Miracle-dz/UniFAR-FTUs huggingface dataset:
Refugees in the Netherlands : Victims or Intruders ? The power of images in media coverage of the refugee crisis

While framing and framing effects theories of text media coverage are extensively studied, visual framing effects often receive less scholarly attention. This article uses the refugee crisis as a case study to test how different visual frames of refugees affect people’s emotions and attitudes towards refugees in the Netherlands. Furthermore, I test whether the attitudinal effect of visual frames is mediated by emotions. In an experimental design, participants were exposed to two visual frames that portray refugees either as victims or intruders, and then measured participants’ level of, empathy, hope, anger and fear as well as their attitude towards welcoming refugees into the Netherlands. Findings show that participants’ feelings of hope and empathy are significantly higher in the victim frame, while there are no significant differences in the emotions of fear and anger between the victim and the intruder frame. Results also show that visual frames have no significant effects on participants’ tolerance towards refugees coming to their country. The study found that empathy mediated the effect of the victim frame on participants’ tolerance levels, while anger, fear and hope did not have any mediating effects between visual frames and attitude. The findings of this study deepen our understanding of how visuals differ from textual framing in their effect on emotions and attitudes, and provide an opportunity to fill the gap in visual framing effect literature and the role of mediation in visual framing.
SMEs ’ innovation capacity assessment : a dedicated analysis of SMEs ’ innovation performance determinant factors

This study explores innovation capacity in the specific context of small and medium-sized enterprises (SMEs). Innovation capacity is particularly difficult to define in SMEs because most of their innovative activities are informal and merge into overall firm activities. The objective is to test the central dimensions of innovation capacity to propose insights for assessing the innovation capacity of SMEs. Our nine-dimension framework is built on theoretical insights from the entrepreneurship and innovation literature and is tested through a quantitative survey administered to a first sample of 213 SMEs. Those preliminary research will be completed with a second sample of 320 SMEs. Our preliminary findings discuss the nine critical dimensions of the innovation capacity of SMEs that have been previously emphasized in the literature; six dimensions appear to be significant in our model, whereas three other dimensions are not significant. These findings allow us to propose a new framework for analyzing the innovation capacity of SMEs that is based on SME specificities. We plan a second row of analysis based on the second sample. We would perform a factor analysis to discuss our 9 dimensions emerging from literature and propose a new model of SMEs innovation capacity
Exploring the Associations Between Personality and Subjective Well-Being

Decades worth of research on subjective well-being provides evidence for the idea that personality plays a strong role reports of positive affect, negative affect, and life satisfaction. Specifically, this research shows that subjective well-being, like personality traits themselves, is moderately stable over time and moderately heritable. In addition, some of the strongest correlates of well-being reports are personality traits like extraversion and neuroticism. In this chapter, I review evidence for the importance of personality in explaining subjective well-being, focusing both on the strengths and limitations of existing research and complexities in the interpretation of the empirical evidence that does exist. Ultimately, research on personality and well-being can be seen as a model for how research on other predictors of subjective wellbeing can proceed.
Forage Yield in some Iranian Wild Trifolium Genetic Resources under Different Climatic and Irrigation Conditions

Clovers (Trifolium spp.) are one of the main forage crops in temperate regions. This research was conducted to identify water-stressed tolerance among Iranian wild annual clovers under different climatic regions. Seventeen accessions, belonging to seven species, were planted in a field in two consecutive years, at two locations (Mashhad and Urmia) in Iran, under normal and water-stressed conditions. Combined analysis of variance, Scheffe analysis, and Duncan’s new multiple range test showed significant differences in forage production among clover accessions as well as species. In addition, drought-tolerance/susceptibility indices were calculated for each accession and species. Then, these indices were applied in factor analysis. Extracted Bi-plot based on factor analysis confirmed the results of Duncan and Scheffe analyses. In water-stressed conditions, T. resupinatum (cultivated accession) produced the highest forage in Urmia with 349 mm annual rainfall, whereas in Mashhad, with 149.8 mm annual precipitation, T. purpureum and T. echinatum (both, wild species) had the highest production. The accessions as well as species were ranked based on their forage production for each location and experiment. Ultimately, this work proposed some new Trifolium species, such as T. echinatum, T. diffusum, and T. purpureum, for forage production in
Prognostic value of serum gamma-glutamyltransferase in patients with hepatocellular carcinoma : a meta-analysis

