Miracle-dz/UniFAR-FTUs huggingface dataset:
Blueshifted [O III] Emission: Indications of a Dynamic Narrow-Line Region

The [O III] λ5007 line is commonly used as an indicator of the systemic redshift of active galactic nuclei (AGNs). Also, recent studies have used the width of this emission line as a proxy for the stellar velocity dispersion in the host galaxy. This paper calls both of these assumptions into question by analyzing a sample of approximately 400 AGN spectra from the first data release of the Sloan Digital Sky Survey. These spectra show that the low-ionization forbidden lines ([O II], [N II], and [S II]) define a consistent redshift but that the peak of the [O III] line is blueshifted in approximately half of the AGNs with respect to that redshift. For the sample studied here, the average shift is 40 km s-1, with the largest shift being more than 400 km s-1. The magnitude of this shift is found to be correlated with a number of properties, including the width of the [O III] line and the Eddington ratio (L/LEdd), derived from the luminosity and width of Hβ.
Effects of Corpus‐Aided Language Learning in the EFL Grammar Classroom: A Case Study of Students' Learning Attitudes and Teachers' Perceptions in Taiwan

This study employed a blended approach to form an extensive assessment of the pedagogical suitability of data-driven learning (DDL) in Taiwan's EFL grammar classrooms. On the one hand, the study quantitatively investigated the effects of DDL compared with that of a traditional deductive approach on the learning motivation and self-efficacy of first-year college students majoring in English. On the other, it qualitatively examined a group of early-career teachers' (ECTs') hands-on experience of teaching DDL to these students. The research results via t-tests show that only those who received DDL treatment have enhanced learning attitudes in general. No significant differences, however, were found between the effects of these treatments in a multivariate analysis test of covariance. In contrast, qualitative inquiry shows that, despite facing technical difficulties and increased workload, the ECTs found their DDL teaching experience innovative and interesting, believed in its effectiveness in grammar learning, and judged it to transform Taiwanese students' grammar learning patterns from passivity to active engagement. This article concludes with suggestions for future DDL applications and investigation in the EFL grammar classrooms of Taiwan.
The investigation of melatonin effect on liver antioxidant and oxidant levels in fructose-mediated metabolic syndrome model.

OBJECTIVE Metabolic syndrome (MetS) can be induced by the oxidative stress conditions caused by ingestion of large amounts of fructose. We investigated the possible protective effects of melatonin administration on liver tissues in fructose-fed rats. MATERIALS AND METHODS Thirty-two rats were randomly divided into four groups; control, fructose, melatonin, and fructose plus melatonin. MetS was induced by a fructose solution (20% in tap water) and melatonin (20 mg/kg daily) was administered by oral gavage. Systolic blood pressures (SBP) were measured. After the end of the 8-week experimental period, serum lipid profile, glucose and insulin levels, tissue total oxidant status (TOS) and activities of paraoxonase (PON), glutathione peroxidase (GSH-Px), superoxide dismutase (SOD) and catalase (CAT) were measured. RESULTS Fructose consumption significantly increased SBP, serum triglyceride and insulin levels and induced insulin resistance, confirming successful establishment of the MetS model. After fructose administration, the TOS levels and GSH-Px activities significantly increased in all groups compared to the control group. The PON activity in the fructose group significantly decreased compared to the control group. Melatonin supplementation, with or without fructose, increased PON activity. The SOD activity significantly increased in the fructose group compared to the control group, but significantly decreased in the melatonin group compared to the control and fructose groups. CAT activity was unchanged in all groups. CONCLUSIONS GSH-PX and PON are important antioxidants for reducing oxidant stress. Melatonin might act as a prooxidant at the dose given in our experimental design when administered with fructose.
Interleukin‐2‐induced, melanoma‐specific T cells recognize camel, an unexpected translation product of LAGE‐1

