Miracle-dz/UniFAR-FTUs huggingface dataset:
Tecnologias assistivas : viabilizando a acessibilidade ao potencial individual

Abstact: This paper presents basic concepts about adaptative-assisted-technology and its uses in Special Education. Thus, it includes a general ouverview of the technological aids currently avaiable in trans of hardware and software. Such aids make possible that persons with educational special needs interact in an educational and social context within a more inclusive perspective.
The calculation of electrical parameters of overtone thickness-shear quartz crystal resonators with the higher-order Mindlin plate equations

Quartz crystal resonator design achieves frequency targets through the choice of thickness of quartz crystal blank and vibration modes of overtone. The overtone types of resonators have been widely available to meet the ever increasing needs of high frequency resonators. Earlier studies on quartz crystal resonator analysis have been concentrated on analysis of vibrations of the fundamental thickness-shear mode for solutions of frequency and displacements which are essential in the initial design and subsequent calculation of electrical parameters. We are now in the stage to analyze overtone vibrations and provide frequency, electrodes, displacements, and consequently some electrical parameters for the overtone resonators in a manner analogous to the fundamental thickness-shear vibrations. We have derived the higher-order Mindlin plate equations with the consideration of electrical potential and overtone displacements including the thickness-shear family. These equations have been corrected based on the three-dimensional dispersion relations of anisotropic materials like the AT-cut quartz crystal and selected vibration modes are retained as part of the simplification procedure. The elimination and truncation are validated by making comparison with the exact dispersion relations, and the correction is done with the exact solutions of the cut-off frequencies of the thickness-shear mode family and slopes of some other modes. The frequency spectra are computed in the vicinity of overtone and fundamental thickness-shear modes to study the coupling and interactions with spurious modes. The formulation of capacitance ratio is done with solutions of displacements and electrical potential, and the results are used for the comparison with measurements. The coupling of vibration modes are examined with frequency spectra from the coupled equations of displacements and electrical potentials at the overtone thickness-shear frequencies. We believe theoretical studies can provide more reliable design guidelines in overtone resonators.
Development of a Collision Avoidance Algorithm Using Elastic Band Theory

This paper presents a new Collision Avoidance (CA) Algorithm which uses Elastic Band Theory. Researchers tried to develop warning systems to avoid collisions which warn drivers of possible collision risk with audio and or visual signs. However, these systems are not sufficient for avoidance of a collision in situations where the driver gives no response to the warnings. CA System is a kind of Active Safety System which takes control of the vehicle for a couple of seconds and applies emergency maneuver when the collision is unavoidable through driver action alone. The proposed CA algorithm uses Elastic Band Theory which is an obstacle avoidance method used in robotics. This paper aims to introduce this theory applied with modifications to road vehicle based systems and presents realistic simulation results using high fidelity vehicle models with several different collision scenarios.
Increased expression of miR-155 and miR-222 is associated with lymph node positive status

Identification of prognostic molecular markers of breast cancer is extremely important. The spreading out of the primary breast tumour cells to the lymphatic system is at the forefront of symbolising the first signs of distant organ metastasis. Deregulated genes in breast cancer tissues that spread to lymph nodes may show early predictive molecular markers. In the present study, we selected five microRNAs, which play a key function in the invasion-metastasis cascade. We investigated the levels of microRNAs in 80 paired samples of BC and matched adjoining tissues, and we examined the potential relationships between microRNA levels and positive lymph node status. Our results attest that three microRNAs (miR-21, miR-155, miR-222) were significantly up-regulated, whilst miR-205 was substantially down-regulated in BC tissues in relation to normal adjoining tissues in a heterogeneous patient cohort. The high levels of two microRNAs, miR-155 and miR-222, showed a statistical relation with the positive lymph node status, especially in patients that had triple negative BC. Conversely, miR-155 was substantially down-regulated in tumour tissues of patients who received preoperative neoadjuvant chemotherapy (NAC) compared with tumour tissues of patients without NAC in cohorts sub-classified to lymph node positive status. Our findings show evidence that the miR-155 and the miR-222 can be defined as molecular markers in regards to cancer patients to prognosticate spread to the lymph node. They also showed that the miR-155 could have crucial significances in BC treatment.
Automatic academic advisor