Inconsistent findings have emerged concerning the prognostic value of serum gamma-glutamyltransferase (GGT) in patients with hepatocellular carcinoma (HCC). The current meta-analysis aimed to evaluate the prognostic value of serum GGT in HCC patients. Eligible studies were identified through a search of PubMed, Web of Science, and Embase databases, from inception to May 2018. Only studies reporting the association of elevated serum GGT levels with overall survival (OS) and recurrence-free survival (RFS) in HCC patients were included. Hazard ratios (HR) and 95% confidence intervals (CI) were pooled for high versus low serum GGT levels as effective measures. Twelve studies, with 2,621 HCC patients, were identified and analyzed. The present meta-analysis showed that HCC patients with elevated serum GGT levels were significantly associated with poor OS (HR 2.05; 95% CI, 1.78-2.37) and RFS (HR 1.60; 95% CI 1.39-1.85). Subgroup analysis yielded similar prognostic values for OS in different cut-off values of serum GGT, sample sizes, and treatment method groups. Results suggest that elevated serum GGT levels are independent predicators of poor survival and disease recurrence in HCC patients, especially for Chinese patients.
Influence of the anterior arch shape and root position on root angulation in the maxillary esthetic area

Purpose This study was conducted to characterize the relationship of the angulation between the tooth root axis and alveolar bone axis with anterior alveolar (AA) arch forms and sagittal root position (SRP) in the anterior esthetic region using cone-beam computed tomography (CBCT) images. Materials and Methods CBCT images that met the inclusion and exclusion criteria were categorized using a recent classification of AA arch forms and a SRP classification. Then, the angulation of the root axis and the alveolar bone axis was measured using mid-sagittal CBCT images of each tooth. The relationships of the angulation with each AA arch form and SRP classification were evaluated using 1-way analysis of variance and a linear regression model. Results Ninety-eight CBCT images were included in this study. SRP had a greater influence than the AA arch form on the angulation of the root axis and the alveolar bone axis (P<0.05). However, the combination of AA arch form and SRP was more predictive of the angulation of the root axis and the alveolar bone axis than either parameter individually. Conclusion The angulation of the root axis and alveolar bone axis demonstrated a relationship with the AA arch form and SRP in teeth in the anterior esthetic region. The influence of SRP was greater, but the combination of both parameters was more predictive of root-to-bone angulation than either parameter individually, implying that clinicians should account for both the AA arch form and SRP when planning implant placement procedures in this region.
Development of Fermented Banana Vinegar : Chemical Characterization and Antioxidant Activity

This study was carried out to examine the chemical properties, antioxidant activities and sensory scores of banana vinegar produced from four banana cultivars, namely ‘Khai Pra Tabong’, ‘Nak’, ‘Hin’, and ‘Phama Heak Kuk’. The initial soluble solid contents in the banana juice were adjusted to 25o Brix before taking to fermentation. Alcoholic fermentation was conducted using Saccharomyces cerevisiae as the inoculant while Acetobacter pasteurianus was used for acetous fermentation. As observed, all samples during the alcoholic fermentation the levels of soluble solids decreased continuously and the level of alcohol were found to increase at the end of fermentation process. Notably, the wine produced from ‘Phama Heak Kuk’ cultivar exhibited the highest level of alcohol (9.54%) and exhibited the highest levels of antioxidant activity (87.04%). Similar results were observed for all samples during the acetous fermentation, in which the level of alcohol dropped continuously and the levels of acetic acid were noted to elevate at the end of the fermentation process. The highest levels of acetic acid (3.49 %) was detected in the vinegars produced from ‘Phama Heak Kuk’ cultivar while those produced form ‘Khai Pra Tabong’ cultivar exhibited the highest levels of antioxidant activity (80.59 %). Sensory evaluation based on the 9-point hedonic scales showed that the vinegars produced from ‘Hin’ cultivar showed the highest overall acceptability with an average score of 8.13, equivalent to the hedonic scale of 9, which indicated a high pleasant level of the vinegar preference of the consumers. A b s t r a c t
Evaluation of different phenotypic assays for the detection of metallo-β-lactamase production in carbapenem susceptible and resistant Acinetobacter baumannii isolates

