Miracle-dz/UniFAR-FTUs huggingface dataset:
01 05 01 8 v 1 6 M ay 2 00 1 Robust control in the quantum domain

Recent progress in quantum physics has made it possible to perform experiments in which individual quantum systems are monitored and manipulated in real time. The advent of such new technical capabilities provides strong motivation for the development of theoretical and experimental methodologies for quantum feedback control. The availability of such methods would enable radically new approaches to experimental physics in the quantum realm. Likewise, the investigation of quantum feedback control will introduce crucial new considerations to control theory, such as the uniquely quantum phenomena of entanglement and measurement back-action. The extension of established analysis techniques from control theory into the quantum domain may also provide new insight into the dynamics of complex quantum systems. We anticipate that the successful formulation of an input-output approach to the analysis and reduction of large quantum systems could have very general applications in non-equilibrium quantum statistical mechanics and in the nascent field of quantum information theory.
Object orientation recognition based on SIFT and SVM by using stereo camera

The goal of this research is to recognize an object and its orientation in space by using stereo camera. The principle of object orientation recognition in this paper was based on the Scale Invariant Feature Transform (SIFT) and Support Vector Machine (SVM). SIFT has been successfully implemented on object recognition but it had a problem recognizing the object orientation. For many autonomous robotics applications, such as using a vision-guided industrial robot to grab a product, not only correct object recognition will be needed in this process but also object orientation recognition is required. In this paper we used SVM to recognize object orientation. SVM has been known as a promising method for classification accuracy and its generalization ability. The stereo camera system adopted in this research provided more useful information compared to single camera one. The object orientation recognition technique was implemented on an industrial robot in a real application. The proposed camera system and recognition algorithms were used to recognize a specific object and its orientation and then guide the industrial robot to perform some alignment operations on the object.
Automated Essay Scoring Using the KNN Algorithm

The K-Nearest Neighbor (KNN) algorithm for text categorization is applied to CET4 essays. In this paper, each essay is represented by the vector space model (VSM). After removing the stop words, we chose the words, phrases and arguments as features of the essays, and the value of each vector is expressed by the term frequency and inversed document frequency (TF-IDF) weight. The TF and information fain (IG) methods are used to select features by predetermined thresholds. We calculated the similarity of essays with cosine in the KNN algorithm. Experiments on CET4 essays in the Chinese Learner English Corpus (CLEC) show accuracy above 76% is achieved.
Detecting Identity Spoofs in 802 . 11 e Wireless Networks

Wireless networks are vulnerable to identity spoofing attacks, where an attacker can forge the MAC address of hi s wireless device to assume the identity of another victim dev ice on the network. Identity spoofing allows an attacker to avail network services that are normally restricted to legitimate users. Prior techniques to detect such attacks rely on characteris tics such as progressions of MAC sequence numbers. However, thes e techniques can wrongly classify benign flows as malicious wi th newer 802.11e wireless devices that allow multiple progres sions of MAC sequence numbers from the same device. Several other techniques that rely on physical properties of transmitting devices are ineffective when the attacker and the victim are mobile. In this paper, we propose an architecture to robustly detect identity spoofing attacks under varying operating conditions. Our architecture employs a series of increasingly powerful detctors to identify or eliminate the possibility of an attack, culminating in a powerful, RSSI-based per-packet localizer that reliablydetects identity spoofing attacks. We implemented this architectur e and used it to detect a variety of identity spoofing attacks. Our experiments show that it can effectively detect identity sp oofs with a low false positive rate of0.5%.
Tutors seen through the eyes of mentors assumptions for participation in third space in teacher education

ABSTRACT The aim of this Norwegian study is to get a deeper understanding of the assumptions for building third spaces in teacher education. Learning in different contexts may open for development of new knowledge in the third space through intersubjectivity based on confidence, respectful disagreement and a common aim. This is the backdrop for the current study where a group of mentors with and without mentor education are interviewed focusing on tutors’ competences and responsibilities. Findings show that mentors have an unclear understanding of who the tutors are. Experiences from teaching are essential for mentors’ understanding of tutors as respectful collaborators. Educated mentors value theoretical knowledge and research higher than non-educated. The conclusion is that tutors and mentors should have knowledge about and respect for each-others’ competence and responsibilities and that mentor education is a promising assumption for building third spaces and developing a pedagogy for teacher education.
WNT Signaling Pathway and Stem Cell Signaling Network

