Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural Complementarity of Toll/Interleukin-1 Receptor Domains in Toll-like Receptors and the Adaptors Mal and MyD88*

The Toll/interleukin 1 receptor (TIR) domain is a region found in the cytoplasmic tails of members of the Toll-like receptor/interleukin-1 receptor superfamily. The domain is essential for signaling and is also found in the adaptor proteins Mal (MyD88 adaptor-like) and MyD88, which function to couple activation of the receptor to downstream signaling components. Experimental structures of two Toll/interleukin 1 receptor domains reveal a α–β-fold similar to that of the bacterial chemotaxis protein CheY, and other evidence suggests that the adaptors can make heterotypic interactions with both the receptors and themselves. Here we show that the purified TIR domains of Mal and MyD88 can form stable heterodimers and also that Mal homodimers and oligomers are dissociated in the presence of ATP. To identify structural features that may contribute to the formation of signaling complexes, we produced models of the TIR domains from human Toll-like receptor 4 (TLR4), Mal, and MyD88. We found that although the overall fold is conserved the electrostatic surface potentials are quite distinct. Docking studies of the models suggest that Mal and MyD88 bind to different regions in TLRs 2 and 4, a finding consistent with a cooperative role of the two adaptors in signaling. Mal and MyD88 are predicted to interact at a third non-overlapping site, suggesting that the receptor and adaptors may form heterotetrameric complexes. The theoretical model of the interactions is supported by experimental data from glutathione S-transferase pull-downs and co-immunoprecipitations. Neither theoretical nor experimental data suggest a direct role for the conserved proline in the BB-loop in the association of TLR4, Mal, and MyD88. Finally we show a sequence relationship between the Drosophila protein Tube and Mal that may indicate a functional equivalence of these two adaptors in the Drosophila and vertebrate Toll pathways.
The Effectiveness of Refactoring, Based on a Compatibility Testing Taxonomy and a Dependency Graph

In this paper, we describe and then appraise a testing taxonomy proposed by van Deursen and Moonen (VD&M) based on the post-refactoring repeatability of tests. Four categories of refactoring are identified by VD&M ranging from semantic-preserving to incompatible, where, for the former, no new tests are required and for the latter, a completely new test set has to be developed. In our appraisal of the taxonomy, we heavily stress the need for the inter-dependence of the refactoring categories to be considered when making refactoring decisions and we base that need on a refactoring dependency graph developed as part of the research. We demonstrate that while incompatible refactorings may be harmful and time-consuming from a testing perspective, semantic-preserving refactorings can have equally unpleasant hidden ramifications despite their advantages. In fact, refactorings which fall into neither category have the most interesting properties. We support our results with empirical refactoring data drawn from seven Java open-source systems (OSS) and from the same analysis form a tentative categorization of code smells
Six-Weeks training program to enhance wrestler relative strength

This study explores the effect of six-week (36 sessions) programmed training on improving wrestling athletes' relative strength . It analyses the relative strength by calculati ng the total strength of arms/shoulders, abdominal, back, and leg , divided by subject’s body weight . T h is one group of prete st-posttest design indicates a group of subjects was given a specific treatment for 60 seconds of each push-up; sit-up; back dynamometer; and leg dynamometer . The study found that t he programmed training is able to in creas e the strength of 11 athletes and decreas e the mean value of their body mass index.
CLASS B0827+525: 'Dark lens' or binary radio-loud quasar?

We present radio, optical, near-infrared and spec troscopic observations of the source B0827+525. We consider this source as the best candidate from the Cosmic Lens All-Sky Survey (CLASS) for a 'dark-lens' system or binary radio-loud quasar. The system consists of two radio components with somewhat different spectral indices, separated by 2.815 arcsec. VLBA observations show that each component has substructure on a scale of a few mas. A deep K-band exposure with the W.M. Keck-II Telescope reveals emission near both radio components. The K-band emission of the weaker radio component appears extended, whereas the emission from the brighter radio component is consistent with a point source. Hubble Space Telescope F160W-band observations with the NICMOS instrument confirms this. A redshift of 2.064 is found for the brighter component, using the LRIS instrument on the W.M. Keck-II Telescope. The probability that B0827+525 consists of two unrelated compact flat-spectrum radio sources is similar to3%, although the presence of similar substructure in both component might reduce this. We discuss two alternative scenarios to explain this system: (i) CLASS B0827+525 is a 'dark-lens' system or (ii) B0827+525 is a binary radio-loud quasar. B0827+525 has met all criteria that thus far have in 100% of the cases confirmed a source as an indisputable gravitational lens system. Despite this, no lens galaxy has been detected with m(F160W)less than or equal to 23 mag. Hence, we might have found the first binary radio-loud quasar. At this moment, however, we feel that the 'dark-lens' hypothesis cannot yet be fully excluded.
Unsupervised Content Based Image Retrieval by Combining Visual Features of an Image With A Threshold

