Miracle-dz/UniFAR-FTUs huggingface dataset:
Organizational Dynamics of Change in China : A Multimedia Simulation Approach

As organizational change, and in particular Information and Communication Technology (ICT) driven change, has become an important way to improve the efficiency of business processes, more and more organizations are paying increasing attention to helping their managers acquire the necessary knowledge and skills for better managing such change. This paper describes the design of a computer-based interactive multimedia simulation called LingHe Simulation, which models the dynamics of organizational change in a typical Chinese business environment. The simulation aims to stimulate and enhance managers’ understanding of organizational resistance to change and how to more effectively implement changes. Having tested the simulation among both Western and Chinese managers in a series of workshops, the paper further examines the effectiveness of the simulation as an innovative learning tool and technique for improving their understanding of the organizational dynamics and the corresponding knowledge and skill in managing organizational change in a Chinese environment.
Large Scale Image Clustering with Active Pairwise Constraints

In this paper, we propose a method of clustering large image sets using human input. We assume an algorithm provides us with pairwise similarities. We then actively ask for more accurate pairwise similarities between images from humans. Using all similarities, we cluster the images and show that the improvement gain is significant even when the available human resources are very limited.
Skyline web service selection with MapReduce

With the development of Service and Cloud Computing, more and more web services with similar function attributes but different QoS are available. Efficient selecting from these large numbers of web services brings challenges to the existing methods. Furthermore, service selection has been always a tedious process. In this paper, toward these issues, we make use of skyline with MapReduce to select the appropriate services efficiently and equally. An analytical and experimental comparison shows that our computing scheme of skyline with MapReduce outperforms traditional selection techniques in reducing the response time and sharing the computational workload more fairly.
A joint design of admission control and transmission rate adaptation for VoIP over wireless network

The ideal design for VoIP should be able to maximize the number of concurrent users while each admitted user enjoys the satisfactory quality of voice communication. In a recent packet-based wireless system, the quality-of-service (QoS) provisioning for VoIP raises several challenging issues including correlated delay performance among users and the rate-reliability tradeoff in managing multiple transmission rates on top of the inherent difficulty originating from the dependency of QoS on end-to-end delay. For these reasons, it is rarely found in the literature the work which presents the admission criteria for VoIP in an explicit manner. In this paper, our major contributions include 1) deriving the link-level QoS requirement from the E-model; 2) presenting the admission criteria in an explicit manner; 3) proposing a transmission rate adaptation algorithm specialized for VoIP application; and 4) illustrating the feasibility of our proposed schemes by getting the necessary information from the measurement. In addition to the theoretical justification, through the intensive simulation study in the Rayleigh fading environment, we prove that our joint designs composed of the rate adaptation, measurement-based admission control algorithm, and its extension to supporting the cell-boundary users indeed work well. Also, we evaluate the impact of various parameters including the average SNR, the Doppler rate, and the wireline delay.
A high potency nonformylated peptide agonist for the phagocyte N- formylpeptide chemotactic receptor

Analysis of synthetic tri- and tetrapeptides has previously indicated that N-formylation is required for high biological activity when they react with the phagocyte N-formylpeptide receptor, suggesting that the natural ligand for the receptor is from bacterial and/or mitochondrial sources. To explore this requirement further, we synthesized the pentapeptide methionyl-norleucyl-leucyl-phenylalanyl-phenylalanine (MNleLFF) and studied the effects of different NH2-terminal modifications on its activity. N-formyl-MNleLFF induced transient alterations of [Ca2+]i and superoxide production in human neutrophils with 10- and 100-fold greater potency, respectively, than the proto- type N-formylpeptide, N-formylmethionyl-leucyl-phenylalanine (fMLF). Surprisingly, N-acetyl-MNleLFF was a potent as N-formyl-MNleLFF. Moreover, the unacylated counterpart H-MNleLFF was also highly active, having an EC50 for calcium mobilization of 10 nM, and for respiratory burst activation of 100 nM. All three pentapeptides could completely desensitize calcium transients elicited by stimulation of neutrophils with fMLF, whereas the neutrophil chemoattractants C5a and interleukin 8 only weakly affected fMLF-induced transients, suggesting that they activate neutrophils via the same receptor as fMLF. Finally, all three pentapeptides activated the recombinant human N-formylpeptide receptor expressed in frog oocytes, but did not effectively activate related phagocyte receptors. These data broaden the potential sources of natural ligands for the N-formyl-peptide receptor from N-formylated bacterial and mitochondrial products to other nonformylated endogenous peptides.
A scalable and topology configurable protocol for distributed parameter synchronization

