Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of remaining axial walls on failure of root filled teeth restored with a single crown and adhesively bonded fibre post: a systematic review and meta-analysis

Objectives: To synthesise evidence on structural failures and prevalence of post-treatment endodontic disease (PTD) in anterior and posterior root filled teeth with a single crown and adhesively bonded fibre post with regards to the number of axial walls. Data: An electronic search was performed, no language constraints or restriction on the year of publication were applied. Sources: PubMed, Medline, Cochrane and Scopus on 13 th of July 2021. Study selection: Clinical studies that reported the remaining number of axial walls for permanent anterior and posterior root filled teeth (RFT) restored with single crowns and adhesively bonded fibre posts with a minimum of 1 year follow-up were included. Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines [1] were used. The number of axial walls and the success/failures were analysed as follows: fibre post and/or core decementation, post and/or core fracture, post treatment endodontic disease, and root fracture. Conclusions: A total of 811 studies were identified with 5 meeting the inclusion criteria. The two randomized controlled trials included had ‘some concerns’ as determined by the Cochrane risk-of-bias 2 tool while the Newcastle-Ottawa scale found low risk of bias for the remaining three studies. The random effects model for subgroup meta-analysis revealed failures for posterior RFT increased with decreasing numbers of remaining walls. Failures for 0 remaining walls were 23% (95% CI = 10% - 36%) and for one remaining wall 15% (CI: 3% -26%), irrespective of follow-up times. Fibre post debonding and PTD increased with decreasing numbers of walls. Relative & catastrophic failure of posterior teeth restored with a fibre post and single crown after root canal treatment increased with decreasing numbers of remaining axial walls. Clinical Significance: This synthesis is unique as it minimizes the presence of confounding factors by reviewing evidence of failures and post-treatment endodontic disease associated with teeth restored with single crowns. Therefore, it provides valuable predictive evidence of potential coronal restoration catastrophes and post-treatment endodontic disease associated with root filled teeth
A Lower Liassic offshore bar environment, contribution to the sedimentology of the Luxemburg Sandstone

Dans le quart NE du Bassin parisien, les sediments arenaces des Gres du Luxembourg sont inseres dans le facies lorrain du Lias inferieur. Les faunes en place ou remaniees indiquent un milieu de depot subtidal. Le transport des sediments a travers le detroit marin du Sillon eifelien vers le Bassin de Paris s'est effectue par des courants tidaux predominant dans une direction et qui masquent largement les effets des courants de retour. Dans l'ouest et le sud du Grand-Duche ainsi que dans le Luxembourg belge on constate egalement les effets produits par des courants induits par des tempetes. L'affleurement de Reckange/Mersch montre les caracteristiques lithologiques et sedimentaires typiques des Gres du Luxembourg. On y distingue six lithotypes principaux. Les teneurs en carbonate peuvent atteindre 80 % et possedent generalement une origine bioclastique. Bien que des processus diagenetiques soient evidents, ils n'expliquent pas a eux seuls les variations verticales des teneurs en carbonate. Les structures sedimentaires comportent des stratifications obliques a pendage oppose, des surfaces de reactivation sedimentaire, des interlits couples d'argile ainsi que des flaques argileuses. Ces structures et les populations granulometriques plaident pour un milieu marin peu profond ou les remaniements ont ete frequents. Dans ce milieu de "offshore sand waves" s'inscrivent six sub-environnements qui connaissent dans l'aire de repartition des Gres du Luxembourg une distribution caracteristique.
DNS and LES of the Compressible Flow Over a Delta Wing With the Symmetry-Preserving Discretization