Content-based image retrieval (CBIR) uses the visual features of an image such as color, shape and texture to represent and index the image. In a typical content based image retrieval system, a set of images that exhibit visual features similar to that of the query image are returned in response to a query. CLUE (CLUster based image rEtrieval) is a popular CBIR technique that retrieves images by clustering. In this paper, we propose a CBIR system that also retrieves images by clustering just like CLUE. But, the proposed system combines all the features (shape, color, and texture) with a threshold for the purpose. The combination of all the features provides a robust feature set for image retrieval. We evaluated the performance of the proposed system using images of varying size and resolution from image database and compared its performance with that of the other two existing CBIR systems namely UFM and CLUE. We have used four different resolutions of image. Experimentally, we find that the proposed system outperforms the other two existing systems in ecery resolution of image.
Ideal observers , real observers , and the return of Elvis

Knill, Kersten, & Mamassian (Chapter 6) provide an interesting discussion of how the Bayesian formulation can be used to help investigate human vision. In their view, computational theories can be based on an ideal observer that uses Bayesian inference to make optimal use of available information. Four factors are important here: the image information used, the output structures estimated, the priors assumed (i.e., knowledge about the structure of the world), and the likelihood function used (i.e., knowledge about the projection of the world onto the sensors). Knill & Kersten argue that such a framework not only helps analyze a perceptual task, but can also help investigators to define it. Two examples are provided (the interpretation of surface contour and the perception of moving shadows) to show how this approach can be used in practice. As the authors admit, most (if not all) perceptual processes are ill-suited to a "strong" Bayesian approach based on a single consistent model of the world. Instead, they argue for a "weak" variant that assumes Bayesian inference to be carried out in modules of more limited scope. But how weak is "weak"? Are such approaches suitable for only a few relatively low-level tasks, or can they be applied more generally? Could a weak Bayesian approach, for example, explain how we would recognize the return of Elvis Presley?
On counting special Lagrangian homology 3-spheres

We attempt to define a new invariant I of (almost) Calabi-Yau 3-folds M, by counting special Lagrangian rational homology 3-spheres N in M in each 3-homology class, with a certain weight w(N) depending on the topology of N. This is motivated by the Gromov-Witten invariants of a symplectic manifold, which count the J-holomorphic curves in each 2-homology class. In order for this invariant to be interesting, it should either be unchanged by deformations of the underlying (almost) Calabi-Yau structure, or else transform according to some rigid set of rules as the periods of the almost Calabi-Yau structure pass through some topologically determined hypersurfaces in the cohomology of M. As we deform the underlying almost Calabi-Yau 3-fold, the collection of special Lagrangian homology 3-spheres only change when they become singular. Thus, to determine the stability of the invariant under deformations we need know about the singular behaviour of special Lagrangian 3-folds, which is not well understood. We describe two kinds of singular behaviour of special Lagrangian 3-folds, and derive identities on the weight function w(N) for I to be unchanged or transform well under them. The weight function w(N)=|H_1(N,Z)| satisfies these identities. We conjecture that an invariant I defined with this weight is independent of the Kahler class, and changes in certain ways as the holomorphic 3-form passes through some real hypersurfaces in H^3(M,C). Finally we consider connections with String Theory. We argue that our invariant I counts isolated 3-branes, and that it should play a part in the Mirror Symmetry story for Calabi-Yau 3-folds.
Speeded-up cuckoo search using opposition-based learning

For several decades, swarm intelligence (SI), emergent collective intelligence of groups of simple agents, has been applied to diverse research areas including optimization problems. Particle swarm optimization, ant colony optimization, artificial bee colony algorithm are well-known examples, and many variants are proposed so far. Recently proposed cuckoo search is also one class of SI. It mimics behaviors of cuckoo: intraspecific brood parasitism, cooperative breeding, and nest takeover. From the previous studies, it has quite a potential, so that it could outperform existing algorithms such as PSO. However, with respect to the convergence, CS shows slow performance. In this paper, we combine opposition-based learning (OBL) with CS, so that the convergence speed of CS becomes faster, not deteriorating the search ability of the algorithm. Through the simulation, the results indicate that the proposed algorithm outperforms the original algorithm not only in terms of convergence speed but also in terms of solution accuracy and success rate.
Co and Adjacent Channel Interference Evaluation in GSM and UMTS Cellular Networks

