Miracle-dz/UniFAR-FTUs huggingface dataset:
Two-stage cut saturation algorithm for designing all-optical networks

We design and optimize the physical topology of all-optical networks. This problem is more challenging than the traditional one for electronic communication networks, because of the wavelength-continuous constraint and it involves routing and wavelength assignment. In this problem, we are given the number of lightpaths required by every node pair and a cost specification, and our objective is to determine a physical topology of minimal cost. We formulate the problem, prove that it is NP-hard, and design an efficient algorithm called two-stage cut saturation algorithm for it. In the first stage, we relax the wavelength-continuous constraint and apply the main idea of the cut saturation method to determine a good initial network. In the second stage, we impose the wavelength-continuous constraint and perform routing and wavelength assignment to establish the specified lightpaths on the initial network. When some lightpaths cannot be established, we apply the main idea of the cut saturation method to optimize the insertion of additional links into the network. Simulation results show the following: (1) the proposed algorithm can efficiently design networks with low costs and high utilization and (2) if wavelength converters are available to support full wavelength conversion, the total cost of the links can be significantly reduced.
Emulating Loss and Delay for AD HOC Networks

Ad hoc networks have gained place in the research area recently. There are many researches regarding different topics related to such networks, such as routing, media access control, security, scalability, and many others. There are two usual methods to test and evaluate the performance of ad hoc networks: simulations and real test-bed. A network emulator is a tradeoff between pure simulation and real test-bed. Here, we propose a multi-hop wireless ad hoc network emulator that uses the advantages of Network Simulator (NS-2) and traffic shaping (DummyNet), that is called SEDLANE. SEDLANE is a network emulator that is based on TCP behavior characteristics. Using SEDLANE, we can emulate a whole multi-hop ad hoc network through the data packet loss and Round Trip Time (RTT) values over the TCP connection. SEDLANE helps testing and evaluating ad hoc network protocols using very simple and inexpensive test-bed configuration. The results confirm that; introducing SEDLANE within a simple configuration network (possibly 2 nodes) gives exactly the same results as having a wireless mobile multi-hop ad hoc network of any size.
A neotropical Miocene pollen database employing image-based search and semantic modeling1

Premise of the study: Digital microscopic pollen images are being generated with increasing speed and volume, producing opportunities to develop new computational methods that increase the consistency and efficiency of pollen analysis and provide the palynological community a computational framework for information sharing and knowledge transfer. Methods: Mathematical methods were used to assign trait semantics (abstract morphological representations) of the images of neotropical Miocene pollen and spores. Advanced database-indexing structures were built to compare and retrieve similar images based on their visual content. A Web-based system was developed to provide novel tools for automatic trait semantic annotation and image retrieval by trait semantics and visual content. Results: Mathematical models that map visual features to trait semantics can be used to annotate images with morphology semantics and to search image databases with improved reliability and productivity. Images can also be searched by visual content, providing users with customized emphases on traits such as color, shape, and texture. Discussion: Content- and semantic-based image searches provide a powerful computational platform for pollen and spore identification. The infrastructure outlined provides a framework for building a community-wide palynological resource, streamlining the process of manual identification, analysis, and species discovery.
Induction of lysosomal phospholipase A2 through the retinoid X receptor in THP-1 cells Published, JLR Papers in Press, February 1, 2004. DOI 10.1194/jlr.M300342-JLR200

An acidic phospholipase A2 (LPLA2) was recently purified and cloned. THP-1 cells were used to characterize the gene induction of LPLA2. THP-1 cells were stimulated with several differentiation agents. The LPLA2 mRNA and activity increased in cells treated with phorbol ester but not with vitamin D3, interferon-γ, or granulocyte macrophage colony-stimulating factor. All-trans-retinoic acid enhanced mRNA expression and enzyme activity in a dose- and time-dependent manner. The natural 9-cis and 13-cis isomers of retinoic acid enhanced transcription and activity. Two classes of nuclear receptors, the retinoic acid receptor (RAR) and the retinoid X receptor (RXR), mediate retinoic acid signaling. Specific RAR and RXR agonists were used to identify the nuclear receptor responsible for LPLA2 induction by retinoic acid. Treatment with the RAR agonist 4-[E-2-tetrahydro-5,5,8,8-tetra-methyl-2-naphthalenyl]1-propenyl benzoic acid (TTNPB) resulted in a small and statistically significant increase of the mRNA expression and activity of LPLA2. The RXR agonist methoprene acid worked as well as all-trans-retinoic acid at increasing both mRNA and enzyme activity. The methoprene acid and TTNPB effects were not synergistic. The peroxisome proliferator-activated receptor γ agonists 15-deoxy-Δ12,14-prostaglandin J2 and troglitazone failed to induce LPLA2 activity and mRNA. Thus, an RXR-dependent pathway controls LPLA2 gene activation by retinoic acid in THP-1 cells.
Removal of false positive in object detection with contour-based classifiers

