Miracle-dz/UniFAR-FTUs huggingface dataset:
Destination image differences between first-time and return visitors: An exploratory study on the city of Rome

This study aims to analyse the image of the city of Rome held by first-time and return visitors, and the influence of such an image on tourist behaviour. First, we measure the cognitive and the affective image of Rome; second, we analyse whether tourists’ previous experiences in the city significantly influence the components of Rome’s perceived image; and finally, we examine the extent to which cognitive and affective images are valid predictors of tourist behavioural intentions. The objectives are pursued through quantitative analyses conducted on 312 questionnaires compiled by national and international visitors of the city. Based on the results, the study confirms the previous literature on the topic while adding some further evidence. Moreover, different managerial implications are proposed.
Bayesian GMM ∗

In this paper, I study a semiparametric Bayesian method for over-identified moment condition models. A mixture of parametric distributions with random weights is used to flexibly model an unknown data generating process. The random mixture weights are defined by the exponential tilting projection method to ensure that the joint distribution of the data distribution and the structural parameters are internally consistent with the moment restrictions. In this framework, I make several contributions to Bayesian estimation and inference, as well as model specification. First, I develop simulation-based posterior sampling algorithms based on Markov chain Monte Carlo (MCMC) and sequential Monte Carlo (SMC) methods. Second, I provide a method to compute the marginal likelihood and use it for Bayesian model selection (moment selection) and model averaging. Lastly, I extend the scope of Bayesian analysis for moment condition models. These generalizations include dynamic moment condition models with time-dependent data and moment condition models with exogenous dynamic latent variables.
THE INFLUENCE OF ROMANTIC ATTACHMENT STYLES AND IMAGINED PARTNER REJECTION ON FEMALE BODY IMAGE

The purpose of this research was to examine how attachment style and rejection interact to influence female body image. I hypothesized that women who were high in attachment anxiety would report more negative self-evaluations than women who were low in attachment anxiety. I also hypothesized that this main effect would be qualified by a significant interaction between attachment anxiety and rejection, such that highly anxious women who were rejected would report even more negative self-evaluations than highly anxious women who were not rejected. In Study One, I found that higher levels of attachment anxiety were associated with lower self-evaluations but, contrary to expectations, attachment avoidance and rejection condition interacted to influence selfevaluations. At low levels of avoidance, women in the rejection condition reported significantly higher levels of appearance state self-esteem, body esteem, and trait selfesteem than women in the non-rejection condition. However, at high levels of avoidance, women in the rejection condition reported lower levels of these three constructs than women in the non-rejection condition, although this finding was statistically significant only for appearance state self-esteem. In Study Two, my goal was to replicate and extend these unexpected findings by examining perceived partner regard and public selfawareness as potential mediators of the interaction between avoidance and rejection on self-evaluations. Although a main effect of attachment anxiety was revealed for each of the dependent measures, contrary to Study One and my hypotheses, attachment avoidance and rejection did not interact to influence any of the self-evaluation measures and, thus, no mediational analyses were performed. Importantly, I discovered that even though participants‟ mean ratings of their body esteem did not change following the rejection
On the perception of band-limited phase distortion in natural scenes

It is widely believed that the phase spectrum of an image contributes much more to the image's visual appearance than the magnitude spectrum. Several researchers have also shown that this phase information can be computed indirectly from local magnitude information, a theory which is consistent with the physiological evidence that complex cells respond to local magnitude (and are insensitive to local phase). Recent studies have shown that tasks such as image recognition and categorization can be performed using only local magnitude information. These findings suggest that the human visual system (HVS) uses local magnitude to infer global phase (image-wide phase spectrum) and thereby determine the image's appearance. However, from a signal-processing perspective, both local magnitude and local phase are related to global phase. Moreover, in terms of image quality, distorting the local phase can result in a severely degraded image. These latter facts suggest that the HVS uses both local magnitude and local phase to determine an image's appearance. We conducted an experiment to quantify the contributions of local magnitude and local phase toward image appearance as a function of spatial frequency. Hybrid images were created via a complex wavelet transform in which the the low frequency magnitude, low frequency phase, high frequency magnitude, and high frequency phase were taken from 2-4 different images. Subjects were then asked to rate how much each of the 2-4 images contributed to the the appearance of the hybrid image. We found that local magnitude is indeed an important factor for image appearance; however, local phase can play an equally important role, and in some cases, local phase can dominate the image's appearance. We discuss the implication of these results in terms of image quality and visual coding.
Numerical estimation of electromagnetic backscattering from near-zone vehicles for the side-look vehicle-detection radar applications at millimeter waves