WNT signals are transduced to the canonical pathway for cell fate determination, and to the noncanonical pathway for control of cell movement and tissue polarity. Canonical WNT signals are transduced through Frizzled family receptors and LRP5/LRP6 coreceptor to the β-catenin signaling cascade. Microtubule affinity–regulating kinase (PAR-1) family kinases, casein kinase Iε (CKIε), and FRAT are positive regulators of the canonical WNT pathway, whereas APC, AXIN1, AXIN2, CKIα, NKD1, NKD2, βTRCP1, βTRCP2, ANKRD6, Nemo-like kinase (NLK), and peroxisome proliferator–activated receptor γ (PPARγ) are negative regulators. Nuclear complex, consisting of T-cell factor/lymphoid enhancer factor, β-catenin, BCL9/BCL9L, and PYGO, activates transcription of canonical WNT target genes such as FGF20, DKK1, WISP1, MYC, CCND1, and Glucagon (GCG). Noncanonical WNT signals are transduced through Frizzled family receptors and ROR2/RYK coreceptors to the Dishevelled-dependent (Rho family GTPases and c-jun NH2-terminal kinase) or the Ca2+-dependent (NLK and nuclear factor of activated T cells) signaling cascades. WNT signals are context-dependently transduced to both pathways based on the expression profile of WNT, SFRP, WIF, DKK, Frizzled receptors, coreceptors, and the activity of intracellular WNT signaling regulators. Epigenetic silencing and loss-of-function mutation of negative regulators of the canonical WNT pathway occur in a variety of human cancer. WNT, fibroblast growth factor (FGF), Notch, Hedgehog, and transforming growth factor β/bone morphogenetic protein signaling network are implicated in the maintenance of tissue homeostasis by regulating self-renewal of normal stem cells as well as proliferation or differentiation of progenitor (transit-amplifying) cells. Breakage of the stem cell signaling network leads to carcinogenesis. Nonsteroidal anti-inflammatory drugs and PPARγ agonists with the potential to inhibit the canonical WNT signaling pathway are candidate agents for chemoprevention. ZTM000990 and PKF118-310 are lead compounds targeted to the canonical WNT signaling cascade. Anti-WNT1 and anti-WNT2 monoclonal antibodies show in vitro effects in cancer treatment. After the optimization, derivatives of small-molecule compound and human monoclonal antibody targeted to the WNT signaling pathway could be used in cancer medicine.
Adaptive but non-optimal visual search behavior with highlighted displays q Action editor : Andrea Stocco

Previous research [Fisher, D. L. , & Tan, K. C. (1989). Visual displays: The highlighting paradox. Human Factors, 31(1), 17–30] suggested that making certain items visually salient, or highlighting, can speed performance in visual search tasks. But interface designers cannot always anticipate users’ intended targets, and highlighting non-target items can lead to performance decrements. An experiment presented suggests that people attend to highlighting less than what an algebraic visual search model of highlighted displays [Fisher, D. L. , Coury, B. G. , Tengs, T. O. , & Duffy, S. A. (1989). Minimizing the time to search visual displays: The role of highlighting. Human Factors, 31(2), 167–182] predicts. Users adjust their visual search strategies by probability-matching to their visual environment. An ACT-R [Anderson, J. R. , Bothell, D. , Byrne, M. D. , Douglass, S. , Lebiere, C. , & Quin, Y. (2004). An integrated theory of the mind. Psychological Review, 111, 1036–1060] model reproduced the major effects of the experiment and suggests that learning in this task occurs at very small cognitive and time scales. 2007 Elsevier B.V. All rights reserved.
Long-term effectiveness of first-line non-nucleoside reverse transcriptase inhibitor (NNRTI)-based antiretroviral therapy in Ghana.