One of the problems that face a Distance Education academic advisor (and for lesser degree local academic advisors) is to identify courses that best suit a student's interests and academic skills from a wide collection of elective courses. This is because an advisor needs to select courses that suit both the interest and academic skills of the student. The student may not be able to know his interest in a course from merely its title or from the description of the course provided in the course catalogue. Also, the advisor needs to advise the student to take a course that suits the student's academic performance and skills. Towards this, the advisor needs to consider the performance of students in all his prior courses, which is time consuming. These problems can be overcome using a course recommender system. We introduce in this paper an XML user-based Collaborative Filtering (CF) system called AAA. The system advises a student to take courses that were taken successfully by students, who have the same interest and academic performance as the student. We experimentally evaluated AAA. Results showed marked improvement.
A Modified Method of Insulin Producing Cells' Generation from Bone Marrow-Derived Mesenchymal Stem Cells

Type 1 diabetes mellitus is a result of autoimmune destruction of pancreatic insulin producing β-cells and so far it can be cured only by insulin injection, by pancreas transplantation, or by pancreatic islet cells' transplantation. The methods are, however, imperfect and have a lot of disadvantages. Therefore new solutions are needed. The best one would be the use of differentiated mesenchymal stem cells (MSCs). In the present study, we investigated the potential of the bone marrow-derived MSCs line for in vitro differentiation into insulin producing cells (IPSs). We applied an 18-day protocol to differentiate MSCs. Differentiating cells formed cell clusters some of which resembled pancreatic islet-like cells. Using dithizone we confirmed the presence of insulin in the cells. What is more, the expression of proinsulin C-peptide in differentiated IPCs was analyzed by flow cytometry. For the first time, we investigated the influence of growth factors' concentration on IPCs differentiation efficiency. We have found that an increase in the concentration of growth factors up to 60 ng/mL of β-FGF/EGF and 30 ng/mL of activin A/β-cellulin increases the percentage of IPCs. Further increase of growth factors does not show any increase of the percentage of differentiated cells. Our findings suggest that the presented protocol can be adapted for differentiation of insulin producing cells from stem cells.
Parameterized Approximation Scheme for the Multiple Knapsack Problem

The multiple knapsack problem (MKP) is a well-known generalization of the classical knapsack problem. We are given a set A of n items and set B of m bins (knapsacks) such that each item a ∈ A has a size size(a) and a profit value profit(a), and each bin b ∈ B has a capacity c(b). The goal is to find a subset U ⊂ A of maximum total profit such that U can be packed into B without exceeding the capacities. The decision version of MKP is strongly NP-complete, since it is a generalization of the classical knapsack and bin packing problem. Furthermore, MKP does not admit an FPTAS even if the number m of bins is two. Kellerer gave a PTAS for MKP with identical capacities and Chekuri and Khanna presented a PTAS for MKP with general capacities with running time nO(log(1/e)/e8). In this paper we propose an EPTAS with parameterized running time 2O(log(1/e)/e5) · poly(n) + O(m) for MKP. This solves also an open question by Chekuri and Khanna.
Amplification of nanogram amounts of total RNA by the SMART-based PCR method for high-density oligonucleotide microarrays.

-fold can be achieved in ashort time. However, reports in the literature have rarelydiscussed the feasibility and reproducibility of PCR-basedmethods when the amount of starting total RNA in asample is only a very few nanograms or less, which isoften the case for clinical samples.We developed a modified SMART-based PCR protocolwith which reliable and robust gene expression data canbe obtained from 1 ng of starting total RNA. We alsoinvestigated sources of array data variations.The modified protocol (see Supplement 1 in the DataSupplement that accompanies the online version of thisTechnical Brief at http:www.clinchem.org/content/vol51/issue12) has three major changes compared with thepublished standard procedure
A Semantic Modeling Approach for Medical Image Semantic Retrieval Using Hybrid Bayesian Networks

A multi-level semantic modeling method, which integrates support vector machines (SVM) into hybrid Bayesian networks (HBN), is proposed in this paper. SVM discretizes the continuous variables of medical image features by classifying them into finite states as middle-level semantics. Based on the HBN, the semantic model for medical image semantic retrieval can be designed at multi-level semantics. To validate the method, a model is built to achieve automatic image annotation at the content level from a small set of astrocytona MRI (magnetic resonance imaging) samples. Multi-level annotation is a promising solution to enable medical image retrieval at different semantic levels. Experiment results show that this approach is very effective to enable multi-level interpretation of astrocytona MRI scan. It outperforms the Bayesian network-based model using k-nearest neighbor classifiers (K-NN). This study provides a novel way to bridge the gap between the high-level semantics and the low-level image features
The Rule Retranslation Problem and the Validation Interface

