Miracle-dz/UniFAR-FTUs huggingface dataset:
Metamodels and Design Patterns in CSL4

The task of building a description language for audio synthesis and processing consists of balancing a variety of conflicting demands and constraints such as easy learning curve, usability, flexibility, extensibility, and run-time performance. There are many alternatives as to what a modern language for describing signal processing patches should look like. This paper describes the object-oriented models and design patterns used in version 4 of the CREATE Signal Library (CSL), a full rewrite that included an effort to use concepts from the ”4MS” metamodel for multimedia systems, and to integrate a set of design patterns for signal processing. We refer the reader to other publications for an introduction to CSL, and
Effect of Relaxing Incisions on the Maxillary Growth after Primary Unilateral Cleft Palate Repair in Mild and Moderate Cases: A Randomized Clinical Trial

Background: The purpose of this study was to evaluate the association between the use of relaxing incisions and maxillary growth disturbance after primary palatoplasty in patients with unilateral cleft lip and palate. Methods: This is a prospective, randomized, double-blind controlled trial study with ethical committee approval between 2 groups of patients with unilateral cleft lip and palate who were operated on using the two-flap and one-flap techniques from 2008 to 2011. Two groups of patients with unilateral cleft lip and palate were operated on using the mentioned techniques by the Outreach Surgical Center Program Lima since 2008. Data collection was accomplished by evaluation of maxillary arch dimensions and dental arch relationships (scored using the 5-year-olds’ index). Results: The mean score for the 5-year-olds’ index was 2.57 for two-flap technique and 2.80 for one-flap technique without statistical significant differences (P = 0.71). Our comparative study did not find statistically significant differences in maxillary arch dimensions between the studied techniques for unilateral cleft palate repair. Good levels of agreement were observed according to the &kgr; statistics. Conclusions: The results arising from this clinical trial do not provide statistical evidence that one technique let us obtain better maxillary development than the other at 5 years. The use of relaxing incisions was not associated with maxillary growth impairment. A technique with limited relaxing incisions does not has better maxillary growth. Additional longer term study is necessary to confirm this preliminary report.
Maximum Likelihood Linear Regression 32 . 1 Maximum likelihood linear regression

Maximum likelihood linear regression (MLLR) is an adaptation technique suitable for both speaker and environmental model-based adaptation. The models are adapted using a set of linear transformations, estimated in a maximum likelihood fashion from the available adaptation data. As these transformations can capture general relationships between the original model set and the current speaker, or new acoustic environment, they can be e ective in adapting all the HMM distributions with limited adaptation data. Two important decisions that must be made are (i) how to cluster components together, such that they all have a similar transformation matrix, and (ii) how many transformation matrices to generate for a given block of adaptation data. This paper addresses both problems. Firstly it describes two optimal clustering techniques, in the sense of maximising the likelihood of the adaptation data. The rst assigns each component to one of the regression classes. This may be used to generate standard regression class trees. The second scheme performs a fuzzy assignment of base class to regression class, so the transformation associated with each component is a linear combination of a set of transformations. Secondly two schemes are examined which address the problem of how to determine the number of regression classes, transforms, for a given amount of adaptation data. Two schemes are examined here. A cross-validation scheme based on the auxiliary function of the adaptation data is described. Another scheme based on the use of iterative MLLR is also detailed. Both these schemes require no a-priori thresholding information. An initial evaluation of the techniques was performed using data from the ARPA 1994 test data. On this task, though \good" trees, in terms of the likelihood of the adaptation training data were generated, neither of the optimal clustering schemes yielded gains in recognition performance. The performance of the cross-validation scheme was found to be comparable to an empirically determined threshold scheme. The best performance was achieved using iterative MLLR, which outperformed both xed classes and threshold based schemes.
Contextually Cooperating Agents for User Assistance in Web-based Knowledge Gathering Tasks

availability of rich and diverse nature of unstructured and hyper-textual content in the Web coupled with the power of modern search engines either necessitate or lure the users to undertake the task of Web-based Knowledge Gathering (WKG). WKG is typically a complex and cognitive task under taken by the users on the Web for their learning, exploration, discovery investigation or decision-making. Though search is the primary operation in WKG, the involvement of many other human factors makes it difficult for the search engines to address this special requirement. In this paper, we argue that an active support system can be built around today's search engines that could assist the users in their WKG tasks. We propose an intelligent support system composed of cooperating agents that build contextual structures in the form of semantic link network by observing the task of their users. The agents share these structures and seek assistance from other agents who may provide their task structures based on the similarity of the tasks. The requesting agents then use these newly obtained task structures to extract out information that would help their users in achieving their goals. We implemented this as a prototype system by wrapping around a popular search engine and carried out user evaluation with tasks from diverse domains. The results showed that the users were able to save considerable efforts in the process of knowledge gathering and hence the system was able to support its users.
Letters to Children project: A letter-writing group designed to help incarcerated women develop or reinforce their roles as mothers