This paper addresses the problem of model synchronization in data-parallelism of deep-learning systems. In such systems, workers on different machines continuously update their local copies of the model, and the updates need to be merged so that the copies are roughly consistent to each other. In modern implementations using GPUs, workers generate very high updates, posing significant scalability challenges. We model this as a distributed state anti-entropy problem, and propose a fully asynchronous and decentralized parameter sharing protocol that allows machines to reconcile model differences to their connected peers. The protocol is provably correct to achieve eventual consistency, and recovers gracefully from common failures without invasive maneuver. In addition, it is flexible in that both different consistency requirements and topology connections can be dynamically reconfigured. We show that such flexibility is important for better trade-off between system performance and model convergence rate. For example, under high update rates, the existing master-slave architecture performs poorly against other configurations with larger diameter.
Anticonvulsant effects of 3, 4-Dimethoxy toluene, the major constituent of Phoenix dactylifera L Spathe in mice

The anticonvulsant effects of 3,4-Dimethoxy toluene (DMT), the major constituent of the date palm (Phoenix dactylifera L.) spathe, were investigated using pentylenetetrazole (PTZ), picrotoxin (Pic), nicotine (Nic) and maximal electroshock (MES)-induced seizure models. In PTZ (85 mg/kg)-induced seizures, the intraperitoneally injection of DMT at a dose of 100 mg/kg significantly delayed the onset time of seizures and produced 50% protective effect against mortality. In MES model, DMT showed complete inhibition of tonic hind-limb extension (THLE) and exhibited complete protection against mortality. After mice were injected with picrotoxin (12 mg/kg), DMT (100 mg/kg) significantly delayed the onset time of convulsions and death. DMT exhibited complete protection against nicotine (0.8 mg/kg)-induced convulsions. These results indicate that DMT may have a promising anticonvulsant activity.
Estimating information flow through a memory system: the utility of meta-analytic methods for genetics

Critics of significance testing claim that this statistical framework promotes discrepancies by using arbitrary thresholds (α) to impose reject/accept dichotomies on continuous data, which is not reflective of the biological reality of quantitative phenotypes. Here we explore this idea and evaluate an alternative approach, demonstrating the potential for meta-analysis and related estimation methods to resolve discordance generated by the use of traditional significance tests. We selected a set of behavioral studies proposing differing models of the physiological basis of Drosophila olfactory memory and used systematic review and meta-analysis approaches to define the true role of lobular specialization within the brain. The mainstream view is that each of the three lobes of the Drosophila mushroom body play specialized roles in short-term aversive olfactory memory [1-5], but a number of studies have made divergent conclusions based on their discordant experimental findings [6-8]. Multivariate meta-regression models revealed that short-term memory lobular specialization is not in fact supported by the data, and identified the cellular extent of a transgenic driver as the major predictor of its effect on short-term memory. Our findings demonstrate that meta-analysis, meta-regression, hierarchical models and estimation methods in general can be successfully harnessed to identify knowledge gaps, synthesize divergent results, accommodate heterogeneous experimental design and quantify genetic mechanisms.
Potential Function in a Continuous Dissipative Chaotic System: Decomposition Scheme and Role of Strange Attractor

In this paper, we demonstrate, first in literature known to us, that potential functions can be constructed in continuous dissipative chaotic systems and can be used to reveal their dynamical properties. To attain this aim, a Lorenz-like system is proposed and rigorously proved chaotic for exemplified analysis. We explicitly construct a potential function monotonically decreasing along the system's dynamics, revealing the structure of the chaotic strange attractor. The potential function can have different forms of construction. We also decompose the dynamical system to explain for the different origins of chaotic attractor and strange attractor. Consequently, reasons for the existence of both chaotic nonstrange attractors and nonchaotic strange attractors are clearly discussed within current decomposition framework.
Humour Research: State of Art

Humour is a multi-disciplinary field of research. People have been working on humour in many fields of research like psychology, philosophy and linguistics, sociology and literature. Especially in the context of computer science (or Artificial Intelligence) humour research aims at modeling humour in a computationally tractable way. Having computational models of humour allows interface designers to have the computer generate and interpret humour when interacting with users. There are many situations in human-human interaction where humour plays an important role in keeping the conversation going. Making use of the so-called CASA paradigm (Computers Are Social Actors) we may expect that a similar role can be played in human-computer interaction. In this report we survey current humour research with the aim to identify useful theories that can be applied in the human-computer interaction context. We focus on the following subjects: humour theories, related humour research, linguistic aspects of humour, computational aspects of humour, applications and resources.
Ambiguity spotting using wordnet semantic similarity in support to recommended practice for Software Requirements Specifications

