Miracle-dz/UniFAR-FTUs huggingface dataset:
Fatores que influenciam a aprendizagem de conceitos matemáticos em cursos de engenharia: Um estudo exploratório com estudantes da Universidade do Minho

O sucesso na aprendizagem da Matematica no ensino superior constitui um campo emergente de pesquisa, em particular nos cursos de Engenharia. No entanto, em Portugal ainda e incipiente a pesquisa na area, pelo que e pertinente explorar fatores que podem esclarecer a relacao entre os estudantes de Engenharia e a Matematica. Com base em tres focus group realizados com estudantes de dois cursos de Engenharia da Universidade do Minho, este estudo exploratorio pretende investigar as atitudes dos estudantes na aprendizagem de conceitos matematicos e averiguar os fatores que influenciam a sua experiencia no processo de aprendizagem. Para alem da percecao da importância da Matematica no seu curso e na sua futura profissao, os resultados sugerem que ha fatores que influenciam o seu desempenho, nomeadamente o papel do professor e a sua metodologia de ensino, bem como a aplicabilidade dos conceitos matematicos no contexto da Engenharia, o papel ativo do estudante na aprendizagem e a influencia dos pais e da sociedade.PALAVRAS-CHAVEAprendizagem de conceitos matematicos; Engenharia; Focus group; EnsinoSuperior ABSTRACTSuccess in the learning of Mathematics in higher education constitutes anemerging field of research, particularly in the Engineering courses. In Portugal, however, the research in this area remains incipient. It is therefore relevant to explore which factors may clarify the relation between the Engineering students and Mathematics. Based on three focus groups carried out with students from two Engineering courses at the University of Minho, this exploratory study aims to investigate the attitudes of students in the learning of mathematical concepts and find out the factors that influence their experience in the learning process. Beyond the perception of the importance of Mathematics in their course and their future profession, the results suggest that there are factors that influence their performance, such as the teacher's role and his/her teaching methodology, as well as the applicability of mathematical concepts in the context of Engineering, the student’s active role in learning and the influence of parents and society.KEYWORDSLearning of mathematical concepts; Engineering; Focus group; Highereducation
A simple add-on microfluidic appliance for accurately sorting small populations of cells with high fidelity

Current advances in single cell sequencing, gene expression and proteomics require the isolation of single cells, frequently from a very small source population. In this work we describe the design and characterization of a manually operated microfluidic cell sorter that (1) can accurately sort single or small groups of cells from very small cell populations with minimal losses, (2) that is easy to operate and that can be used in any laboratory that has a basic fluorescent microscope and syringe pump, (3) that can be assembled within minutes, (4) that can sort cells in very short time (minutes) with minimum cell stress, (5) that is cheap and reusable. This microfluidic sorter is made from hard plastic material (PMMA) into which microchannels are directly milled with hydraulic diameter of 70 µm. Inlet and outlet reservoirs are drilled through the chip. Sorting occurs through hydrodynamic switching ensuring low hydrodynamic shear stresses, which were modeled and experimentally confirmed to be below the cell damage threshold. Manually operated, the maximum sorting frequencies were approximately 10 cells min−1. Experiments verified that cell sorting operations could be achieved in as little as 15 min, including the assembly and testing of the sorter. In only one out of ten sorting experiments the sorted cells were contaminated with another cell type. This microfluidic cell sorter represents an important capability for protocols requiring fast isolation of single cells from small number of rare cell populations.
Preoptic activation and connectivity during thermal sweating in humans

Animal studies have identified the preoptic area as the key thermoregulatory region of the brain but no comparable information exists in humans. We used fMRI to study the preoptic area of human volunteers. Subjects lay in a 3T MRI scanner and were subjected to whole body heating by a water-perfused suit, to a level that resulted in a low rate of discrete sweating events (measured by finger skin resistance). Control scans were taken under thermoneutral conditions in another group. A discrete cluster of voxels in the preoptic area showed activity that was significantly correlated with thermal sweating events. We then used this cluster as a seed to investigate whether other brain areas had activity correlated with its signal, and whether that correlation depended on thermal state. Several brain regions including the dorsal cingulate cortex, anterior insula and midbrain showed ongoing activity that was correlated with that of the preoptic seed more strongly during heating than during thermoneutrality. These data provide the first imaging evidence for a thermoregulatory role of the human preoptic area. They further suggest that during thermal stress, the preoptic area communicates to several other brain regions with known relevance to the control of autonomic effectors.
GABA and Glutamate Transporters in Brain