OBJECTIVES Information on the long-term effectiveness and tolerability of efavirenz- or nevirapine-based antiretroviral therapy (ART) in Africa is lacking. The primary objective of this retrospective observational study was to compare the long-term clinical and immunological outcomes of efavirenz- versus nevirapine-based first-line ART in a large government clinic in Ghana. PATIENTS AND METHODS The main outcomes were AIDS, death, ART-related toxicity, discontinuation of ART and a composite endpoint of death, AIDS or ART discontinuation. These time-to-event outcomes were compared using a Cox proportional hazards regression model. CD4 counts on ART were compared using a mixed-effects model. RESULTS A total of 3990 patients started non-nucleoside reverse transcriptase inhibitor (NNRTI)-based ART between 2004 and 2010, of which 2369 (59%) were on efavirenz. No significant differences were apparent between each NNRTI for subsequent risk of AIDS, death or the composite of treatment failure; however, stavudine use was independently associated with an increased risk of death [adjusted hazard ratio (HR) 1.60 (95% CI: 1.21-2.11)]. There was an increased risk of early toxicity with nevirapine leading to discontinuation [adjusted HR 1.53 (95% CI: 1.23-1.97)], mostly due to excess skin rashes in the first 2 months of treatment; however, overall discontinuation rates were low. CONCLUSIONS There was no difference in the long-term effectiveness of efavirenz- and nevirapine-based ART in this population; however, patients initiating nevirapine were more likely to develop early toxicity and discontinue this drug. The excess mortality observed in patients taking stavudine is of concern and should prompt increased efforts to replace it with alternative antiretroviral drugs in developing countries.
- based Named Entity Disambiguation to Arbitrary Web Text

This paper investigates the “named-entity disambiguation” task on the Web—identifying the referent of a string, found on an arbitrary Web page. The GROUNDER system, introduced in this paper, addresses two challenges not considered by previous work: how to utilize a priori information (e.g., Bill Clinton is more prominent on the Web than Clinton County) to improve disambiguation, and how to compose this prior information with contextual evidence. GROUNDER addresses both challenges by leveraging the user-contributed knowledge in Wikipedia and providing a novel formulation of the task. On a sample of strings drawn from the Web, GROUNDER achieves precision of 1.0 at recall 0.34, and precision 0.90 at recall 0.60.
Crystal structure of the NurA–dAMP–Mn2+ complex

Generation of the 3′ overhang is a critical event during homologous recombination (HR) repair of DNA double strand breaks. A 5′–3′ nuclease, NurA, plays an important role in generating 3′ single-stranded DNA during archaeal HR, together with Mre11–Rad50 and HerA. We have determined the crystal structures of apo- and dAMP-Mn2+-bound NurA from Pyrococcus furiousus (Pf NurA) to provide the basis for its cleavage mechanism. Pf NurA forms a pyramid-shaped dimer containing a large central channel on one side, which becomes narrower towards the peak of the pyramid. The structure contains a PIWI domain with high similarity to argonaute, endoV nuclease and RNase H. The two active sites, each of which contains Mn2+ ion(s) and dAMP, are at the corners of the elliptical channel near the flat face of the dimer. The 3′ OH group of the ribose ring is directed toward the channel entrance, explaining the 5′–3′ nuclease activity of Pf NurA. We provide a DNA binding and cleavage model for Pf NurA.
Effect of Contact Friction between Seatbelt and Human Body Model on Simulation of Rib Fracture in Frontal Impact

Seatbelt contact friction coefficient may have some influence on chest injury prediction because it can affect the position of the seatbelt during the impact. The objective was to study the influence of the seatbelt contact friction coefficient on predicted rib fracture outcome in frontal impact. Four simulations of frontal impact sled tests in the same environment were conducted wherein the contact friction coefficient between the seatbelt and the chest model was varied. A noticeable effect was observed wherein increasing friction coefficient which tended to cause a slight decrease in the number of predicted fractures. Despite this, the magnitude of sensitivity was small, suggesting that in the absence of other information arbitrary values of friction coefficient within a reasonable intermediate range may be justified for this specific test condition.
Modeling a 3D City Model and Its Levels of Detail as a True 4D Model

