Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of model female quality in the mate choice copying behaviour of sailfin mollies

Female mate choice copying is a socially mediated mate choice behaviour, in which a male's attractiveness to females increases if he was previously chosen by another female as a mate. Although copying has been demonstrated in numerous species, little is known about the specific benefits it confers to copying females. Here we demonstrate that the mate choice behaviour of female sailfin mollies (Poecilia latipinna) is influenced by the phenotypic quality of model females with whom males are observed consorting. Test females choosing between two males of similar body length were found to significantly increase time spent with previously non-preferred males after having observed them with a relatively high-quality female. Conversely, females were found to significantly decrease time spent with previously preferred males after having observed them with a relatively low-quality female. Female mate choice copying might be maintained by selection based on the heuristic value it provides females choosing between males whose quality differences are not easily distinguishable.
Experimental Analysis of the Impact of the Message Management in the Case of the ABT Family

In this article are analyzed the message queues aiming to improve the message management, more precisely to reduce or eliminate the obsolete messages and, thus, reduce the costs for obtaining the solution. This thing allows the improvement of the performances of the ABT family techniques. Asynchronous techniques use some message processing routines. Those procedures process sequentially or in batches the messages that are in the message queues. Typically, each agent extracts one or more messages from its communication channel and calls the appropriate message processing routine, this operation is achieved based on a strategy of message processing, strategy that specifies the order and the way of treating the messages based on a formal protocol. In this article we analyzed this protocol for message management for the purpose of identifying the conditions where this could be applyed to allow us to decrease or eliminate the redundant messages. A new strategy for message management is proposed, strategy that allows obtaining variants of more efficient asynchronous techniques, in the case of the ABT family. An improved protocol for complete treating of the messages is proposed. The performances of the ABT family techniques are investigated, the experiments showing a decrease of the necessary costs for obtaining a solution in the case of applying the message management. A comparative study of the ABT versions is presented, the sequential versions are compared with the versions with redundant messages filtering, those based on various strategies of message processing.
Some Effects of Deception and Level of Self-Monitoring on Planning and Reacting to a Self-Presentation

This experiment addressed issues in impression management. First, this study investigated whether type of impression intended (accurate or fabricated) and level of self-monitori ng (high or low) affect the amount of information about a target person that individuals would acquire, at some cost to themselves, prior to interacting with that person. As predicted, high self-monitors planning a fabrication purchased more information than high self-monitors planning an accurate impression or low self-monitors planning either type of impression. In addition, reactions of both participants to the actor's performance were analyzed. Impression type affected both actors' and targets' reactions, whereas self-monitoring affected only the targets' ratings. Erving Goffman, in his seminal work on impression management (19S9), has discussed how individuals present an impression of self that influences the definition of the situation that others come to formulate. It is in the various parties' best interest to induce others to attribute qualities to them that are supportive of their own interaction goals. People can do this by expressing themselves in a manner that communicates impressions intended to lead others to support their plans voluntarily. The current experiment focuses on actors' preparation for an upcoming encounter and reactions to their performance.
The SAMOVA Shot Boundary Detection for TRECVID Evaluation 2004

This paper describes the system used by the SAMOVA team (IRIT) to perform the shot boundary detection task of the TRECVID 2004 workshop. Our main algorithm is based on detection of illumination changes, as well as on the length of these transitions. The results are then re(cid:12)ned by ckecking all the candidate transitions. We propose three versions of our application. Samova01: the simplest form, only uses illumination changes with image di(cid:11)erence. Samova02
Crisis Management: Government Strategy in Framing Reform Proposals and Communications

One of the key determinants of the popularity of politicians is keeping election pledges, which promises voters’ satisfaction and ensures their backing for those in power. Economic slowdowns and social and political crises are the most challenging periods in terms of retaining or boosting popularity. To face up to such dire circumstances, authorities seek to pass through drastic reforms affecting either all or some selected groups of voters. Based on Polish examples, the empirical studies presented herein demonstrate such strategies of governance and the creation of such electoral political messages that help maintain the popularity of the government or, at least, materially alleviate the negative consequences of introduced, yet unpopular reforms. The strategies rest upon regularities derived from the prospect theory concerning the linking of negative events in the minimizing of dissatisfaction and the separation of positive events in the maximizing of satisfaction. The investigated hypothesis covers the internal consistency of different but negative information about unpopular reforms. For it is not enough to combine negative events with a view to reducing the negative emotions in political messages. The effect of such a reduction will only be guaranteed when the linked events are perceived as consistent by voters.
Exploiting self-modification mechanism for program protection

