Miracle-dz/UniFAR-FTUs huggingface dataset:
A hybrid evolutionary approach with search strategy adaptation for mutiobjective optimization

Hybrid evolutionary algorithms have been successfully applied to solve numerous multiobjective optimization problems (MOP). In this paper, a new hybrid evolutionary approach based on search strategy adaptation (HESSA) is presented. In HESSA, the search process is carried out through adopting a pool of different search strategies, each of which has a specified success ratio. A new offspring is generated using a randomly selected strategy. Then, according to the success of the generated offspring to update the population or the archive, the success ratio of the selected strategy is adapted. This provides the ability for HESSA to adopt the appropriate search strategy according to the problem on hand. Furthermore, the cooperation among different strategies leads to improve the exploration and the exploitation of the search space. The proposed pool is combined to a suitable evolutionary framework for supporting the integration and cooperation. Moreover, the efficient solutions explored over the search are collected in an external repository to be used as global guides. The proposed HESSA is verified against some of the state of the art MOEAs using a set of test problems commonly used in the literature. The experimental results indicate that HESSA is highly competitive and can be considered as a viable alternative.
Time Profiles for Identifying Users in Online Environments

Many people who discuss sensitive or private issues on web forums and other social media services are using pseudonyms or aliases in order to not reveal their true identity, while using their usual accounts when posting messages on nonsensitive issues. Previous research has shown that if those individuals post large amounts of messages, stylometric techniques can be used to identify the author based on the characteristics of the textual content. In this paper we show how an author's identity can be unmasked in a similar way using various time features, such as the period of the day and the day of the week when a user's posts have been published. This is demonstrated in supervised machine learning (i.e., author identification) experiments, as well as unsupervised alias matching (similarity detection) experiments.
Preface Benefits and Limitations of Continuous Representations of Emotions in Affective Computing : Introduction to the Special Issue

Affective computing (Picard, 1997) has witnessed tremendous progress over the past decade, in all four of its core areas: recognition of human emotions by machines, affective user modeling, modeling of emotions in agent architectures, and expression of emotions in virtual agents and robots (Gunes & Pantic, 2010; Hudlicka, 2011a). Thus far, affective computing can best be characterized as an engineering discipline. A number of methods, techniques, algorithms and architectures have been developed in all four of the core areas. These have enabled achievements in emotion recognition that are beginning to approach human performance (Gunes et al. 2003), which integrate techniques from multiple areas of affective computing. Advancement in affective computing techniques has also given rise to a distinct subfield in game development: Yet in spite of these successes, the field still lacks firm theoretical foundations and systematic guidelines in many areas, particularly so in emotion modeling (Broekens, 2010): the construction of computational models of emotion generation and emotion effects, both as standalone models and as models integrated in agent architectures. This is in large part due to the difficulties associated with developing theoretical explanatory frameworks for emotions and affective phenomena in general, as well as the difficulties in obtaining the necessary empirical data about transient, multi-modal affective states (Hudlicka, 2011a). Recent developments in the field have contributed to an integrated effort to transition affective computing into a more scientific discipline (e.g., Broekens et al., 2008). This is evidenced by an increased emphasis on comparing and validating existing emotion models (categorical vs. dimensional models), with the aim of developing systematic guidelines for affective modeling (e.g., Hudlicka, 2011a; Broekens & Hudlicka, 2009), creating frameworks that use these models for automatic analysis (e.g., Nicolaou et al., 2011a, 2011b) and synthesis purposes (see Gunes et al. 2011, for a review), and in attempts to develop standards in the form of affective markup languages, e.g., EmotionML (Schröder et al., 2011), and open source development frameworks and tools, An important component of this effort is the increased interest in understanding the relative benefits and drawbacks of alternative theoretical perspectives on emotions, and the associated representations. Three dominant theoretical perspectives on emotions have emerged in affective computing: discrete / categorical, dimensional, and componential. In emotion modeling, emphasis has been on the use of cognitive appraisal as a means of generating emotions in agents, with the majority of models using the Ortony, Clore, and Collins theory (OCC) (Ortony …
New approach for testing dynamic balance and motion feasibility of humanoids in presence of multiple spatial contacts *