This paper proposes a method of constructing a contour-based classifier to remove the false positive objects after Haar-based detection. The classifier is learned with the discrete AdaBoost. During the training, the oriented chamfer is introduced to construct strong learners. Experimental results have demonstrated that the proposed method is feasible and promising in the removal of the false positive.
Blogging while black and British : an exploratory study on the use of blogs as social cultural and counterhegemonic practice

This thesis is an exploratory study on how people of African descent in the UK use blogs as social, cultural and counterhegemonic practice and is positioned within the theoretical frameworks of alternative media and critical race theory (CRT). The research questions at the centre of this study are what motivates African Caribbean people in the UK to become bloggers; what gratification they experience through authoring blogs; how they use blogs to address issues of representation in the mainstream media and their perceptions of the social impact of their activities as bloggers. The findings reveal that motivation for blogging is linked to voice, visibility and empowerment and gratification is linked to voice, knowledge sharing, knowledge acquisition and social interaction. While voice, as a motivational factor and gratification for some participants is linked to interests in creative writing and journalism, for many others motivation and gratification are driven by a complex set of factors linked to issues of race and representation. These stem from feelings of being voiceless, invisible and marginalised as African Caribbean people in British society and blogs function as an assertive strategy and medium for self-representation. The constructed narratives of the bloggers who participated in this study reveal their experience of subtle forms of prejudice and discrimination perpetuated through dominant discourses in the mainstream media and marginalisation in the wider society. The findings demonstrate that race and ethnicity are inextricably linked to motivation and gratification and influence blogging practice and content production. This thesis expands on current literature by documenting how African Caribbean people have appropriated blogs to harness social and cultural capital, to mediate against racism and marginalisation within British society and to empower themselves and their communities.
Deduction of functional peptide motifs in scorpion toxins

Scorpion toxins are important physiological probes for characterizing ion channels. Molecular databases have limited functional annotation of scorpion toxins. Their function can be inferred by searching for conserved motifs in sequence signature databases that are derived statistically but are not necessarily biologically relevant. Mutation studies provide biological information on residues and positions important for structure–function relationship but are not normally used for extraction of binding motifs. 3D structure analyses also aid in the extraction of peptide motifs in which non‐contiguous residues are clustered spatially. Here we present new, functionally relevant peptide motifs for ion channels, derived from the analyses of scorpion toxin native and mutant peptides. Copyright © 2006 European Peptide Society and John Wiley & Sons, Ltd.
Proteomic Analysis of Candida albicans Cell Walls Reveals Covalently Bound Carbohydrate-Active Enzymes and Adhesins

ABSTRACT Covalently linked cell wall proteins (CWPs) of the dimorphic fungus Candida albicans are implicated in virulence. We have carried out a comprehensive proteomic analysis of the covalently linked CWPs in exponential-phase yeast cells. Proteins were liberated from sodium dodecyl sulfate (SDS)-extracted cell walls and analyzed using immunological and advanced protein sequencing (liquid chromatography-tandem mass spectrometry [LC/MS/MS]) methods. HF-pyridine and NaOH were used to chemically release glycosylphosphatidylinositol-dependent proteins (GPI proteins) and mild alkali-sensitive proteins, respectively. In addition, to release both classes of CWPs simultaneously, cell walls were digested enzymatically with a recombinant β-1,3-glucanase. Using LC/MS/MS, we identified 14 proteins, of which only 1 protein, Cht2p, has been previously identified in cell wall extracts by using protein sequencing methods. The 14 identified CWPs include 12 GPI proteins and 2 mild alkali-sensitive proteins. Nonsecretory proteins were absent in our cell wall preparations. The proteins identified included several functional categories: (i) five CWPs are predicted carbohydrate-active enzymes (Cht2p, Crh11p, Pga4p, Phr1p, and Scw1p); (ii) Als1p and Als4p are believed to be adhesion proteins. In addition, Pga24p shows similarity to the flocculins of baker's yeast. (iii) Sod4p/Pga2p is a putative superoxide dismutase and is possibly involved in counteracting host defense reactions. The precise roles of the other CWPs (Ecm33.3p, Pir1p, Pga29p, Rbt5p, and Ssr1p) are unknown. These results indicate that a substantial number of the covalently linked CWPs of C. albicans are actively involved in cell wall remodeling and expansion and in host-pathogen interactions.
Middle range theories