This study was conducted to evaluate the combined disc test and the double disc synergy test for MBL detection among imipenem sensitive and resistant A. baumanni strains, to study the co-resistance to other classes of antibiotics and to determine the prevalence of some antibiotic resistance determinants (bla OXA 51 like gene and class I integron) among these isolates. We isolated a total of 51 A. baumannii strains. The antibiotic sensitivity pattern was determined by Kirby Bauer disc diffusion method. For imipenem, the minimum inhibitory concentrations (MICs) were determined using the Epsilometer (E test). The isolates were tested for the presence of MBLs by the combined disc test (CDT) and the double disc synergy test (DDST). For all isolates, PCR was performed for the detection of the bla OXA-51-like and Class I integrase genes. The highest rates of resistance were against ciprofloxacin (64.7%), amoxacillin clavulanic acid (58.8%), amikacin (58.8%), ceftriaxone (56.9%) and chloramphenicol (52.9%). Lower rates of resistance were to imipenem (31.4%) and tetracyclines (25.5%). MBLs were detected in both imipenem sensitive and resistant A. baumannii isolates. The CDT had a sensitivity ranging from 92% to 100% , while the DDST had a sensitivity ranging from 86.2% to 100%. The bla OXA-51 like gene was detected in 96.1% and Class I integrase gene was detected in (72.5%) of A. baumannii strains . The later conferred significantly higher resistance rates to various antibiotics. [Enas A. Daef, Ismail S.Mohamed, Ahmed S. Ahmed, Nahla M Elsherbiny, Ibrahim M. Sayed. Evaluation of different phenotypic assays for the detection of metallo-β-lactamase production in carbapenem susceptible and resistant Acinetobacter baumannii isolates. J Am Sci 2012;8(11):292-299]. (ISSN: 1545-1003). http://www.jofamericanscience. org. 41
The Acquisition of syntax in children from 5 to 10 / Carol homsky

This study is concerned with the general question of the extent to which children between the age of 5 and 10 have achieved mastery of their native language, and explores areas of disparity between adult and child grammar. Mrs. Chomsky has examined a sample of 40 children and presents the actual interview material as well as a report on her experiments, theoretical considerations of linguistic complexity, and a summary. This pioneering attempt to unravel the complex network of the later stages of syntax acquisition will undoubtedly be of great relevance to linguists and psychologists.
Results From a Controlled Study of the iPad Fractions Game Motion Math

Although fractions knowledge is essential for future success in mathematics, data show that most U.S. students fail to become proficient in fractions. With the advent of mobile technologies such as iPad tablets, new kinds of interactions with subject matter have become possible that have potential for improving learning. The present study used an experimental repeated measures crossover design to investigate whether the iPad fractions game Motion Math would improve fourth graders’ fractions knowledge and attitudes. In results from 122 participants, students’ fractions test scores improved an average of over 15% after playing Motion Math for 20 min daily over a 5-day period, representing a significant increase compared to a control group. In addition, children’s self-efficacy for fractions, as well as their liking of fractions, each improved an average of 10%, representing a statistically significant increase compared to a control group. Implications for the design and study of interactive games are discussed.
IMPLEMENTATION OF A METHOD TO ESTIMATE CHANGE IN EIGENVALUE DUE TO PERTURBED FISSION SOURCE DISTRIBUTION INTO MCNP