In this paper, we present a new method to protect software against illegal acts of hacking. The key idea is to add a mechanism of self-modifying codes to the original program, so that the original program becomes hard to be analyzed. In the binary program obtained by the proposed method, the original code fragments we want to protect are camouflaged by dummy instructions. Then, the binary program autonomously restores the original code fragments within a certain period of execution, by replacing the dummy instructions with the original ones. Since the dummy instructions are completely different from the original ones, code hacking fails if the dummy instructions are read as they are. Moreover, the dummy instructions are scattered over the program, therefore, they are hard to be identified. As a result, the proposed method helps to construct highly invulnerable software without special hardware.
An instructional approach to drive computer science courses through virtual learning environments

Nowadays, many universities have adopted Virtual Learning Environments for delivering and distributing educational resources. In the context of Computer Science (CS) courses, the use of these environments addresses several issues ranging from the application of instructional strategies to the selection of the most adequate learning platform. In this work, we propose an instructional approach to drive CS courses through virtual learning environments. The concept of driving a CS course adds a pedagogical value to the classical approach delivering educational resources. This pedagogical value is supported by applying instructional methods based on pedagogical patterns to design specific components of CS courses. The use of these pedagogical patterns helps to guide the deployment of Virtual Learning Environments (VLE) in CS courses enabling a connection between the course requirements and the VLE features. We have evaluated the proposed approach using an example of VLE called Poliformat. The evaluation focuses on the platform role as the road to drive Operating System courses during the 2005-06, 2006-07 and 2007-08 academic years. The evaluation results have contributed to a better understanding of how virtual learning environments can be used in CS courses and they confirm the benefits of applying instructional based approaches.
A proposed checklist for the technical maturity of open government data: an application on GCC countries

Open Government Data (OGD) initiatives and more specifically OGD portals have increased rapidly worldwide since the late 2000's, including the Gulf Cooperation Council (GCC) countries. A comprehensive analysis of the capabilities and potential of these initiatives particularly for the GCC members from a technical perspective is currently missing from existing research literature. To address this gap, this paper aims at assessing the technical maturity of OGD Portals for each of the six countries of the GCC through investigating their services and characteristics. Our study results illustrate the current technical quality of the surveyed portals and spotlight the work that needs to be done to reach a full technical maturity in order to make public data truly open and readily available for citizens, researchers, and innovation in general.
Data independent visual vocabulary

In this paper we present a novel method of generating visual vocabulary. Unlike traditional methods, where the visual vocabulary is generated from very specific image data, we use an analytic generative mechanism that is independent of training data. The motivation behind generating data-independent visual vocabulary is due to its usage in distributed applications. It is necessary to use a common, fixed visual vocabulary for multiple, dynamically changing image repositories, which may need to share data and support remote queries. Generating visual vocabulary in itself is time consuming job, as it requires capturing data and clustering high dimensional data. The advantage of using a data-independent visual vocabulary eases the design of Net Centric computing system for image and video retrieval. We have examined large number of visual vocabularies generated from various data set such as Caltech, Pascal, Correll and worked out approximation model for visual vocabulary. Experimental results shows that our visual vocabulary outperforms the domain specific visual vocabularies. We empirically conclude that our visual vocabulary suits the requirement of Net Centric applications.
Supervised Template Estimation for Document Image Decoding

An approach to supervised training of character templates from page images and unaligned transcriptions is proposed. The template training problem is formulated as one of constrained maximum likelihood parameter estimation within the document image decoding framework. This leads to a three-phase iterative training algorithm consisting of transcription alignment, aligned template estimation (ATE), and channel estimation steps. The maximum likelihood ATE problem is shown to be NP-complete and, thus, an approximate solution approach is developed. An evaluation of the training procedure in a document-specific decoding task, using the University of Washington UW-II database of scanned technical journal articles, is described.
Facial Expression Feature Extraction Based on FastLBP

The methods of facial expression feature extraction based on traditional LBP have some drawbacks such as complexity, high dimension of feature vectors, which may reduce the efficiency of subsequent recognition process. To solve the above problems, this paper proposes an improved LBP algorithm——FastLBP(FLBP). FLBP compresses the feature vectors described by LBP histogram to decrease the complexity of the algorithm. This method increases the efficiency of training and testing in facial expression recognition and ensures the accuracy of recognition at the same time. The experimental results show that FLBP proposed by this paper is fast and effective.
Analysis of Robust Implementation of an EMG Pattern Recognition based Control

