Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamical Model and Simulations for Gamification of Learning

In this paper an example for the dynamical model for gamification is considered and simulated. Based on the theories of Game Design Features (GDF cool features, fancy graphics, challenging puzzles, and an intriguing setting and story), Key Characteristics of a Learning Game (KCLG Challenge, Curiosity, Fantasy and Control), a theory of educational environment design model (ARCS attention, relevance, confidence and satisfaction), and the theoretical background of Gamification labeled as the MDA (Mechanics, dynamics, and aesthetics) framework, four primary factors such as curiosity, challenge, fantasy and control have been originated. By using these four primary factors, the dynamical model for Gamification was developed and simulated. Furthermore the sensitivities of the four primary factors are considered for different individuals and simulations are represented. The examples and simulations make the values and characteristics of the four primary factors meaningful.
Development of Articulation Assessment and Training System with Speech Recognition and Articulation Training Strategies Selection

Articulation problems seriously reduce speech intelligent and speech communication and affect person's interpersonal communication, personality, social adaptive capacity, and learning ability. In the clinical protocol, language therapist utilizes clinical experience to individualized assessment, treatment, and training. However, the manpower of language therapists and the assistant instruments are insufficient. In this paper, an articulation assessment and training system is proposed to assist language therapists and articulation disorders. The articulation errors in phonetic are analyzed and modeled by clinical linguist. Using clinical experience of language therapists, articulation training strategies for each type of articulation errors are designed. The articulation characteristics of user can be effectively detected. Speechreading information is responded to improve the performance of training program. The articulation training strategy is automatically selected to suggest articulation disorder in language training activities. Experimental results reveal the practicability of proposed method and system.
Decision Tree Algorithms for the Contextual Bandit Problem

To address the contextual bandit problem, we propose online decision tree algorithms. The analysis of proposed algorithms is based on the sample complexity needed to find the optimal decision stump. Then, the decision stumps are assembled in a decision tree, KMDTree, and in a random collection of decision trees, KMD-Forest. We show that the proposed algorithms are optimal up to a logarithmic factor. The dependence of the sample complexity upon the number of contextual variables is logarithmic. The computational cost of the proposed algorithm with respect to the time horizon is linear. These analytical results allow the proposed algorithms to be efficient in real applications, where the number of events to process is huge, and where we expect that some contextual variables, chosen from a large set, have potentially non-linear dependencies with the rewards. When KMDTrees are assembled into a KMD-Forest, the analysis is done against a strong reference, the Random Forest built knowing the joint distribution of contexts and rewards. We show that the expected dependent regret bound against this strong reference is logarithmic with respect to the time horizon. In the experiments done to illustrate the theoretical analysis, KMD-Tree and KMD-Forest obtain promising results in comparison with state-of-theart algorithms.
The resource locating strategy based on sub-domain hybrid P2P network model

P2P networks are important parts of the next generation Internet and P2P file sharing has become one of the most important internet application systems in the world. But P2P network faces a challenge in locating resource: the unstructured P2P network has complex search functions, but the efficiency of resource locating is low. However, it is efficient to locate resources in structure P2P network, but it does not support fuzzy queries and has the higher maintenance cost of network. So how to search the resources in the P2P networks efficiently is becoming the key problem. In traditional network structure, it is difficult to simultaneously meet users' requirements in resource locating efficiency and recall ratio. So this paper proposes a sub-domain hybrid P2P network model (SHPNM), which makes full use of the advantages of supporting fuzzy queries in the unstructured network and maintains efficient in resource locating in structured P2P network. Then it gives a detailed analysis about the design idea of SHPNM as well as the method of resources locating in this model. The nodes are gathered into a domain according to the approaching of nodes' physical location, and the nodes in a domain can form a structured P2P network. Each domain provides two nodes with biggest comprehensive performance value as a boundary node and a backup node, and the boundary nodes are connected together in the form of unstructured P2P networks. Simulations results show that SHPNM can both improve efficiency in locating resource and promote the recall ratio.
Robotic surgery for the sinuses and skull base: what are the possibilities and what are the obstacles?

Purpose of reviewRobotic surgery in otolaryngology – head and neck surgery has become a valuable tool in certain anatomic approaches; however, its application in surgery of the paranasal sinuses and anterior skull base is still in an investigatory phase and requires further evaluation. Recent findingsExisting robotic surgical systems face particular limitations in their application at the skull base because of instrument size and lack of variability. Unfortunately, only one system is available commercially that is applicable in the head and neck region and FDA approved for use in patients. This system, although advantageous in many otolaryngologic procedures, is difficult to use for endoscopic sinus and skull base surgery. However, other systems that target this anatomic subsite specifically are in development and show promise. Advances in the design of robotic arms, materials, and shape will potentially give surgeons a significant advantage over traditional endoscopic techniques. SummaryThis article will review the current applications of robotic systems in paranasal sinus and skull base surgery, describe the requirements of a robotic system for use in this type of surgery, and describe a system under development at our institution.
Multi-objective Design Optimization of Functionally Graded Materials

