Miracle-dz/UniFAR-FTUs huggingface dataset:
Tyrosine Phosphatase SHP-1 Is Involved in CD66-Mediated Phagocytosis of Opa52-ExpressingNeisseria gonorrhoeae

ABSTRACT Opa proteins of Neisseria gonorrhoeae bind to CD66 receptors on human phagocytes, thereby inducing efficient uptake of the bacteria in the absence of opsonins. The interaction of Opa proteins and CD66 receptors leads to activation of Src family tyrosine kinases, a process that is of critical importance for the efficient, CD66-mediated internalization. Here we show that during Opa-mediated stimulation of CD66 the activity of the host cell tyrosine phosphatase SHP-1 is strongly downregulated, concomitant with increases in the tyrosine phosphorylation of several cellular proteins. Since the SHP-1 tyrosine phosphorylation level itself is influenced by Opa-induced events, this phosphatase comprises an important regulatory checkpoint of the pathogen-triggered signaling cascade in human phagocytes.
The Development of System Identification Approaches for Complex Haptic Devices and Modelling Virtual Effects Using Fuzzy Logic

Haptic applications often employ devices with many degrees of freedom in order to allow the user to have natural movement during human-machine interaction. From the development point of view, the complexity in mechanical dynamics imposes a lot of challenges in modelling the behaviour of the device. Traditional system identification methods for nonlinear systems are often computationally expensive. Moreover, current research on using neural network approaches disconnect the physical device dynamics with the identification process. This thesis proposes a different approach to system identification of complex haptic devices when analytical models are formulated. It organizes the unknowns to be identified based on the governing dynamic equations of the device and reduces the cost of computation. All the experimental work is done with the Freedom 6S, a haptic device with input and feedback in positions and velocities for all 6 degrees of freedom . Once a symbolic model is developed, a subset of the overall dynamic equations describing selected joint(s) of the haptic robot can be obtained. The advantage of being able to describe the selected joint(s) is that when other non-selected joints are physically fixed or locked up, it mathematically simplifies the subset dynamic equation. Hence, a reduced set of unknowns (e.g. mass, centroid location, inertia, friction, etc) resulting from the simplified subset equation describes the dynamic of the selected joint(s) at a given mechanical orientation of the robot. By studying the subset equations describing the joints, a locking sequence of joints can be determined to minimize the number of unknowns to be determined at a time. All the unknowns of the system can be systematically determined by locking selected joint(s) of the device following this locking sequence. Two system identification methods are proposed: Method of Isolated Joint and Method of Coupling Joints. Simulation results confirm that the latter approach is able to successfully identify the system unknowns of Freedom 6S. Both open-loop experimental tests and close-loop verification comparison between the measured and simulated results are presented. Once the haptic device is modelled, fuzzy logic is used to address chattering phenomenon common to strong virtual effects. In this work, a virtual wall is used to demonstrate this approach. The fuzzy controller design is discussed and experimental comparison between the performance of using a proportional-derivative gain controller and the designed fuzzy controller is presented. The fuzzy controller is able
Identifying Correspondences Between Words: an Approach Based on a Bilingual Syntactic Analysis of French/English Parallel Corpora

We present a word alignment procedure based on a syntactic dependency analysis of French/English parallel corpora called "alignment by syntactic propagation". Both corpora are analysed with a deep and robust parser. Starting with an anchor pair consisting of two words which are potential translations of one another within aligned sentences, the alignment link is propagated to the syntactically connected words. The method was tested on two corpora and achieved a precision of 94.3 and 93.1% as well as a recall of 58 and 56%, respectively for each corpus.
Parameters modeling for a modified mixture of experts

This investigation was performed to see the regularity of parameters in the modified mixture of experts (MoE) to direct parameter selection in real applications. The experiment was performed on the mean of monthly precipitation in May from 1956a through 2004a in a Chinese region. We got stable parameter combinations through testing on various combinations of parameters in various value ranges, and made statistics on the parameters in the stable combinations. The results showed that all the three parameters follow certain laws and suggest their importance. The relationship between the fuzzy weighting exponent and the value ranges of the cluster number and the index of the effectiveness factor are linear. It is of guiding significance to parameter selection in MoE systems.
Mindfulness Research Update: 2008

Objective: To briefly review the effects of mindfulness on the mind, the brain, the body, and behavior. Methods: Selective review of MEDLINE, PsycINFO, and Google Scholar databases (2003—2008) using the terms ``mindfulness,'' ``meditation,'' ``mental health,'' ``physical health,'' ``quality of life,'' and ``stress reduction. '' A total of 52 exemplars of empirical and theoretical work were selected for review. Results: Both basic and clinical research indicate that cultivating a more mindful way of being is associated with less emotional distress, more positive states of mind, and better quality of life. In addition, mindfulness practice can influence the brain, the autonomic nervous system, stress hormones, the immune system, and health behaviors, including eating, sleeping, and substance use, in salutary ways. Conclusion: The application of cutting-edge technology toward understanding mindfulness— an ``inner technology''—is elucidating new ways in which attention, awareness, acceptance, and compassion may promote optimal health—in mind, body, relationships, and spirit.
Creating Reports with Query Objects