Control of active hand prostheses is an open challenge. In fact, the advances in mechatronics made available prosthetic hands with multiple active degrees of freedom; however the predominant control strategies are still not natural for the user, enabling only few gestures, thus not exploiting the prosthesis potential. Pattern recognition and machine learning techniques can be of great help when applied to surface electromyography signals to offer a natural control based on the contraction of muscles corresponding to the real movements. The implementation of such approach for an active prosthetic system offers many challenges related to the reliability of data collected to train the classification algorithm. This paper focuses on these problems and propose an implementation suitable for an embedded system.
The Usefulness of an Accelerometer for Monitoring Total Energy Expenditure and Its Clinical Application for Predicting Body Weight Changes in Type 2 Diabetic Korean Women

Background The purpose of this study was to evaluate the usefulness of an accelerometer in predicting body weight (BW) change during a lifestyle intervention and to find out whether exercise or overall physical activity is associated with change in insulin sensitivity and body composition. Methods A total of 49 overweight (body mass index [BMI] ≥ 23 kg/m2) women with diabetes were enrolled and performed lifestyle intervention while monitoring BW, total energy expenditure (TEE) and physical activity energy expenditure (PAEE) using an accelerometer, and energy intake (EI) using a three-day dietary record at baseline and every 2 weeks for 12 weeks. We assessed body composition using bioimpedance analysis and compared the actual BW change to the predicted BW change, which was calculated from the energy deficit (ED) between EI and TEE (ED = EI-TEE). Results Mean age was 57.2 years, duration of diabetes was 8.0 years, and BMI was 27.8 kg/m2. There was no significant difference between EI and TEE at baseline. For 12 weeks, the ED was 474.0 kcal·day-1, which was significantly correlated with BW change (-3.1 kg) (r = 0.725, P < 0.001). However, the actual BW change was 50% lower than the predicted BW change. Both TEE and PAEE correlated with change in KITT (r = 0.334, P = 0.019; r = 0.358, P = 0.012, respectively), BMI (r = -0.395, P = 0.005; r = -0.347, P = 0.015, respectively), and fat mass (r = -0.383, P = 0.007; r = -0.395, P = 0.005, respectively), but only TEE correlated with fat free mass change (r = -0.314, P = 0.030). Conclusion The accelerometer appears to be a useful tool for measuring TEE under free-living conditions for both short- and long-term periods.
A new on-demand routing algorithm based on nodes' locations for MANET

Mobile ad-hoc network (MANET) is a dynamic and autonomous network composed of wireless mobile hosts or nodes. It is significant that running an on-demand routing protocol with bandwidth assurance in MANET. This paper presents a new on-demand routing algorithm LABGR (location-aided bandwidth guaranteed routing), which is based on nodes' physical locations. The algorithm unifies route stability and nodes' limited energy, and by using constrained diffusing routing and utilizing multi mechanisms to avoid flooding in whole network, it also limits the number of nodes affected during routing request. Hence, the algorithm efficiently increases the efficiency of routing request and guarantees the bandwidth of links. Finally, the paper analyzes the characteristics of LABGR.
Grapheme-to-Phoneme Conversion of Arabic Numeral Expressions for Embedded TTS Systems

Despite the increasing need for accuracy, current text-to-speech (TTS) systems are still poor at generating the correct pronunciation of Arabic numerals due to their high ambiguity and various interpretations. In this paper, we propose a mini-transliteration system for Arabic-numeral expressions, which can efficiently and correctly convert Arabic numeral expressions found in Korean text into phonemes for embedded TTS systems. For the purpose of building grapheme-to-phoneme rules, we deduced the components of ANEs, and investigated their pattern and arithmetic features based on the analyzed corpus. A word sense disambiguation based on lexical hierarchies in KorLex 1.0 was developed to resolve ambiguities caused by the homographic components of the ANEs. Our system minimized the amount of memory used by 1) separating the morphological analysis module from the transliteration system, 2) compacting the lexicon size, and 3) removing named entities. It reduced the process time dramatically without any serious loss of accuracy, and showed an accuracy of 97.2%-98.3%, which was 21.4%-22.5% higher than that of the baseline, and 5.5%-19.5% higher than current commercial Korean TTS systems
The origins and evolution of links between word learning and conceptual organization: new evidence from 11‐month‐olds