Interference is the major limiting factor when evaluating the performance of cellular radio systems. Sources of interference could be another mobile at the same cell, a call in progress in a neighboring cell or other base stations operating in the same frequency band. Interference on voice channels causes cross talk due to an undesired transmission. On control channels, interference leads to missed and blocked calls due to errors in the digital signaling. Interference is more severe in urban areas, due to the large number of base stations and mobiles. Interference has been recognized as a major bottleneck when looking for increasing capacity and is often responsible for dropped calls. The two major types of system-generated cellular interference are co-channel interference and adjacent channel interference. Even though interfering signals are often generated within the cellular system, they are difficult to control in practice (due to random propagation effects). Even more difficult to control this interference caused out-of-band users, which arises without warning due to front end overload of subscriber equipment or intermittent inter-modulation products. In practice, the transmitters from competing cellular carriers are often a significant source of out-of-band interference, since competitors often locate their base stations in close proximity to one another in order to provide comparable coverage to customers. This paper presents study of co and adjacent channel interferences in second and third generations of cellular radio systems.
Adaptive threshold generation in robust fault detection using interval models: time‐domain and frequency‐domain approaches

In this paper, robust fault detection is addressed on the basis of evaluating the residual energy that it is compared against worst‐case value (threshold) generated considering parametric modeling uncertainty using interval models. The evaluation of the residual/threshold energy can be performed either in the time or frequency domain. This paper proposes methods to compute such energy in the two domains. The first method generates the adaptive threshold in the time domain through determining the worst‐case time evolution of the residual energy using a zonotope‐based algorithm. The second method evaluates the worst‐case energy evolution in the frequency domain using the Kharitonov polynomials. Results obtained using both approaches are related through the Parseval's theorem. Finally, two application examples (a smart servoactuator and a two DOFs helicopter) will be used to assess the validity of the proposed approaches and compare the results obtained. Copyright © 2012 John Wiley & Sons, Ltd.
DETECTION OF ACUTE LEUKEMIA USING WHITE BLOOD CELLS SEGMENTATION BASED ON BLOOD SAMPLES

In order to improve patient diagnosis various image processing software are developed to extract useful information from medical images. An essential part of the diagnosis and treatment of leukemia is the visual examination of the patient’s peripheral blood smear under the microscope. Morphological changes in the white blood cells are commonly used to determine the nature of the malignant cells, namely blasts. Morphological analysis of blood slides are influenced by factors such as hematologists experience and tiredness, resulting in non standardized reports. So there is always a need for a cost effective and robust automated system for leukemia screening which can greatly improve the output without being influenced by operator fatigue. This paper presents an application of image segmentation, feature extraction, selection and cell classification to the recognition and differentiation of normal cell from the blast cell. The system is applied for 108 images available in public image dataset for the study of leukemia. The methodology demonstrates that the application of pattern recognition is a powerful tool for the differentiation of normal cell and blast cell leading to the improvement in the early effective treatment for leukemia.
Involvement of prefrontal cortex in scalar implicatures: evidence from magnetoencephalography

The present study investigated the neural correlates of the realisation of scalar inferences, i.e., the interpretation of some as meaning some but not all. We used magnetoencephalography, which has high temporal resolution, to measure neural activity while participants heard stories that included the scalar inference trigger some in contexts that either provide strong cues for a scalar inference or provide weaker cues. The middle portion of the lateral prefrontal cortex (Brodmann area 46) showed an increased response to some in contexts with fewer cues to the inference, suggesting that this condition elicited greater effort. While the results are not predicted by traditional all-or-nothing accounts of scalar inferencing that assume the process is always automatic or always effortful, they are consistent with more recent gradient accounts which predict that the speed and effort of scalar inferences is strongly modulated by numerous contextual factors.
Digital image tampering detection and localization using singular value decomposition technique

Recent years have witnessed an exponential growth in the use of digital images due to development of high quality digital cameras and multimedia technology. Easy availability of image editing software has made digital image processing very popular. Ready to use software are available on internet which can be easily used to manipulate the images. In such an environment, the integrity of the image can not be taken for granted. Malicious tampering has serious implication for legal documents, copyright issues and forensic cases. Researchers have come forward with large number of methods to detect image tampering. The proposed method is based on hash generation technique using singular value decomposition. Design of an efficient hash vector as proposed will help in detection and localization of image tampering. The proposed method shows that it is robust against content preserving manipulation but extremely sensitive to even very minute structural tampering.
Effects of additional knowledge of results on modifying highly practiced acyclic swimming techniques with knowledge of performance