Melanoma‐specific cytotoxic T lymphocytes (CTLs) were induced by in vitro stimulation of peripheral blood mononuclear cells of a melanoma patient with autologous IL‐2‐producing melanoma 518/IL2.14 cells. CTL clone 1/29 recognized, in addition to autologous melanoma cell lines, a panel of HLA‐A*0201‐expressing allogeneic melanoma cell lines but was not reactive with normal melanocytes. Here, we report the full molecular characterization of the target structure for CTL 1/29, which was identified by cDNA expression cloning. The recognized antigen was named CAMEL (CTL‐recognized antigen on melanoma). The CAMEL cDNA turned out to be derived from the LAGE‐1 gene, a recently described tumor antigen that is strongly homologous to NY‐ESO‐1. CAMEL, however, is not encoded by the putative open reading frame (ORF) of LAGE‐1 but by an alternative frame starting from the second ATG of the mRNA. The first 11 amino acids of the CAMEL protein, MLMAQEALAFL, constitute the epitope of CTL 1/29. This epitope is also encoded by a similar alternative ORF in NY‐ESO‐1. In summary, CTL induction with IL‐2‐transfected melanoma cells has revealed a new tumor antigen that may serve as a target for immunotherapy. Int. J. Cancer 82:442–448, 1999. © 1999 Wiley‐Liss, Inc.
Stochastic functional gradient for motion planning in continuous occupancy maps

Safe path planning is a crucial component in autonomous robotics. The many approaches to find a collision free path can be categorically divided into trajectory optimizers and sampling-based methods. When planning using occupancy maps, the sampling-based approach is the prevalent method. The main drawback of such techniques is that the reasoning about the expected cost of a plan is limited to the search heuristic used by each method. We introduce a novel planning method based on trajectory optimization to plan safe and efficient paths in continuous occupancy maps. We extend the expressiveness of the state-of-the-art functional gradient optimization methods by devising a stochastic gradient update rule to optimize a path represented as a Gaussian process. This approach avoids the need to commit to a specific resolution of the path representation, whether spatial or parametric. We utilize a continuous occupancy map representation in order to define our optimization objective, which enables fast computation of occupancy gradients. We show that this approach is essential in order to ensure convergence to the optimal path, and present results and comparisons to other planning methods in both simulation and with real laser data. The experiments demonstrate the benefits of using this technique when planning for safe and efficient paths in continuous occupancy maps.
High school students’ scientific epistemological beliefs, self-efficacy in learning physics and attitudes toward physics: a structural equation model

Background: There are some theoretical evidences that explain the relationships between core beliefs (i.e., epistemological beliefs) and peripheral beliefs (self-efficacy in learning) in the literature. The close relationships of such type of beliefs with attitudes are also discussed by some researchers. Constructing a model that investigates these relationships by considering theoretical and empirical evidences can empower researchers to discuss these relationships more comprehensively. Purpose: The purpose of this study is to explore the relationships among Turkish high school students’ scientific epistemological beliefs, self-efficacy in learning physics and their attitudes toward physics. Sample: A total of 632 high school students participated in this study; however, 269 female and 229 male (a total of 498) high school students’ data were used. Design and methods: Three distinct instruments that measure scientific epistemological beliefs, self-efficacy in learning physics and attitudes toward physics were combined into a unique questionnaire form and it was distributed to high school students. To explore the relationships among these variables, structural equation modeling was used. Results: The results showed that scientific epistemological belief dimensions uncovered by the nature of knowing (source and justification) significantly and positively related to both self-efficacy in learning physics and attitudes toward other important physics dimensions. Additionally, self-efficacy in learning physics significantly and positively predicted attitudes toward multiple physics dimensions (importance, comprehension and requirement). However, epistemological belief dimensions related to the nature of knowledge (certainty and development) did not have significant impact on self-efficacy in learning physics or attitudes toward physics. Conclusions: This study concludes that there are positive and significant relationships among Turkish high school students’ scientific epistemological beliefs, self-efficacy in learning physics and their attitudes toward physics.
Recovering system specific rules from software repositories

