Miracle-dz/UniFAR-FTUs huggingface dataset:
Changing mindsets in the modern foreign languages classroom: an intervention combining intelligence theories and reading strategies

ABSTRACT Recent research has established that it is academically advantageous for students to adopt an incremental view of their intelligence and that this is a key marker of a student’s level of self-efficacy. The self-efficacy of students following Modern Foreign Languages (MFL) courses in UK secondary schools is known to be low. Interventions have been successful in modifying students’ intelligence theories in the short term, but less research has been conducted into the longer-term impact of such interventions. This paper investigates the impact of intervention training focussed on the benefits of adopting both an incremental theory of intelligence and a strategic approach to learning. We report the results of a year-long intervention study with a quasi-experimental design based in a large comprehensive secondary school in England. The participants were five Year 9 German as a foreign language classes (N = 127). The impact of two interventions is assessed through in-depth questionnaires, analysis of student outcomes, and students’ intentions to continue with post-compulsory language study. The findings of this study yield significant implications for teachers’ classroom practice. Targeted intervention is shown to have a lasting impact on students’ theories of intelligence. The combination of interventions appears to have had an effect on the frequency with which students report adaptive attributions for failure. Most strikingly, for students of lower initial attainment, such interventions may have the power to transform attainment and motivation to continue with language study.
Human T-Cell Lymphotropic Virus Type 1 (HTLV-1) and HTLV-1–Associated Myelopathy/Tropical Spastic Paraparesis

The human T-cell lymphotropic virus type 1 (HTLV-1) is an oncogenic retrovirus that is transmitted from mother to child, particularly through prolonged breastfeeding; between sexual partners through unprotected intercourse; and from donors to recipients through transfusion and transplantation. Thirty-five years after its discovery, screening for HTLV-1 infection is at best patchy and mostly nonexistent. There are 2 main reasons for this: first, the most recent estimate of the prevalence of HTLV-1 is 5–10 million persons worldwide, with the important caveat that 86% of the global population is data poor in this regard [1]; second, there is a perception that disease related to this virus, which has coexisted with humankind for 60 000 years, is uncommon. Whether this reputation is justified requires upto-date and reliable sero- and clinical epidemiology. The lifetime risk, among carriers, of adult-T-cell leukemia/lymphoma is 2%– 6% regardless of the region of study. However, for HTLV-1–associated myelopathy/ tropical spastic paraparesis (HAM/TSP), more varied risks are reported with strong hints that, apart from the route of infection, ethnicity and human leukocyte antigen (HLA) types impact significantly on risk. Furthermore, HTLV-1 has been associated with a range of other inflammatorymanifestationsaffectingmanyorgans but particularly eyes, lungs, and thyroid and with increased susceptibility to a number of infections, most notably Strongyloides stercoralis hyperinfestation syndrome. (Given the high mortality of this latter condition, it is our policy to screen all HTLV-1 carriers who have resided in endemic areas for S. stercoralis). These diseases are much less well recognized even than HAM/TSP, with no data on incidence or prevalence among carriers. How, then, are we to judge the global disease burden of HTLV-1 infection? In this edition of Clinical Infectious Diseases, Tanajura et al report on a longitudinal study of 414 HTLV-1–infected individuals in Brazil [2]. There are a number of striking findings. First, among study participants not previously diagnosed with HAM/TSP, 18.4% had, at baseline assessment, symptoms, signs, and investigations consistent with a definite diagnosis of HAM/TSP. Second, an additional 21%, again at baseline, had possible or probable HAM/TSPon the basis of having either 1 motor sign consistent with HAM/TSP or a neurogenic bladder (probable) or a clinical diagnosis of HAM/TSP without exclusion of other possible diagnoses (possible). Third, during up to 8 years of follow-up, 5 subjects (all from the probable HAM/TSP category) were diagnosed with definite HAM, an incidence of 1.5%. Finally, very high incidences of a range of neurological symptoms were documented, particularly sensory, including upper limb, even though the median perperson follow-up was only 2 years.
Look-ahead cruise control considering road geometry and traffc flow

