Miracle-dz/UniFAR-FTUs huggingface dataset:
An Experimental Evaluation of Logiocando, an Intelligent Tutoring Hypermedia System

Several hypermedia learning environments have been developed in the last years, with the objective of helping students to acquire specific concepts in a given domain, as well as problem-solving abilities. However, there are still many different and sometimes conflicting claims about learning effectiveness using such environments. We present an empirical evaluation of a learning hypermedia with a tutorial component that exploits Artificial Intelligence techniques. This hypermedia, called Logiocando, has been designed for use by a special category of user, namely children of the fourth level of primary school (9-10 years old), to help them to learn basic concepts of logic. This category of user demands special attention to usability of the hypermedia. For this reason, design and development of the hypermedia have been carried out following a learner-centred methodology, in order to build a system that satisfies clear usability objectives. The aim of the study herein reported was to evaluate the learning effectiveness of Logiocando and to estimate the difference between two approaches: computer-based using a hypermedia system, and traditional, namely a typical lesson in the classroom. The results have shown that the hypermedia can be considered a valid support in the process of learning and deepening a topic.
Sensitivity-optimized rigging for example-based real-time clothing synthesis

We present a real-time solution for generating detailed clothing deformations from pre-computed clothing shape examples. Given an input pose, it synthesizes a clothing deformation by blending skinned clothing deformations of nearby examples controlled by the body skeleton. Observing that cloth deformation can be well modeled with sensitivity analysis driven by the underlying skeleton, we introduce a sensitivity based method to construct a pose-dependent rigging solution from sparse examples. We also develop a sensitivity based blending scheme to find nearby examples for the input pose and evaluate their contributions to the result. Finally, we propose a stochastic optimization based greedy scheme for sampling the pose space and generating example clothing shapes. Our solution is fast, compact and can generate realistic clothing animation results for various kinds of clothes in real time.
Composite Fermions and Integer Partitions

We utilize the KOH theorem to prove the unimodality of integer partitions with at most a parts, all parts less than or equal to b, that are required to contain either repeated or consecutive parts. We connect this result to an open question in quantum physics relating the number of distinct total angular momentum multiplets of a system of N fermions, each with angular momentum ? , to those of a system in which each Fermion has angular momentum ? *=? N+1.
Text Mining in Clinical Domain: Dealing with Noise

Text mining in clinical domain is usually more difficult than general domains (e.g. newswire reports and scientific literature) because of the high level of noise in both the corpus and training data for machine learning (ML). A large number of unknown word, non-word and poor grammatical sentences made up the noise in the clinical corpus. Unknown words are usually complex medical vocabularies, misspellings, acronyms and abbreviations where unknown non-words are generally the clinical patterns including scores and measures. This noise produces obstacles in the initial lexical processing step as well as subsequent semantic analysis. Furthermore, the labelled data used to build ML models is very costly to obtain because it requires intensive clinical knowledge from the annotators. And even created by experts, the training examples usually contain errors and inconsistencies due to the variations in human annotators' attentiveness. Clinical domain also suffers from the nature of the imbalanced data distribution problem. These kinds of noise are very popular and potentially affect the overall information extraction performance but they were not carefully investigated in most presented health informatics systems. This paper introduces a general clinical data mining architecture which is potential of addressing all of these challenges using: automatic proof-reading process, trainable finite state pattern recogniser, iterative model development and active learning. The reportability classifier based on this architecture achieved 98.25% sensitivity and 96.14% specificity on an Australian cancer registry's held-out test set and up to 92% of training data provided for supervised ML was saved by active learning.
Monocular SLAM with Inverse Scaling Parametrization

The recent literature has shown that it is possible to solve t he monocular Simultaneous Localization And Mapping using both undelayed features initialization and an Extedend Kalman Filter. The key concept, to achieve this result, was the introduction of a new parametrization calle d Unified Inverse Depth that produces measurements equations with a high degree of linearity and allows an efficient and accurate modeling of uncertai nties. In this paper we present a monocular EKF SLAM filter based on an altern ative parametrization, i.e., the Inverse Scaling Parametrizati on, characterized by a reduced number of parameters, a more linear measurement model, and a better modeling of features uncertainty for both low and high parallax features. Experiments in simulation demonstrate that the use of the Inverse Scaling solution improves the monocular EKF SLAM filter when compared with the Unified Inverse Depth approach, while experiments on real da ta show the system working as well.
Distribution of Monocarboxylate Transporters in the Peripheral Nervous System Suggests Putative Roles in Lactate Shuttling and Myelination