Besides the contacts between the feet and the ground, in some cases motion of humanoids may require additional contacts with environment. When spatial distribution of contacts is needed in order to perform planned motion, decision where the next contact will be established may be of fundamental importance. To ensure that planned motion will be feasible and dynamically balanced, all contacts with environment should remain sustained. However, the main indicator of dynamical balance, the ZMP, is only applicable to the robots walking on flat horizontal surfaces. For that reason, method for testing dynamical balance when contacts are distributed spatially will be presented. To do so, constraints on all contact wrenches are written in the form of Composite Dynamic Balance Matrix. Based on that, condition which can tell if desired motion is feasible or not, is derived. Those conditions are in form of inequalities and maintaining them satisfied is of highest importance. For synthesizing whole body motion where robot has to fulfill several tasks (in form of equalities and inequalities), generalized task prioritization framework could be used.
Two MHC Class I Molecules Associated with Elite Control of Immunodeficiency Virus Replication, Mamu-B*08 and HLA-B*2705, Bind Peptides with Sequence Similarity12

HLA-B27- and -B57-positive HIV-infected humans have long been associated with control of HIV replication, implying that CD8+ T cell responses contribute to control of viral replication. In a similar fashion, 50% of Mamu-B*08-positive Indian rhesus macaques control SIVmac239 replication and become elite controllers with chronic-phase viremia <1000 viral RNA copies/ml. Interestingly, Mamu-B*08-restricted SIV-derived epitopes appeared to match the peptide binding profile for HLA-B*2705 in humans. We therefore defined a detailed peptide-binding motif for Mamu-B*08 and investigated binding similarities between the macaque and human MHC class I molecules. Analysis of a panel of ∼900 peptides revealed that despite substantial sequence differences between Mamu-B*08 and HLA-B*2705, the peptide-binding repertoires of these two MHC class I molecules share a remarkable degree of overlap. Detailed knowledge of the Mamu-B*08 peptide-binding motif enabled us to identify six additional novel Mamu-B*08-restricted SIV-specific CD8+ T cell immune responses directed against epitopes in Gag, Vpr, and Env. All 13 Mamu-B*08-restricted epitopes contain an R at the position 2 primary anchor and 10 also possess either R or K at the N terminus. Such dibasic peptides are less prone to cellular degradation. This work highlights the relevance of the Mamu-B*08-positive SIV-infected Indian rhesus macaque as a model to examine elite control of immunodeficiency virus replication. The remarkable similarity of the peptide-binding motifs and repertoires for Mamu-B*08 and HLA-B*2705 suggests that the nature of the peptide bound by the MHC class I molecule may play an important role in control of immunodeficiency virus replication.
Primal Leadership: Realizing the Power of Emotional Intelligence- A Book Review

The book Primal Leadership was written by Daniel Goleman and his colleagues Richard Boyatzis and Annie McKee. Together they draw information and experiences from different educational disciplines and backgrounds. The book evolved from responses of people to two articles in Harvard Business Review of the titles ‘What Makes a Leader’ and ‘Leadership That Gets Results’. The authors provide totally different perspectives on the leadership discourse that speaks to the importance of emotional intelligence that drives great leaders. The book builds on links to neurology and break through in brain research that shows how as leaders our moods and actions whether good or bad have enormous impact on the people we lead. Good leaders are not just focused on visions, dreams, targets, and performance, but recognize the importance of also being emotionally intelligent. The most important task of a leader is to generate a good feeling among the people he/she leads, which creates resonance and brings out the best in people.
On the complexity of sphere decoding in digital communications