The most complete and detailed book devoted to middle range theories, this text examines theories and their applications in clinical nursing research and practice. The authors provide expert advice on selecting an appropriate theory for a nursing research project and on critiquing theories. The most frequently cited middle range nursing theories are explored in individual chapters. Each theory chapter includes examples of the theory's use in research, sample application of the theory, analysis exercises, and critical thinking exercises. The Third Edition includes new chapters on Attachment theory and the Shuler Nurse Practitioner Practice Model.
Analysis of Post-Deployment Cognitive Performance and Symptom Recovery in U.S. Marines

Background Computerized neurocognitive testing (NCAT) has been proposed to be useful as a screening tool for post-deployment cognitive deficits in the setting of mild traumatic brain injury (mTBI). We assessed the clinical utility of post-injury/post-deployment Automated Neurocognitive Assessment Metric (ANAM) testing, using a longitudinal design to compare baseline ANAM tests with two post-deployment ANAM tests in a group of Marines who experienced combat during deployment. Methods and Findings Post-deployment cognitive performance and symptom recovery were compared in a subsample of 1324 U.S. Marines with high rates of combat exposure during deployment. Of the sample, 169 Marines had available baseline and twice repeated post-deployment ANAM results. A retrospective analysis of the ANAM data, which consisted of a self-report questionnaire about deployment-related blast exposure, recent history of mTBI, current clinical symptoms, and cognitive performance. Self-reported concussion sustained anytime during deployment was associated with a decrease in cognitive performance measured between 2–8 weeks post-deployment. At the second post-deployment test conducted on average eight months later, performance on the second simple reaction time test, in particular, remained impaired and was the most consistent and sensitive indicator of the cognitive decrements. Additionally, post-concussive symptoms were shown to persist in injured Marines with a self-reported history of concussion for an additional five months after most cognitive deficits resolved. Results of this study showed a measurable deployment effect on cognitive performance, although this effect appears to resolve without lasting clinical sequelae in those without history of deployment-related concussion. Conclusions These results highlight the need for a detailed clinical examination for service members with history of concussion and persistent clinical symptoms. Reliance solely upon computerized neurocognitive testing as a method for identifying service members requiring clinical follow-up post-concussion is not recommended, as cognitive functioning only slowly returned to baseline levels in the setting of persistent clinical symptoms.
Political Volunteering From Late Adolescence to Young Adulthood

Political and general volunteering were characterized in late adolescence and young adulthood and related to predictive factors from infancy, childhood, and adolescence. One hundred five White participants (48 boys) completed measures of their volunteer involvement at 18 and 21 years of age. In addition, cognitive, social, adjustment, stress, and family data were collected from infancy through adolescence. Results indicated that most adolescents are involved in at least one volunteer activity. From 18 to 21 years of age, the likelihood of volunteering in a political activity increases significantly. In examining predictors of volunteering, results indicate that the strongest relations with volunteering are shown by adolescent factors including cognitive ability, family coherence, and membership in a prosocial organization (such as the Boy Scouts). Results support the notion that the social structure may be modified to provide incentives that increase volunteering.
Electronically steerable large-scale ultrasound phased-array for noninvasive transcranial therapy

A hemispherical focused ultrasound phased-array was designed and fabricated for noninvasive transcranial therapy. The array had a diameter of 31 cm. It was constructed with 1372 custom-made 6 mm long, 10 mm and 7.2 mm outer and inner diameter, cylindrical shape PZT-4 tube elements. The elements were driven at length-mode resonance (306 kHz) or third harmonic (840 kHz) frequency, which reduced the electrical impedance at least an order of magnitude compared with standard PZT plates driven at thickness mode. A scanning laser vibrometer was used to demonstrate clear length mode oscillation of the element. The ultrasound field measurements in water showed that the effective beam steering ranges, measured at a 50% of its maximum pressure-squared amplitude, were 100 times 100 times 80 mm3 at 306 kHz and 30 times 30 times 30 mm3 at 840 kHz, respectively. The focal spot sizes at the geometric focus were approximately 2.3 mm in diameter at 306 kHz and 0.7 mm in diameter at 840 kHz, respectively. The functionality of the array, including its beam steering and focusing capabilities, was evaluated with an ex vivo human skull.
A Chatbot as a Novel Corpus Visualization Tool