The author investigated the effects of additional knowledge of results on modifying swimming starts and turns with video-based knowledge of performance. A total of 18 swimming experts (15–18 years of age) learned modifications of start and turn techniques with knowledge of performance or a combination of knowledge of performance and knowledge of results. The feedback condition was switched between the groups from experiment 1 to experiment 2. Both experiments contained 50 trials with augmented feedback distributed over five sessions. Both experiments revealed no detrimental effects of additional knowledge of results on process-related performance variables. With respect to the result-related variables (start time and turn time), only the groups without knowledge of results exhibited temporary impairment in the immediate retention tests. The results are largely replicated in both experiments. Knowledge of results seems to have positive effects on modifying with knowledge of performance. The presence of knowledge of results might reduce the deautomatizing conscious control processes that are induced by knowledge of performance and might cause temporary performance impairments.
Enhancement in cellular Na+K+ATPase activity by low doses of peroxynitrite in mouse renal tissue and in cultured HK2 cells

In the normal condition, endogenous formation of peroxynitrite (ONOOˉ) from the interaction of nitric oxide and superoxide has been suggested to play a renoprotective role. However, the exact mechanism associated with renoprotection by this radical compound is not yet clearly defined. Although ONOOˉ usually inhibits renal tubular Na+K+ATPase (NKA) activity at high concentrations (micromolar to millimolar range [μM–mM], achieved in pathophysiological conditions), the effects at lower concentrations (nanomolar range [nM], relevant in normal condition) remain unknown. To examine the direct effect of ONOOˉ on NKA activity, preparations of cellular membrane fraction from mouse renal tissue and from cultured HK2 cells (human proximal tubular epithelial cell lines) were incubated for 10 and 30 min each with different concentrations of ONOOˉ (10 nmol/L–200 μmol/L). NKA activity in these samples (n = 5 in each case) was measured via a colorimetric assay capable of detecting inorganic phosphate. At high concentrations (1–200 μmol/L), ONOOˉ caused dose‐dependent inhibition of NKA activity (−3.0 ± 0.6% and −36.4 ± 1.4%). However, NKA activity remained unchanged at 100 and 500 nmol/L ONOOˉ concentration, but interestingly, at lower concentrations (10 and 50 nmol/L), ONOOˉ caused small but significant increases in the NKA activity (3.3 ± 1.1% and 3.1 ± 0.6%). Pretreatment with a ONOOˉ scavenger, mercaptoethylguanidine (MEG; 200 μmol/L), prevented these biphasic responses to ONOOˉ. This dose‐dependent biphasic action of ONOO− on NKA activity may implicate that this radical compound helps to maintain sodium homeostasis either by enhancing tubular sodium reabsorption under normal conditions or by inhibiting it during oxidative stress conditions.
Expanding normative profiles of elite squash players using momentum of winners and errors.

This paper aims to extend these ideas and explore a new application of these analysis techniques to develop ‘momentum profiles’ through notational analysis. We defined positive momentum as a player hitting successive winners, negative momentum, as a player hitting errors, and if the player is passive, not hitting winners or making errors, then the player’s momentum will stay the same. With the data processed by the software it was possible to present the 2 sets of data for both players at the same time. It is possible to examine these curves and see where the ‘turning points’ in the match occurred. For the coach and/or the team psychologist to discuss with the player what happened at these turning points would enhance insight into each respective performance. This study demonstrates a quantitative, yet qualitative, approach to psychological momentum. Both the world number 1 male and female players have averages of peak length significantly higher than their peers. Further research needs to be done to analyse why their peaks are longer and steeper.
Robust Object Tracking by Simultaneous Generation of an Object Model

Although robust object tracking has a wide variety of applications ranging from video surveillance to recognition from motion, it is not completely solved. Difficulties in tracking objects ar ise due to abrupt object motion, changing appearance of the object or partial and full object oc clusions. To resolve these problems, assumptions are usually made concerning the motion or appearance of an o bject. However in most applications no models of object motion or appearance are previously available. This paper presents an approach which improves the performance of a tracking algorithm due to simultaneous onlin e model generation of a tracked object. The achieved results testify the stability and the robustness of this app roach.
Security and privacy considerations for Wireless Sensor Networks in smart home environments

Wireless Sensor Network (WSN) has emerged as a dependable technology to improve the quality of life in smart homes through offering various automated, interactive and comfortable services. Sensors integrated at different places in homes, offices, and even in clothes, equipment, and utilities are used to sense and monitor occupants' positions, movements, vital signs, utility usage, temperature and humidity levels of rooms, etc. Along with sensing and monitoring capabilities, sensors cooperate and communicate with themselves to deliver, share and process sensed information and assist real-time decision-making procedures through triggering appropriate alerts and actions. However, ensuring privacy and providing adequate security in these crucial services provided by WSNs is a major issue in smart home environments. In this paper, we examine the privacy and security challenges of WSNs and survey its practicality for smart home environments. We discuss the unique characteristics that distinguish a smart environment from the rest, elaborate on security and privacy issues and their respective solution measures. A number of challenges and interesting research issues emerging from this study have been reported for further investigation.