A new method to estimate a change in an eigenvalue (a multiplication factor) due to the perturbed fission source distribution has been implemented into a beta version of MCNP5. Various benchmark problems have been set up and the method has been verified with the problems. The new method improves conventional MCNP differential operator sampling estimates significantly. It is also shown that the method is applicable not only for uniform perturbation problems but also for localized perturbation problems. Furthermore, results for the benchmark problems have been compared among various methods : two independent Monte Carlo calculations, conventional MCNP differential operator sampling method, the F − A method and the new method with different algorithms.
Can satellite imagery evaluate the pre-condition of a grazing experiment?

Most studies on grazing effects are based on the assumption that vegetation conditions at experiment sites that are subject to different grazing treatments, are the same prior to grazing, which may not be true. The pre-existing differences in vegetation may be wrongly attributed to the influence of grazing if pre-validation of vegetation conditions at the site is not performed. In this paper, the assumption stated above was verified by comparing vegetation condition between nine experiment units (pastures) in a grazing experiment site set up by Grasslands National Park (GNP) before grazing treatment started. The leaf area index (LAI) was applied to represent vegetation conditions within the grazing experiment site. The vegetation conditions between the nine pastures were compared at different scales and vegetation growing stages. Results indicate that vegetation conditions measured with 1m2 sampling scale showed a significant difference among the nine pastures (p<0.1). No significant differences were observed when measurements were conducted with 100m2 and 400m2 sampling scales (p>0.1). Variation of vegetation conditions of the nine pastures in peak and late growing stages were very consistent. These results indicate that sampling scale plays an important role in vegetation condition assessment. Remote sensing offers data in multi-spatial resolution which provides an efficient way for investigating vegetation condition at different scales.
Adversarial Deep Domain Adaptation for Multi-Band SAR Images Classification

Deep convolutional neural networks (CNNs) have made a breakthrough on supervised SAR images classification. However, SAR imaging is considerably affected by the frequency band. That means a neural network trained on a SAR image set of one band is not suitable for the classification of another band images. As manually labeling the training samples of each band is always time-consuming, we propose an unsupervised multi-level domain adaptation method based on adversarial learning to solve the problem of multi-band SAR images classification. First, we train a discriminative CNN using samples of one frequency band data set that contains labels to map the data to a latent feature space. Then, we adjust the trained CNN to map the unlabeled samples of another frequency band data set to the same feature space through alternately optimizing two adversarial loss functions. Thus, the features of these two band images are fused and can be classified by the same classifier. We checked the performance of our method using both simulated data and measured data. Our method made a breakthrough in the classification of multi-band images with accuracies of 99% on both data sets. The results are even very close to the supervised CNN trained using a large number of labeled samples.
The Tomographic Approach to Ground-Penetrating Radar for Underground Exploration and Monitoring: A more user-friendly and unconventional method for subsurface investigation

Underground exploration and characterization via nondestructive imaging is of great interest in the modern scientific community [1]. The reason for such enthusiasm is related to the methodology? s wide range of applications, which span from civil engineering to the archaeological and forensic fields and to planetary exploration. In this framework, groundpenetrating radar (GPR) is becoming one of the leading technologies because of its flexibility and ease of application. However, standard GPR provides a user-dependent map, known as a radargram, of underground and subsurface targets, the interpretation of which requires strong human expertise and does not allow for inferences about the nature of the buried targets, unless some a priori information is available.
Detection and Classification of Pulmonary Nodules Using Convolutional Neural Networks: A Survey