A fourth-order accurate symmetry-preserving discretization for compressible ﬂow is used to perform simulations of the turbulent ﬂow over a delta wing. A symmetry-preserving discretization eliminates the non-linear convective instability by preserving conservation of kinetic energy at the discrete level. This en-hances the stability of a simulation method, so that little artiﬁcial dissipation is needed for numerical stability. It is shown that simulations of the ﬂow over a sharp-edge delta wing at Re = 50,000 with the symmetry-preserving discretization are stable without artiﬁcial dissipation in a region of interest around the delta wing. To assess the accuracy of the simulation method, results obtained on a ﬁne computational grid are compared with results obtained on a coarser grid. Also results obtained with large-eddy simulation models and with sixth-order artiﬁcial dissipation are presented.
Language Ego as An Affective Factor Influencing Second Language Acquisition in the Learning Process: A Literature Review

: Real-life observation has shown that second language (L2) learners differ in their L2 learning in which this individual difference is closely related to the factors influencing second language acquisition. Many researchers have been interested in finding those factors, yet there is still a little study examining the impact of language ego as the affective factor. Thus, this paper aims to elaborate on how the language ego influences second language acquisition. By having a thorough understanding of language ego in L2 learning, it is expected that it can give some enlightenment to a better L2 learning. To provide an adequate explanation of language ego, this research used a literature review method. This method is used to aggregate empirical findings related to the research question which is the language ego as one of the affective factors influencing second language acquisition. Some previous studies that discuss the similar topic were collected
Synergistic association of FOXP3+ tumor infiltrating lymphocytes with CCL20 expressions with poor prognosis of primary breast cancer

Abstract Studies have shown that forkhead/winged helix transcription factor P3 (FOXP3)+ tumor infiltrating lymphocytes (TILs) are intimately associated with invasion and survival of many invasive tumors. The inflammatory chemokine ligand 20 (CCL20) and its receptor CCR6 were found to be associated with tumor prognosis in some studies. Although increases in FOXP3+ TILs infiltration and CCL20 expression have been revealed in several malignancies, their correlation in human breast tumors is as yet unclear. Surgically resected samples from 156 patients with invasive breast cancer (BC) were assessed for the expression of FOXP3 and CCL20 by immunohistochemistry. Correlation between their expressions and the association with clinicopathological characteristics and patient's prognosis were studied. Forty pairs of fresh BC and their nontumor adjacent tissues (NATs) in BC were carried out by real-time quantitative PCR (qRT-PCR) to evaluate the correlation between FOXP3 and CCL20 mRNA expression. CCL20 and FOXP3+ TILs mRNA expression in tumor tissue demonstrated a high correlation (rs = 0.359, P < .001) in this cohort of breast cancer patients. Both elevated CCL20 expression and FOXP3+ TILs infiltration were significantly correlated with high histological grade, positive human epidermal growth factor receptor-2 (HER2), high Ki67 index, and axillary lymph node metastases. Tumors with concomitant high expressions of both markers had the worst prognosis. Multivariate analysis showed that these 2 markers were independent predictors of overall survival. The patients with axillary lymph node metastases with the concomitant CCL20 high expression and increased FOXP3+ TILs infiltration had the worst overall survival (OS) (P < .001), In lymph node-negative breast cancer patients, the status of CCL20 and FOXP3 was not related to OS (P = .22). The results suggest that CCL20 and FOXP3+ TILs may have synergistic effects, and their upregulated expressions may lead to immune evasion in breast cancer. Combinatorial immunotherapeutic approaches aiming at blocking CCL20 and depleting FOXP3 might improve therapeutic efficacy in breast cancer patients.
Characterization of well-posedness of piecewise-linear systems

One of the basic issues in the study of hybrid systems is the well-posedness (existence and uniqueness of solutions) problem of discontinuous dynamical systems. This paper addresses this problem for a class of piecewise-linear discontinuous systems under the definition of solutions of Carath\'eodory. The concepts of jump solutions or a sliding mode are not considered here. In this sense, the problem to be discussed is one of the most basic problems in the study of well-posedness for discontinuous dynamical systems. First, we derive necessary and sufficient conditions for bimodal systems to be well-posed, in terms of an analysis based on lexicographic inequalities and the smooth continuation property of solutions. Next, its extensions to the multi-modal case are discussed. As an application to switching control, in the case that two state feedback gains are switched according to a criterion depending on the state, we give a characterization of all admissible state feedback gains for which the closed loop system remains well-posed.
Determinasi Pajak, Mekanisme Bonus, dan Tunneling Incentive terhadap Keputusan Transfer Pricing pada Emiten BEI