One of the most successful applications of static analysis based bug finding tools is to search the source code for violations of system-specific rules. These rules may describe how functions interact in the code, how data is to be validated or how an API is to be used. To apply these tools, the developer must encode a rule that must be followed in the source code. The difficulty is that many of these system-specific rules are undocumented and "grow" over time as the source code changes. Most research in this area relies on expert programmers to document these little-known rules. In this paper we discuss a method to automatically recover a subset of these rules, function usage patterns, by mining the software repository. We present a preliminary study that applies our work to a large open source software project.
Vaccination with Conserved Regions of Erythrocyte-Binding Antigens Induces Neutralizing Antibodies against Multiple Strains of Plasmodium falciparum

Background A highly effective vaccine against Plasmodium falciparum malaria should induce potent, strain transcending immunity that broadly protects against the diverse population of parasites circulating globally. We aimed to identify vaccine candidates that fulfill the criteria. Methods We have measured growth inhibitory activity of antibodies raised to a range of antigens to identify those that can efficiently block merozoite invasion for geographically diverse strains of P. falciparum. Results This has shown that the conserved Region III-V, of the P. falciparum erythrocyte-binding antigen (EBA)-175 was able to induce antibodies that potently inhibit merozoite invasion across diverse parasite strains, including those reliant on invasion pathways independent of EBA-175 function. Additionally, the conserved RIII-V domain of EBA-140 also induced antibodies with strong in vitro parasite growth inhibitory activity. Conclusion We identify an alternative, highly conserved region (RIV-V) of EBA-175, present in all EBA proteins, that is the target of potent, strain transcending neutralizing antibodies, that represents a strong candidate for development as a component in a malaria vaccine.
Coping Strategies of Cancer Patients: Actual Communication and Imagined Interactions

We examined cancer patients' actual and imagined interactions with health care professionals. Imagined interactions were defined as cognitive representations of conversation experienced as internal dialogues with significant others. The results of a survey of 48 cancer patients indicate that communication satisfaction is associated with amount of information about the disease, whereas fear reduction is associated with amount of communication about one's illness. The pleasantness of imagined interactions, their catharsis function, and imagining the self free of cancer were intercorrelated. The frequency and cathartic function of imagined interaction were correlated with actual communication and fear reduction.
A Constrained non-dominated sorting genetic algorithm of sequential tasks planning for Multi-EOS

Multi-EOS (Earth Observing Satellites) tasks planning problem is a typical over-subscribed resource allocation problem with multi-objective, especially to make schedule for both LEO (Low Earth Orbit) and HEO (High Earth Orbit) satellites. The optimization work of scheduling is assigning appropriate time window to every request (including data transmission process between satellites and ground facilities) under physical and task precedence constraints. In this paper, we construct a mixed integer programming model for this problem. Then we proposed a multi-objective constrained non-dominated sorting genetic algorithm based on the strategy of elitist selection, in this algorithm, a fast non-dominated sorting approach with computational complexity of O(MN2) is used, to be able to keep a better spread of solutions and better convergence near the true Pareto-optimal front, crowd-distance comparison operator is used and get a better result compare to Strength Pareto Evolutionary Algorithm, constraints control are also used to guarantee the feasibility of solutions. The approach is tested upon three applications derived from satellites data base of AGI's Satellite toolkit.
Content-Based Image Retrieval ( CBIR ) For Identifying Image Based Plant Disease

This paper presents a method for identify plant disease based on color, edge detection and histogram matching. Farmers are suffering from the problem rising from various types of plant traits/diseases. Sometimes plant’s doctors are also unable to recognize the disease that results in lack of identification of right type of disease and this leads to crop spoil if not taken care of at right time. The most significant part of research on plant disease to identify the disease based on CBIR (content based image retrieval) that is mainly concerned with the accurate detection of diseased plant. It has significant perspective in field of agriculture. This research describes effective; sample technique for identify plant disease. The method used in this research is divided into two major phases. First phase concerns with training of healthy sample and diseased sample. Second phase concerns with the training of test sample and generates result based on the edge detection and histogram matching.
Representations and the Corruption of Goods