ABSTRACT There are few evidence-based treatment programs for incarcerated mothers with promising outcomes. Recognizing this failure and the neglect of the children left behind, the researchers present a conceptual model focused on mothers in prison. The model, Letters to Children, was developed to help female prisoners reconnect with their children through the process of a letter-writing group. The model incorporates the importance of the gendered experience and employs strategies to empower incarcerated women as they attempt to strengthen their relationships with their children. Theoretical underpinnings, an overview of the model’s components, participants’ feedback, conclusions, limitations, and future implications are presented.
On statistical machine translation method for lexicon refinement in speech recognition

In low resource Automatic Speech Recognition (ASR), one usually resorts to the Statistical Machine Translation (SMT) technique to learn transform rules to refine grapheme lexicon. To do this, we face two challenges. One is to generate grapheme sequences from the training data as the targets, which is paired with the original transcripts to train SMT models; the other is to effectively prune the learned rules from the translation model. In this paper we further this study. First we propose a simple but effective pruning method; second, to see in which case we are able to learn better rules, different setups with various acoustic and language model combinations are investigated; finally, to examine if the rules in different setups are complementary, lexicons generated via different rule tables are merged in ASR experiments. We report a WER reduction of up to 6.2% with the proposed technique.
A New Approach towards Zero-Crossing Localization

A new zero-crossing edge detection method is described. Similar to Laplace of a Gaussian (LoG) algorithm, a 7x7 point spread function (PSF) is convolved with the original image to generate a smoothed image. Instead of locating edge position from the smoothed image, as in the case of LoG, we use the smoothed image as a reference to convert the original image into a three-value edge polarity map (negative edges, positive edges, and zerocrossing pixels). We show that an optimal threshold can be derived from the analytical study of the gray value difference between the original and the reference images, taking into account four edge models (ramp, step, roof, and gate). This threshold is determined such that the zero-crossings in the polarity map are of single pixel width. Finally a corner preserving detector with a moving 5x5 window is implemented to identify real zero-crossings. The advantage of the proposed method over LoG is that it is more robust in preserving edges around sharp corners and thin lines. The new method is also 40% faster than the LoG. However, the LoG performs better for noisy, low contrast images. Experimental results with a test pattern image, a normal and a low contrast images are presented.
Cardiovascular program to improve physical fitness in those over 60 years old – pilot study

Background In Spain, more than 50% of 60-year-olds are obese. Obesity is a disease with serious cardiovascular risks. The mortality rate for cardiovascular disease in Spain is 31.1%. Objectives To improve aerobic fitness, strength, flexibility and balance, and body composition (BC) in persons over 60 years old. Materials and methods A clinical intervention study of 24 participants was carried out over a period of 3 months. Aerobic fitness was assessed using the Rockport 1-Mile Walk Test. Upper-body strength was evaluated with an ad hoc test. Flexibility and balance were evaluated using the Sit and Reach Test and the Stork Balance Stand Test, respectively. Anthropometric measurements were taken by bioelectrical impedance. Results After 3 months of training, aerobic fitness was improved, as demonstrated by improved test times (pretest 13.04 minutes, posttest 12.13 minutes; P<0.05). Body composition was also improved, but the results were not statistically significant (fat mass pretest 31.58%±5.65%, posttest 30.65%±6.31%; skeletal muscle mass pretest 43.99±9.53 kg, posttest 46.63±10.90 kg). Conclusion Our data show that in subjects over 60 years old, aerobic fitness was improved due to program intervention. However, these results should be treated with caution, because of the limited sample size and the brief time period of this pilot study. A more rigorous study would include a sample of at least 100 participants.
Models for quantitative Neuroimaging

A number of different tracers suitably labelled for being detected by photon emission tomography are being used for functional neuroimagi ng. The pictorial representation of the distribution of a given tracer within the brain tis sue, however, may be meaningless if the tissue concentration of the tracer itself, for each homoge nous area of the brain, is not related to the functional parameter of interest by a theoretical m odel. The model describes the biochemical and physiological behaviour of the tracer with resp ect to the functional parameter, and the variables to be measured, or to be known, in order to obtain quantization.
Learning styles and supervision: A critical review

ABSTRACT Attending to supervisees’ learning styles is a noted component of supervision best practices. However, the extant literature on learning styles is complex and controversial, leaving supervisors with little direction on whether or not—or how—to use them. In the following critical review, the literature on learning styles is reviewed and discussed, and recommendations for supervision practice and future research are provided.
Poly(ADP‐ribose)‐mediated interplay of XPA and PARP1 leads to reciprocal regulation of protein function