This study aims to determine the effect of taxes, bonus mechanism, and tunneling incentive to transfer pricing decisions. Dependent Variables used in this research is transfer pricing and Independent Variables used in this study is the tax bonus mechanism, and tunneling incentive.The population in this study are all companies listed in Indonesia Stock Exchange except for those engaged in the field of finance. The sample selection using purposive sampling method with a final sample of 140 observation period of 2012-2015. The data used is taken from the secondary financial statements of the company. Data analysis techniques used in this study is the technique of logistic regression analysis. With the help of SPSS program application. The results showed that the variables and tunneling tax incentive does not affect tehadap transfer pricing decisions, whereas a variable bonus mechanism of influence on transfer pricing decisions. The coefficient of determination in this study amounted to 13.4%. Future studies are expected to add another independent variable such as an arm's length.
Computer Animation: Algorithms and Techniques

Driven by demand from the entertainment industry for better and more realistic animation, technology continues to evolve and improve. The algorithms and techniques behind this technology are the foundation of this comprehensive book, which is written to teach? you the fundamentals of animation programming. In this third edition, the most current techniques are covered along with the theory and high-level computation that have earned the book a reputation as the best technically-oriented animation resource. Key topics such as fluids, hair, and crowd animation have been expanded, and extensive new coverage of clothes and cloth has been added. New material on simulation provides a more diverse look at this important area and more example animations and chapter projects and exercises are included. Additionally, spline coverage has been expanded and new video compression and formats (e.g., iTunes) are covered. * Includes companion site with contemporary animation examples drawn from research and entertainment, sample animations, and example code * Describes the key mathematical and algorithmic foundations of animation that provide you with a deep understanding and control of technique * Expanded and new coverage of key topics including: fluids and clouds, cloth and clothes, hair, and crowd animation *? Explains the algorithms used for path following, hierarchical kinematic modelling, rigid body dynamics, flocking behaviour, particle systems, collision detection, and more Table of Contents Chapter 1: Introduction Chapter 2: Technical Background Chapter 3: Interpolating Values Chapter 4: Interpolation-Based Animation Chapter 5: Kinematic Linkages Chapter 6: Motion Capture Chapter 7: Physically Based Animation Chapter 8: Fluids: Liquids & Gases Chapter 9: Modeling and Animating Human Figures Chapter 10: Facial Animation Chapter 11: Behavioral Animation Chapter 12: Special Models for Animation Appendix A: Rendering Issues Appendix B: Background Information and Techniques Index
Combined action observation and motor 1 imagery facilitates visuomotor adaptation in 2 children with Developmental Coordination 3 Disorder

51 The internal modelling deficit (IMD) hypothesis suggests that motor control issues 52 associated with Developmental Coordination Disorder (DCD) are the result of impaired 53 predictive motor control. In this study, we examined the benefits of a combined action 54 observation and motor imagery (AO+MI) intervention designed to alleviate deficits in 55 internal modelling and improve eye-hand coordination during a visuomotor rotation task. 56 Twenty children with DCD were randomly assigned to either an AO+MI group (who watched 57 a video of a performer completing the task whilst simultaneously imagining the kinaesthetic 58 sensations associated with action execution) or a control group (who watched unrelated 59 videos involving no motor content). Each group then attempted to learn a 90 o visuomotor 60 rotation while measurements of completion time, eye-movement behaviour and movement 61 kinematics were recorded. As predicted, after training, the AO+MI group exhibited quicker 62 completion times, more target-focused eye-movement behaviour and smoother movement 63 kinematics compared to the control group. No significant after-effects were present. These 64 results offer further support for the IMD hypothesis and suggest that AO+MI interventions 65 may help to alleviate such deficits and improve motor performance in children with DCD. 66 67
Machine learning & artificial intelligence in the quantum domain: a review of recent progress