The mammalian genome contains four genes encoding GABA transporters (GAT1, slc6a1; GAT2, slc6a13; GAT3, slc6a11; BGT1, slc6a12) and five glutamate transporter genes (EAAT1, slc1a3; EAAT2, slc1a2; EAAT3, slc1a1; EAAT4, slc1a6; EAAT5, slc1a7). These transporters keep the extracellular levels of GABA and excitatory amino acids low and provide amino acids for metabolic purposes. The various transporters have different properties both with respect to their transport functions and with respect to their ability to act as ion channels. Further, they are differentially regulated. To understand the physiological roles of the individual transporter subtypes, it is necessary to obtain information on their distributions and expression levels. Quantitative data are important as the functional capacity is limited by the number of transporter molecules. The most important and most abundant transporters for removal of transmitter glutamate in the brain are EAAT2 (GLT-1) and EAAT1 (GLAST), while GAT1 and GAT3 are the major GABA transporters in the brain. EAAT3 (EAAC1) does not appear to play a role in signal transduction, but plays other roles. Due to their high uncoupled anion conductance, EAAT4 and EAAT5 seem to be acting more like inhibitory glutamate receptors than as glutamate transporters. GAT2 and BGT1 are primarily expressed in the liver and kidney, but are also found in the leptomeninges, while the levels in brain tissue proper are too low to have any impact on GABA removal, at least in normal young adult mice. The present review will provide summary of what is currently known and will also discuss some methodological pitfalls.
A Dash of Psychopathy May Help Women Entrepreneurs

The term “psychopath” conjures up dark images of serial murderers, straitjackets, stalkers and that maniac in the corner office. It is part of the Dark Triad (narcissism, Machiavellianism and psychopathy) and always viewed as negative and harmful -but are there actually conditions, professions and environments in which non-clinical levels are actually beneficial? Can a modest amount of psychopathy allow you to get things done or overcome biases and obstacles? Entrepreneurship is perhaps one such profession.
The Effects of a Cognitive Intervention Strategy on Competitive State Anxiety and Performance in Semiprofessional Soccer Players

The aims of this field-based study were to evaluate the effects of a cognitive intervention technique and to further examine the anxiety–performance relationship in semiprofessional soccer players. Participants completed a composite version of the Competitive State Anxiety Inventory-2 (CSAI-2) 20 minutes before three soccer league matches. Two experimental groups, one suffering from debilitative cognitive anxiety (n = 8), one suffering from debilitative somatic anxiety (n = 8), undertook a 12-week cognitive intervention. Player performances were evaluated using intraindividual criteria. A series of two-way analyses of variance (group and event), with repeated measures on the second factor, indicated significant Group × Event interactions for cognitive anxiety intensity and direction, and somatic anxiety intensity and direction, yet failed to reveal significant interactions or main effects for the performance measures. This study provided partial support for the “matching hypothesis” in that a compatible t.
An Combined Scheduling Algorithm for HSDPA Mode of TD-SCDMA

In high-speed downlink packet access (HSDPA) mode of TD-SCDMA system, high speed downlink traffic channel and some associated control channels are shared by all user equipments (UEs). This shared mechanism causes feedback problem for scheduling, so some scheduling algorithms (for example proportional fair) are not applicable any more. In this paper, an improved scheme is proposed to accommodate to this condition on the basis that system structure is not modified and for the sake of minimizing performance loss. In the proposed algorithm, proportional fair and round robin are combined so that system can work and throughput can be guaranteed. A numerical simulation platform is established to evaluate system performance. Simulation results show that feedback frequency is of great importance to system throughput, and lower feedback rate may eliminate multi-user diversity with large number of users.
Towards a Unified and Modular Approach for Visual Analysis of Enterprise Models

From the point of view of an enterprise architect, the visual analysis of the structure of an Enterprise Model can provide powerful insights and facilitate various analysis tasks. However, analysis methods and visualizations that offer the most valuable results usually depend on the concepts found on the Enterprise Metamodel, and are subjected to a concrete EA modeling tool. In this paper we argue that many structural and domain-specific analysis methods can be automated, composed, and their results visualized in a modular manner. To achieve this, we describe the foundations of a flexible and configurable approach for EA Analysis that is based on components that encapsulate metamodel-specific analysis and visualization techniques, supported by a metamodel-independent platform. The approach is explained with ArchiMate by using a module, currently in development, which we call PRIMate. Benefits from this approach include the integration with existing modeling environments, the reuse of analysis and visualization capabilities in any metamodel, as well as an explicit, composite, and traceable visual analysis process.
Semi-automatic emotion recognition from textual input based on the constructed emotion thesaurus

