Miracle-dz/UniFAR-FTUs huggingface dataset:
An Empirical Study of Recent Face Alignment Methods

The problem of face alignment has been intensively studied in the past years. A large number of novel methods have been proposed and reported very good performance on benchmark dataset such as 300W. However, the differences in the experimental setting and evaluation metric, missing details in the description of the methods make it hard to reproduce the results reported and evaluate the relative merits. For instance, most recent face alignment methods are built on top of face detection but from different face detectors. In this paper, we carry out a rigorous evaluation of these methods by making the following contributions: 1) we proposes a new evaluation metric for face alignment on a set of images, i.e., area under error distribution curve within a threshold, AUC$_\alpha$, given the fact that the traditional evaluation measure (mean error) is very sensitive to big alignment error. 2) we extend the 300W database with more practical face detections to make fair comparison possible. 3) we carry out face alignment sensitivity analysis w.r. t. face detection, on both synthetic and real data, using both off-the-shelf and re-retrained models. 4) we study factors that are particularly important to achieve good performance and provide suggestions for practical applications. Most of the conclusions drawn from our comparative analysis cannot be inferred from the original publications.
Practical Speed and Elongation Measurement, Using Encoders, for a Temper Mill

Speed and differential speed measurements are necessary for almost all of manufacturing steel processes. Use of incremental rotary encoder is the cheapest method for this purpose. Classical theoretical algorithms are analyzed in terms of error and sampling time. These methods are used for a temper mill real case, showing the practical limitations in both speed and differential speed. A new differential speed measurement algorithm is introduced, showing how to solve eccentricity problems and that a bad processing but not slippage is the source of observed false elongation peaks. Thus, incremental rotary encoder with a proper processing algorithm can offer higher accuracy than other more expensive noncontact speed sensors.
Fast detrending of unevenly sampled series with application to HRV

Detrending RR series is a common processing step prior to HRV analysis. In the classical approaches RR series, which are inherently unevenly sampled, are interpolated and uniformly resampled, thus introducing errors in subsequent HRV analysis. In this paper, we propose a novel approach to detrending unevenly sampled series and apply it to RR series. The approach is based on the notion of weighted quadratic variation, which is a suitable measure of variability for unevenly sampled series. Detrending is performed by solving a constrained convex optimization problem that exploits the weighted quadratic variation. Numerical results confirm the effectiveness of the approach. The algorithm is simple and favorable in terms of computational complexity, which is linear in the size of the series to detrend. This makes it suitable for long-term HRV analysis. To the best of the authors' knowledge, it is the fastest algorithm for detrending RR series.
Visual Memory-Control Auditory Memory-Control Left Lateral Superior Right Lateral

Cover Photo. Rows 1 and 2 show left lateral, posterior, and right lateral views of PET activation reflecting brain regions tied to visual-verbal (row 1) and auditory-verbal (row 2) encoding processes. Rows 3 and 4 show left lateral, superior, and right lateral views of PET activation reflecting brain regions mediating working memory processes for visually (row 3) and aurally (row 4) presented verbal material. See the article by Schumacher et al. in this issue. Current models of verbal working memory assume that modality-specific representations are translated into phonological representations before entering the working memory system. We report an experiment that tests this assumption. Positron emission tomogra-phy measures were taken while subjects performed a verbal working memory task. Stimuli were presented either visually or aurally, and a visual or auditory search task, respectively, was used as a control. Results revealed an almost complete overlap between the active memory areas regardless of input modality. These areas included dorsolateral frontal, Broca's area, SMA, and premotor cortex in the left hemisphere; bilateral superior and posterior parietal cortices and anterior cingulate; and right cerebellum. These results correspond well with previous research and suggest that verbal working memory is modality independent and is mediated by a circuit involving frontal, parietal, and cerebellar mechanisms. o 1996Academic Press, Inc.
PixFRET, an ImageJ plug‐in for FRET calculation that can accommodate variations in spectral bleed‐throughs