Current rule base maintenance is wasting refinement and inference performance. There are only few maintenance concepts, which enjoy both (1) formal rule refinement and (2) utilizing topical knowledge provided by experts within the refinement process. The current state of the art in rule base validation and refinement reveals that there is no generic validation interface and no optimal rule trace refinement. This paper characterizes two different retranslation approaches for reduced rule bases and proposes a two‐step validation process, which combines a case‐based approach with a rule trace validation approach.
One-Class to Multi-Class Model Update Using the Class-Incremental Optimum-Path Forest Classifier

Incremental learning capabilities of classiﬁers is a relevant topic, specially when dealing with scenarios such as data stream mining, concept drift and active learning. We investigate the capabilities of an incremental version of the Optimum-Path Forest clas-siﬁer (OPF-CI) in the context of learning new classes and compare its behavior against Support Vector Machines and k Nearest Neigh-bours classiﬁers. The OPF-CI classiﬁer is a parameter-free, graph-based approach to incremental training that runs in linear time with respect to the number of instances. Our results show OPF-CI keeps the running time low while producing an accuracy behavior similar to the other classiﬁers for increments of instances. Also, it is robust to variations on the order of the learned classes, demonstrating the applicability of the method.
Identification of systems with friction via distributions using the modified friction LuGre model

This paper presents the identification procedures based on distributions theory to continuous time systems with friction using the modified LuGre friction model. Mainly it applies the results of the identification procedures based on distributions theory to continuous time systems with friction. There are defined the so called generalized friction dynamic systems (GFDS) as a closed loop structure around a smooth system with discontinuous feedback loops representing friction reaction vectors. Both GFDS with static friction models (SFM) and dynamic friction models (DFM), also the modified friction LuGre model is analyzed. The identification problem is formulated as a condition of vanishing the existence relation of the system. Then, this relation is represented by functionals using techniques from distribution theory based on testing function from a finite dimensional fundamental space. The advantage of representing information by distributions are pointed out when special evolutions as sliding mode, or limit cycle can appear.The proposed method is a batch on-line identification because identification results are obtained during the system evolution after some time intervals but not in any time moment. This method does not require the derivatives of measured signals for its implementation. Some experimental results are presented to illuminate its advantages and practical use.
A practical education of space engineering by using CanSat and pico-satellite - Fruitful collaboration with UNISEC for success of student satellite program -

This paper reports the history of the student pico-satellite program in Nihon University, especially about how a small laboratory which had no knowledge on satellite technology has succeeded the launch and operation of the student pico-satellite. The author hopes that his method would be a helpful example for supervisors who will start the student satellite program.
Automated Refinement and Augmentation of Web Service Description Files

Web Service Description Language (WSDL) is being increasingly used to specify web service interfaces. Specifications of this type, however, are often incomplete or imprecise. For example, cursory examination of the WSDL file for Amazon's E-Commerce Web Service reveals that it often uses a less spe- cific type where a more specific type is applicable, or declares that elements could be missing where other documentation indicates that they are required. Further, specifications reflecting the temporal relationships between operations are com- pletely missing, which is not surprising since they are not supported by the cur- rent WSDL standard. These problems in WSDL specifications can cause tools that use them to perform poorly or unreliably, and can mislead developers who rely on them. To address these problems, in this paper we present an automated methodology for collecting static and dynamic information about a web service, and using this information to suggest improvements to the WSDL file as well as providing complementary information about the behavior of the web service that cannot be captured by the WSDL. Additionally, we present the results of two case studies performed on commercial web services that show our methodology can find problems in WSDL files and suggest improvements.
Action recognition robust to position changes using skeleton information and SVM

Aiming at the problem that the action recognition algorithms based on vision have a high requirement of the background and the human position relative to the sensor, an algorithm which is robust to the position changing of the human is proposed. The Microsoft v2 is used to collect skeleton data and standardize it, then the feature vectors are extracted from the data, at last after the correction of the feature information, the distribution related with the skeleton data is collected and input to the SVM to train. This method can keep stable action recognition when the angle between human torso and Kinect is changed. Experiment result turns out that this position-robust recognition algorithm keeps a recognition accuracy rate above 80%, which is over the state-of-art solutions.
A diverse family of novel peptide toxins from an unusual cone snail, Conus californicus