Sphere decoding has been suggested by a number of authors as an efficient algorithm to solve various detection problems in digital communications. In some cases, the algorithm is referred to as an algorithm of polynomial complexity without clearly specifying what assumptions are made about the problem structure. Another claim is that although worst-case complexity is exponential, the expected complexity of the algorithm is polynomial. Herein, we study the expected complexity where the problem size is defined to be the number of symbols jointly detected, and our main result is that the expected complexity is exponential for fixed signal-to-noise ratio (SNR), contrary to previous claims. The sphere radius, which is a parameter of the algorithm, must be chosen to ensure a nonvanishing probability of solving the detection problem. This causes the exponential complexity since the squared radius must grow linearly with problem size. The rate of linear increase is, however, dependent on the noise variance, and thus, the rate of the exponential function is strongly dependent on the SNR. Therefore sphere decoding can be efficient for some SNR and problems of moderate size, even though the number of operations required by the algorithm strictly speaking always grows as an exponential function of the problem size.
FORMATION OF ORDERED ZnO STRUCTURES GROWN BY THE ALD METHOD ON HYBRID SiC / Si ( 100 ) SUBSTRATES

Crystalline structure and composition of the ZnO films grown by atomic layer deposition (ALD) on the nand p-type Si (100) substrates with a SiC buffer layer were studied. The SiC buffer layers have been synthesized by a novel method of atomic substitution (partial chemical replacement) of Si atoms by carbon atoms in the subsurface layer of the Si substrate. A four-component epitaxial texture of ZnO in a direction close to [101] on the nand p-type (100) Si vicinal substrates with a SiC buffer layer has been revealed and investigated with electron diffraction. Formation mechanism of the epitaxial textures of ZnO was found to depend on the conductivity type (nor p-type) of the Si (100) substrates. A theoretical model explaining the effect of the texture formation and its dependence on the type of Si substrate conductivity has been proposed. The effect is associated with the transformation of the vicinal Si (100) surfaces into the SiC surfaces during its synthesis by the atomic substitution method. Significant differences have been found between the structures and between the growth mechanisms of the ZnO layers on the SiC/Si (111) and (100) substrates.
Changes in Expression Pattern of Selected Endometrial Proteins following Mesenchymal Stem Cells Infusion in Mares with Endometrosis

Mesenchymal stem cells (MSCs) due to their self-renewal potential and differentiation capacity are useful for tissue regeneration. Immunomodulatory and trophic properties of MSCs were demonstrated suggesting their use as medicinal signaling cells able to positively change local environment in injured tissue. Equine endometrosis is a progressive degenerative disease responsible for glandular alterations and endometrial fibrosis which causes infertility in mares. More precisely, this disease is characterized by phenotypic changes in the expression pattern of selected endometrial proteins. Currently, no effective treatment is available for endometrosis. Herein, we aimed at the evaluation of expression pattern of these proteins after allogeneic equine adipose tissue-derived multipotent mesenchymal stem cells (eAT-MSCs) infusion as well as at testing the capacity of these cells to promote endometrial tissue remodeling in mares with endometrosis. eAT-MSC (2×107/animal) were transplanted into mares’ uterus and control animals received only placebo. Uterine biopsies were collected before (day 0) and after (days 7, 21 and 60) cells transplantation. Conventional histopathology as well as expression analysis of such proteins as laminin, vimentin, Ki-67-antigen, α-smooth muscle actin (α-SMA) and cytokeratin 18 (CK18) have been performed before and after eAT-MSCs transplantation. We demonstrated that eAT-MSCs induced early (at day 7) remodeling of endometrial tissue microenvironment through changes observed in intra cellular and intra glandular localization of aforementioned proteins. We demonstrated that eAT-MSCs were able to positively modulate the expression pattern of studied secretory proteins as well as, to promote the induction of glandular epithelial cells proliferation suggesting local benefits to committed endometrial tissue environment after eAT-MSCs transplantation.
Path-based routing provisioning with mixed shared protection in WDM mesh networks

