning, conducting, and discussing.
A Bayesian Framework for Recognizing Textured Objects in a Content- Based Image Retrieval System

We present an image retrieval system for finding textured objects by text query. The algorithm considers each image as a set of independent segments. It learns the relationship of segments features with text from a training set of images where a set of segments is manually labeled. The algorithm is capable of generating text labels from a segment and finding images that are relevant to a query consisting of text labels. We present the first experimental results.
Criteria for selecting a subset of indirect measurements for analog testing

This work proposes a criterion to select a subset of indirect measurements avoiding redundant information. The key idea of the proposal is to reduce the actual number of measurements to be performed to those strictly providing relevant information to the testing procedure, therefore keeping the incurred misclassification costs at acceptable levels. The proposed method selects the measurements presenting minimum mean and spread of the correlations between all the possible pairs formed by the measurements within the target subset. In order to show the viability of the proposal, the method has been applied to select a subset of indirect measurements in several analog filters affected by parametric variations. The obtained misclassification levels using the subset of measurements indicated by the proposed method are considerably low. In average, the number of misclassified circuits using the selected subset are within the first 2.4% of the misclassification population obtained when all the possible subsets are explored, therefore validating the proposal.
The Real Price of Construction : Identification and Estimation of an Asymmetric Model of Entry

Risk aversion has been shown to have adverse effects on agents’ bidding. In private value auctions, risk aversion induces more aggressive bidding, whenever the number of participants remain unchanged. Risk aversion may also prevent agents from entering the auction, in the first place, if a certain outcome is available, which lessens competition and, eventually the agent’s bids. Moreover, if bidders incur a cost to learn their values, as in construction procurement auction where plans may need to be drawn, and/or ground may need to be tested, the optimal auction mechanism should consider both the determinants to the firm’s entry, and the factors which affect its bidding. This paper studies a two-stage model of heterogenous risk averse bidders which decide first wether to enter or not the auction, learn their valuation upon entry, then submit their bid. I show that the model is semiparametrically identified, and propose a two-stage estimation procedure of the model primitives. The estimates yield a measure of the price of entry, or real price of construction: the bidder’s certainty equivalent of the auction.
Changes in Sensory Thresholds of the Pulp and Periodontal Ligaments after Standardized Tooth Clenching

Objective: It is not clear how the magnitude and duration of occlusal force affects pulpal and periodontal sensations. We investigated the effects of various tooth clenching loads, in which the product of the occlusal force and duration was kept constant, on pulpal and periodontal sensations. Materials and methods: Ten men and 10 women associated with Tokyo Medical and Dental University (age ≥ 20 years) participated in this study. Changes in pulpal sensation and periodontal sensation at the left or right mandibular first premolar were compared before and after 3 experimental clenching tasks. The total loading amount, determined as “occlusal force × duration”, was kept constant across tasks. For pulpal sensation, the electrical stimulation threshold (EDT) was measured using an electric pulp tester that caused pulpal discomfort. For periodontal sensation, the interocclusal tactile threshold (ITT) was measured using the foil test. Results: There was no significant difference with respect to the change rates of EDT and ITT relative to baseline between tasks. However, change rates varied across individuals. Both EDT and ITT could be divided into 3 types: increase type, decrease type ,and no-change type. For EDT, the smaller the bite force was, the more the proportion of the decrease type tended to increase. For ITT, the increase type was predominant in each task. However, there was no statistically significant difference between tasks in both EDT and ITT. Conclusion: Although we observed no statistically significant differences, transient changes in pulpal as well as periodontal sensation were found. Even if the product of occlusal force and duration (total loading) remained constant, transient changes in pulpal and periodontal sensations might differ. In particular, the pulp may become hypersensitive, while periodontal sensation may become hyposensitive.
Brain Imaging in Patients With Diabetes

Diabetes is associated with impaired cognitive functioning and an increased risk of dementia (1,2). Patients with type 1 diabetes may show mild to moderate slowing of mental speed and diminished mental flexibility, whereas learning and memory are relatively spared (3). In patients with type 2 diabetes, cognitive impairment may be relatively more pronounced, particularly affecting verbal memory or complex information processing (4,5). The pathogenesis is still uncertain, but chronic hyperglycemia, vascular disease, repeated hypoglycemic episodes, and possibly direct effects of insulin on the brain have been implicated (6). Brain imaging studies can help to clarify the pathogenesis. An increasing number of studies report both focal vascular and more global (e.g., atrophy) cerebral changes, but the results are not always consistent. Our aim was to systematically review brain imaging studies in patients with diabetes. Data on the relation of imaging with cognition and with relevant disease variables were also recorded. Medline and EMBASE (1966 to February 2006) were searched with the following medical subject heading terms: computed tomography (CT) and magnetic resonance imaging (MRI) studies: white matter, leukoaraiosis, lacunar infarction, subcortical, periventricular, brain, cerebral, hippocampus, atrophy, MRI, magnetic resonance imaging, CT, and tomography; magnetic resonance spectroscopy (MRS) studies: magnetic resonance spectroscopy, MRS, brain, and cerebral; positron emission tomography (PET), single-photon emission CT (SPECT), and Xenon-enhanced CT studies: cerebral blood flow, glucose metabolism, brain, cerebral, PET, SPECT, Xenon, positron emission tomography, single-photon emission tomography, and tomography; all combined with “diabetes. ” The abstracts were screened and potentially relevant articles retrieved. These articles were included if they met the following four criteria: 1 ) original article, written in English, on brain imaging in adult patients with diabetes in comparison with control subjects; 2 ) diagnostic criteria for diabetes specified; 3 ) sample size of at least 20 diabetic patients, or a total sample …
Cognitive functions in methamphetamine induced psychosis compared to schizophrenia and normal subjects