Fluorescence resonance energy transfer (FRET) allows the user to investigate interactions between fluorescent partners. One crucial issue when calculating sensitized emission FRET is the correction for spectral bleed‐throughs (SBTs), which requires to calculate the ratios between the intensities in the FRET and in the donor or acceptor settings, when only the donor or acceptor are present. Theoretically, SBT ratios should be constant. However, experimentally, these ratios can vary as a function of fluorophore intensity, and assuming constant values may hinder precise FRET calculation. One possible cause for such a variation is the use of a microscope set‐up with different photomultipliers for the donor and FRET channels, a set‐up allowing higher speed acquisitions on very dynamic fluorescent molecules in living cells. Herein, we show that the bias introduced by the differential response of the two PMTs can be circumvented by a simple modeling of the SBT ratios as a function of fluorophore intensity. Another important issue when performing FRET is the localization of FRET within the cell or a population of cells. We hence developed a freely available ImageJ plug‐in, called PixFRET, that allows a simple and rapid determination of SBT parameters and the display of normalized FRET images. The usefulness of this modeling and of the plug‐in are exemplified by the study of FRET in a system where two interacting nuclear receptors labeled with ECFP and EYFP are coexpressed in living cells. Microsc. Res. Tech. 68:51–58, 2005. © 2005 Wiley‐Liss, Inc.
Query Rewriting Based on User's Profile Knowledge

Query personalization was introduced as an advanced mechanism to allow the reformulation of database queries and adapt them to the user's domain of interest and preferences. Domain of interest and preferences are captured into a profile which is explicitly defined by the user or derived from his or her logged interactions with the information system. A substantial effort was done in recent years to provide reformulation techniques which enrich user queries prior to their execution. These approaches are often limited to a single data source. However, query personalization is much more crucial in a context where data sources are numerous and distributed, i.e. a mediation or P2P systems, as the user is generally overloaded with massive results in response to his or her queries. To deal with such a context of distributed data sources, we have studied two naive approaches and proposed an advanced approach, based on a schemafree profile. A comparison of the three approaches is performed, through two metrics we have defined. The limitations of the two first approaches are shown and the improvements provided by the third approach are demonstrated through the experiment.
Changes in background electroencephalography and regional cerebral glucose metabolism in focal epilepsy patients after 1-month administration of levetiracetam

The antiseizure efficacy and safety of levetiracetam (LEV) is well documented; however, few clinical studies have investigated the predictability of patient responsiveness to LEV, especially when the drug is first administered. The aim of this study was to ascertain the utility of clinical, electrophysiological, and neuroimaging parameters for assessing the early response to LEV treatment in focal epilepsy patients. Twelve confirmed focal epilepsy patients were included who had never taken LEV before. At baseline and 1 month after LEV administration, all subjects underwent 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) and electroencephalography (EEG), and completed the Quality of Life in Epilepsy questionnaire (QOLIE-31). Participants were divided by drug response: good versus poor. The good response group (seven subjects) was defined by a >50% decrease in seizure frequency compared to baseline (3 months before LEV intake). The other five participants with a <50% decrease in seizure frequency were placed into the poor response group. We compared the differential changes in brain glucose metabolism on FDG-PET, power spectrum on the EEG, and QOLIE-31 results between the two groups after a 1-month LEV trial. In the good response group, it was possible to identify brain regions with increased glucose metabolism, including the bilateral caudate nuclei and both frontal and left parietal regions (uncorrected P<0.005). In the poor response group, FDG-PET did not reveal any areas with significantly increased glucose metabolism. In the good response group, spectral EEG analysis revealed decreased delta power (1–3 Hz, P<0.05) in the parietal region and increased beta1 power (13–19 Hz, P<0.05) in the frontal region, whereas no significant changes were observed in the poor response group. There were no significant changes on the QOLIE-31 in either group after a 1-month LEV trial. Our results suggest that LEV-induced glucose metabolism and EEG spectral changes may be indicative of initial drug responsiveness as early as 1 month following treatment initiation. These parameters may be useful prognostic markers of antiseizure effects caused by LEV medication or may indicate an epiphenomenon of LEV-induced changes in glucose metabolism and EEG frequency. Further studies with larger sample sizes are warranted.
Synthesis, in vitro pharmacology, and molecular modeling of very potent tacrine-huperzine A hybrids as acetylcholinesterase inhibitors of potential interest for the treatment of Alzheimer's disease.