In this paper, we present a methodology for the simulation and multi- objective optimization of material distribution of functionally graded materials (FGMs). The proposed approach focuses on metal/ceramic and metal/metal functionally graded materials, which oer great promise in high temperature and high heat flux applications. The spatial dis- tribution of the volume fraction is defined using piecewise cubic interpolation of volume fractions at a finite number of control points. The eective material properties are estimated from the local volume fractions of the material constituents us- ing the Mori-Tanaka and self-consistent homoge- nization schemes. Functionally graded rectangu- lar structures that are graded in two-dimensions are analyzed using the element-free Galerkin method to obtain the temperature and stress fields. An exact solutions to the heat conduc- tion and thermoelasticity problems has also been developed for functionally graded thick shells that are graded in the radial direction. The volume fraction distribution is optimized using an elitist, non-dominated sorting multi-objective genetic algorithm. Results for two model prob- lems demonstrate that the proposed methodol- ogy provides a useful design tool for tailoring the material composition of functionally graded components for multiple, often conflicting, ob- jectives.
Knowledge of Healthcare Coverage for Refugee Claimants: Results from a Survey of Health Service Providers in Montreal

Following changes to the Interim Federal Health (IFH) program in Canada in 2012, this study investigates health service providers’ knowledge of the healthcare coverage for refugee claimants living in Quebec. An online questionnaire was completed by 1,772 staff and physicians from five hospitals and two primary care centres in Montreal. Low levels of knowledge and significant associations between knowledge and occupational group, age, and contact with refugees were documented. Social workers, respondents aged 40–49 years, and those who reported previous contact with refugee claimants seeking healthcare were significantly more likely to have 2 or more correct responses. Rapid and multiple changes to the complex IFH policy have generated a high level of confusion among healthcare providers. Simplification of the system and a knowledge transfer strategy aimed at improving healthcare delivery for IFH patients are urgently needed, proposing easy avenues to access rapidly updated information and emphasizing ethical and clinical issues.
Best-Response Dynamics in Combinatorial Auctions with Item Bidding

In a combinatorial auction with item bidding, agents participate in multiple single-item second-price auctions at once. As some items might be substitutes, agents need to strategize in order to maximize their utilities. A number of results indicate that high welfare can be achieved this way, giving bounds on the welfare at equilibrium. Recently, however, criticism has been raised that equilibria are hard to compute and therefore unlikely to be attained. In this paper, we take a different perspective. We study simple best-response dynamics. That is, agents are activated one after the other and each activated agent updates his strategy myopically to a best response against the other agents' current strategies. Often these dynamics may take exponentially long before they converge or they may not converge at all. However, as we show, convergence is not even necessary for good welfare guarantees. Given that agents' bid updates are aggressive enough but not too aggressive, the game will remain in states of good welfare after each agent has updated his bid at least once. In more detail, we show that if agents have fractionally subadditive valuations, natural dynamics reach and remain in a state that provides a $1/3$ approximation to the optimal welfare after each agent has updated his bid at least once. For subadditive valuations, we can guarantee an $\Omega(1/\log m)$ approximation in case of $m$ items that applies after each agent has updated his bid at least once and at any point after that. The latter bound is complemented by a negative result, showing that no kind of best-response dynamics can guarantee more than an $o(\log \log m/\log m)$ fraction of the optimal social welfare.
SAFIUS - A Secure and Accountable Filesystem over Untrusted Storage

We describe SAFIUS, a secure accountable file system that resides over an untrusted storage. SAFIUS provides strong security guarantees like confidentiality, integrity, prevention from rollback attacks, and accountability. SAFIUS also enables read/write sharing of data and provides the standard UNIX-like interface for applications. To achieve accountability with good performance, it uses asynchronous signatures; to reduce the space required for storing these signatures, a novel signature pruning mechanism is used. SAFIUS has been implemented on a GNU/Linux based system modifying OpenGFS. Preliminary performance studies show that SAFIUS has a tolerable overhead for providing secure storage: while it has an overhead of about 50% of OpenGFS in data intensive workloads, it is comparable (or better in some cases) to OpenGFS in metadata intensive workloads.
On synthesizing cross ambiguity functions

The cross ambiguity function (CAF) arises in many areas such as radar/sonar and communications when correlation processing is performed in the presence of a Doppler frequency shift. In this paper, the CAF synthesis problem is tackled: a pair of waveforms are jointly designed so that their CAF approximates a desired one. The so-generated waveforms have relatively low peak-to-average power ratios and in certain cases can be constant modulus. Numerical examples are provided to show the effectiveness of the proposed algorithm in synthesizing different types of CAF.
Making “ The Parthenon ” ( Invited Paper )