Poly(ADP‐ribose) (PAR) is a complex and reversible post‐translational modification that controls protein function and localization through covalent modification of, or noncovalent binding to target proteins. Previously, we and others characterized the noncovalent, high‐affinity binding of the key nucleotide excision repair (NER) protein XPA to PAR. In the present study, we address the functional relevance of this interaction. First, we confirm that pharmacological inhibition of cellular poly(ADP‐ribosyl)ation (PARylation) impairs NER efficacy. Second, we demonstrate that the XPA–PAR interaction is mediated by specific basic amino acids within a highly conserved PAR‐binding motif, which overlaps the DNA damage‐binding protein 2 (DDB2) and transcription factor II H (TFIIH) interaction domains of XPA. Third, biochemical studies reveal a mutual regulation of PARP1 and XPA functions showing that, on the one hand, the XPA–PAR interaction lowers the DNA binding affinity of XPA, whereas, on the other hand, XPA itself strongly stimulates PARP1 enzymatic activity. Fourth, microirradiation experiments in U2OS cells demonstrate that PARP inhibition alters the recruitment properties of XPA‐green fluorescent protein to sites of laser‐induced DNA damage. In conclusion, our results reveal that XPA and PARP1 regulate each other in a reciprocal and PAR‐dependent manner, potentially acting as a fine‐tuning mechanism for the spatio‐temporal regulation of the two factors during NER.
Parallel texts alignment

Alignment of parallel texts (texts that are translation of each other) is a required step for many applications that use parallel texts, including statistical machine translation, automatic extraction of translation equivalents, automatic creation of concordances, etc. This dissertation presents a new methodology for parallel texts alignment that departs from previous work in several ways. One important departure is a shift of goals concerning the use of lexicons for obtaining correspondences between the texts. Previous methods try to infer a bilingual lexicon as part of the alignment process and use it to obtain correspondences between the texts. Some of those methods can use external lexicons to complement the inferred one, but they tend to consider them as secondary. This dissertation presents several arguments supporting the thesis that lexicon inference should not be embedded in the alignment process. The method described complies with this statement and relies exclusively on externally managed lexicons to obtain correspondences. Moreover, the algorithms presented can handle very large lexicons containing terms of arbitrary length. Besides the exclusive use of external lexicons, this dissertation presents a new method for obtaining correspondences between translation equivalents found in the texts. It uses a decision criteria based on features that have been overlooked by prior work. The proposed method is iterative and refines the alignment at each iteration. It uses the alignment obtained in one iteration as a guide to obtaining new correspondences in the next iteration, which in turn are used to compute a finer alignment. This iterative scheme allows the method to correct correspondence errors from previous iterations in face of new information.
Closed-Form Error Exponent for the Neyman–Pearson Fusion of Dependent Local Decisions in a One-Dimensional Sensor Network

We consider a distributed detection system formed by a large number of local detectors and a data fusion center that performs a Neyman-Pearson fusion of the binary quantizations of the sensor observations. In the analyzed two-stage detection system the local decisions are taken with no kind of cooperation among the devices and they are transmitted to the fusion center over an error free parallel access channel. In addition, the sensors are randomly deployed along a straight line, and the corresponding sensor spacings are drawn independently from a common probability density function (pdf). For both hypothesis, H0 and H1, depending on the correlation structure of the observed phenomenon the local decisions might be dependent. In the case of being dependent, their correlation structure is modelled with a one-dimensional Markov random field with nearest neighbor dependency and binary state space. Under this scenario, we first derive a closed-form error exponent for the Neyman-Pearson fusion of the local decisions when the involved data fusion center only knows the distribution of the sensor spacings. Second, based on a single parameter that captures the mean correlation strength among the local decisions, some analytical properties of the error exponent are investigated. Finally, we develop a physical model for the conditional probabilities of the Markov random fields that might be present under each hypothesis. Using this model we characterize the error exponent for two well-known models of the sensor spacing: i) equispaced sensors with failures, and ii) exponentially spaced sensors with failures.
Energy efficient system-on-chip architecture for non-invasive mobile monitoring of diabetics

This paper presents an integrated biomedical processor system consists of a biomedical processor chip, MEMS-based ECG and oximetry-based Glucose alert sensors to achieve a non-invasive home diagnostic health monitoring system for diabetics. The biomedical processor integrates various computational engines such as FFT core, CAN severity algorithm classification and wireless interface. The chip targets extremely low power consumption to enable battery-powered operation for extended period of time. The sensors will provide non-invasive monitoring of ECG signals, and blood glucose levels alert at the same physical location on the human body. The unique sensor platform inevitably drives the SoC architecture to be wearable and less intrusive; thereby, providing patients with constant feedback on their critical health parameters.
Decentralized complex envelope controller for ASAC by virtual mechanical impedances

