Miracle-dz/UniFAR-FTUs huggingface dataset:
PERCEPCIÓN DOCENTE DEL DESARROLLO EMOCIONAL Y CREATIVO DE LOS ESCOLARES DERIVADO DEL DISEÑO COLABORATIVO DE DIGITAL STORYTELLING

El diseno colaborativo de digital storytelling (DST) puede convertirse en una estrategia eficaz para potenciar multiples habilidades y competencias en escolares, al ofrecerles la oportunidad de crear sus propias historias apoyandose en herramientas digitales. Concretamente, esta investigacion constata: a) el cambio percibido por el profesorado sobre el desarrollo emocional y creativo alcanzado por el alumnado de Educacion Infantil y Primaria (N=282), tras participar en un proyecto colaborativo de narracion digital impulsado por la Consejeria de Educacion; y b) el nivel de expresion emocional y creativa plasmada en los relatos finales elaborados. El analisis descriptivo muestra las valoraciones cualitativas del profesorado relativas al cambio percibido en el nivel de habilidades emocionales y creativas desarrollado por los escolares tras el diseno de DST, utilizando 13 indicadores cualitativos. Igualmente, el nivel de expresion emocional y creativa plasmada en los relatos elaborados (N=14) es sometido a evaluacion experta. Los resultados subrayan que – a juicio de los docentes– esta narrativa digital colaborativa ha potenciado las habilidades emocionales del alumnado de Infantil, destacando las alumnas por su capacidad empatica y por preocuparse por los demas, asi como por cumplir lo que se proponen. Respecto a las habilidades emocionales, ellas se adaptan mejor a las situaciones nuevas e identifican y resuelven problemas creativamente. Asimismo, las alumnas de Primaria sobresalen por su desarrollo emocional y creativo, y los cursos superiores presentan mas empatia y preocupacion por los demas, reflexion critica y sensibilidad estetica. Tras analizar los relatos finales, los expertos reconocen que todos poseen originalidad y son adecuados a su intencionalidad, aunque prima el caracter logocentrico que minimiza su impacto emocional. Resaltan la empatia y poder persuasivo de los personajes, especialmente en Primaria. Se puede afirmar que las tematicas abordadas, las tecnicas audiovisuales adoptadas y la ejecucion colaborativa proporcionaron un escenario adecuado para ejercitar habilidades emocionales y creativas.
Both Radioresistant and Hemopoietic Cells Promote Innate and Adaptive Immune Responses to Flagellin

The TLR5 agonist flagellin induces innate and adaptive immune responses in a MyD88-dependent manner and is under development as a vaccine adjuvant. In vitro studies indicate that, compared with other bacteria-derived adjuvants, flagellin is a very potent activator of proinflammatory gene expression and cytokine production from cells of nonhemopoietic origin. However, the role of nonhemopoietic cells in promoting flagellin-induced immune responses in vivo remains unclear. To investigate the relative contributions of the nonhemopoietic (radioresistant) and the hemopoietic (radiosensitive) compartments, we measured both innate and adaptive immune responses of flagellin-treated MyD88 radiation bone marrow chimeras. We observed that radiosensitive and radioresistant cells played distinct roles in the innate response to flagellin, with the radiosensitive cells producing the majority of the TNF-α, IL-12, and IL-6 cytokines and the radioresistant cells most of the KC, IP-10, and MCP-1 cytokines. Direct activation of either compartment alone by flagellin initiated dendritic cell costimulatory molecule up-regulation and induced a significant humoral immune response to the protein itself as well as to coinjected OVA. However, robust humoral responses were only observed when MyD88 was present in both cell compartments. Further studies revealed that hemopoietic and nonhemopoietic expression of the cytokines TNF-α and IL-6, but not IL-1, played an important role in promoting flagellin-induced Ab responses. Thus, in vivo both radioresistant and hemopoietic cells play key nonredundant roles in mediating innate and adaptive immune responses to flagellin.
Design of modified low power booth multiplier

The design of normal multiplier consumes most of the power in DSP processors. In order to reduce the power consumption of multiplier, the low power Booth recoding methodology is implemented by recoding technique. This booth decoder will increase number of zeros in multiplicand. Booth multiplier has booth decoder to recode the given input to booth equivalent. Hence the number of switching activity will be reduced so the power consumption of the design can be reduced. The input bit coefficient will determine the switching activity of the component that is when the input coefficient is zero corresponding rows or column of the adder should be deactivated. When multiplicand contains more number of zeros the higher power reduction can takes place. So in booth multiplier high power reductions will be achieved.
Direct Mismatch Characterization of Femtofarad Capacitors