The various levels of detail (LODs) of a 3D city model are often stored independently, without links between the representations of the same object, causing inconsistencies, as well as update and maintenance problems. One solution to this problem is to model the LOD as an extra geometric dimension perpendicular to the three spatial ones, resulting in a true 4D model in which a single 4D object (a polychoron) represents a 3D polyhedral object (e.g., a building) at all of its LODs and a multiple-LOD 3D city model is modeled as a 4D cell complex. While such an approach has been discussed before at a conceptual level, our objective in this paper is to describe how it can be realized by appropriately linking existing 3D models of the same object at different LODs. We first present our general methodology to construct such a 4D model, which consists of three steps: (1) finding corresponding 0D–3D cells; (2) creating 1D–4D cells connecting them; and (3) constructing the 4D model. Because of the complex relationships between the objects in different LODs, the creation of the connecting cells can become difficult. We therefore describe four different alternatives to do this, and we discuss the advantages and disadvantages of each in terms of their feasibility in practice and the properties that the resulting 4D model has. We show how the different linking schemes result in objects with different characteristics in several use cases. We also show how our linking method works in practice by implementing the linking of matching cells to construct a 4D model.
Calling, Career Preparation Behaviors, and Meaning in Life Among South Korean College Students

Abstract:We examined whether each subscale of the Calling and Vocational Questionnaire (i.e., transcendent summons, purposeful work, and prosocial orientation) relates to career preparation behavior (CPB) after controlling for demographic variables, current employment-seeking status, self-esteem, and work volition. We also looked into whether CPB mediates the relationship between calling and meaning in life (MIL) among 214 South Korean college students. Hierarchical multiple regression analyses revealed that the 3 subscales of calling in combination additionally explained 17% of the variance in the CPB, with the purposeful work subscale as the only significant variable. CPB was found to partially mediate the relationship between calling and MIL, indicating that students with a higher sense of calling are likely to experience a higher sense of MIL in part because they tend to engage in higher levels of CPB.
POSE SELECTION FOR THE KINEMATIC CALIBRATION OF A PROTOTYPED 4 DEGREES OF FREEDOM MANIPULATOR

This paper explores the pose selection for the kinematic calibration of the constraining linkage of a 4 degrees of freedom parallel manipulator. The aim is to select a set of poses out of a larger pool of possible poses which improve the calibration accuracy. Five different criteria have been suggested in the literature and are investigated in this article. The results show that the pose selection criteria did not significantly improve the calibration of this parallel manipulator. There was very little difference between applying the criteria and not applying it and some of the results using the criteria were worse than not using any criteria.
Geodesic Learning Algorithms Over Flag Manifolds

Recently manifold structures have attracted attentions in two folds in the machine learning literature. One is in the manifold learning problem, that is learning the intrinsic manifold structure in high dimensional datasets. Another is in the information geometric approach to learning – exploiting the geometry of the parameter space of learning machines such as neural networks for improving conventional learning algorithms [1]. In this presentation we discuss the use of manifolds for the latter aim, particularly, we investigate the flag manifold arising from one layer neural networks for solving subspace ICA problems. When the parameter space of neural networks forms a manifold, the learning equation is defined over that manifold and should be integrated taking the manifold structure into account. The Riemannian learning method [3], by introducing a Riemannian metric into the manifold, yields a discretization scheme for solving differential equations on the manifold: integration of the differential equation is performed along piecewise geodesics which approximate the original learning trajectory. This Riemannian method was successfully applied to the orthogonal group, i.e. the Lie group of orthogonal matrices, for the non-negative ICA problem [5]. In the context of optimization this Riemannian approach was also considered over the Stiefel and the Grassmann manifolds in [2]. The Grassmann manifold just considers the set of subspaces of a fixed dimension, while the flag manifold consists of the set of the direct sum of subspaces and includes the Grassmannian manifold as a special case. Therefore the flag manifold can deal with several subspaces simultaneously and is suitable for tackling subspace ICA problems. We extend the formulas obtained in [2] to the flag manifold. The effectiveness of the Riemannian learning method over the standard Euclidean algorithms is illustrated in independent subspace analysis (ISA) and complex ICA experiments. Also, the issue of local minima in ISA is discussed. We combine the Riemannian learning method over the flag manifold and an MCMC method to overcome the problem of local minima of the ISA cost function.
Iesem: Integrated Environment for Software Evolution Management