The paper deals with the design of an adaptive cruise control system considering the optimal energy and fuel consumption of the vehicle as well as safety aspects of cornering maneuvers. In the velocity design the look-ahead system considers several information of the road sections ahead of the vehicle. By incorporating road information about the geometrical characteristics and traffic of the oncoming road sections, e.g. speed limits, road slopes, road curvature and traffic mean speed it is possible to alter the velocity of the vehicle in advance. Such way, the longitudinal energy required by the vehicle motion can be reduced significantly. The main novelty of the paper is the adaptation of forward traffic mean speed and safe cornering velocity in the look-ahead control algorithm. It is demonstrated in real data simulation that with the proposed method significant amount of fuel can be saved and the safety of the vehicle motion can also be enhanced.
An Augmented-Based Approach for Compiling Min-based Possibilistic Causal Networks

This paper emphasizes on handling uncertain and causal information in a min-based possibility theory framework. More precisely, we focus on studying the representational point of view of interventions under a compilation framework. We propose two compilation-based inference algorithms for min-based possibilistic causal networks based on encoding the augmented network into a propositional theory and compiling this output in order to efficiently compute the effect of both observations and interventions.
A New Intelligent Contour Tracking Algorithm in Binary Image

There are some problems in the traditional contour tracking algorithms based on direction to track boundary points. Such as low accuracy, low efficiency and easy to fall into the cycle of death. To solve these problems, this paper presents a new boundary contour tracking algorithm, it combines the boundary points' scanning direction and weights to determine the next boundary point, the algorithm can scan multiple connected region contours. Experiments show that our algorithm is not only very accurate, but also to get a complete and accurate target area outline. Especially for those contour feature points which distributed complicated area, it has better reflect superiority of the algorithm.
Genome-Wide Associations of Gene Expression Variation in Humans

The exploration of quantitative variation in human populations has become one of the major priorities for medical genetics. The successful identification of variants that contribute to complex traits is highly dependent on reliable assays and genetic maps. We have performed a genome-wide quantitative trait analysis of 630 genes in 60 unrelated Utah residents with ancestry from Northern and Western Europe using the publicly available phase I data of the International HapMap project. The genes are located in regions of the human genome with elevated functional annotation and disease interest including the ENCODE regions spanning 1% of the genome, Chromosome 21 and Chromosome 20q12–13.2. We apply three different methods of multiple test correction, including Bonferroni, false discovery rate, and permutations. For the 374 expressed genes, we find many regions with statistically significant association of single nucleotide polymorphisms (SNPs) with expression variation in lymphoblastoid cell lines after correcting for multiple tests. Based on our analyses, the signal proximal (cis-) to the genes of interest is more abundant and more stable than distal and trans across statistical methodologies. Our results suggest that regulatory polymorphism is widespread in the human genome and show that the 5-kb (phase I) HapMap has sufficient density to enable linkage disequilibrium mapping in humans. Such studies will significantly enhance our ability to annotate the non-coding part of the genome and interpret functional variation. In addition, we demonstrate that the HapMap cell lines themselves may serve as a useful resource for quantitative measurements at the cellular level.
Chapter 3. Strategy 1

The word “strategy” has been in use since Sun Tzu wrote the Art of War in the fourth century B.C. (Sun Tzu 1971). Sun Tzu wrote, of course, about military strategy. The literature on corporate strategy, which emerged in the 1950s and 1960s (Chandler 1962; Ansoff 1965; Learned et al. 1965) is vast and continues to grow at an astonishing rate. Strategic management – the way in which a firm identifies its strategic direction and aligns its operational processes to its strategy – has become an academic discipline in its own right, like marketing and finance (Mintzberg et al. 1998:18; Rumelt et al. 1994:15). In essence, strategy has to do with understanding where an organization will go in the future and how it will get there. Most academicians and corporate managers believe strategy affects the overall welfare of the corporation, and strategy making is an important activity, though a few believe firms are better off without a strategy (see Inkpen and Choudhury 1995). Many who believe strategy is important, however, find fault with the ability of formalized strategic planning processes to deal adequately with the pace of change facing organizations in today’s environment.
A new wireless underground network system for continuous monitoring of soil water contents

A new stand‐alone wireless embedded network system has been developed recently for continuous monitoring of soil water contents at multiple depths. This paper presents information on the technical aspects of the system, including the applied sensor technology, the wireless communication protocols, the gateway station for data collection, and data transfer to an end user Web page for disseminating results to targeted audiences. Results from the first test of the network system are presented and discussed, including lessons learned so far and actions to be undertaken in the near future to improve and enhance the operability of this innovative measurement approach.
Modeling the Semantics of Sound