The development of vehicle-detection radar system has attracted much attention in recent years due to the increasing interest of smart car and traffic control applications [1, 2]. The success of such radar applications highly depend on reliable estimation of signal echo from the targets, which provide the information of target detection, vehicle identification, and the estimation of locations and speeds. In contrast to the conventional radar applications, where the targets are very far away from the antennas, the vehicles under detection are in the near zone. The detection highly depends on a proper use of antennas, in particular a proper radiation beamwidth for the target illumination. Since the radar detection is directly related to the electromagnetic (EM) backscattering, the estimation of various vehicles is apparently helpful to the radar system design. In this paper, we will present a full-wave numerical simulation over popular vehicle types including sedan and trucks, where the multi-level fast multipole method (MLFMM) of method of moment (MoM) is applied. The vehicles are assumed to be in the near zone of antennas, where the phased array antennas with various beamwidths are used to estimate the EM backscattering fields. To improve the detection accuracy, we also developed a moving signal average technique of signal estimation such that the influence of structure variation in a vehicle on the radar signals can be reduced. Thus in the presentation, the moving signal average method is also applied to the estimation of backscattering fields to exhibit their characteristics.
Reversal and transposition distance of linear chromosomes

In recent years we are seeing increasing interest in research on mutational events acting on large portions of chromosomes. Among these events, a reversal acts on a fragment of a chromosome, reversing the order and orientation of the genes, and a transposition moves fragments from one region to another within a chromosome. We analyze genomes evolving by reversals and transpositions. We present approximation algorithms to compute the reversal and transposition distance for linear permutations, and a lower bound on the reversal and transposition diameter of signed linear permutations.
Is machine learning losing the battle to produce transportable signatures against VoIP traffic?

Traffic classification becomes more challenging since the traditional techniques such as port numbers or deep packet inspection are ineffective against voice over IP (VoIP) applications, which uses non-standard ports and encryption. Statistical information based on network layer with the use of machine learning (ML) can achieve high classification accuracy and produce transportable signatures. However, the ability of ML to find transportable signatures depends mainly on the training data sets. In this paper, we explore the importance of sampling training data sets for the ML algorithms, specifically Genetic Programming, C5.0, Naive Bayesian and AdaBoost, to find transportable signatures. To this end, we employed two techniques for sampling network training data sets, namely random sampling and consecutive sampling. Results show that random sampling and 90-minute consecutive sampling have the best performance in terms of accuracy using C5.0 and SBB, respectively. In terms of complexity, the size of C5.0 solutions increases as the training size increases, whereas SBB finds simpler solutions.
Explorer BK channels affect glucose homeostasis and cell viability of murine pancreatic beta cells

Aims/hypothesis—Evidence is accumulating that Ca2+-regulated K+ (KCa) channels are important for beta cell function. We used BK channel knockout (BK-KO) mice to examine the role of these KCa channels for glucose homeostasis, beta cell function and viability. Methods—Glucose and insulin tolerance were tested with male wild-type and BK-KO mice. BK channels were detected by single-cell RT-PCR, cytosolic Ca2+ concentration ([Ca]c) by fura-2 fluorescence, and insulin secretion by radioimmunoassay. Electrophysiology was performed with the patch-clamp technique. Apoptosis was detected via caspase 3 or TUNEL assay. Results—BK channels were expressed in murine pancreatic beta cells. BK-KO mice were normoglycaemic but displayed markedly impaired glucose tolerance. Genetic or pharmacological deletion of the BK channel reduced glucose-induced insulin secretion from isolated islets. BK-KO and BK channel inhibition (with iberiotoxin, 100 nmol/l) broadened action potentials and abolished the after-hyperpolarisation in glucose-stimulated beta cells. However, BK-KO did not affect action potential frequency, the plateau potential at which action potentials start or glucoseinduced elevation of [Ca]c. BK-KO had no direct influence on exocytosis. Importantly, in BKKO islet cells the fraction of apoptotic cells and the rate of cell death induced by oxidative stress (H2O2, 10–100 μmol/l) were significantly increased compared with wild-type controls. Similar effects were obtained with iberiotoxin. Determination of H2O2-induced K+ currents revealed that BK channels contribute to the hyperpolarising K+ current activated under conditions of oxidative stress. Conclusions/interpretation—Ablation or inhibition of BK channels impairs glucose homeostasis and insulin secretion by interfering with beta cell stimulus–secretion coupling. In addition, BK channels are part of a defence mechanism against apoptosis and oxidative stress.
Perception-Guided Multimodal Feature Fusion for Photo Aesthetics Assessment