In this paper, the authors focus on studying the problem of survivable routing provisioning to prevent single link failure in wavelength-division-multiplexing (WDM) mesh networks, and propose a novel protection scheme called mixed shared path protection (MSPP). With MSPP, the authors define three types of resources: 1) primary resources that can be used by primary paths; 2) spare resources that can be shared by backup paths; and 3) mixed resources that can be shared by both the primary and the backup paths. In the proposed protection scheme, each connection is assigned a primary path and a link disjoint backup path. Differing from pervious protection schemes, MSPP allows some primary paths and backup paths to share the common mixed resources if the corresponding constraints can be satisfied. In this paper, the authors consider three types of path-based protection schemes, i.e., dedicated path protection (DPP), shared path protection (SPP), and MSPP, and evaluate their performance for both the static and the dynamic provisioning problems. Simulation results show that MSPP outperforms DPP and SPP
A Model-Based Approach to Constructing Safe Soft Real-Time Programs for Non-Real-Time Environments

The primary goal of this work is to provide an easy and systematic way of developing safe soft real-time systems. To achieve this goal, we propose a method of generating real-time programs from formally verified models written as systems of timed automata. The models are verified using UPPAAL model checker prior to be processed by our code generators. A characteristic of our code generator is that the generated code runs in a non-real-time environment, i.e., a runtime environment without inherent real-time schedulers. To realize this, the code generator weaves timing checking code fragments within the generated programs. The generated code explicitly checks the real-time clock of its runtime to obey the timing constraints specified in the model. In this paper, we describe how to generate Java/C programs from UPPAAL timed automata and show the benefits of our method using a robot controller case study.
Reviews Analysis Based on Sentence and Word Relevance

Assuming that one sentence in review expresses one opinion, LDA based on sentence is performed to analysis the massive online reviews. When computing the topic's word, word relevance measure is designed which penalizes the word frequency by a factor that captures how much the word is shared across topics, words for topics can been selected more accurately. Experiments on massive review crawled from network show that the result of analyzing is better than the standard LDA, there is clearer topic cue, and recognition is improved among the topics.
Exploring the Academic English Socialization of International Graduate Students in Taiwan

Through 24 semi-structured interviews with non-native English-speaking (NNES) international graduate students, this study explores their academic English socialization experiences in Taiwan guided by Lave and Wenger’s (1991) community of practice framework and Lee and Rice’s (2007) concept of neo-racism. Throughout a complicated academic English socialization process, newcomers became increasingly competent in communicating with the university community in English. However, this process was not unproblematic; challenges included differential welcome and treatment, a relative lack of interaction with Taiwanese peers or students outside their own ethnic groups, and negative perceptions of their accents and non-fluent English. Findings suggest a need to stimulate deeper reflection on international students’ experiences in host communities, where they are increasingly the targets of nationality-based discrimination.
Endogenous Matching and the Empirical Determinants of Contract Form

Empirical work on contracts typically regresses contract choice on observed principal and agent characteristics. If (i) some of these characteristics are unobserved or partially observed and (ii) there are incentives whereby particular types of agents end up contracting with particular types of principals, estimated coefficients on the observed characteristics may be misleading. We address this endogenous matching problem using a data set on agricultural contracts between landlords and tenants in early Renaissance Tuscany. Controlling for endogenous matching has an impact on parameters of interest, and tenants’ risk aversion appears to have influenced contract choice.
Zig-zag diffusion of pentamer on (110) surface

In this work we investigate the diffusion of Cu pentamer island on Ag(110). The problem is studied using molecular dynamics simulation based on embedded atom method. It was shown that the anisotropic geometry of (110) surface gave preferential occurrence to the diffusion via zig-zag process. In this context, we have calculated the activation energy corresponding to this mechanism which has been found to be 0.47eV. However, the pentamer shape showed also a transition from (3D) to (2D) geometry.
Horizontal Mergers with Free-Entry: Why Cost Efficiencies May Be a Weak Defense and Asset Sales a Poor Remedy