In this paper we overview the technology and production processes used to create “The Parthenon”, a short computer animation that visually reunites the Parthenon and its sculptural decorations, separated since the beginning of the 19th century. The film used combinations of time-of-flight laser scanning, structured light scanning, photometric stereo, inverse global illumination, photogrammetric modeling, imagebased rendering, BRDF measurement, and monte-carlo global illumination in order to create the twenty-some shots used in the film.
Multi-resolution Image Segmentation using Geometric Active Contours

Image segmentation is an important step in image processing, with many applications such as pattern recognition, object detection, and medical image analysis. It is a technique that separates objects of interests from the background in an image. Geometric active contour is a recent image segmentation method that overcomes previous problems with snakes. It is an attractive method for medical image segmentation as it is able to capture the object of interest in one continuous curve. The theory and implementation details of geometric active contours are discussed in this work. The robustness of the algorithm is tested through a series of tests, involving both synthetic images and medical images. Curve leaking past boundaries is a common problem in cases of non-ideal edges. Noise is also problematic for the advancement of the curve. Smoothing and parameters selection are discussed as ways to help solve these problems. This work also explores the incorporation of the multi-resolution method of Gaussian pyramids into the algorithm. Multi-resolution methods, used extensively in the areas of denoising and edge-selection, can help capture the spatial structure of an image. Results show that similar to the multi-resolution methods applied to parametric active contours, the multi-resolution can greatly increase the computation without sacrificing performance. In fact, results show that with successive smoothing and sub-sampling, performance often improves. Although smoothing and parameter adjustment help improve the performance of geometric active contours, the edge-based approach is still localized and the improvement is limited. Regionbased approaches are recommended for further work on active contours.
Critical Role for Arginine Methylation in Adenovirus-Infected Cells

ABSTRACT During the late stages of adenovirus infection, the 100K protein (100K) inhibits the translation of cellular messages in the cytoplasm and regulates hexon trimerization and assembly in the nucleus. However, it is not known how it switches between these two functions. Here we show that 100K is methylated on arginine residues at its C terminus during infection and that this region is necessary for binding PRMT1 methylase. Methylated 100K is exclusively nuclear. Mutation of the third RGG motif (amino acids 741 to 743) prevents localization to the nucleus during infection, suggesting that methylation of that sequence is important for 100K shuttling. Treatment of infected cells with methylation inhibitors inhibits expression of late structural proteins. These data suggest that arginine methylation of 100K is necessary for its localization to the nucleus and is a critical cellular function necessary for productive adenovirus infection.
A 18 /spl mu/A-standby-current 1.8 V 200 MHz microprocessor with self substrate-biased data-retention mode

A 1.8 V 200 MHz low-subthreshold-leakage-current microprocessor is fabricated in a 0.2 /spl mu/m CMOS technology. It uses a switched substrate-impedance scheme to bias substrates while maintaining 200 MHz operating speed. It also offers a battery backup capability in a self substrate-biased data retention mode, in which it consumes only 17.8 /spl mu/A operating off a 1.0 V supply.
Neamine Inhibits Xenografic Human Tumor Growth and Angiogenesis in Athymic Mice

Purpose: We have previously shown that the aminoglycoside antibiotic neomycin blocks the nuclear translocation of angiogenin and inhibits its angiogenic activity. However, neomycin has not been considered as a favorable drug candidate for clinical development because of its known nephrotoxicity and ototoxicity. The aim of this study is to determine whether neamine, a nontoxic derivative of neomycin, possesses antitumor activity. Experimental Design: The effect of neamine on the nuclear translocation of angiogenin was examined by means of immunofluorescence and Western blotting. The antitumor activity of neamine was determined with three different animal models. Results: Neamine effectively blocked the nuclear translocation of angiogenin in endothelial cells and inhibited angiogenin-induced cell proliferation. It inhibited the establishment of human tumor xenografts in athymic mice in both ectopic and orthotopic tumor models. It also inhibited the progression of established human tumor transplants, whereas the structurally related antibiotic paromomycin had no effect. Immunohistochemical staining showed that both angiogenesis and cancer cell proliferation are inhibited by neamine. Conclusion: These results suggest that the nontoxic aminoglycoside antibiotic neamine is an effective inhibitor of nuclear translocation of angiogenin and may serve as an inhibitor for angiogenin-induced angiogenesis and cancer progression.
Dual-Mode Low-Complexity Codebook Searching Algorithm and VLSI Architecture for LTE/LTE-Advanced Systems