The problem of Active Structural Acoustic Control (ASAC) is to attenuate the radiated sound power by energy injection using structural actuators to modify deflection shapes. Collocated and dual actuator-sensor pairs allow the feedback problem to be formulated as the implementation of virtual mechanical impedances. The approach is based on a two-step process: (1) the virtual impedance is derived from measurements of the primary sound and transfer functions; (2) the centralized or decentralized complex envelope controller is designed to ensure stable feedback loops. Experiments are performed on a curved composite aircraft panel comprising a window. The proposed approach leads to the implementation of active virtual impedances and unstable compensators. An increased kinetic energy of the panel is observed, thus demonstrating that the control inputs needs to provide vibrational energy to achieve sound power reduction (2.7dB).
Comparative Effects of Methylmercury and Hg2+ on Human Neuronal N- and R-Type High-Voltage Activated Calcium Channels Transiently Expressed in Human Embryonic Kidney 293 Cells

Expression cDNA clones of α1B-1 or α1E-3 subunits coding for human neuronal N-(Cav2.2) or R-subtype (Cav2.3) Ca2+ channels, respectively, was combined with α2-bδ and β3-a Ca2+ channel subunits, and transfected into human embryonic kidney cells for transient expression to determine whether specific types of neuronal voltage-sensitive Ca2+ channels are affected differentially by methylmercury (MeHg) and Hg2+. For both Ca2+ channel subtypes, MeHg (0.125-5.0 μM) or Hg2+ (0.1-5 μM) caused a time- and concentration-dependent reduction of current. MeHg caused an initial, rapid component and a subsequent more gradual component of inhibition. The rapid component of block was completed between 100 and 150 s after beginning treatment. At 0.125 to 1.25 μM, MeHg caused a more gradual decline in current. Apparent IC50 values were 1.3 and 1.1 μM for MeHg, and 2.2 and 0.7 μM for Hg2+ on N- and R-types, respectively. For N-type current, effects of Hg2+ were initially greater on the peak current than on the sustained current remaining at the end of a test pulse; subsequently, Hg2+ blocked both components of current. For R-type current, Hg2+ affected peak and sustained current approximately equally. Kinetics of inactivation also seemed to be affected by Hg2+ in cells expressing N-type but not R-type current. Washing with MeHg-free solution could not reverse effects of MeHg on either type of current. The effect of Hg2+ on N- but not R-type current was partially reversed by Hg2+-free wash solution. Therefore, different types of Ca2+ channels have differential susceptibility to neurotoxic mercurials even when expressed in the same cell type.
Efficient and robust allocation algorithms in clouds under memory constraints

We consider robust resource allocation of services in Clouds. More specifically, we consider the case of a large public or private Cloud platform such that a relatively small set of large and independent services accounts for most of the overall CPU usage of the platform. We will show, using a recent trace from Google, that this assumption is very reasonable in practice. The objective is to provide an allocation of the services onto the machines of the platform, using replication in order to be resilient to machine failures. The services are characterized by their demand along several dimensions (CPU, memory,.) and by their quality of service requirements, that have been defined through an SLA in the case of a public Cloud or fixed by the administrator in the case of a private Cloud. This quality of service defines the required robustness of the service, by setting an upper limit on the probability that the provider fails to allocate the required quantity of resources. This maximum probability of failure can be transparently turned into a set of (price, penalty) pairs. Our contribution is two-fold. First, we propose a formal model for this allocation problem, and we justify our assumptions based on an analysis of a publicly available cluster usage trace from Google. Second, we propose a resource allocation strategy whose complexity is low in the number of resources, what makes it well suited to large platforms. Finally, we provide an analysis of the proposed strategy through an extensive set of simulations, showing that it can be succesfully applied in the context of the Google trace.
Extensive feature detection of N-terminal protein sorting signals

MOTIVATION The prediction of localization sites of various proteins is an important and challenging problem in the field of molecular biology. TargetP, by Emanuelsson et al. (J. Mol. Biol., 300, 1005-1016, 2000) is a neural network based system which is currently the best predictor in the literature for N-terminal sorting signals. One drawback of neural networks, however, is that it is generally difficult to understand and interpret how and why they make such predictions. In this paper, we aim to generate simple and interpretable rules as predictors, and still achieve a practical prediction accuracy. We adopt an approach which consists of an extensive search for simple rules and various attributes which is partially guided by human intuition. RESULTS We have succeeded in finding rules whose prediction accuracies come close to that of TargetP, while still retaining a very simple and interpretable form. We also discuss and interpret the discovered rules.