Word Sense Disambiguation is a crucial problem in documents whose purpose is to serve as specifications for automatic systems. The combination of different techniques of Natural Language Processing can help in this task. In this paper, we show how to detect ambiguous terms in Software Requirements Specifications. And we propose a computer-aided method that signals the reader for possibly ambiguous usage of terms. The method uses compound term measure (C-value), WordNet semantic similarity (WordNet wup_similarity) and a proposed semantic similarity measure between sentences.
Meta-Analysis of Pulsed-Field Gel Electrophoresis Fingerprints Based on a Constructed Salmonella Database

A database was constructed consisting of 45,923 Salmonella pulsed-field gel electrophoresis (PFGE) patterns. The patterns, randomly selected from all submissions to CDC PulseNet during 2005 to 2010, included the 20 most frequent serotypes and 12 less frequent serotypes. Meta-analysis was applied to all of the PFGE patterns in the database. In the range of 20 to 1100 kb, serotype Enteritidis averaged the fewest bands at 12 bands and Paratyphi A the most with 19, with most serotypes in the 13−15 range among the 32 serptypes. The 10 most frequent bands for each of the 32 serotypes were sorted and distinguished, and the results were in concordance with those from distance matrix and two-way hierarchical cluster analyses of the patterns in the database. The hierarchical cluster analysis divided the 32 serotypes into three major groups according to dissimilarity measures, and revealed for the first time the similarities among the PFGE patterns of serotype Saintpaul to serotypes Typhimurium, Typhimurium var. 5-, and I 4,[5],12:i:-; of serotype Hadar to serotype Infantis; and of serotype Muenchen to serotype Newport. The results of the meta-analysis indicated that the pattern similarities/dissimilarities determined the serotype discrimination of PFGE method, and that the possible PFGE markers may have utility for serotype identification. The presence of distinct, serotype specific patterns may provide useful information to aid in the distribution of serotypes in the population and potentially reduce the need for laborious analyses, such as traditional serotyping.
Germline Fitness-Based Scoring of Cancer Mutations

A key goal in cancer research is to find the genomic alterations that underlie malignant cells. Genomics has proved successful in identifying somatic variants at a large scale. However, it has become evident that a typical cancer exhibits a heterogenous mutation pattern across samples. Cases where the same alteration is observed repeatedly seem to be the exception rather than the norm. Thus, pinpointing the key alterations (driver mutations) from a background of variations with no direct causal link to cancer (passenger mutations) is difficult. Here we analyze somatic missense mutations from cancer samples and their healthy tissue counterparts (germline mutations) from the viewpoint of germline fitness. We calibrate a scoring system from protein domain alignments to score mutations and their target loci. We show first that this score predicts to a good degree the rate of polymorphism of the observed germline variation. The scoring is then applied to somatic mutations. We show that candidate cancer genes prone to copy number loss harbor mutations with germline fitness effects that are significantly more deleterious than expected by chance. This suggests that missense mutations play a driving role in tumor suppressor genes. Furthermore, these mutations fall preferably onto loci in sequence neighborhoods that are high scoring in terms of germline fitness. In contrast, for somatic mutations in candidate onco genes we do not observe a statistically significant effect. These results help to inform how to exploit germline fitness predictions in discovering new genes and mutations responsible for cancer.
Parametric Reconstruction of Bent Tube Surfaces

We present a method for parametric reconstruction of a piecewise defined pipe surface, consisting of cylinder and torus segments, from an unorganized point set. Our main contributions are reconstruction of the spine curve of a pipe surface from surface samples, and approximation of the spine curve by G^1 continuous circular arcs and line segments. Our algorithm accurately outputs the parametric data required for bending machines to create the reconstructed tube.
Generalized dynamic object removal for dense stereo vision based scene mapping using synthesised optical flow

Mapping an ever changing urban environment is a challenging task as we are generally interested in mapping the static scene and not the dynamic objects, such as cars and people. We propose a novel approach to the problem of dynamic object removal within stereo based scene mapping that is both independent of the underlying stereo approach in use and applicable to varying object and camera motion. By leveraging stereo odometry, to recover camera motion in scene space, and stereo disparity, to recover synthesised optic flow over the same pixel space, we isolate regions of inconsistency in depth and image intensity. This allows us to illustrate robust dynamic object removal within the stereo mapping sequence. We show results covering objects with a range of motion dynamics and sizes of those typically observed in an urban environment.
“If You Show Who You are, Then They are Going to Try to Fix You”: The Capitals and Costs of Schooling for High-Achieving Latina Students