Reducing the capacitance of programmable capacitor arrays (PCAs), commonly used in analog integrated circuits, is necessary for low-energy applications. However, limited mismatch data are available for small capacitors. We report mismatch measurement for a 2-fF poly-insulator-poly (PIP) capacitor, which is the smallest reported PIP capacitor to the best of the authors' knowledge. Instead of using complicated custom on-chip circuitry, direct mismatch measurement is demonstrated and verified using Monte Carlo simulations and experimental measurements. Capacitive test structures composed of 9-bit PCAs are implemented in a low-cost 0.35-μm CMOS process. Measured data are compared to the mismatch of large PIP capacitors, theoretical models, and recently published data. Measurement results indicate an estimated average relative standard deviation of 0.43% for the 2-fF unit capacitor, which is better than the reported mismatch of metal-oxide-metal (MOM) fringing capacitors implemented in an advanced 32-nm CMOS process.
Propolis: A Complex Natural Product with a Plethora of Biological Activities That Can Be Explored for Drug Development

The health industry has always used natural products as a rich, promising, and alternative source of drugs that are used in the health system. Propolis, a natural resinous product known for centuries, is a complex product obtained by honey bees from substances collected from parts of different plants, buds, and exudates in different geographic areas. Propolis has been attracting scientific attention since it has many biological and pharmacological properties, which are related to its chemical composition. Several in vitro and in vivo studies have been performed to characterize and understand the diverse bioactivities of propolis and its isolated compounds, as well as to evaluate and validate its potential. Yet, there is a lack of information concerning clinical effectiveness. The goal of this review is to discuss the potential of propolis for the development of new drugs by presenting published data concerning the chemical composition and the biological properties of this natural compound from different geographic origins.
Text recognition on traffic panels from street-level imagery

Text detection and recognition in images taken in uncontrolled environments still remains a challenge in computer vision. This paper presents a method to extract the text depicted in road panels in street view images as an application to Intelligent Transportation Systems (ITS). It applies a text detection algorithm to the whole image together with a panel detection method to strengthen the detection of text in road panels. Word recognition is based on Hidden Markov Models, and a Web Map Service is used to increase the effectiveness of the recognition. In order to compute the distance from the vehicle to the panels, a function that estimates the distance in meters from the text height in pixels has been obtained. After computing the direction vector of the vehicle, world coordinates are computed for each panel. Experimental results on real images from Google Street View prove the efficiency of our proposal and give way to using street-level images for different applications on ITS such as traffic signs inventory or driver assistance.
Title Global Optimization of Centroidal Voronoi Tessellation withMonte Carlo Approach

Centroidal Voronoi Tessellation (CVT) is a widely used geometric structure in applications including mesh generation, vector quantization and image processing. Global optimization of the CVT function is important in these applications. With numerical evidences, we show that the CVT function is highly nonconvex and has many local minima and therefore the global optimization of the CVT function is nontrivial. We apply the method of Monte Carlo with Minimization (MCM) to optimizing the CVT function globally and demonstrate its efficacy in producing much improved results compared with two other global optimization methods.
Incentives for Transshipment in a Supply Chain with Decentralized Retailers

We examine transshipment incentives in a decentralized supply chain where a monopolist distributes a product through independent retailers. A key insight is that the transshipment price determines whether the firms benefit from, or are hurt by, transshipment. In particular, we show that the manufacturer prefers to set the transshipment price as high as possible, whereas retailers prefer a lower transshipment price. Given the important role of the transshipment price in determining the benefits that each firm gets from transshipment, it is useful to consider transshipment in the case where retailers are under joint ownership (a “chain store”) and the transshipment price does not play a role. This comparison yields two surprising results. First, if decentralized retailers control the transshipment price, they will choose a relatively low transshipment price as a way to mitigate the manufacturer's ability to extract profits by increasing wholesale prices; therefore, the manufacturer may prefer dealing with the chain store, which does not have a transshipment price, rather than with decentralized retailers. Similarly, the decentralized retailers can use a low transshipment price to achieve higher total profits than a chain store.
Distributed Apriori for Malls

—Data mining is used for knowledge discovery in database i.e. data is mined from database and it generates information data which is used by humans effectively and efficiently. Data mining has area known as Association rule mining, which is based on pruning candidate keys. An Apriori algorithm is commonly used Association Rule mining. Apriori algorithm was already been used for single shopping mall. This paper introduces a new way to use Apriori algorithm for distributed shopping mall system. The purpose of this system is to increase the profits of mall administration and develop a customer relationship.
The Anatomy of Corruption: The Practice of Pension Fund Trustee Decisionmaking