Natural language has attracted importance to some researchers working on Emotion recognizing. Our study focuses on the semi-automatic acquisition technique to obtain the emotion information with the constructed emotion thesaurus we have made. In this paper, we set up a system to recognize the affect sensing from the sentence or the text. During the building processing of our system, we firstly construct a Chinese language emotion thesaurus, the word in which thesaurus has its own classifying (such as commendatory, derogatory sense and neuter and the image value of the corresponding emotion information. Secondly, we set up the system to recognize the object sentence including functions of the syntax analysis, accidence analysis, emotion sensing and emotion computing. The following investigations are presented to show that the concept of "image value" can be used by the constructed system to obtain the emotion information from the sentence based on the constructed emotion thesaurus.
Experimentation and Modeling of the Tension Behavior of Polycarbonate at High Strain Rates

A comprehensive understanding of the mechanical behavior of polycarbonate (PC) under high-rate loadings is essential for better design of PC products. In this work, the mechanical behavior of PC is studied during tensile loading at high strain rates, using a split Hopkinson tension bar (SHTB). A modified experimental technique based on the SHTB is proposed to perform the tension testing on PC at rates exceeding 1000 s−1. The effect of strain rates on the tension stress–strain law of PC is investigated over a wide range of strain rates (0.0005–4500 s−1). Based on the experiments, a physically based constitutive model is developed to describe the strain rate dependent tensile stress–strain law. The high rate tensile deformation mechanics of PC are further studied via finite element simulations using the LSDYNA code together with the developed constitutive model.
Competition of Banks as Two-Sided Markets

Banks are two-sided markets when they supply payment platforms and make users interacting. The main characteristic of two-sided market is network externality, network externality determine the value of two-sided markets which is determined by users' number of both sides. A key question is the boundary or equilibrium of two-sided markets, if network externality works, the return of scale is increasing and the equilibrium is complete monopoly. The model in this paper indicate that if buyers and sellers intense attracted each other, the scale of this two-sided market will grow unlimited and the equilibrium is complete monopoly. If buyers and sellers mutual benefit each other not so intense, the scale of this two-sided market will convergence. The most important thing for platform competition is not only client quantity, but also reduce transaction costs and make both sides attract each other. For banks, improve user experience and supply more attractive financial goods and services is important for competition.
Leveraging Collusion In Combinatorial Auctions

We investigate dominant-strategy auction mechanisms that, should a sufficiently informed coalition of players be present, exploit it so as to guarantee more efficiency and revenue than is otherwise possible. (Coming from a cryptographic tradition and prizing extreme settings, we refrain from relying on weaker notions of equilibrium; the availability of Bayesian information; any restrictions on the number of players, goods, and colluders; or any restrictions on the type of valuations and the ability of the colluders.)
Maladaptive Synaptic Plasticity in L-DOPA-Induced Dyskinesia

The emergence of L-DOPA-induced dyskinesia (LID) in patients with Parkinson disease (PD) could be due to maladaptive plasticity of corticostriatal synapses in response to L-DOPA treatment. A series of recent studies has revealed that LID is associated with marked morphological plasticity of striatal dendritic spines, particularly cell type-specific structural plasticity of medium spiny neurons (MSNs) in the striatum. In addition, evidence demonstrating the occurrence of plastic adaptations, including aberrant morphological and functional features, in multiple components of cortico-basal ganglionic circuitry, such as primary motor cortex (M1) and basal ganglia (BG) output nuclei. These adaptations have been implicated in the pathophysiology of LID. Here, we briefly review recent studies that have addressed maladaptive plastic changes within the cortico-BG loop in dyskinetic animal models of PD and patients with PD.
Exploring Learning Management System Interaction Data: Combining Data-driven and Theory-driven Approaches

This research connects several data-driven educational data mining approaches to a framework for interaction developed in educational research. In particular, 10 million usage data points collected by a Learning Management System used by students and teachers in 450 online undergraduate courses were analyzed with this framework. A range of educational data mining techniques were employed, including K-means clustering, multiple regression, and classiﬁcation, to both explore and predict student ﬁnal grades and course completion rates. Findings show that support for the overall model varied with the way data were mapped to the framework (e.g., static vs. temporal features) and the analysis technique used (with clustering and classiﬁcation providing more useful insights).
Grasp planning for precision manipulation by multifingered robotic hand

This paper describes a model-based grasp planner for an articulated multi-fingered robotic hand. The planner searches for an initial grasp from which a required continuous motion of an object is achieved using fingertips alone while keeping rolling contact with the object. An adaptive search strategy has been developed and implemented: the error analysis of the failed grasp is made to find the most promising search direction. A quality measure of manipulation is newly introduced and evaluated to select a better grasp among possible candidates. Simulation results are demonstrated.
Nearest Neighbour Search with Zero-Suppressed Decision Diagram for Text Retrieval