I analyze the effects of a merger between two firms in a differentiated-goods duopoly. I make the crucial assumption that the industry is at a free-entry equilibrium both before and after the merger. In particular, I allow for the possibility of entry subsequent to the merger. Not surprisingly, this possibility improves the effect of the merger on consumer welfare. In fact, for reasonable parameter values, I show that consumer welfare may actually increase as a result of the merger. More importantly, I show that post-merger entry dramatically shifts the perspective on cost efficiencies as a merger defense and asset sales as a remedy. Post-merger consumer welfare may be lower when the efficiencies generated by the merger (lower marginal cost) are greater. The reason is that greater efficiency gains decrease the probability of post-merger entry to an extent that may outweigh the beneficial effects from cost-savings passed on to consumers. Likewise, by selling stores to their rival, merging firms effectively "buy off" the potential entrant, that is, dissuade it from opening new stores, an effect that is detrimental to consumers.
P o S ( M R U ) 0 4 1 UHE particle astrophysics with the SKA

The Lunar Cherenkov technique is a method to detect ultra-hi gh energy (UHE) cosmic rays and neutrinos. It involves observing the Moon with ground-base d radio-telescopes to identify pulses of coherent Cherenkov radiation from such particles intera cting near the lunar surface. Initially devised to solve the mystery of the origin of the highest-ene rgy cosmic rays, fluxes of UHE neutrinos are predicted from AGN, topological defects, and UHE cosmic ray interactions. Successful detection or otherwise would provide great insight into t hese exotic phenomena, with the possibility of new physics at energies inaccessible to terrestri al particle accelerators. This contribution describes the current state of observations, and why the cha ra teristics of the SKA will make it the most powerful instrument for performing UHE particle as tronomy.
Multiple antenna spectrum sensing in cognitive radios

In this paper, we consider the problem of spectrum sensing by using multiple antenna in cognitive radios when the noise and the primary user signal are assumed as independent complex zero-mean Gaussian random signals. The optimal multiple antenna spectrum sensing detector needs to know the channel gains, noise variance, and primary user signal variance. In practice some or all of these parameters may be unknown, so we derive the generalized likelihood ratio (GLR) detectors under these circumstances. The proposed GLR detector, in which all the parameters are unknown, is a blind and invariant detector with a low computational complexity. We also analytically compute the missed detection and false alarm probabilities for the proposed GLR detectors. The simulation results provide the available traded-off in using multiple antenna techniques for spectrum sensing and illustrates the robustness of the proposed GLR detectors compared to the traditional energy detector when there is some uncertainty in the given noise variance.
Design and Development of Fuzzy Sliding Modefor Series-Parallel HEV

Global warming is a major problem in the modern world has been facing at the present time. Hybrid Electrical Vehicle (HEV) provides significant solution to this. The control objective of minimizing of the fuelconsumption and exhaust emission in hybrid electric vehicle(HEV) has generally been achieved by a supervisory controller.The drivability and NVH of HEV especially during modechanges, on the other hand, have drawn significant attention inrecent years. The basics of design principle have been used for sizing its elements to meet the proposed specifications of the vehicle and its driving cycle.In this paper, for the purpose of control simulation,anHEV including a slipping clutch is firstdeveloped. A robust control strategy based on fuzzy sliding modecontrol (FSMC) technique is then proposed for smooth modechanges of HEV. Simulation results demonstrate that smoothand fast transition from pure electric driving to hybrid drivingcan be achieved by controlling the integrated starter generator(ISG). The FSMC smoothing controller, along with a rulebasedsupervisory controller, is robust against modeling uncertaintiesin the vehicle mass and the friction coefficient of the clutch. KeywordsHybrid Electric Vehicle, Series and Parallel Hybrid ElectricsVehicle, Current Source Inverter, Brushless DC Motor converter