Lactate, a product of glycolysis, has been shown to play a key role in the metabolic support of neurons/axons in the CNS by both astrocytes and oligodendrocytes through monocarboxylate transporters (MCTs). Despite such importance in the CNS, little is known about MCT expression and lactate function in the PNS. Here we show that mouse MCT1, MCT2, and MCT4 are expressed in the PNS. While DRG neurons express MCT1, myelinating Schwann cells (SCs) coexpress MCT1 and MCT4 in a domain-specific fashion, mainly in regions of noncompact myelin. Interestingly, SC-specific downregulation of MCT1 expression in rat neuron/SC cocultures led to increased myelination, while its downregulation in neurons resulted in a decreased amount of neurofilament. Finally, pure rat SCs grown in the presence of lactate exhibited an increase in the level of expression of the main myelin regulator gene Krox20/Egr2 and the myelin gene P0. These data indicate that lactate homeostasis participates in the regulation of the SC myelination program and reveal that similar to CNS, PNS axon–glial metabolic interactions are most likely mediated by MCTs.
EXISTENCE OF $q$ -ANALOGS OF STEINER SYSTEMS

Let $\mathbb{F}_{q}^{n}$ be a vector space of dimension $n$ over the finite field $\mathbb{F}_{q}$ . A $q$ -analog of a Steiner system (also known as a $q$ -Steiner system), denoted ${\mathcal{S}}_{q}(t,\! k,\! n)$ , is a set ${\mathcal{S}}$ of $k$ -dimensional subspaces of $\mathbb{F}_{q}^{n}$ such that each $t$ -dimensional subspace of $\mathbb{F}_{q}^{n}$ is contained in exactly one element of ${\mathcal{S}}$ . Presently, $q$ -Steiner systems are known only for $t\,=\,1\! $ , and in the trivial cases $t\,=\,k$ and $k\,=\,n$ . In this paper, the first nontrivial $q$ -Steiner systems with $t\,\geqslant \,2$ are constructed. Specifically, several nonisomorphic $q$ -Steiner systems ${\mathcal{S}}_{2}(2,3,13)$ are found by requiring that their automorphism groups contain the normalizer of a Singer subgroup of $\text{GL}(13,2)$ . This approach leads to an instance of the exact cover problem, which turns out to have many solutions.
Computing Lyapunov functions for strongly asymptotically stable differential inclusions

Abstract We present a numerical algorithm for computing Lyapunov functions for a class of strongly asymptotically stable nonlinear differential inclusions which includes switched systems and systems with uncertain parameters. The method relies on techniques from nonsmooth analysis and linear programming and leads to a piecewise affine Lyapunov function. We provide a thorough analysis of the method and present two numerical examples.
Searching for Diamonds in the Apomictic Rough: A Case Study Involving Boechera lignifera (Brassicaceae)

Abstract The genus Boechera is one of the most difficult species complexes in North America, with about 70 sexual diploids and hundreds of apomictic taxa representing diverse combinations of nearly every known sexual genome. In this study, we set out to clarify the taxonomy of Boechera lignifera, which currently includes a small number of sexual diploid populations in addition to the widespread apomictic diploid upon which the name is based. Using data from cytological studies, microsatellite DNA analyses, geography, and morphology, we demonstrate that the apomictic populations are genetically quite divergent from the sexual diploids. We propose the name Boechera kelseyana to accommodate the sexual diploid taxon, which occurs entirely south of the geographic range of B. lignifera. Boechera kelseyana is consistently separable from B. lignifera based on pollen and seed morphology, the length and proximal orientation of fruiting pedicels, differences in the branching and orientation of trichomes on the lowers stems, and the number of flowers and cauline leaves on unbranched fertile stems.
The liberalization of environmental goods and services: overview and implications for Latin America and the Caribbean

This paper focuses primarily on proposals to liberalize trade of Environmental Goods, characterizing the trade of these products in Latin America and the Caribbean. The objective is to help identify trends, risks and opportunities for exporters as well as for importers, in a context of increased global competition in manufactured products from Asia and China in particular. For Latin America and the Caribbean, implementing policies aimed at both lowering trade barriers to environmental goods and services and "greening" the region's export basket will result in gains both for the environment and for productive and export diversification since some countries are already leaders in global markets of environmental goods and services and are well positioned to expand their positions. There are large risks, however, given the existing preferential access by some developing countries and the significant differences in manufacturing capacity that threaten domestic industries of key technologies.
Exchange rates and monetary policy regimes in Canada and the U.S