How do infants map words to their meaning? How do they discover that different types of words (e.g. noun, adjective) refer to different aspects of the same objects (e.g. category, property)? We have proposed that (1) infants begin with a broad expectation that novel open-class words (both nouns and adjectives) highlight commonalities (both category- and property-based) among objects, and that (2) this initial expectation is subsequently fine-tuned through linguistic experience. We examine the first part of this proposal, asking whether 11-month-old infants can construe the very same set of objects (e.g. four purple animals) either as members of an object category (e.g. animals) or as embodying a salient object property (e.g. four purple things), and whether naming (with count nouns vs. adjectives) differentially influences their construals. Results support the proposal. Infants treated novel nouns and adjectives identically, mapping both types of words to both category- and property-based commonalities among objects.
Bonobo Food Items, Food Availability and Bonobo Distribution in the Lake Tumba Swampy Forests, Democratic Republic of Congo

Data on food items were collected from the Lac Tumba Swampy Forests (LTSF) with the objective to gauge the effect of food type and availability on the distribution of the bonobos. Bonobos at the LTSF feed on at least 61 plant species and eat more Terrestrial Herbaceous Vegetation (THV) than at other sites (t = 0.676, df = 3, p = 0.548 > 0.05; in- significant). Fruits were available for most of the year at sites within the LTSF. At the Mbou-Mon-Tour (MMT), a site with higher bonobo density, the mean density of 1.42 fruits/m 2 per month (range 0.62 - 3.82 fruits/m 2 per month) was re- corded, higher than in other sites where bonobos occur (general univariate linear model � = 0.422, t = 1.543, df = 11, p = 0.151, non-significant). In-site differences between MMT and other sub-sites in the LTSF were significant (t = 2.793, df = 12, p = 0.016 < 0.05). Fruit abundance in the LTSF ( X =138 fruits/km, SD = 13.80) was higher than in the Salonga Na- tional Park (SNP) ( X =83 fruits/km, SD = 6.49). There were five species of THV in the LTSF, with the most abundant being Megaphrynium macrostachyum (41.18%), which was scarce in the Lomako Forests. Comparisons between sites in- dicated that sites in SNP consistently had lower stem densities than sites in LTSF (t = -7.528, df = 3, p =0.005, signifi- cant). These results, in agreement with previous studies, concluded that the distribution of THV in different sites signifi- cantly determined the bonobo distribution.
The Virtual Trial

Although brain network analysis in neurodegenerative disease is still a fairly young discipline, expectations are high. The robust theoretical basis, the straightforward detection and explanation of otherwise intangible complex system phenomena, and the correlations of network features with pathology and cognitive status are qualities that show the potential power of this new instrument. We expect “connectomics” to eventually better explain and predict that essential but still poorly understood aspect of dementia: the relation between pathology and cognitive symptoms. But at this point, our newly acquired knowledge has not yet translated into practical methods or applications in the medical field, and most doctors regard brain connectivity analysis as a wonderful but exotic research niche that is too technical and abstract to benefit patients directly. This article aims to provide a personal perspective on how brain connectivity research may get closer to obtaining a clinical role. I will argue that network intervention modeling, which unites the strengths of network analysis and computational modeling, is a great candidate for this purpose, as it can offer an attractive test environment in which positive and negative influences on network integrity can be explored, with the ultimate aim to find effective countermeasures against neurodegenerative network damage. The virtual trial approach might become what both dementia and connectivity researchers have been waiting for: a versatile tool that turns our growing connectome knowledge into clinical predictions.
SynProt: A Database for Proteins of Detergent-Resistant Synaptic Protein Preparations

Chemical synapses are highly specialized cell–cell contacts for communication between neurons in the CNS characterized by complex and dynamic protein networks at both synaptic membranes. The cytomatrix at the active zone (CAZ) organizes the apparatus for the regulated release of transmitters from the presynapse. At the postsynaptic side, the postsynaptic density constitutes the machinery for detection, integration, and transduction of the transmitter signal. Both pre- and postsynaptic protein networks represent the molecular substrates for synaptic plasticity. Their function can be altered both by regulating their composition and by post-translational modification of their components. For a comprehensive understanding of synaptic networks the entire ensemble of synaptic proteins has to be considered. To support this, we established a comprehensive database for synaptic junction proteins (SynProt database) primarily based on proteomics data obtained from biochemical preparations of detergent-resistant synaptic junctions. The database currently contains 2,788 non-redundant entries of rat, mouse, and some human proteins, which mainly have been manually extracted from 12 proteomic studies and annotated for synaptic subcellular localization. Each dataset is completed with manually added information including protein classifiers as well as automatically retrieved and updated information from public databases (UniProt and PubMed). We intend that the database will be used to support modeling of synaptic protein networks and rational experimental design.