This paper contains a collection of patterns for creating database-reporting applications. While there are many different aspects of reporting, this paper focuses on the ability to dynamically create formulas and queries so that new reports can be generated at runtime. It does not discuss user interface issues or good database design. These patterns pull data from the database and manipulate data after it has been extracted from the database. This is accomplished by converting both queries and formulas into objects. These objects are then assembled into reports through the high-level Report Objects pattern. Introduction These database-reporting patterns are based upon our research using VisualWorks Smalltalk to dynamically generate reports that map to a relational database. We discovered these patterns while we were building a Business Modeling tool for Caterpillar. Although these patterns are described from a Smalltalk perspective, we feel that they are applicable to anyone building reporting applications. Furthermore, even though our examples apply to relational database queries, these ideas could be extended to other types of queries. The Caterpillar Business Modeling project is a pilot to demonstrate how an appropriate tool can support financial analysis and business decision-making more effectively. This project translates legacy data into a relational database format where it is then mapped to and from objects. Reporting the financial aspects of the Business Model required building many reports based upon business logic and SQL queries. Earlier versions used predefined reports, but this solution was not dynamic enough since users kept requesting new reports. Although predefined reports initially produce fewer bugs by statically checking the queries and values, they required programmatic changes whenever a new report or query is needed. Such changes can introduce bugs and are time consuming since developer must meet with the users to understand their request. As a result, we researched making a flexible and user-configurable system. The difficulty here is to make a system that is both easy to understand and modify. If done incorrectly, you’ve just pushed off the task of programming to the end-users since they would have to specify everything the programmer would normally specify for them. Furthermore, such a system is more difficult to understand since everything is created at runtime and cannot be statically analyzed. This paper describes a collection of patterns, which avoids these two extremes by making objects such as query and formula objects that represent reports . These objects can be predefined so that they give the user reasonable defaults but can later be customized. Our pattern language comprises five patterns (see Figure 1). Report Objects is the top-level pattern for defining reports. It consists of Query Objects and Formula Objects. Query Objects pull data from the database and can be composed into more complex queries by applying Composable Query Object. Formula Objects process data returned from Query Objects and are maintained by Constraint Observers.
GBoost : A Generative Framework for Boosting with Applications to Real-Time Eye Coding ?

Recent imaging studies show that the human brain has structures specialized for the detection of eyes and the recognition of eye-related behavior. There is some evidence that such systems may be innate and play an important role in infant social development. The development of machine perception systems that detect eyes and analyze eye behavior will also enable new approaches to human-computer interaction that emphasize natural, face-to-face communication with the user. For such systems to have an impact in everyday life it is important for them to work robustly in natural, unconstrained conditions. We formulate a probabilistic model of image generation and derive optimal inference algorithms for finding eyes within this framework. The approach models the image as a collage of patches of arbitrary size, some of which contain the object of interest and some of which are background. The approach requires development of likelihood-ratio models for object versus background generated patches. These models are learned using boosting methods. One advantage of the generative approach proposed here is that it makes explicit the conditions under which the approach is optimal, thus facilitating progress towards methods that model the image generation process in more realistic ways. The approach proposed here searches the entire image plane in each frame, making it resistant to fast, unpredictable motion. The system is robust to changes in lighting, illumination, and differences in facial structure, including facial expressions and eyeglasses. Furthermore, the system can simultaneously track the eyes and blinks of multiple individuals. We also present pilot results using this system for analysis of eye-openness in EEG studies. Finally we reflect on how the development of perceptive systems like this may help advance our understanding of the human brain.
Finite alphabet iterative decoding (FAID) of the (155,64,20) Tanner code

It is now well established that iterative decoding approaches the performance of Maximum Likelihood Decoding of sparse graph codes, asymptotically in the block length. For a finite length sparse code, iterative decoding fails on specific subgraphs generically termed as trapping sets. Trapping sets give rise to error floor, an abrupt degradation of the code error performance in the high signal to noise ratio regime. In this paper, we will study a recently introduced class of quantized iterative decoders, for which the messages are defined on a finite alphabet and which successfully decode errors on subgraphs that are uncorrectable by conventional decoders such as the min-sum or the belief propagation. We will especially study the performance of the proposed finite alphabet iterative decoders on the famous (155,64,20) Tanner code.
A Guide to Effective School Leadership Theories