Eleven new 12-amino-6,7,10,11-tetrahydro-7, 11-methanocycloocta[b]quinoline derivatives [tacrine (THA)-huperzine A hybrids, rac-21-31] have been synthesized as racemic mixtures and tested as acetylcholinesterase (AChE) inhibitors. For derivatives unsubstituted at the benzene ring, the highest activity was obtained for the 9-ethyl derivative rac-20, previously prepared by our group. More bulky substituents at position 9 led to less active compounds, although some of them [9-isopropyl (rac-22), 9-allyl (rac-23), and 9-phenyl (rac-26)] show activities similar to that of THA. Substitution at position 1 or 3 with methyl or fluorine atoms always led to more active compounds. Among them, the highest activity was observed for the 3-fluoro-9-methyl derivative rac-28 [about 15-fold more active than THA and about 9-fold more active than (-)-huperzine A]. The activity of some THA-huperzine A hybrids (rac-19, rac-20, rac-28, and rac-30), which were separated into their enantiomers by chiral medium-pressure liquid chromatography (chiral MPLC), using microcrystalline cellulose triacetate as the chiral stationary phase, showed the eutomer to be always the levorotatory enantiomer, their activity being roughly double that of the corresponding racemic mixture, the distomer being much less active. Also, the activity of some of these compounds inhibiting butyrylcholinesterase (BChE) was tested. Most of them [rac-27-31, (-)-28, and (-)-30], which are more active than (-)-huperzine A as AChE inhibitors, turned out to be quite selective for AChE, although not so selective as (-)-huperzine A. Most of the tested compounds 19-31 proved to be much more active than THA in reversing the neuromuscular blockade induced by d-tubocurarine. Molecular modeling of the interaction of these compounds with AChE from Torpedo californica showed them to interact as truly THA-huperzine A hybrids: the 4-aminoquinoline subunit of (-)-19 occupies the same position of the corresponding subunit in THA, while its bicyclo[3.3. 1]nonadiene substructure roughly occupies the same position of the corresponding substructure in (-)-huperzine A, in agreement with the absolute configurations of (-)-19 and (-)-huperzine A.
Differential fuzzy clustering for categorical data

Differential evolution has emerged as one of the fast, robust, and efficient global search heuristics of current interest. Besides its good convergence properties and suitability for parallelization, Differential evolution's main assets are its conceptual simplicity and ease of use. This paper describes an application of differential evolution to the fuzzy clustering for categorical data sets. The performance of the proposed method has been compared with the simulated annealing based fuzzy c-medoids clustering algorithm, fuzzy c-medoids, fuzzy c-modes and average linkage hierarchical clustering algorithm for two artificial and two real life categorical data sets. Statistical significance test has been carried out to establish the statistical significance of the proposed method.
An Automated Mail Sorter System using SVM Classifier

paper proposes an Automated Mail Sorter (AMS) system that scans a mail and interprets one of the imperative fields of the destination address, the pin code to sort the mails. The scanned document was segmented into different fields to extract the pin code. A general classifier for the recognition of pin-code digits written in English was then employed. The recognition system consists of a feature extractor and a classification network. The feature extracted was Hu moments and the classification network was the support vector machine using a polynomial kernel of order 2. Other classification networks such as the multi feature recognizer and decomposing network were also used, but SVM gave the maximum accuracy. General Terms
Feature Extraction and Loss training using CRFs : A Project Report ∗