Schools are supposed to be places where students learn academic and technical skills while also expanding their social networks. Although much research exists that examines academic achievement from a variety of lenses, schools and educators continue to lack insight into the various strengths—or capital—students bring with them to school alongside the barriers—or costs—they face once there. To help bridge the gap between the extant research and what is practiced in schools, we provide insight into what educators can do to capitalize on students' strengths and minimize the barriers to achievement. This article draws from two theoretical frameworks, Community Cultural Wealth (CCW) and Racial Opportunity Cost (ROC), and two qualitative research projects that examined Latina high school students' academic achievement from a capitals and costs perspective. Although significant research has identified assets-based approaches to schooling, our results indicate that the interplay between the norms of the school and the norms the students embraced played a critical role in terms of creating conditions for a positive school experience. Based on our findings, we offer recommendations for educators to address the costs that students experience.
Characterisation of Nitric Oxide Synthase in Three Cnidarian-Dinoflagellate Symbioses

Background Nitric oxide synthase (NOS) is an enzyme catalysing the conversion of L-arginine to L-citrulline and nitric oxide (NO), the latter being an essential messenger molecule for a range of biological processes. Whilst its role in higher vertebrates is well understood little is known about the role of this enzyme in early metazoan groups. For instance, NOS-mediated signalling has been associated with Cnidaria-algal symbioses, however controversy remains about the contribution of enzyme activities by the individual partners of these mutualistic relationships. Methodology/Principal Findings Using a modified citrulline assay we successfully measured NOS activity in three cnidarian-algal symbioses: the sea anemone Aiptasia pallida, the hard coral Acropora millepora, and the soft coral Lobophytum pauciflorum, so demonstrating a wide distribution of this enzyme in the phylum Cnidaria. Further biochemical (citrulline assay) and histochemical (NADPH-diaphorase) investigations of NOS in the host tissue of L. pauciflorum revealed the cytosolic and calcium dependent nature of this enzyme and its in situ localisation within the coral's gastrodermal tissue, the innermost layer of the body wall bearing the symbiotic algae. Interestingly, enzyme activity could not be detected in symbionts freshly isolated from the cnidarians, or in cultured algal symbionts. Conclusions/Significance These results suggest that NOS-mediated NO release may be host-derived, a finding that has the potential to further refine our understanding of signalling events in cnidarian-algal symbioses.
Our Followers Are Lions, Theirs Are Sheep: How Social Identity Shapes Theories About Followership and Social Influence

Two studies examine how self-categorization theory can be used to refine our understanding of people's implicit theories about followership and social influence. Results from Study 1 show that perceivers regard followers of a group they themselves identify strongly with (rather than not at all) to be more representative of the prototype of effective followers (displaying enthusiasm, industry, good citizenship) and to be less representative of the antiprototype of effective followers (displaying conformity, incompetence, and insubordination). Results are replicated in a second experiment in which we compare the views of those self-categorizing as either Republican or Democrat responding to followers of the Republican and Democratic Party. Results of Study 2 replicate those of Study 1 and also reveal qualitative differences in the preferred influence strategy for dealing with followers. Specifically, respondents seek to engage in persuasion when trying to change the behavior of ingroup followers, while resorting to coercion when trying to change the behavior of outgroup followers. Our results are the first to provide evidence that perceivers' theories about what followers are like and how they are influenced most effectively are structured by perceivers' identification (and dis-identification) with the particular groups that leaders are championing.
Geo-WordNet: Automatic Georeferencing of WordNet

WordNet has been used extensively as a resource for the Word Sense Disambiguation (WSD) task, both as a sense inventory and a repository of semantic relationships. Recently, we investigated the possibility to use it as a resource for the Geographical Information Retrieval task, more specifically for the toponym disambiguation task, which could be considered a specialization of WSD. We found that it would be very useful to assign to geographical entities inWordNet their coordinates, especially in order to implement geometric shapebased disambiguation methods. This paper presents Geo-WordNet, an automatic annotation of WordNet with geographical coordinates. The annotation has been carried out by extracting geographical synsets from WordNet, together with their holonyms and hypernyms, and comparing them to the entries in the Wikipedia-World geographical database. A weight was calculated for each of the candidate annotations, on the basis of matches found between the database entries and synset gloss, holonyms and hypernyms. The resulting resource may be used in Geographical Information Retrieval related tasks, especially for toponym disambiguation.
Smart framework for managing diabetes based on service oriented architecture

Due to the increase of sedentary life style in most of the world and specifically in the region where this research is conducted, led to the raise in chronic diseases that start to emerge in the region. These diseases appear in the form of increase in obesity, heart disease, and diabetes. In order to manage such diseases, a close monitoring to patients is essential in order to control its level. The system that we are proposing in the paper is capable of collecting the data from the patients, analyzing them and suggesting the appropriate diagnosis. Hence, this work advises a system that is capable of reducing the physical access load on healthcare centers via notifying both healthcare provider and patients with the acquired results