CT screening has been proven to be effective for diagnosing lung cancer at its early manifestation in the form of pulmonary nodules, thus decreasing the mortality. However, the exponential increase of image data makes their accurate assessment a very challenging task given that the number of radiologists is limited and they have been overworked. Recently, numerous methods, especially ones based on deep learning with convolutional neural network (CNN), have been developed to automatically detect and classify pulmonary nodules in medical images. In this paper, we present a comprehensive analysis of these methods and their performances. First, we briefly introduce the fundamental knowledge of CNN as well as the reasons for their suitability to medical images analysis. Then, a brief description of various medical images datasets, as well as the environmental setup essential for facilitating lung nodule investigations with CNNs, is presented. Furthermore, comprehensive overviews of recent progress in pulmonary nodule analysis using CNNs are provided. Finally, existing challenges and promising directions for further improving the application of CNN to medical images analysis and pulmonary nodule assessment, in particular, are discussed. It is shown that CNNs have transformed greatly the early diagnosis and management of lung cancer. We believe that this review will provide all the medical research communities with the necessary knowledge to master the concept of CNN so as to utilize it for improving the overall human healthcare system.
Eigenvalue Based Mutual Coupling Reduction

This work introduces a novel decoupling technique which employs the theory of coupled characteristic modes for a two element microstrip array. The key idea is to optimize the shape of the decoupling structure using the eigenvalues of the coupled array which can be computed with no prior knowledge of the excitation arrangement. A template example with parasitic isolating strip has been verified with full-wave simulation. The proposed method can find future application in the multi-antenna system for any desired frequency of interest.
Efficient Parallel and Serial Systolic Structures for Multiplication and Squaring Over GF( ${2^{m}}$ )

In this paper, we present efficient parallel and serial systolic structures for combined multiplication and squaring over GF( ${2^{m}}$ ). The proposed structures have the advantage of computing both modular multiplication and squaring simultaneously for fast execution of modular exponentiation. They share the same hardware components for both operations and this gives them the advantage of saving more space than the case of using a separate structure for each operation. In addition, they have a regular structure and local communication between the processing elements and this makes them more efficient for VLSI implementation. Complexity analysis of the proposed designs and the existing most recent and efficient designs indicates that the proposed serial design has 31.7% lower area-time (AT) complexity than the previously reported most recent serial one. In addition, the proposed parallel design has a significant lower AT complexity over the recent efficient parallel designs by at least 96.9%.
Preliminary Study of a New Meander Line for W-band TWT

A new meander line topology for 71–76 GHz Traveling Wave Tubes is proposed. This new shape offers flatter dispersion relation and enhanced interaction impedance in comparison with the standard meander line. Results of the interaction impedance over the beam cross section and the effect of a meander line-to-waveguide coupler are also analyzed in this work.
A Time-Slotted Molecular Communication (TS-MOC): Framework and Time-Slot Errors

Synchronization is a critical issue in molecular communications (MC). Additionally, the lack of an appropriate time-slotted framework for MC systems hinders the in-depth analysis of desynchronization. Therefore, this paper addresses both issues. First, taking inspiration from oscillators found in nature, we propose a time-slotted framework suitable for MC systems where the time instances of the oscillations demarcate the time-slot boundaries. The use of biological oscillators readily satisfies biocompatibility requirements. We name such system as a time-slotted molecular communication-based (TS-MOC) system. A TS-MOC system will be beneficial to many MC applications, such as when multiple nanomachines have to transmit data simultaneously to a control/sink node or share the channel in a time-division multiplexing manner. Second, oscillation perturbations induce desynchronization — the misalignment of time-slots. Desynchronization combined with large propagation delay results in a time difference between the arrival of a signal and the beginning of a time-slot. This phenomenon is called time-slot error, and it can degrade a system’s performance. Therefore, the immediate goal is to mitigate time-slot errors. Depending on the initiation type, we propose two synchronization schemes: sender-initiated time-slot alignment and receiver-initiated time-slot alignment. An analytical model for time-slot error is also derived. Our analysis demonstrates that the proposed schemes are robust and energy-efficient — they achieve relatively low errors indicating robustness and relatively less synthesizing energy costs indicating energy efficiency. Our analysis also highlights the good agreement between the simulations and the analytical model. Finally, in conclusion, we provide brief insights into key open research challenges.