POS tagging has been a very important problem in the domain of Natural Language Processing. It has been approached at by different tools like Maximum entropy Models [3], Cyclic Dependency Networks [2] and Conditional Random Fields as well. My work mainly revolved around Conditional Random Fields, developing it as a loss function for an optimization solver and then training the loss function and using Viterbi algorithm to develop an estimator for the process.
Computing Tumour Coverage as a Result of Respiratory Motion during Radiotherapy Treatment

The objective of radiotherapy treatment is to kill cancerous cells while minimizing damage to surrounding healthy tissues. The tumour location uncertainty "forces" oncologists to prescribe a larger treatment area than required in order to ensure that the whole tumour is receiving the prescribed dose. The problem is more acute when a tumour can move during treatment, e.g., as a result of breathing. In this paper, we present an algorithm for computing the area covered by a tumor as a result of a cyclic motion during treatment. Our algorithm solves the following geometric problem: Given an n-vertices convex polygon P = {v1, v2, . , vn}, a monotone chain C = {c1, c2, . , Cm}, compute a minimums area polygon Q that includes all the space covered by P as it is translated along C such that v1isin P touches C. Here, we present a simple algorithm when P is a convex polygon. Our algorithm takes O(mn + m logn log(m + n)) time in the worst case
Text extraction from natural images based on stroke width map

This paper proposes a text extraction method for text in natural images, which apply color and edge information to obtain text candidate areas, and use stroke width information to filter out non-text areas. The stroke width map (SWM) is proposed to compute the stroke width by finding the maximal distance among the shortest distances with the same nearest boundary pixel. It can reflect the true stroke width and adapt to complex situations by improving the accuracy of stroke width. It does not require any training process. Experiment results demonstrate that this approach can achieve a good performance of text extraction with various degradations, highlighting the system efficiency and the text extraction capability.
Clustering routing protocol based on local optimization for wireless sensor networks

This paper has proposed the wireless sensor network routing protocol which has the advantages of low energy consumption. In consider data delay, the protocol using the cluster head forwards strategy transmit information to the base station. In the clustering phase, combining with both the residual energy of nodes and randomly generated threshold to generate cluster heads and establish clusters; In the data transfer phase, using local optimal strategy to make the number of the information forwards is reduced, so that avoiding delay of the information and decreasing the energy consumption of the cluster head. Theoretical analysis and simulation results show that the protocol, through balanced energy consumption, stable clusters and data transfer times decrease, makes the network lifetime longer than LEACH and DEEC protocols.
A stalled retrotranslocation complex reveals physical linkage between substrate recognition and proteasomal degradation during ER-associated degradation

Inactivation of Cdc48p/p97 triggers formation of a complex that contains the 26S proteasome, Cdc48p/p97, ubiquitinated substrates, select components of the Hrd1 complex, and the lumenal recognition factor, Yos9p. A model is proposed in which the Hrd1 complex links substrate recognition and degradation on opposite sides of the ER membrane.
Exploiting the convex-concave penalty for tracking: A novel dynamic reweighted sparse Bayesian learning algorithm

We propose a novel dynamic reweighted ℓ<sub>2</sub> (DRℓ<sub>2</sub>) algorithm in the regime of dynamic compressive sensing. Our analysis shows that aiming to solve a Type II optimization problem, DRℓ<sub>2</sub> is effectively minimizing a `convex-concave' penalty in the coefficients that transitions from a convex region to a concave function using knowledge of past estimations. DRℓ<sub>2</sub> thus provides superior reconstruction performance compared with state-of-the-art dynamic CS algorithms.
A Linguistic Approach to a Chinese Query Model

As network and input technologies have improved rapidly, researches in information retrieval have become more important than ever. An user-friendly and efficient query interface will certainly facilitate utilization of an information retrieval system. In this paper, a linguistic approach to Chinese query models is proposed and investigated. It includes Chinese linguistic variables, quantifiers and combination queries. Meanwhile, an improved computation method is proposed to handle general conjunctive queries, and it is proved to be better than traditional fuzzy computation in terms of a higher level of retrieval satisfaction. Experimental results also verify that the proposed quantifiers do not only simplify a multi-criteria request, but also yield a higher level of retrieval satisfaction than do Boolean queries.
Nouns and verbs in Italian children 1 Nouns and verbs in vocabulary acquisition of Italian children *