Despite the recent focus on semantic image/video annotation and retrieval, relatively little work has been done on semantic audio annotation and retrieval. We show that the supervised mutli-class naı̈ve Bayes model, which has successfully been used for image annotation, can be used to model the semantics of audio data. This model, as opposed a host of recently proposed unsupervised model, has shown superior performance and requires relatively little computation time for both parameter estimation and inference. Fast parameter estimation is achieved using the mixture hierarchies algorithm. We consider two heterogeneous audio and text data sets; sound efffects with captions, and music with associated reviews. We show that, with the supervised multi-class model, we can both annotate a novel audio track with semantically meaningful words and retrieve relevant audio track given a text-based query.
Towards optimization of toeplitz matrices for compressed sensing

Compressed sensing is a new theory that samples a signal below the Nyquist rate. While Gaussian and Bernoulli random measurements perform quite well on the average, structured matrices such as Toeplitz are mostly used in practice due to their simplicity. However, the signal compression performance may not be acceptable. In this paper, we propose to optimize the Toeplitz matrices to improve its compression performance to recover sparse signals. We establish the optimization on minimizing the coherence of the measurement matrix by an intelligent optimization method called Particle Swarm Optimization. Our simulation results show that the optimized Toeplitz matrix outperforms the non-optimized one in reconstructing sparse signals in terms of quality and sampling rate.
Rendering Line-Drawings with Limited Resources

Pictures play an important role in the communication process. Communicative goals can be expressed for instance with the specific use of different levels of abstraction in pictures. Especially in textbooks and scientific publications, images are used where the level of detail of different objects is deliberately changed to express the importance of an object in the picture. In this paper we introduce the concept of “drawing resources” for rendered line-drawings. This concept defines measures for controlling the level of detail of single objects in a drawing. We present a system which is based on a line-renderer and which enables a user to interact with the drawing thus created. The concept of drawing resources yields a new basis for formulating the user’s ideas of the appearance of the final image.
On additive higher Chow groups of affine schemes

We show that the multivariate additive higher Chow groups of a smooth affine $k$-scheme $\Spec (R)$ essentially of finite type over a perfect field $k$ of characteristic $\not = 2$ form a differential graded module over the big de Rham-Witt complex $\W_m\Omega^{\bullet}_{R}$. In the univariate case, we show that additive higher Chow groups of $\Spec (R)$ form a Witt-complex over $R$. We use these structures to prove an \'etale descent for multivariate additive higher Chow groups.
Mechanism design for fair division: allocating divisible items without payments

We revisit the classic problem of fair division from a mechanism design perspective and provide an elegant truthful mechanism that yields surprisingly good approximation guarantees for the widely used solution of Proportional Fairness. This solution, which is closely related to Nash bargaining and the competitive equilibrium, is known to be not implementable in a truthful fashion, which has been its main drawback. To alleviate this issue, we propose a new mechanism, which we call the Partial Allocation mechanism, that discards a carefully chosen fraction of the allocated resources in order to incentivize the agents to be truthful in reporting their valuations. This mechanism introduces a way to implement interesting truthful outcomes in settings where monetary payments are not an option. For a multi-dimensional domain with an arbitrary number of agents and items, and for the very large class of homogeneous valuation functions, we prove that our mechanism provides every agent with at least a 1/e ≈ 0.368 fraction of her Proportionally Fair valuation. To the best of our knowledge, this is the first result that gives a constant factor approximation to every agent for the Proportionally Fair solution. To complement this result, we show that no truthful mechanism can guarantee more than 0.5 approximation, even for the restricted class of additive linear valuations. In addition to this, we uncover a connection between the Partial Allocation mechanism and VCG-based mechanism design. We also ask whether better approximation ratios are possible in more restricted settings. In particular, motivated by the massive privatization auction in the Czech republic in the early 90s we provide another mechanism for additive linear valuations that works really well when all the items are highly demanded.
Robust Analysis of Preferential Attachment Models with Fitness

The preferential attachment network with fitness is a dynamic random graph model. New vertices are introduced consecutively and a new vertex is attached to an old vertex with probability proportional to the degree of the old one multiplied by a random fitness. We concentrate on the typical behaviour of the graph by calculating the fitness distribution of a vertex chosen proportional to its degree. For a particular variant of the model, this analysis was first carried out by Borgs, Chayes, Daskalakis and Roch. However, we present a new method, which is robust in the sense that it does not depend on the exact specification of the attachment law. In particular, we show that a peculiar phenomenon, referred to as Bose–Einstein condensation, can be observed in a wide variety of models. Finally, we also compute the joint degree and fitness distribution of a uniformly chosen vertex.
The excedances and descents of bi-increasing permutations