This paper examines monetary regime switching in Canada and the United States and the implications of regime switching for exchange rates and key nominal and real macroeconomic aggregates for the two countries. Evidence of Markov regime switching in the process governing monetary base growth and in the bilateral exchange rate between the two countries is presented. Given this evidence, a two-country general equilibrium monetary model is constructed to account for observed properties of the U.S.-Canadian dollar exchange rate and for measured effects of monetary policy on key variables. Agents in the model face a monetary policy process with regime switching and form beliefs about regimes and money growth using observations and Bayesian learning. With the driving process for money growth rates parameterized using estimates from U.S. and Canadian data, quantitative implications of the model for behaviors of exchange rates and other key variables are examined. The findings are that inc lusion of learning by agents contributes somewhat to the model's ability to account for persistence in effects of money shocks on variables, provided that the shocks themselves are persistent; inclusion of learning contributes little in accounting for business cycle fluctuations and exchange rate variability; inclusion of a nonlinear driving process for money growth rates is important for the model to account for long swings in exchange rates; inclusion of learning adds only slightly to the ability of the model to account for long swings. The importance of nonlinearities in the driving process and the relative lack of importance of learning are consistent with other findings in the literature of learning effects in the face of regime switches.
Separation of Narrow Bandwidth Spectral Light from Femtosecond Pulses Using Optical Coupler with Fiber Grating

We have developed spectral separation devices for processing femtosecond pulses. These devices are based on an optical coupler structure with fiber gratings. In a computer simulation, we confirmed that these devices could extract <1 nm bandwidth light with 80% efficiency. We fabricated the spectral separation devices using single mode fibers and highly Ge-doped fibers. These devices successfully extracted narrow spectral light of 0.3 nm bandwidth with 37% efficiency from femtosecond pulses of 40 nm bandwidth. We also fabricated 2-channel spectral separation devices, which could extract the light from each grating channel. key words: ber grating, femto-second pulse, spectral separa-
Neurological Basis for Eye Movements of the Blind

When normal subjects fix their eyes upon a stationary target, their gaze is not perfectly still, due to small movements that prevent visual fading. Visual loss is known to cause greater instability of gaze, but reported comparisons with normal subjects using reliable measurement techniques are few. We measured binocular gaze using the magnetic search coil technique during attempted fixation (monocular or binocular viewing) of 4 individuals with childhood-onset of monocular visual loss, 2 individuals with late-onset monocular visual loss due to age-related macular degeneration, 2 individuals with bilateral visual loss, and 20 healthy control subjects. We also measured saccades to visual or somatosensory cues. We tested the hypothesis that gaze instability following visual impairment is caused by loss of inputs that normally optimize the performance of the neural network (integrator), which ensures both monocular and conjugate gaze stability. During binocular viewing, patients with early-onset monocular loss of vision showed greater instability of vertical gaze in the eye with visual loss and, to a lesser extent, in the normal eye, compared with control subjects. These vertical eye drifts were much more disjunctive than upward saccades. In individuals with late monocular visual loss, gaze stability was more similar to control subjects. Bilateral visual loss caused eye drifts that were larger than following monocular visual loss or in control subjects. Accurate saccades could be made to somatosensory cues by an individual with acquired blindness, but voluntary saccades were absent in an individual with congenital blindness. We conclude that the neural gaze-stabilizing network, which contains neurons with both binocular and monocular discharge preferences, is under adaptive visual control. Whereas monocular visual loss causes disjunctive gaze instability, binocular blindness causes both disjunctive and conjugate gaze instability (drifts and nystagmus). Inputs that bypass this neural network, such as projections to motoneurons for upward saccades, remain conjugate.
The COP9 signalosome, cullin 3 and Keap1 supercomplex regulates CHOP stability and adipogenesis

Summary Obesity is one of the most serious health problems of the 21st century. It is associated with highly increased risk of type 2 diabetes, high blood pressure, cardiovascular disease as well as several cancers. The expansion of the fat tissue needs the differentiation of preadipocytes to adipocytes, a process called adipogenesis. Dysfunction of adipogenesis is a hallmark of obesity and delineation of underlying mechanisms has high priority for identifying targets for pharmacological intervention. Here we investigate the impact of the COP9 signalosome (CSN), a regulator of cullin-RING ubiquitin ligases (CRLs), and of C/EBP homologous protein (CHOP) on the differentiation of LiSa-2 preadipocytes. CHOP induced by piceatannol or by permanent overexpression in LiSa-2 cells blocks adipocyte differentiation as characterized by inhibited fat droplet formation and vascular endothelial growth factor (VEGF) production. Knockdown of the CSN by permanent downregulation of CSN1 in LiSa-2 cells elevates CHOP and retards adipogenesis. The effect of the CSN knockdown on CHOP stability can be explained by the protection of the CRL component Keap1 by the CSN associated ubiquitin-specific protease 15 (USP15). Pulldowns and glycerol gradients reveal that CHOP interacts with a supercomplex consisting of the CSN, cullin 3 and Keap1. Transient knockdown of Keap1 increases CHOP steady state level and retards its degradation. We conclude that CHOP stability is controlled by a CSN-CRL3Keap1 complex, which is crucial for adipogenesis. Our data show that CHOP is a distinguished target for pharmacological intervention of obesity.
Preference reasoning for argumentation: non-monotonicity and algorithms