Preface Acknowledgments Chapter 1: Transformational Leadership: The (Un)Disputed Champion of Leadership Strategies Chapter 2: Instructional Leadership: A Catalyst for the Promotion of Teaching and Learning Chapter 3: Distributed Leadership: A Humanistic Approach to Shared Governance Chapter 4: Ethical Leadership: Using Your Moral Compass to Steer the Ship Chapter 5: Emotional Leadership: Using Your Heart to Lead Chapter 6: Entrepreneurial Leadership: How Schools Can Learn from Business Leaders Chapter 7: Strategic Leadership: Those Who Fail to Plan, Plan to Fail Chapter 8: Sustainable Leadership: The Race Is Won by Those Who Endure Chapter 9: Invitational Leadership: Developing a School Culture of Trust, Respect, and Hope Chapter 10: Constructivist Leadership: A Framework for Building Sustainable School Improvement
Effective Teaching Practices: Effective Teaching Practices that Promote a Positive Classroom Environment

W ho is the most effective teacher you know? Take a moment to reflect on teachers you had when you were a student, have worked with, or have observed. Now, consider what makes (or made) that teacher effective. Although your answer may include both observable behaviors and other less tangible qualities, there is often a salient group of practices that makes a skilled teacher stand out. Effective teaching is both an art and a science. Successful teachers expertly weave together academic, behavioral, and social threads to achieve a unique classroom tapestry. Undoubtedly, one article cannot begin to cover all of the nuanced skills essential to creating an ideal classroom environment. However, research, practice, and experience have identified critical effective teaching practices when working with all students, including those with challenging behaviors. In this article, we present a framework for organizing concrete effective teaching practices and highlight specific strategies educators can use to establish and promote a positive classroom environment. In particular, we focus on three key areas of effective teaching: (a) delivering explicit and engaging academic instruction, (b) implementing empirically supported classroom management strategies, and (c) building relationships with students and their families. To assist teachers in the integration of effective teaching strategies, we (a) describe each of the three key areas of effective teaching, (b) suggest strategies to integrate these practices into teaching, and (c) provide helpful resources to support practitioners. Framework for Organizing Effective Class-Wide Teaching Practices
Assessment of Symptoms in Cancer Patients Undergoing Chemotherapy in Northern Greece

Introduction: Cancer patients experience a variety of symptoms that can be physical or psychological. These symptoms may vary in terms of occurrence, severity and distress and can be the result of the illness or the treatment. Purpose: The purpose of this study is to investigate the frequency, severity and distress of symptoms that chemotherapy induces in cancer patients. Material-Method: This study included 200 cancer patients undergoing chemotherapy in a major city of Northern Greece. Data was collected using the Memorial Symptom Assessment Scale and Questionnaire, with demographic and clinical characteristics. Results: The vast majority of those included in the sample were male participants (n=127, 63.5%). Their mean age was 58.95 (SD=9.95, range 29-79). The most prevalent physical symptoms were numbness/tingling in the hands/feet (54%), followed by lack of energy (46%). Feeling nervous (52%) and having trouble sleeping (41%) were the two most common psychological symptoms. Conclusions: The results of this study demonstrate that cancer patients undergoing chemotherapy experience various symptoms in high prevalence, and that they are quite severe. Therefore nurses should take into account these findings and plan appropriate, suitable care plans and interventions in order to alleviate them and improve patients’ quality of life.
Robust free space segmentation using active contours and monocular omnidirectional vision

In this paper, we propose a robust and fast active contour based method to free space detection in omnidirectional images where the problem of falsely detected obstacles is solved. We define a new functional energy formulation including altitude estimation of keypoints extracted nearby the active contour modeling the free space. The free space, so extracted, could help the robot in real time navigation and environment exploration tasks. To validate the efficiency of the proposed approach, the paper shows comparative results achieved with a classical formulation and our formulation of active contour energies, using images acquired by a robot exploring unknown indoor and outdoor environments, with no prior knowledge of the shape or the extend of the free space.
HEATING OF FLARE LOOPS WITH OBSERVATIONALLY CONSTRAINED HEATING FUNCTIONS

We analyze high-cadence high-resolution observations of a C3.2 flare obtained by AIA/SDO on 2010 August 1. The flare is a long-duration event with soft X-ray and EUV radiation lasting for over 4 hr. Analysis suggests that magnetic reconnection and formation of new loops continue for more than 2 hr. Furthermore, the UV 1600 Å observations show that each of the individual pixels at the feet of flare loops is brightened instantaneously with a timescale of a few minutes, and decays over a much longer timescale of more than 30 minutes. We use these spatially resolved UV light curves during the rise phase to construct empirical heating functions for individual flare loops, and model heating of coronal plasmas in these loops. The total coronal radiation of these flare loops are compared with soft X-ray and EUV radiation fluxes measured by GOES and AIA. This study presents a method to observationally infer heating functions in numerous flare loops that are formed and heated sequentially by reconnection throughout the flare, and provides a very useful constraint to coronal heating models.
A hybrid method for feature selection in the context of alternate test