Critiques of Economics by the philosophers Michael Sandel and Ruth Grant reveal a substantive issue within economic theorising, that of attitude change, leading to the socalled “corruption of goods”. It is argued that current models within economics cannot sensibly handle attitude change in the dimensions discussed by Sandel and Grant. Instead it can be modelled using multirepresentational games- games that allow interpretations of situations by players to change within the game. Although this may result in inconsistency within games, it is demonstrated how this can be resolved and how useful they are in analysing the corruption of goods.
Spinal cord injury: From inflammation to glial scar

Background: Glial scar (GS) is the most important inhibitor factor to neuroregeneration after spinal cord injury (SCI) and behaves as a tertiary lesion. The present review of the literature searched for representative studies concerning GS and therapeutic strategies to neuroregeneration. Methods: The author used the PubMed database and Google scholar to search articles published in the last 20 years. Key words used were SCI, spinal cord (SC) inflammation, GS, and SCI treatment. Results: Both inflammation and GS are considered important events after SCI. Despite the fact that firstly they seem to cause benefit, in the end they cause more harm than good to neuroregeneration. Each stage has its own aspects under the influence of the immune system causing inflammation, from the primary to secondary lesion and from those to GS (tertiary lesion). Conclusion: Future studies should stress the key points where and when GS presents itself as an inhibitory factor to neuroregeneration. Considering GS as an important event after SCI, the author defends GS as being a tertiary lesion. Current strategies are presented with emphasis on stem cells and drug therapy. A better understanding will permit the development of a therapeutic basis in the treatment of the SCI patients considering each stage of the lesion, with emphasis on GS and neuroregeneration.
Using Regression Mixture Analysis in Educational Research

Conventional regression analysis is typically used in educational research. Usually such an analysis implicitly assumes that a common set of regression parameter estimates captures the population characteristics represented in the sample. In some situations, however, this implicit assumption may not be realistic, and the sample may contain several subpopulations such as high math achievers and low math achievers. In these cases, conventional regression models may provide biased estimates since the parameter estimates are constrained to be the same across subpopulations. This paper advocates the applications of regression mixture models, also known as latent class regression analysis, in educational research. Regression mixture analysis is more flexible than conventional regression analysis in that latent classes in the data can be identified and regression parameter estimates can vary within each latent class. An illustration of regression mixture analysis is provided based on a dataset of authentic data. The strengths and limitations of the regression mixture models are discussed in the context of educational research.
Nocardioides taihuensis sp. nov., isolated from fresh water lake sediment.

A novel actinobacterial strain, designated X17T, was isolated from the sediment of Taihu Lake in China and its taxonomic position was investigated by using a polyphasic approach. The isolate formed milky-white colonies comprising aerobic, Gram-stain-positive, rod-shaped cells. Phylogenetic analysis based on the 16S rRNA gene sequences revealed that the organism belonged to the genus Nocardioides and consistently formed a distinct cluster with Nocardioides agariphilus JCM 16020T and Nocardioides islandensis MSL 26T, sharing 95.5 and 94.8 % 16S rRNA gene sequence similarities, respectively. The genomic DNA G+C content was 69.9 mol%. Chemotaxonomically, the isolate contained ll-diaminopimelic acid in the cell-wall peptidoglycan, MK-8 (H4) as the predominant menaquinone, and diphosphatidylglycerol, phosphatidylglycerol and phosphatidylinositol as the polar lipids found in the cell wall. The major fatty acids were 18 : 1 ω9c (38.6 %), 16 : 0 iso (20.3 %), 15 : 0 iso (6.8 %) and 18 : 0 (5.8 %). Based on its physiological, biochemical and chemotaxonomic characteristics, the strain represents a novel species of the genus Nocardioides, for which the name Nocardioides taihuensis sp. nov. (type strain X17T=CGMCC 4.7318T=NBRC 112321T) is proposed.
Efficient Algorithms for Robust One-bit Compressive Sensing