In this paper we are interested in the role of preferences in argumentation theory. To promote a higher impact of preference reasoning in argumentation, we introduce a novel preference-based argumentation theory. Using non-monotonic preference reasoning we derive a Dung-style attack relation from a preference specification together with a defeat relation. In particular, our theory uses efficient algorithms computing acceptable arguments via a unique preference relation among arguments from a preference relation among sets of argu-
The Simulation of the Movement of Fish Schools

In this paper, I explain a school behavior model, which was constructed by Aoki, Huth, and Wissel, used to describe the motion of schools of fish. Schools of fish are characterized by strong cohesion and high parallel orientation without using a leader. In this model, each fish can exhibit one of four basic behavior patterns – repulsion, parallel orientation, attraction, and search – based on its proximity to a neighbor fish. I modified the model in how the fish mixed the influence of its neighbors; the fish takes ̋ a w ighted average of the influences of its neighbors. I ̋ constructed a computer simulation model using r̋obots to test this model, and my data has ̋ shown that the model is quite successful in simulating the characteristics of a school of fish. The ultimate goal of this research is to apply the school behavior model to algorithms for robot formations.
Regional Underdevelopment: Is FDI the Solution? A Semiparametric Analysis

In this Paper we aim to examine the regional impact of foreign-owned establishments on the performance of domestic establishments in the electronics industry in the UK. We use establishment-level data taken from the UK Census of Production (the ARD) to this end. In the econometric specification, we allow for the time-varying endogeneity of the factors of production function, and correct for the sample-selection bias generated by plants with larger capital stocks surviving in spite of lower productivity realisations. The FDI spillover literature has so far abstracted from the selection problem generated by plant exit. To our knowledge, this is the first Paper that simultaneously attempts to correct the production parameter estimates for selectivity induced by plant exit as well as time-varying endogeneity (the ‘not so fixed’ effect), before identifying the impact of foreign direct investment on domestic plant’s productivity. The results indicate that positive spillovers exist but are mostly confined to the region in which the MNE locates. A number of characteristics influence their level, they are higher from non-US firms (in particular Japanese firms) and in more-developed regions.
Industrial cluster involvement and organizational adaptation: An empirical study in international industrial clusters

Purpose – The research of industrial cluster and organizational adaptation can be traced back to early strategic management and organization theory. This paper initiates an attempt to empirically examine the relationship between a firm's involvement in an industrial cluster and its adaptive outcomes.Design/methodology/approach – Field survey research method was used and data were collected from four international industrial clusters which consist of 188 company responses. Regression analysis and path analysis were used to analyze the data.Findings – The paper found that the degree of a firm's involvement in an industrial cluster affects its adaptation outcomes. But the nature of the adaptation benefits depends, to a large degree, on the type of cluster involvement.Research limitations/implications – Using self‐reported data could be a potential limitation of this paper. It would be preferable to have other forms of data for a study.Practical implications – Industrial clusters are widely considered a netwo.
Finding minimal resource allocation in grid with reliability and trust computations using 2-way split backward search

This paper aims at solving the problem of minimally allocating resources on the grid to maximize the grid service reliability with trust integration using deterministic state space search. This project develops modeling and evaluation algorithms to evaluate the grid service reliability. Based on the grid service reliability evaluation, we present a model for the grid resource allocation problem which uses trust to effectively solve it. The quantification of reliability depends upon many factors. Amongst them Task Processing Time, Communication Time & Rate of Failure of grid elements are the three most important factors. The reliability and trust factors plays a vital role in decision making for which resource allocation is minimal. This reliability and trust factors contributes as an important ingredient to the scheduler and resource manager that makes them more efficient. In this work it is assumed that the arrival rate of failure of grid elements follows the Poisson process.
Cooperating Onboard and on the Ground Decision Modules for the Management of an Earth Watching Constellation

In this paper, we show how an Earth watching mission, dedicated to the detection and the tracking of forest fires and volcanic eruptions, and involving a constellation of low-orbiting satellites, equipped with detection and observation instruments, can be reactively and efficiently managed via the cooperation of decision modules implemented on the ground in a mission control center and onboard each satellite.
Compact device modeling for established and emerging technologies with the Qucs GPL circuit simulator

Current trends in circuit simulation technology suggest a strong movement towards software packages which promote equation-defined compact semiconductor device modeling and circuit macromodeling. Today, the Verilog-A subset of the Verilog-AMS hardware description language is one of the most popular choices of hardware description language for model construction. The “Quite universal circuit simulator” (Qucs) is a GPL software package supporting the MOS-AK Verilog-A standardization initiative. This paper outlines how equation centered modeling can act as a strong support vehicle for the construction of new device models and circuit macromodels. The material presented in the text explores the relationship between device model specifications, equation-defined devices and Verilog-A code generation. A number of examples demonstrate the capabilities of the model construction tools implemented by the Qucs development team.