Exact NNS on text document becomes very expensive for its high dimensionality and the volumes. We demonstrate Exact NNS on text can be performed in linear time by using Zero-Suppressed Binary Decision Diagram (ZDD). We also demonstrate ZDD combined with Multi-hash technique can perform Approximate NNS on text with sublinear time. The exact NNS Naïve NN-ZDD model query time is order of magnitude faster than exhaustive NN for text, and approximate NNS using ZDD Multi-hash's query time is closer to LSH with less build time and better accuracy.
Quality-driven Integration of Heterogenous Information Systems

Integrated access to information that is spread over multiple, distributed, and heterogeneous sources is an important problem in many scienti c and commercial domains. While much work has been done on query processing and choosing plans under cost criteria, very little is known about the important problem of incorporating the information quality aspect into query planning. In this paper we describe a framework for multidatabase query processing that fully includes the quality of information in many facets, such as completeness, timeliness, accuracy, etc. We seamlessly include information quality into a multidatabase query processor based on a view-rewriting mechanism. We model information quality at di erent levels to ultimately nd a set of high-quality queryanswering plans.
NONLINEAR INDEPENDENT COMPONENT ANALYSIS(ICA) USING POWER SERIES AND APPLICATION TO BLIND SOURCE SEPARATION

Contribution of this paper is the derivation of an algorithm that generalizes Bell & Sejnowski’s classic ICA to tackle nonlinear ICA and the introduction of a new and efficient form of ”natural gradient”. This algorithm uses power series of non-linear mixtures to approximate the Taylor expansion of the inverse function mapping from sources to mixtures. The approximation enables derivation of learning rules for weight matrix associated with power series of any order. When applied to blind source separation, it successfully separated non-linear mixtures for which Bell & Sejnowski’s algorithm could not due to its linear mixture model. In separating linear mixtures using this algorithm, the weight matrices for higher order mixtures converge to zero matrix. This is consistent with intuition, suggesting the validity of the generalization.
Hand Gesture Modeling, Analysis, and Synthesis

Hand gestures are a form of communication among people. Yet we still limit human-computer interaction to cumbersome mice movements. The use of hand gestures in the eld of human-computer interaction has attracted new interest in the past several years. Special glove-based devices have been developed to analyze nger and hand motion and use them to manipulate and explore virtual worlds. To further enrich the naturalness of the interaction, different computer vision-based techniques have been brought into use. At the same time the need for more eecient systems has resulted in new gesture modeling approaches. In this paper we present a review of the most recent work related to hand gesture modeling, analysis and synthesis. We describe four major classes of hand gesture interface techniques: glove-based techniques, vision-based techniques , techniques that use drawing gestures, and other gesture analysis techniques. A brief description of more than thirty gesture-interface systems is presented with special attention focused on the systems that use computer vision techniques.
Reverse engineering an iPhone applications using dynamic analysis

Mobile applications are becoming very complex since business applications increasingly move to the mobile. Hence the same problem of code maintenance and comprehension of poorly documented apps, as in the desktop world, happen to the mobile today. One technique to help with code comprehension is to reverse engineer the application. Specifically, we are interested in the functional structure of the app i.e. how the classes that implement the use cases interact. Then we adapted, to the iPhone, the code analysis technique we developed for the desktop applications. In this paper we present the reverse engineering process and tool we used to reverse engineer the code of an iPhone app and show, in a case study, how these tools are used.
Has an aquatic diet been necessary for hominin brain evolution and functional development?

A number of authors have argued that only an aquatic-based diet can provide the necessary quantity of DHA to support the human brain, and that a switch to such a diet early in hominin evolution was critical to human brain evolution. This paper identifies the premises behind this hypothesis and critiques them on the basis of clinical literature. Both tissue levels and certain functions of the developing infant brain are sensitive to extreme variations in the supply of DHA in artificial feeding, and it can be shown that levels in human milk reflect maternal diet. However, both the maternal and infant bodies have mechanisms to store and buffer the supply of DHA, so that functional deficits are generally resolved without compensatory diets. There is no evidence that human diets based on terrestrial food chains with traditional nursing practices fail to provide adequate levels of DHA or othern-3 fatty acids. Consequently, the hypothesis that DHA has been a limiting resource in human brain evolution must be considered to be unsupported.
Traffic-level community protection in telecommunication networks under large-scale failures

Large-scale failures in telecommunication networks make the preservation of the connections inside a community a challenging task, being traditional approaches focused on the preservation of the global connectivity. To achieve this goal, a new concept of community is proposed, which combines not only the topological information of the network but also the traffic-level interaction. Moreover, six novel community-based strategies to determine best node candidates to be protected according to a limited budget are assessed. The proposed strategies have been tested over four different types of networks and compared to other well-known immunization or protection methods. The obtained results show that, depending on the network topology, either an improved intra-community or global traffic preservation can be achieved w.r. t. traditional approaches.