While the conventional compressive sensing assumes measurements of infinite precision, one-bit compressive sensing considers an extreme setting where each measurement is quantized to just a single bit. In this paper, we study the vector recovery problem from noisy one-bit measurements, and develop two novel algorithms with formal theoretical guarantees. First, we propose a passive algorithm, which is very efficient in the sense it only needs to solve a convex optimization problem that has a closed-form solution. Despite the apparent simplicity, our theoretical analysis reveals that the proposed algorithm can recover both the exactly sparse and the approximately sparse vectors. In particular, for a sparse vector with s nonzero elements, the sample complexity is O(s log n/e2), where n is the dimensionality and e is the recovery error. This result improves significantly over the previously best known sample complexity in the noisy setting, which is O(s log n/e4). Second, in the case that the noise model is known, we develop an adaptive algorithm based on the principle of active learning. The key idea is to solicit the sign information only when it cannot be inferred from the current estimator. Compared with the passive algorithm, the adaptive one has a lower sample complexity if a high-precision solution is desired.
Ethnographic Research in Multicultural Educational Contexts as a Contribution to Intercultural Dialogue

In this article, the author argues that the Council of Europe White Paper's invitation to intercultural dialogue is certainly to be welcomed and pursued, but that its focus on ‘managing’ diversity should be complemented by the concern for understanding how diversity can be represented, negotiated and treated by the different actors in multicultural educational contexts. After pointing out that intercultural education has been chosen by Italian educational authorities to respond to the unforeseen prospects and challenges of multicultural classrooms, the author illustrates how ethnographic research is not only relevant for acknowledging and interrogating diversities but also for problematizing the conceptual foundations of educational policies and aims. She further argues that ethnographic research provides fieldworkers and the subjects of research with an effective opportunity to engage in an intercultural dialogue.
Digital Breast Tomosynthesis Reconstruction with Detector Blur and Correlated Noise

This paper describes a new reconstruction method for digital breast tomosynthesis (DBT). The new method incorporates detector blur into the forward model. The detector blur introduces correlation in the measurement noise. We formulate it as a regularized quadratic optimization problem with data-fit term that accounts for the non-diagonal noise covariance matrix. By making a few assumptions based on the breast imaging process, we can model the detector blur in the optimization problem and solve it with a separable quadratic surrogate (SQS) algorithm. This method was applied to DBT reconstruction of breast phantoms and human subjects. The contrast-to-noise ratio and sharpness of microcalcifications and the visual quality of mass margins were analyzed and compared to those by the simultaneous algebraic reconstruction technique (SART). The results demonstrated the potential of the new method in improving the image quality of the reconstructed DBT images. This work is our preliminary step towards a model-based iterative reconstruction (MBIR) for DBT.
Molecular Adaptation during a Rapid Adaptive Radiation

“Explosive” adaptive radiations on islands remain one of the most puzzling evolutionary phenomena and the evolutionary genetic processes behind such radiations remain unclear. Rapid morphological and ecological evolution during island radiations suggests that many genes may be under fairly strong selection, although this remains untested. Here, we report that during a rapid recent diversification in the Hawaiian endemic plant genus Schiedea (Caryophyllaceae), 5 in 36 studied genes evolved under positive selection. Positively selected genes are involved in defence mechanisms, photosynthesis, and reproduction. Comparison with eight mainland plant groups demonstrates both the relaxation of purifying selection and more widespread positive selection in Hawaiian Schiedea. This provides compelling evidence that adaptive evolution of protein-coding genes may play a significant role during island adaptive radiations.