SUMMARY Diversity among Conus toxins mirrors the high species diversity in the Indo-Pacific region, and evolution of both is thought to stem from feeding-niche specialization derived from intra-generic competition. This study focuses on Conus californicus, a phylogenetic outlier endemic to the temperate northeast Pacific. Essentially free of congeneric competitors, it preys on a wider variety of organisms than any other cone snail. Using molecular cloning of cDNAs and mass spectrometry, we examined peptides isolated from venom ducts to elucidate the sequences and post-translational modifications of two eight-cysteine toxins (cal12a and cal12b of type 12 framework) that block voltage-gated Na+ channels. Based on homology of leader sequence and mode of action, these toxins are related to the O-superfamily, but differ significantly from other members of that group. Six of the eight cysteine residues constitute the canonical framework of O-members, but two additional cysteine residues in the N-terminal region define an O+2 classification within the O-superfamily. Fifteen putative variants of Cal12.1 toxins have been identified by mRNAs that differ primarily in two short hypervariable regions and have been grouped into three subtypes (Cal12.1.1–3). This unique modular variation has not been described for other Conus toxins and suggests recombination as a diversity-generating mechanism. We propose that these toxin isoforms show specificity for similar molecular targets (Na+ channels) in the many species preyed on by C. californicus and that individualistic utilization of specific toxin isoforms may involve control of gene expression.
Sex Offender Assessment Procedures: A South African Comparison

This study reports on the results of a reflective case analysis of a first generation assessment procedure of a chronic offender. The assessment focused on offender's experiential world and his pathway to crime, including precipitating crime risk factors as well as treatment needs to direct an intervention. The results of this assessment are compared with the results of a third-generation appraisal scale to evaluate the corresponding and/or different findings of these assessments. Findings suggest comparability of corresponding assessment indicators, suggesting that first and third generation assessment techniques can be integrated in corrections rehabilitation.
Direct Visualization of Single-Molecule DNA-Binding Proteins Along DNA to Understand DNA-Protein Interactions

Single-molecule fluorescence imaging has recently developed into a powerful method for studying biophysical and biochemical phenomena (Moerner, 2007), including DNA metabolism (Ha, 2004; Hilario & Kowalczykowski, 2010; Zlatanova & van Holde, 2006). While classical biochemical methods yield parameters that are ensemble averaged, singlemolecule fluorescence imaging can be used to observe real-time behavior of individual biomolecules, allowing us to study their dynamic characteristics in great detail. Among the various biomolecules, protein molecules, which play central roles in many biological functions, are the prime targets for single-molecule imaging. Direct observations of singlemolecule DNA-binding proteins acting on their DNA targets in real time have provided new insights into DNA metabolism. In this chapter, I focus primarily on recent advances in direct visualization of single-molecule DNA-binding proteins in vitro, especially on the key techniques employed for this visualization.
Model-free POMDP optimisation of tutoring systems with echo-state networks

Intelligent Tutoring Systems (ITSs) are now recognised as an interesting alternative for providing learning opportunities in various domains. The Reinforcement Learning (RL) approach has been shown reliable for finding efficient teaching strategies. However, similarly to other human-machine interaction systems such as spoken dialogue systems, ITSs suffer from a partial knowledge of the interlocutor's intentions. In the dialogue case, engineering work can infer a precise state of the user by taking into account the uncertainty provided by the spoken understanding language module. A model-free approach based on RL and Echo State Newtorks (ESNs), which retrieves similar information, is proposed here for tutoring.
Negotiated Memory: Doukhobor Autobiographical Discourse

Acknowledgments Introduction 1. Beyond Auto-Bio-Graphe: Autobiography and Alternative Identities 2. Doukhobor Beliefs and Historical Moments 3. Vechnaiia Pamit in the Diaspora: Community Meanings of History and Migration 4. Negotiating Identity: Doukhobor Oral Narratives 5. Witness, Negotiation, Performance: Freedomite Autobiography Conclusion: Negotiating the "I" and "We" in Autobiography Notes References Index
Asymptotic analysis of precoded OFDM with hierarchical modulation

This paper investigates the bit error rate (BER) performance of hierarchically modulated precoded Orthogonal Frequency Division Multiplexing (OFDM). We consider a low priority stream modulated on top of a high priority stream with a constellation ratio a and analyze the resulting BER performance. Since the BER depends in a complex way on the particular precoding matrix used, it is difficult for one to gain direct insight into the performance of the hierarchically modulated system. We overcome this difficulty by resorting to the framework of large system analysis [1] in order to derive the asymptotic expression of the BER of the Minimum Mean Squared Error (MMSE) receiver. Assuming that the entries of the precoding matrix are independent and identically distributed (i.i.d) random variables, we derive the limit BER for the 4QAM and the 16QAM low priority stream cases. The limit BER is obtained by assuming that the number of OFDM sub-carriers and the number of OFDM symbols tend to infinity at the same rate. We show that the limit BER is independent of the particular realizations of the precoding matrix. Simulation results show that the asymptotic expression perfectly matches the empirical results obtained for FFT sizes as low as 256 in different channel conditions. We then use the asymptotic expression to gain useful insights into the effect of the different configuration parameters on the system performance.