Starting from some considerations we make about the relations between certain difference statistics and the classical permutation statistics we study permutations whose inversion number and excedance difference coincide. It turns out that these (so-called bi-increasing) permutations are just the 321-avoiding ones. The paper investigates their excedance and descent structure. In particular, we find some nice combinatorial interpretations for the distribution coefficients of the number of excedances and descents, respectively, and their difference analogues over the bi-increasing permutations in terms of parallelogram polyominoes and 2-Motzkin paths. This yields a connection between restricted permutations, parallelogram polyominoes, and lattice paths that reveals the relations between several well-known bijections given for these objects (e.g. by Delest-Viennot, Billey-Jockusch-Stanley, Francon-Viennot, and Foata-Zeilberger). As an application, we enumerate skew diagrams according to their rank and give a simple combinatorial proof for a result concerning the symmetry of the joint distribution of the number of excedances and inversions, respectively, over the symmetric group.
A Study of Analytics Driven Solutions for Customer Targeting and Sales Force Allocation in Data Mining

OnTARGET and MAP are examples of analytics-based solutions that were designed from the outset to address specific business challenges in the broad area of sales force productivity. Although they address different underlying issues, these solutions implement a common approach that is generally applicable to a broad class of operational challenges. Both solutions rely on rigorously defined data models that integrate all relevant data into a common database. Choices of the data to be included in the data model are driven both by end-user requirements as well as the need for relevant inputs to analytical models. Both business problems have a natural mapping to applications of predictive modeling: predicting the probability to purchase in the case of OnTARGET, and estimating the realistic revenue opportunity in the case of MAP. Delivering the underlying data and the analytic insights directly to frontline decision makers (sales representatives for OnTARGET and sales executives for MAP) is crucial to driving business impact, and a significant effort has been invested in developing efficient web-based tools with the necessary supporting infrastructure. In this paper we discuss several aspects and analyze them.
Complexity of Boolean functions satisfying the propagation criterion

Complexity of Boolean functions satisfying the propagation criterion(PC), an extended notion of the perfect nonlinearity, is discussed on several computation models. The following topics are investigated; (i) relationships between the unateness and the degree of the PC, (ii) the inversion complexity of perfectly nonlinear Boolean functions, (iii) the formula size of Boolean functions that satisfy the PC of degree 1, (iv) the area-time-square complexity of VLSI circuits computing perfectly nonlinear Boolean functions, (v) the OBDD size of perfectly nonlinear Boolean functions.
Switchable diffraction device using reversible electrodeposition

A switchable diffraction device capable of driving with segment electrodes has been proposed and its operating characteristics were analyzed. The switchable diffraction device is based on a variable cavity structure using reversible electrodeposition technology and two kinds of diffraction gratings are designed to be selectively switched according to the driving electrode. The fabricated device was able to switch the diffraction patterns without any interference between the electrodes, which means that the interference between the electrodes will not be a problem in further device integration with driving circuits. However, when the electrode isolation is not perfect due to parasitic resistance between the electrodes, a weak interference between the electrodes is observed in the diffraction pattern. Therefore, it is expected that ensuring complete insulation between the electrodes will be a very important in the integration of the device. The proposed device can be used as a light control device, an image switchable hologram, etc. Furthermore, it is expected to be applied to reconfigurable metasurfaces through integration with active matrix circuits in the future.
Clustering of heterogeneous precipitation fields for the assessment and possible improvement of lumped neural network models for streamflow forecasts

Abstract. This work addresses the issue of better considering the heterogeneity of precipitation fields within lumped rainfall-runoff models where only areal mean precipitation is usually used as an input. A method using a Kohonen neural network is proposed for the clustering of precipitation fields. The evaluation and improvement of the performance of a lumped rainfall-runoff model for one-day ahead predictions is then established based on this clustering. Multilayer perceptron neural networks are employed as lumped rainfall-runoff models. The Bas-en-Basset watershed in France, which is equipped with 23 rain gauges with data for a 21-year period, is employed as the application case. The results demonstrate the relevance of the proposed clustering method, which produces groups of precipitation fields that are in agreement with the global climatological features affecting the region, as well as with the topographic constraints of the watershed (i.e., orography). The strengths and weaknesses of the rainfall-runoff models are highlighted by the analysis of their performance vis-a-vis the clustering of precipitation fields. The results also show the capability of multilayer perceptron neural networks to account for the heterogeneity of precipitation, even when built as lumped rainfall-runoff models.