Photo aesthetic quality evaluation is a challenging task in multimedia and computer vision fields. Conventional approaches suffer from the following three drawbacks: 1) the deemphasized role of semantic content that is many times more important than low-level visual features in photo aesthetics; 2) the difficulty to optimally fuse low-level and high-level visual cues in photo aesthetics evaluation; and 3) the absence of a sequential viewing path in the existing models, as humans perceive visually salient regions sequentially when viewing a photo. To solve these problems, we propose a new aesthetic descriptor that mimics humans sequentially perceiving visually/semantically salient regions in a photo. In particular, a weakly supervised learning paradigm is developed to project the local aesthetic descriptors (graphlets in this work) into a low-dimensional semantic space. Thereafter, each graphlet can be described by multiple types of visual features, both at low-level and in high-level. Since humans usually perceive only a few salient regions in a photo, a sparsity-constrained graphlet ranking algorithm is proposed that seamlessly integrates both the low-level and the high-level visual cues. Top-ranked graphlets are those visually/semantically prominent graphlets in a photo. They are sequentially linked into a path that simulates the process of humans actively viewing. Finally, we learn a probabilistic aesthetic measure based on such actively viewing paths (AVPs) from the training photos that are marked as aesthetically pleasing by multiple users. Experimental results show that: 1) the AVPs are 87.65% consistent with real human gaze shifting paths, as verified by the eye-tracking data; and 2) our photo aesthetic measure outperforms many of its competitors.
Developing Self-Esteem and Empowerment through Expressive Computational Materials

We present a case study analysis of teacher empowerment and student learning through Constructionist engagement with computational technologies and learning about learning itself. Looking beyond how a teacher overcomes hesitations about new technologies, we consider how he redefines his own understandings of learning as he begins to use computational technologies in working alongside his students. The teacher’s emerging self-reflective practice and heightened selfesteem enable him to better understand the multifaceted structure of the learning situation and his own relations to its social, cognitive, and affective aspects.
South Korean Perspective on Learning Disabilities

In the context of the educational system and the nature of special education in South Korea, I describe policy, practice, and research about children with learning disabilities (LD). Recently, the study of LD has attracted professionals from multiple disciplines including general and special education, medicine, psychology, and social work. In Korea, the field of LD has developed rapidly over a brief period, but there are many problems to be solved in the near future. In particular, the field of LD in Korea lacks: (a) consensus about a conceptual definition, (b) a clear set of criteria for identifying students with LD, (c) lack of assessment instruments for identifying LD, and (d) general low understanding or misunderstanding of students with LD among teachers and parents.
Senior Chinese high school students' awareness of thematic and taxonomic relations in L1 and L2*

In the development of their semantic networks, bilinguals can be influenced by the levels of proficiency they have in their second language (L2) and by the age at which they acquired the language. Two exercises, one in word association and one in forced-choice decision-making, were used to test whether the pattern of relative awareness of thematic and taxonomic relations that senior Chinese high school students had in L2 differed from the pattern they had in their first language (L1). The results consistently indicated that (i) the participants appeared as aware of taxonomic relations in L2 as they were in L1; and (ii) they were more readily aware of thematic than of taxonomic relations in L1 but less readily aware of thematic than of taxonomic relations in L2. It was concluded that with taxonomic relations, low-proficiency bilinguals could have a common set of conceptual representations for both L2 and L1, as they are assumed in the revised hierarchical model (RHM) to have. With thematic associations, they might have more difficulty gaining access to their representations in L2 than they might have in L1.
Pattern-based design evolution using graph transformation

In recent years, design patterns gain more interest in software engineering communities for both software development and maintenance. As a template to solve a certain recurring problem, a design pattern documents successful experiences of software experts and gradually becomes the design guidelines of software development. Applying design patterns correctly can improve the efficiency of software design in terms of reusability and enhance maintainability during reverse engineering. Software can be evolved when developers modify their initial designs as requirements change. For instance, a developer may add/delete a set of design elements, such as classes and methods. Modifications on software artifacts can introduce conflicts and inconsistencies in the previously applied design patterns, which are difficult to find and time-consuming to correct. This paper presents a graph-transformation approach to pattern level design validation and evolution. Based on a well founded formalism, we validate a given design by a graph grammar parser and automatically evolve the design at pattern level using a graph-transformation system. Rules for potential pattern evolutions are predefined. The graph-transformation approach preserves the integrity and consistency of design patterns in the system when designs change. A prototype system is built and a case study on the Strategy pattern demonstrates the feasibility of pattern-based design validation and evolution using graph transformation techniques. Published by Elsevier Ltd.
A new integrated inductor with balanced switching technique for common mode EMI reduction in high step-up DC/DC converter

This paper proposes a new integrated inductor with balanced switching technique applied for high step-up converter. The advantage of the proposed converter is the reduction of the common mode conducted EMI using balanced switching technique. This step-up converter requires more magnetic components than that of the conventional converter. Therefore, the integrated magnetic technique is proposed to reduce two separated coupled inductors into a single core inductor. Finally, the good feature of proposed converter, by reducing common mode conducted EMI with small amount of inductors, is confirmed by the experimental results of a 50 W converter
Nonpromotion in Kindergarten: The Role of Cognitive, Perceptual, Visual-Motor, Behavioral, Achievement, Socioeconomic, and Demographic Characteristics