Machine-learning test strategy has been developed in the last decade as an alternative to costly specification-driven tests for Analog, Mixed-Signal and RF circuits (AMS-RF). The concept is simple: powerful algorithms are used to map simple measurements onto specifications. But the proper execution requires an information-rich input space. This paper presents an efficient hybrid algorithm to select the best subset of signatures (or features) among a large number of candidates and shows how it can be applied to eventually propose the development of new ones.
Model-driven development for user-centric well-being support from dynamic well-being domain models to context-aware applications

Applications that can use information obtained through device sensors to alter their behavior are called context-aware. Design and development of such applications is currently done by modeling the application's context or by using novel requirements engineering methods. If the application is to support the user's well-being, these methods fall short due to their technical focus. We propose a model-driven approach that deals with the specifics of the well-being domain by using a DSL that captures the user's personal well-being context. The development method is user-centric, rather than technology focused. Initial user experiments show promising results.
Replicon Typing of Plasmids Encoding Resistance to Newer β-Lactams

Polymerase chain reaction–based replicon typing represents a novel method to describe the dissemination and follow the evolution of resistance plasmids. We used this approach to study 26 epidemiologically unrelated Enterobacteriaceae and demonstrate the dominance of incompatibility (Inc) A/C or Inc N-related plasmids carrying some emerging resistance determinants to extended-spectrum cephalosporins and carbapenems.
Conformational Investigation of A,b-dehydropeptides. Xiii. Conformational Properties of N-acetyl-a,b-dehydrovaline N¢,n¢-dimethylamide

The crystal structure of AcVal-NMe2 ( Val = -dehydrovaline) was determined by X-ray crystallography. The found angles = –60 and = 125 correspond exactly to the respective values of the (i + 1)th residue in idealised -turn II/VIa. Ab initio/DFT studies revealed that the molecule adopts the angle restricted only to about |130 | and very readily attains the angle = about –50 . This is in line with its solid-state conformation. Taken together, these data suggest that the Val residue combined with a C-terminal tertiary amide is a good candidate at the (i + 1)th position in a type II/VIa -turn. Vol. 51 No. 1/2004
An evolutionary solver for mixed integer programming

In this paper we introduce an evolutionary algorithm for the solution of mixed integer programs. The strategy is based on the separation of the set of variables into the integer subset and the continuous subset. The main idea is that if the integer variables are ﬁxed by the evolutionary system, the continuous ones can be determined in function of them by a linear program, which simultaneously provides an evaluation of those variables. We extend this idea to the case were some of the integer variables are ﬁxed by the evolutionary system and the remaining ones, as well as the continuous ones, are determined in function of them. Branch-and-bound and a specialised version of the relax-and-ﬁxed heuristic are used to solve the mixed-integer subproblems. When a particular assignment of the integer variables set by the evolutionary system leads to a feasible solution, its evaluation is determined directly by the objective function. If the variables correspond to an infeasible solution, the evaluation is measured by the number of variables that could not be ﬁxed, due to infeasibility in the subproblem; solutions with more variables ﬁxed are preferred. We report results obtained for some standard benchmark instances, and compare them with those obtained by time limited branch-and-bound. For a set of diﬃcult instances, the evolutionary algorithm could almost always improve the solution obtained by branch-and-bound on the same amount of CPU time.
Reliable Semi-supervised Learning

In this paper, we propose a Reliable Semi-Supervised Learning framework, called ReSSL, for both static and streaming data. Instead of relaxing different assumptions, we do model the reliability of cluster assumption, quantify the distinct importance of clusters (or evolving micro-clusters on data streams), and integrate the cluster-level information and labeled data for prediction with a lazy learning framework. Extensive experiments demonstrate that our method has good performance compared to state-of-the-art algorithms on data sets in both static and real streaming environments.
Application of CRISPR/Cas9 Technology to HBV

More than 240 million people around the world are chronically infected with hepatitis B virus (HBV). Nucleos(t)ide analogs and interferon are the only two families of drugs to treat HBV currently. However, none of these anti-virals directly target the stable nuclear covalently closed circular DNA (cccDNA), which acts as a transcription template for viral mRNA and pre-genomic RNA synthesis and secures virus persistence. Thus, the fact that only a small number of patients treated achieve sustained viral response (SVR) or cure, highlights the need for new therapies against HBV. The clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 gene editing system can specifically target the conserved regions of the HBV genome. This results in robust viral suppression and provides a promising tool for eradicating the virus. In this review, we discuss the function and application of the CRISPR/Cas9 system as a novel therapy for HBV.