Software evolution has no common paradigm which practitioners can adhere to. On the contrary, there is a wide range of models, methods, techniques, and tools which are selected according to the specific task, the application domain, the professional experience, and the organizational culture. We argue that different approaches and technologies may be combined into a unique platform to satisfy the needs of software systems which evolve over long periods of time. This paper presents the Integrated Environment for Software Evolution Management (IESEM) which includes software repositories, reverse engineering tools, rationale capture tools, software measurement tools, and a user-friendly interface. It can manage heterogeneous systems characterized by various design methods and programming languages. IESEM is based on a central repository which stores software engineering artifacts, program code, design, and implementation decisions in the form of a traceability graph. The repository stores also software measures computed both from programs and external CASE repositories. Measures are used to control software degradation during its evolution and to support decisions based on quality factors. The key concepts of IESEM, its design, and implementation are presented. The use of IESEM during development and maintenance is discussed. A case study shows IESEM's effectiveness in performing maintenance tasks.
Process Management 1-2-3 – a maturity model and diagnostics tool

In this article, we provide an insight into Process Management that offers a simple hands-on method to improve Process Management. Organisations implementing ‘some modern’ management concept sometimes fail or do not achieve the expected results. From our own industrial experiences, we found that organisations implementing Process Management sometimes start off on a ‘too-advanced’ level without having fulfilled the necessary prerequisites. For that purpose, in this article, we present a Process Management maturity model developed in an environment of industrial and academic cooperation. In addition to the model, we present a diagnostics tool that has been developed together with several companies to be used by organisations to assess their current level of process maturity. By using this, it is the purpose that organisations could reduce their risk of starting off ‘too high’ and thus failing in their efforts.
Event-driven loop closure in multi-robot mapping

A large-scale mapping approach is combined with multiple robots events to achieve cooperative mapping. The mapping approach used is based on hierarchical SLAM -global level and local maps-, which is generalized for the multi-robot case. In particular, the consequences of multi-robot loop closing events (common landmarks detection and relative pose measurement between robots) are analyzed and managed at a global level. We present simulation results for each of these events using aerial and ground robots, and experimental results obtained with ground robots.
Power and performance aware reconfigurable cache for CMPs

This paper investigates the problem of partitioning a shared cache among threads executing in a Chip Multi-Processor (CMP). We propose Reconfigurable Cache for CMPs (ReCaC), a low-overhead run-time mechanism that dynamically partitions the cache based on the phase behavior of threads. Unlike the previously proposed performance aware partitioning approaches, ReCaC targets to use a minimum number of ways to trade-off between power and performance. ReCaC dynamically reverts back to a performance centric cache partitioning scheme if the power savings are not achievable. Our results show that in a 2-core architecture ReCaC saves on average 51.5% power in a L2 cache, which corresponds to 11.5% power savings of the processor chip and the memory. The overall processor energy efficiency is improved by up to 13.6%, achieving on average 8.5%. ReCaC proves to be scalable, saving on average 10.8% and 12.5% of the processor chip and memory power in 4-and 8-core architectures, respectively.
Least squares twin SVM decision tree for multi-class classification

In order to solve multi-class classification problem in real world, we improved TSVM in this paper. We combined LSTSVM with partial binary tree to improve classification efficiency. Binary tree hierarchy can solved the inseparable regional issues in OVO-SVM and OVA-SVM classification. Experimental results show that it improved the classification accuracy. It also has better speed-up ratio than the OVO-SVM, OVA-SVM. It also reduced the training time. The time advantage is more obvious, especially the data set is large.