The classical way of viewing data set is using the visualization process, which maps the data from numerical or textual form to a visual representation that our mind can easily interpret such as: using graphical diagrams, charts, and geometric representation. In this paper we introduce a new idea to visualize a dialogue corpus using a chatbot interface tool. We developed a java program to convert a readable text (corpus) to AIML language to retrain ALICE. We use specific domains of the BNC spoken files to retrain ALICE, and visualise the data contents of these domains via chatting. Even that visualizing the corpus using a chatbot based on the chatting time and the size of the corpus, certain domains could be scanned easily if they are part of the current corpus or not. Our main conclusion is that it is possible to use the chatbot tool as a visualization process of a dialogue corpus, and to model different chatbot personalities.
Body selectivity in human visual cortex

Perceiving other people is a seemingly effortless process. Yet within a few hundred milliseconds we are aware of who we are looking at, what this person is doing, and even what this person feels. We derive this information from the form and motion of the face and body. Faces may be particularly important for some aspects of person perception (e. g., identity recognition), whereas bodies may be more important for others (e. g., action recognition). Furthermore, information from the body is important in cases where it is not possible to perceive the details of the face, for instance when the face is occluded, or when we see someone from a distance. In most cases, however, it is likely that information from both the face and the body are perceived in parallel and are integrated at an early stage. Previous research on person perception has mostly focused on the brain mechanisms underlying face perception. Much less research has focused on the brain mechanismsu nderlying body perception,w hich is the topic of this thesis. Using functional magnetic resonance imaging (fMRI) I provide evidence for a previously unknown body-selective visual area that overlaps a face-selective area. By employing novel analysis techniques that take into account patterns of activation across voxels I show that body- and face-selective areas can be functionally dissociated. Finally, I show that, in contrast to frontal and parietal action-recognition areas, visual body-selective areasd o not contain a dynamic representationo f observeda ctions. Together, thesef indings increaseo ur understandingo f the brain mechanismsu nderlying body, face and action perception, by showing both similarities and dissimilarities in the brain structures involved in these processes.
Enhancing SAT-based sequential depth computation by pruning search space

The sequential depth determines the completeness of bounded model checking in design verification. Recently, a SAT-based method is proposed to compute the sequential depth of a design by searching the state space. Unfortunately, it suffers from the search space explosion due to the exponential growth of design complexity. To alleviate the impact of state space explosion, we propose a search space reduction method. We collect the learned states and consider them constraints for further path searching. Furthermore, we propose a heuristic to guide the SAT-solver to efficiently find a shortest path. The experimental results show that as compared to another method which also enhances the previous SAT-based method using a branch-and-bound strategy, our approach obtains more improvements.
Party Discourse and Prejudiced Attitudes toward Migrants in Western Europe at the Beginning of the 2000s

Building on framing research and on cognitive dissonance theory, the paper examines the differentiated moderating effect of party discourse on prejudiced attitudes against immigrants. Using ESS 2002 data, the study finds that individuals who are positively oriented toward immigrants become more so when confronted with party discourses with anti-immigrant tones. This effect is, however, visible only when it comes to acceptance in one's private sphere, that is, acceptance of inter-ethnic marriage. The study also found some evidence that friendship with immigrants is not strong enough to impede natives to accept the idea of deporting unemployed immigrants.
Interpreting maps through the eyes of expert and novice users

The experiments described in this article combine response time measurements and eye movement data to gain insight into the users' cognitive processes while working with dynamic and interactive maps. Experts and novices participated in a user study with a ‘between user’ design. Twenty screen maps were presented in a random order to each participant, on which he had to execute a visual search. The combined information of the button actions and eye tracker reveals that both user groups showed a similar pattern in the time intervals needed to locate the subsequent names. From this pattern, information about the users' cognitive load could be derived: use of working memory, learning effect and so on. Moreover, the response times also showed that experts were significantly faster in finding the names in the map image. This is further explained by the eye movement metrics: experts had significantly shorter fixations and more fixations per second meaning that they could interpret a larger part of the map in the same amount of time. As a consequence, they could locate objects in the map image more efficiently and thus faster.
Similarity-based image classification via kernelized sparse representation

We consider the image classification problem based on the similarities between images. The choice of the similarity is related to the particular applications, and it could be based on color, texture, bag-of-features, or even more complex kernels. As long as the pair-wise similarity matrix is transformed into a positive semidefinite one, the similarities of images could be treated as kernels. This transformation makes it possible for kernel methods to solve the similarity-based image classification problem. In this paper, we propose a novel kernelized classification framework based on sparse representation. This new framework casts the classification as finding a sparse linear representation of test image with respect to training images. Unlike the former works, we do this sparse coding procedure through a proposed kernelized orthogonal matching pursuit algorithm, which is performed in inner product space rather than Euclidean space. Through a proper choice of the similarity function, the proposed approach can be applied to diverse image classification problems. Comparative experiments between the proposed method and other existing methods, on two real datasets (Caltech-101 and Face Rec) show that our method performed better.