The model of pension plan trustee decisionmaking introduced in a previous paper is extended here emphasising aspects of the social psychology of investment decisionmaking, including collegiality and the necessity of justification. To give the analysis structure, I begin with the framing logic of Kahneman and Tversky and introduce three different frames structuring decisionmaking, starting with the ‘weapons of influence’, the ‘strategies of justification’, and, finally, the ‘emotions of relationships’. The focus of the paper is on how and why corruption occurs in trustee decisionmaking, especially concerning community development projects. Implications are drawn from the model of corruption for current debate over the proper scope of regulation. It is argued that the current system of trust law and case-by-case adjudication is inadequate in the face of the systematic nature of corruption and the potential harm occasioned by corrupt trustee decisionmaking. It is also argued that the model of corruption sketched in this paper can be applied to a wide range of investment decisions, not just community development projects (the initial reference point for the paper).
Analysis of a tripole array for polarization and direction of arrival estimation

In this paper we evaluate the performance of a tripole array for estimation of the polarization and one dimensional direction of arrival (DOA). We employ a model based on far-field calculations of a tripole antenna and completely polarized electromagnetic waves carrying Gaussian distributed signals. The analysis of the performance is based on calculations of the Cramer-Rao lower bound (CRLB) for the polarization and DOA estimators. It is seen that the tripole array is suitable for polarization estimation with or without knowledge of the DOA. It is also seen that the quality of the DOA estimate depends strongly on the polarization state.
On tangents to quadric surfaces

We study the variety of common tangents for up to four quadric surfaces in projective three-space, with particular regard to congurations of four quadrics admitting a continuum of common tangents. We formulate geometrical conditions in the projective space dened by all complex quadric surfaces which express the fact that several quadrics are tangent along a curve to one and the same quadric of rank at least three, and called, for intuitive reasons: a basket. Lines in any ruling of the latter will be common tangents. These considerations are then restricted to spheres in Euclidean threespace, and result in a complete answer to the question over the reals: "When do four spheres allow infinitely many common tangents? ".
IP cores for hardware acceleration of decision tree ensemble classifiers

This paper proposes four different hardware architectures for parallel implementation of decision trees forming an ensemble classifier are presented. Proposed architectures can accelerate ensemble classifiers composed of axis-parallel, oblique and nonlinear decision tree (DTs). Hardware architectures for the implementation of a number of combination rules are also presented, enabling the complete ensemble classifier hardware accelerators. Conducted experiments, based on 29 UCI datasets, indicate that the Field Programmable Gate Array (FPGA) implementations based on proposed architectures offer significant improvement in the instance classification time in comparison with the traditional software implementations.
Treatment of Missing Data in Intelligent Lighting Applications

The concept of intelligent lighting facilitates the use of machine learning models to adapt the lighting application behavior based on changing context. Ideally, a complete dataset without missing values is used to train the learning algorithm. Nevertheless, it is common to have missing data values in the dataset, e.g. due to lack of rich enough user interfaces such as smart phones. In this paper, we study various probabilistic approaches to treat missing feature values in a dataset collected from an office breakout area. This dataset is used to train the learning model to provide intelligent lighting solutions. We evaluate the performance of five different approaches by simulation, using four rule-based classification algorithms and various proportions of missing data. We find that none of these approaches gives best performance over the necessary range of conditions, and that an adaptive strategy is more suited.
Dynamical mean-field theory for light-fermion-heavy-boson mixtures on optical lattices

We theoretically analyze Fermi-Bose mixtures consisting of light fermions and heavy bosons that are loaded into optical lattices (ignoring the trapping potential). To describe such mixtures, we consider the Fermi-Bose version of the Falicov-Kimball model on a periodic lattice. This model can be exactly mapped onto the spinless Fermi-Fermi Falicov-Kimball model at zero temperature for all parameter space as long as the mixture is thermodynamically stable. We employ dynamical mean-field theory to investigate the evolution of the Fermi-Bose Falicov-Kimball model at higher temperatures. We calculate spectral moment sum rules for the retarded Green's function and self-energy, and use them to benchmark the accuracy of our numerical calculations, as well as to reduce the computational cost by exactly including the tails of infinite summations or products. We show how the occupancy of the bosons, single-particle many-body density of states for the fermions, momentum distribution, and the average kinetic energy evolve with temperature. We end by briefly discussing how to experimentally realize the Fermi-Bose Falicov-Kimball model in ultracold atomic systems.
A Hybrid Distributed Coordination Function for Scalability and Interoperability in Large-scale WLANs ∗