Objective The purpose of this research was to study the cognitive functions in patients with methamphetamine-induced psychosis (MIP) in comparison with schizophrenia patients and normal subjects. Method This was a cross-sectional study, 30 patients with MIP, 30 patients with schizophrenia and 30 normal individuals were selected via convenient sampling and were matched on age, sex and education. Wisconsin Cards Sorting, Stroop, Visual Search and Attention and Wechsler Memory Tests were used to assess the subjects. Results The study showed that patients with MIP and schizophrenia have more deficits in executive functions, selective attention, sustained attention and memory than normal subjects. There were no significant differences in cognitive functions between patients with MIP and schizophrenia except for visual search and attention that showed more impairment in patients with schizophrenia. Conclusion Although, cognitive dysfunctions of patients with MIP are mostly similar to patients with schizophrenia, some differences seem to exist, especially in those functions that are not primarily dependent on frontal lobe.
Longitudinal Study of Mammary Epithelial and Fibroblast Co-Cultures Using Optical Coherence Tomography Reveals Morphological Hallmarks of Pre-Malignancy

The human mammary gland is a complex and heterogeneous organ, where the interactions between mammary epithelial cells (MEC) and stromal fibroblasts are known to regulate normal biology and tumorigenesis. We aimed to longitudinally evaluate morphology and size of organoids in 3D co-cultures of normal (MCF10A) or pre-malignant (MCF10DCIS.com) MEC and hTERT-immortalized fibroblasts from reduction mammoplasty (RMF). This co-culture model, based on an isogenic panel of cell lines, can yield insights to understand breast cancer progression. However, 3D cultures pose challenges for quantitative assessment and imaging, especially when the goal is to measure the same organoid structures over time. Using optical coherence tomography (OCT) as a non-invasive method to longitudinally quantify morphological changes, we found that OCT provides excellent visualization of MEC-fibroblast co-cultures as they form ductal acini and remodel over time. Different concentrations of fibroblasts and MEC reflecting reported physiological ratios [1] were evaluated, and we found that larger, hollower, and more aspherical acini were formed only by pre-malignant MEC (MCF10DCIS.com) in the presence of fibroblasts, whereas in comparable conditions, normal MEC (MCF10A) acini remained smaller and less aspherical. The ratio of fibroblast to MEC was also influential in determining organoid phenotypes, with higher concentrations of fibroblasts producing more aspherical structures in MCF10DCIS.com. These findings suggest that stromal-epithelial interactions between fibroblasts and MEC can be modeled in vitro, with OCT imaging as a convenient means of assaying time dependent changes, with the potential for yielding important biological insights about the differences between benign and pre-malignant cells.
Sparse Representation Theory and its Application for Face Recognition

Abstract Face recognition aims at endowing computers with the ability to identify different human beings according to their face images. However, recognition rate will decrease sharply when it refers to the non-ideal imaging environments or the incorporation of users, such as illumination, pose, expression variations and so on. Besides, it will be also influence the recognition results when the database is too large or small. Sparse representation based classification for face images has been one of efficient approaches for face recognition in recent years. Discrimination performance by using the sparse representation can also be applied to the face recognition, and any test sample can be expressed as a linear span of the all training samples. Experimental results show that face recognition method based on sparse representation is comparable to others.
Diary studies as a macro-ergonomic evaluation tool: Development of a shift diary and its application in ergonomic evaluations

A diary instrument that could be used as a macro-ergonomic evaluation tool was developed and applied to evaluating monitoring tasks. In the first part of the study, the development of the instrument allowing the measurement of employee evaluations of perceived workload, attained performance, and strain is presented. Railway signalers and controllers filled out a diary every four hours over ten consecutive working shifts. Analysis of the objective workload conditions of the railway signalers and their relations to subjective workload perceptions in the diary indicates a satisfying validity of the measures. In the second part of the study, the newly developed diary instrument was used for macro-ergonomic evaluations in two other controller work places. Using the shift diary it was possible to answer practical macro-ergonomic questions that originated from the respective work situations. The strengths and possible limitations of the diary instrument are discussed.
Decoupled sectored caches: conciliating low tag implementation cost and low miss ratio

Sectored caches have been used for many years in order to reconcile low tag array size and small or medium block size. In a sectored cache, a single address tag is associated with a sector consisting on several cache lines, while validity, dirty and coherency tags are associated with each of the inner cache lines. Usually in a cache, a cache line location is statically linked to one and only one address tag word location. In the decoupled sectored cache introduced in the paper, this monolithic association is broken; the address tag location associated with a cache line location is dynamically chosen at fetch time among several possible locations. The tag volume on a decoupled sectored cache is in the same range as the tag volume in a traditional sectored cache; but the hit ratio on a decoupled sectored cache is very close to the hit ratio on a non-sectored cache. A decoupled sectored cache will allow the same level of performance as a non-sectored cache, but at a significantly lower hardware cost. <<ETX>>