Quantum information technologies, on the one hand, and intelligent learning systems, on the other, are both emergent technologies that are likely to have a transformative impact on our society in the future. The respective underlying fields of basic research—quantum information versus machine learning (ML) and artificial intelligence (AI)—have their own specific questions and challenges, which have hitherto been investigated largely independently. However, in a growing body of recent work, researchers have been probing the question of the extent to which these fields can indeed learn and benefit from each other. Quantum ML explores the interaction between quantum computing and ML, investigating how results and techniques from one field can be used to solve the problems of the other. Recently we have witnessed significant breakthroughs in both directions of influence. For instance, quantum computing is finding a vital application in providing speed-ups for ML problems, critical in our ‘big data’ world. Conversely, ML already permeates many cutting-edge technologies and may become instrumental in advanced quantum technologies. Aside from quantum speed-up in data analysis, or classical ML optimization used in quantum experiments, quantum enhancements have also been (theoretically) demonstrated for interactive learning tasks, highlighting the potential of quantum-enhanced learning agents. Finally, works exploring the use of AI for the very design of quantum experiments and for performing parts of genuine research autonomously, have reported their first successes. Beyond the topics of mutual enhancement—exploring what ML/AI can do for quantum physics and vice versa—researchers have also broached the fundamental issue of quantum generalizations of learning and AI concepts. This deals with questions of the very meaning of learning and intelligence in a world that is fully described by quantum mechanics. In this review, we describe the main ideas, recent developments and progress in a broad spectrum of research investigating ML and AI in the quantum domain.
Study on the Coupling Interaction of Green Technology Innovation, New Energy Industry Agglomeration and Carbon Emission Efficiency

This study examines the relationship between green technology innovation, new energy industry agglomeration and carbon emission efficiency from 2008 to 2019 in 30 provinces in China (apart from Tibet, Hong Kong, Macao, and Taiwan). According to the study, the mean value of the three couples’ average coupling coordination degree is between 0.03 and 0.49, which means that they are still in the maladjustment stage and on the verge of forced coordination. And the dynamic PVAR model is further established to study and conclude that green technology innovation is fostered by carbon emission efficiency, which is also boosted by new energy industry agglomeration. However, there is no correlation between green technology innovation and new energy industry agglomeration, and the three systems have not formed a good circular driving effect temporarily.
PRICE VOLATILITY AND FARM INCOME STABILISATION Modelling Outcomes and Assessing Market and Policy Based Responses Dublin , February 23-24 , 2012 The evolution of land values in Italy . Does the influence of agricultural prices really matter ?

Interest towards farmland market has been increasing in recent years. In developing countries there is rising concern about land being purchased by foreign investors, while in the developed world the debate is centred on whether agricultural factors are still the main determinants of land values or not. This work assesses the determinants of land values in Italy using panel data techniques during the time span 1992-2010. In Italy farmland values have historically been influenced more by natural characteristics of the land than agricultural prices. However, lately non-agricultural factors have been increasing their importance. We find that agricultural prices only slightly affect average land values in Italy. Main determinants of land prices are the yield from real estate investment, GDP per capita, house prices, and population density. For arable land also environmental regulations for livestock farms positively affects values.
Mature natural killer cells reset their responsiveness when exposed to an altered MHC environment