The distributed coordination function (DCF) of IEEE 802.11 MAC protocol is not scalable as the number of users on a network increases. We propose two new contention resolution schemes to reduce the number of collisions between a large number of contending mobile stations. The hybrid DCF (H-DCF) scheme splits contention resolution into two phases to improve scalability. Enhanced hybrid DCF (EHDCF) adds fairness with expect to mobile stations using the current IEEE 802.11 MAC and further improves the efficiency of contention resolution. Inter-operability with the IEEE 802.11 DCF is the major advance over previous work. We use an ns-2 simulator to simulate the performance of these new schemes with the IEEE 802.11 DCF. The results show that an improvement in network performance by up to 10∼30%. KeywordsIEEE 802.11; scalability; inter-operability; two phase contentions; null frame; channel occupancy regulation
Natural Selection and Adaptive Evolution of Leptin in the Ochotona Family Driven by the Cold Environmental Stress

Background Environmental stress can accelerate the evolutionary rate of specific stress-response proteins and create new functions specialized for different environments, enhancing an organism's fitness to stressful environments. Pikas (order Lagomorpha), endemic, non-hibernating mammals in the modern Holarctic Region, live in cold regions at either high altitudes or high latitudes and have a maximum distribution of species diversification confined to the Qinghai-Tibet Plateau. Variations in energy metabolism are remarkable for them living in cold environments. Leptin, an adipocyte-derived hormone, plays important roles in energy homeostasis. Methodology/Principal Findings To examine the extent of leptin variations within the Ochotona family, we cloned the entire coding sequence of pika leptin from 6 species in two regions (Qinghai-Tibet Plateau and Inner Mongolia steppe in China) and the leptin sequences of plateau pikas (O. curzonia) from different altitudes on Qinghai-Tibet Plateau. We carried out both DNA and amino acid sequence analyses in molecular evolution and compared modeled spatial structures. Our results show that positive selection (PS) acts on pika leptin, while nine PS sites located within the functionally significant segment 85-119 of leptin and one unique motif appeared only in pika lineages-the ATP synthase α and β subunit signature site. To reveal the environmental factors affecting sequence evolution of pika leptin, relative rate test was performed in pikas from different altitudes. Stepwise multiple regression shows that temperature is significantly and negatively correlated with the rates of non-synonymous substitution (Ka) and amino acid substitution (Aa), whereas altitude does not significantly affect synonymous substitution (Ks), Ka and Aa. Conclusions/Significance Our findings support the viewpoint that adaptive evolution may occur in pika leptin, which may play important roles in pikas' ecological adaptation to extreme environmental stress. We speculate that cold, and probably not hypoxia, may be the primary environmental factor for driving adaptive evolution of pika leptin.
Locality-Aware Concurrency-Driven Issue

The contribution of memory latency to execution time keeps increasing in modern memory systems. The hierarchical memory based on locality is the design to alleviate this effect. However, a modern memory system is also supported by various concurrency-driven technologies and the effect of leveraging locality with the consideration of concurrency becomes uncertain. We found that concurrency-driven technologies may hurt locality in two ways. Firstly, a hit in sequential access can become a miss in parallel data access. Secondly, parallel data accesses leads to bursts, including hit and miss bursts. The miss bursts are detrimental to CPUs' execution. This paper proposes a Locality-Aware Issue (LAI) mechanism, and that creates overlaps between hit and miss accesses. This mechanism allows accesses with small latency in flight to consistently feed the CPUs and at the same time, accommodate as many long-latency accesses as possible to hide the miss penalty. We explore the potential of LAI via a manual method and also provide the online optimization implementation. We empirically evaluate our proposal with cycle-accurate simulator GEM5. Experimental results on memory intensive benchmarks from SPEC2006 demonstrate an average 5.84% (up to 13%) performance improvements.
An Adaptive Controller for Multimodal Systems Based on Fuzzy Reference Model Generator

This paper presents a novel adaptive controller for multimodal systems based on Fuzzy Reference Model Generator (FRMG). The proposed scheme consists of a fuzzy logic switching method working along with a Model Reference Adaptive Control (MRAC) framework. The fuzzy switching scheme produce a 'soft' way of generating the reference model, combining a group of weighted reference models at each plant operating point. Unlike static multiple model algorithms, this scheme provides an interactive multiple model environment with soft switching. Simulation results conducted on two practical examples of multimodal systems show that the scheme is computationally feasible, efficient and fault tolerant in nature.