Codebook is a useful precoding technique for bandwidth limited systems because only few bits are required to feedback channel information. Many researchers propose several codebook selection criteria for linear receivers. However, these selection criteria are very computationally intensive, and most of them are not feasible for aperiodic feedback reporting in both LTE and LTE-Advanced (LTE-A) systems. Under the limited processing hardware and feedback delay constraints, low-complexity receivers with efficient codebook selection scheme are desirable. In this work, a low-complexity codebook searching engine is proposed to support both LTE and LTE-A operations. Also, it can be operated for both aperiodic and periodic feedback reporting. The properties and mutual correlations of the LTE and LTE-A codebooks are firstly analyzed. Then, a low-complexity grouping FFT-based codebook searching algorithm is proposed, which can be shared by LTE and LTE-A systems. Since the proposed algorithm is an algorithmic transformation, there is no performance loss. The proposed schemes have significant effect of reducing the number of multiplications by 56% compared with referenced works. Finally, a dual-mode low-complexity codebook searching engine with TSMC 90 nm is implemented. The IP size is 2.2 mm2 and the equivalent gate count is 547.6 K. The operating frequency is 125 MHz.
Binding of Y-P30 to Syndecan 2/3 Regulates the Nuclear Localization of CASK

The survival promoting peptide Y-P30 has documented neuroprotective effects as well as cell survival and neurite outgrowth promoting activity in vitro and in vivo. Previous work has shown that multimerization of the peptide with pleiotrophin (PTN) and subsequent binding to syndecan (SDC) -2 and -3 is involved in its neuritogenic effects. In this study we show that Y-P30 application regulates the nuclear localization of the SDC binding partner Calcium/calmodulin-dependent serine kinase (CASK) in neuronal primary cultures during development. In early development at day in vitro (DIV) 8 when mainly SDC-3 is expressed supplementation of the culture medium with Y-P30 reduces nuclear CASK levels whereas it has the opposite effect at DIV 18 when SDC-2 is the dominant isoform. In the nucleus CASK regulates gene expression via its association with the T-box transcription factor T-brain-1 (Tbr-1) and we indeed found that gene expression of downstream targets of this complex, like the GluN2B NMDA-receptor, exhibits a corresponding down- or up-regulation at the mRNA level. The differential effect of Y-P30 on the nuclear localization of CASK correlates with its ability to induce shedding of the ectodomain of SDC-2 but not -3. shRNA knockdown of SDC-2 at DIV 18 and SDC-3 at DIV 8 completely abolished the effect of Y-P30 supplementation on nuclear CASK levels. During early development a protein knockdown of SDC-3 also attenuated the effect of Y-P30 on axon outgrowth. Taken together these data suggest that Y-P30 can control the nuclear localization of CASK in a SDC-dependent manner.
Experimental and theoretical studies of agglomeration effects in multi-walled carbon nanotube-polycarbonate melts

In this study we report on morphological and rheological characterization of multi-walled carbon nanotube (MWNT)-polycarbonate composites produced by injection molding. The main focus is to carry out nonlinear viscoelastic experiments that allow following the structural rearrangements of carbon nanotubes in the polycarbonate melt. Small angle X-ray scattering reveals only a slight orientation of MWNTs in the as-received samples, i.e. after application of extremely high shear rates. Thus, the main structural effect observed during the stress growth experiment is the breakage of MWNT agglomerates. To study this effect in detail a flocculation experiment, in which the sample undergoes oscillatory deforma- tion first at a small strain amplitude in the linear regime succeeded by higher amplitudes in the nonlinear regime, has been carried out. The agglomeration process manifests itself in an increase of the storage and loss moduli in the linear regime, whereas the deagglomeration process does vice versa. The corresponding effects can be described in the frame of a super- position approach that takes into account the stress contribution of the polycarbonate matrix, the hydrodynamic reinforce- ment due to embedded nanotubes and the viscoelastic stress due to the presence of a MWNT-network.
Robust adaptive speed control of disturbed brushless direct current motor

We proposed two adaptive control methods for speed control of brushless direct current(BLDC) motor disturbed by two kinds of disturbances in this paper. The dynamic model of BLDC motor possessing either parametric uncertainties disturbed by unknown with known bound external disturbances or parametric uncertainties disturbed by unknown with known structure model external disturbances is considered, respectively. With the prior knowledge of the parametric uncertainties and the bounded functions of external disturbances of BLDC motor, a robust adaptive control method based on backstepping is designed firstly; For the BLDC motor model with parametric uncertainties disturbed by external disturbances with known structure model, an adaptive control method combined with disturbance observer is proposed. The proposed two methods preserve the advantages of adaptive control and robust control and guarantee transient performance with prescribed precision of robust control for the systems with both parametric uncertainties and unknown disturbances. The resulting controllers are more flexible than either adaptive control or robust control, and the rotor speed of BLDC motor can track its desired value with satisfying performances. Simulation results verify the effectiveness of the proposed methods.