An important role of NK cells is to eliminate cells that extinguish or diminish expression of self-MHC class I molecules, which commonly occurs as a result of viral infection or cellular transformation (Herberman et al., 1975; Kiessling et al., 1975; Biron et al., 1999; Diefenbach and Raulet, 2002). This capacity arises because NK cells express stimulatory and inhibitory receptors that engage ligands on normal cells. The majority of inhibitory receptors belong to the KIR (in human), Ly49 (in mouse), and CD94/NKG2A (both in human and mouse) families and are specific for MHC I molecules (Raulet et al., 1997; Moretta et al., 2001; Lanier, 2005). When an NK cell encounters a normal cell, engagement of the inhibitory receptors conveys signals that counteract stimulatory signaling. Lysis occurs when inhibition is lost because the target cell lacks one or more self-MHC molecules or when target cells express high levels of stimulatory ligands that override inhibition (Raulet and Vance, 2006). NK cells vary in the number and specificity of MHC-specific inhibitory receptors that they express (Raulet et al., 1997). Recent studies demonstrate that NK cells vary in basal responsiveness to stimulatory receptor engagement depending on the number of expressed inhibitory receptors specific for self-MHC molecules (Yu et al., 2007; Brodin et al., 2009; Joncker et al., 2009). Cells with several self-MHC– specific receptors exhibit the greatest basal responsiveness and thus mediate the greatest activity against target cells that lose MHC. Cells with no self-MHC–specific receptors are the CORRESPONDENCE David H. Raulet: raulet@berkeley.edu
Leading indicators of balance-of-payments crises : a partial review

This paper reviews the theory of balance-of-payments crises, and its implications for identifying potential leading indicators of crises. It discusses and evaluates three different empirical approaches to balance-of-payments crises: the signalling, discrete-choice, and structural approaches. Despite claims of success in predicting currency crises, we note some serious theoretical and empirical qualifications which throw these claims into question. Nevertheless, we conclude that a range of indicators supported by theory may still be useful for policy-makers interested in preventing financial instability. JEL classification: F31, F47.
A Preliminary Performance Study of Architectural Support for Multithreading

This paper discusses the preliminary performance study of hybrid multithreaded execution model that combines software-controlled multithreaded system with hardware support for efficient context switching and threads scheduling. The hardware support for multithreading is augmented with a software thread scheduling technique called set scheduling, and their benefit to the overall performance is discussed. Set scheduling schedules multiple threads onto the hardware scheduler to minimize the software scheduling and context switching costs. An analytical model of the proposed multithreaded model is discussed and simulation results of processor utilization based on the proposed model are presented. Through simulation, we find that the hybrid multithreaded execution model results in high processor utilization than traditional softwarecontrolled multithreading.
Universal bounds for asset prices in heterogeneous economies

We establish universal bounds for asset prices in heterogeneous complete market economies with scale invariant preferences. Namely, for each agent in the economy we consider an artificial homogeneous economy populated solely by this agent, and calculate the “homogeneous” price of an asset in each of these economies. Dumas (Rev. Financ. Stud. 2, 157–188, [1989]) conjectured that the risk free rate in a heterogeneous economy must lie in the interval determined by the minimal and maximal of the “homogeneous” risk free rates. We show that the answer depends on the risk aversions of the agents in the economy: the upper bound holds when all risk aversions are smaller than one, and the lower bound holds when all risk aversions are larger than one. The bounds almost never hold simultaneously. Furthermore, we prove these bounds for arbitrary assets.
Lyapunov Conditions for Input-to-State Stability of Hybrid Systems With Memory

This paper studies input-to-state stability for hybrid systems with memory, which models hybrid dynamics affected by time delays. Using both Lyapunov–Razumikhin functions and Lyapunov–Krasovskii functionals, Lyapunov-based sufficient conditions are established for input-to-state stability. In addition, further extensions and relaxations are proposed for special cases, such as the stable flow/jump cases and the cases that Lyapunov functions do not decrease strictly during flow/jumps. Finally, two examples are used to illustrate the developed results
Modelling and Prediction of the MXNUSD Exchange Rate Using Interval Singleton Type-2 Fuzzy Logic Systems [Application Notes]

An IT2 SFLS using hybrid RLS-BP training method was tested and compared for forecasting the daily exchange rate between Mexican Peso and U.S. Dollar (MXNUSD). The results showed that the IT2 SFLS forecaster using RLS-BP hybrid learning provided the best performance, and the base line T1 SFLS provided the worst performance. We conclude, therefore, that it is possible to directly use the daily data of exchange rate to train an IT2 SFLS, in order to predict MXNUSD exchange rate one day in advance. It was observed that IT2 SFLS forecasters efficiently managed the uncertainties presented in the raw historical data