* The preparation of this paper was supported by a grant from the Ministero della Pubblica Istruzione (COFIN2003 n.2003107555) Nouns and verbs in Italian children 2 Abstract The vocabulary development of 24 Italian children aged between 16 and 18 months at the beginning of the study has been longitudinally monitored on a monthly basis using the Italian version of the MacArthur Communicative Development Inventory drawn up by their mothers. This study analyzes data from children for whom two sampling stages were available; the first corresponding to a vocabulary size as close as possible to 200 words (mean: 217, range: 167-281), the second to a vocabulary size ranging from 400 to 650 words (mean: 518, range: 416-648). The children's vocabulary composition was analyzed by calculating, for each sampling stage, the percentage of common nouns, verbs and closed class words. The increase in percentage points of the various lexical items between the first and second sampling stages was also analyzed. Data confirmed the predominance of nouns over verbs and closed class words at both sampling stages, while verbs and closed class words had a higher percentage increase than nouns. The results did not give any evidence of a relation between the style of acquisition based on the acquisition of nouns and a faster vocabulary growth.
Atypical E2F activity restrains APC/CCCS52A2 function obligatory for endocycle onset

The endocycle represents an alternative cell cycle that is activated in various developmental processes, including placental formation, Drosophila oogenesis, and leaf development. In endocycling cells, mitotic cell cycle exit is followed by successive doublings of the DNA content, resulting in polyploidy. The timing of endocycle onset is crucial for correct development, because polyploidization is linked with cessation of cell division and initiation of terminal differentiation. The anaphase-promoting complex/cyclosome (APC/C) activator genes CDH1, FZR, and CCS52 are known to promote endocycle onset in human, Drosophila, and Medicago species cells, respectively; however, the genetic pathways governing development-dependent APC/CCDH1/FZR/CCS52 activity remain unknown. We report that the atypical E2F transcription factor E2Fe/DEL1 controls the expression of the CDH1/FZR orthologous CCS52A2 gene from Arabidopsis thaliana. E2Fe/DEL1 misregulation resulted in untimely CCS52A2 transcription, affecting the timing of endocycle onset. Correspondingly, ectopic CCS52A2 expression drove cells into the endocycle prematurely. Dynamic simulation illustrated that E2Fe/DEL1 accounted for the onset of the endocycle by regulating the temporal expression of CCS52A2 during the cell cycle in a development-dependent manner. Analogously, the atypical mammalian E2F7 protein was associated with the promoter of the APC/C-activating CDH1 gene, indicating that the transcriptional control of APC/C activator genes by atypical E2Fs might be evolutionarily conserved.
Constrained keypoint quantization: towards better bag-of-words model for large-scale multimedia retrieval

Bag-of-words models are among the most widely used and successful representations in multimedia retrieval. However, the quantization error which is introduced when mapping keypoints to visual words is one of the main drawbacks of the bag-of-words model. Although some techniques, such as soft-assignment to bags [23] and query expansion [27], have been introduced to deal with the problem, the performance gain is always at the cost of longer query response time, which makes them difficult to apply to large-scale multimedia retrieval applications. In this paper, we propose a simple "constrained keypoint quantization" method which can effectively reduce the overall quantization error of the bag-of-words representation and greatly improve the retrieval efficiency at the same time. The central idea of the proposed quantization method is that if a keypoint is far away from all visual words, we simply remove it. At first glance, this simple strategy seems naive and dangerous. However, we show that the proposed method has a solid theoretical background. Our experimental results on three widely used datasets for near duplicate image and video retrieval confirm that by removing a large amount of keypoints which have high quantization error, we obtain comparable or even better retrieval performance while dramatically boosting retrieval efficiency.