The role of cognitive, perceptual, visual-motor, behavioral, achievement, and demographic factors affecting nonpromotion at kindergarten was examined in a sample of 34 nonpromoted and 34 promoted kindergarten children of a suburban area in Northern California. The major findings of the study, part of a longitudinal follow-up study, indicated that retained students were more likely to be male, of younger age, and of lower socioeconomic status. In addition, retained students had lower IQ and preacademic achievement test scores and demonstrated increased problems in the areas of visual-motor integration, perceptual organization, and behavior. A discriminant analysis indicated that perceptual problems, inattention, age, preacademic reading achievement, and sex were factors that provided the maximum differentiation between retained and promoted students at the end of kindergarten. The findings are suggestive of interventions that may prove beneficial in preparing retained children for entry into first grade.
Mitogen-Activated Protein Kinase-Activated Protein Kinase 2 (MK2) Contributes to Secondary Damage after Spinal Cord Injury

The inflammatory response contributes importantly to secondary tissue damage and functional deficits after spinal cord injury (SCI). In this work, we identified mitogen-activated protein kinase (MAPK)-activated protein kinase 2 (MAPKAPK2 or MK2), a downstream substrate of p38 MAPK, as a potential target using microarray analysis of contused spinal cord tissue taken at the peak of the inflammatory response. There was increased expression and phosphorylation of MK2 after SCI, with phospho-MK2 expressed in microglia/macrophages, neurons and astrocytes. We examined the role of MK2 in spinal cord contusion injury using MK2−/− mice. These results show that locomotor recovery was significantly improved in MK2−/− mice, compared with wild-type controls. MK2−/− mice showed reduced neuron and myelin loss, and increased sparing of serotonergic fibers in the ventral horn caudal to the injury site. We also found differential expression of matrix metalloproteinase-2 and 9 in MK2−/− and wild-type mice after SCI. Significant reduction was also seen in the expression of proinflammatory cytokines and protein nitrosylation in the injured spinal cord of MK2−/− mice. Our previous work has shown that macrophages lacking MK2 have an anti-inflammatory phenotype. We now show that there is no difference in the number of macrophages in the injured spinal cord between the two mouse strains and little if any difference in their phagocytic capacity, suggesting that macrophages lacking MK2 have a beneficial phenotype. These findings suggest that a lack of MK2 can reduce tissue damage after SCI and improve locomotor recovery. MK2 may therefore be a useful target to treat acute SCI.
Application of Wavelet Transform in De-noising Geophysical Data

This paper presents a denoising scheme based on the wavelet transform for geophysical projecting data which are contaminated with various levels and types of local cultural noise which were responsible for hindering the valuable information obtained through shallow depth geophysical exploration of archaeological sites. Wavelet transform techniques were tested as a method for decomposing the original geophysical data in order to eliminate the noise levels inherent to the geophysical measurements. Unsupervised classification techniques were employed for the final fusion of different datasets originating from various surveys or processing procedures. The resulting images were able to enhance the subsurface targets, eliminating the noise levels and exploiting fully the properties of the geophysical techniques used. The scheme is particularly useful in minimizing the cultural noise as much as possible in order to allow the data to be interpreted accurately.
The influence of the steepness of dominance hierarchies on reciprocity and interchange in captive groups of bonobos (Pan paniscus)

Summary Biological market models explain variability in reciprocity and interchange between groups. In groups with a shallow dominance gradient, grooming will be mostly exchanged for itself (i.e. exchange will occur). In groups with steep dominance hierarchies, interchange is expected: individuals will groom higher ranking individuals to get access to limited resources or commodities such as support in conflicts, and grooming will be traded for these commodities. We examine patterns of reciprocity in grooming and support, and of interchange of grooming for support or for tolerance in six captive groups of bonobos. We test whether differences between groups in patterns of reciprocity and interchange can be attributed to differences in a measure of steepness of dominance hierarchies, which is based on dyadic agonistic interactions. We found that grooming was reciprocal in some, but not all groups. Support was highly reciprocal, but this was a side effect of dominance in most groups. Interchange between grooming and support was observed in some groups. Corroborating earlier findings, this was a side effect of individuals preferring high ranking individuals as grooming and support partners, possibly because these high-ranking individuals provide more efficient support in conflicts. There was no evidence for interchange of grooming for tolerance. Variability in grooming reciprocity was explained by differences in steepness of dominance hierarchies, as predicted by the biological market models. In groups with a shallow dominance hierarchy, grooming was more reciprocal. This was not true for reciprocity in