Miracle-dz/UniFAR-FTUs huggingface dataset:
Making pacts and cooperative acts: the archaeology of coalition and consensus

Interest in the nature and dynamics of consensus, coalition-building, and collective action has increased dramatically in archaeology during recent years. In a volume edited almost 80 years ago, Margaret Mead (1937, 8) defined cooperation as ‘the act of working together to one end’, acknowledging the obvious fact that people working together achieve far more than isolated individuals. At the same time, her title, Cooperation and Competition among Primitive Peoples, emphasized contrasting modes of human interaction. Archaeologists have, understandably, placed great emphasis on understanding competition – for resources, for territory and for power – in the human past. This issue, focusing on the archaeology of coalition and consensus, reflects expanding interest in consensus, in its diverse manifestations, in the archaeological record. As outlined in more detail below, theoretical approaches are also diverse, encompassing archaeologies of lived experience and daily life (Overholtzer and Robin 2015; McGuire 2008; Robin 2013), practice theory and relational approaches (Hastorf 2010; Watts 2013; Pauketat 2013), as well as political economy perspectives (Dye 2008; Price and Feinman 2012b). Contributors to this issue seek to identify and interpret the archaeological correlates of coalition-building and consensus, to adapt and refine theoretical ideas and to investigate, through case studies, conditions that allowed ‘more corporate’ or consensus-based forms of interaction to take hold and persist in past societies.
Advances in emerging drugs for osteosarcoma

Introduction: Osteosarcoma (OS), the most common primary malignant bone tumor, is currently treated with pre- and postoperative chemotherapy in association with the surgical removal of the tumor. Conventional treatments allow to cure about 60 – 65% of patients with primary tumors and only 20 – 25% of patients with recurrent disease. New treatment approaches and drugs are therefore highly warranted to improve prognosis. Areas covered: This review focuses on the therapeutic approaches that are under development or clinical evaluation in OS. Information was obtained from different and continuously updated data bases, as well as from literature searches, in which particular relevance was given to reports and reviews on new targeted therapies under clinical investigation in high-grade OS. Expert opinion: OS is a heterogeneous tumor, with a great variability in treatment response between patients. It is therefore unlikely that a single therapeutic tool will be uniformly successful for all OS patients. This claims for the validation of new treatment approaches together with biologic/(pharmaco)genetic markers, which may select the most appropriate subgroup of patients for each treatment approach. Since some promising novel agents and treatment strategies are currently tested in Phase I/II/III clinical trials, we may hope that new therapies with superior efficacy and safety profiles will be identified in the next few years.
TSCAN: A Content Anatomy Approach to Temporal Topic Summarization

A topic is defined as a seminal event or activity along with all directly related events and activities. It is represented by a chronological sequence of documents published by different authors on the Internet. In this study, we define a task called topic anatomy, which summarizes and associates the core parts of a topic temporally so that readers can understand the content easily. The proposed topic anatomy model, called TSCAN, derives the major themes of a topic from the eigenvectors of a temporal block association matrix. Then, the significant events of the themes and their summaries are extracted by examining the constitution of the eigenvectors. Finally, the extracted events are associated through their temporal closeness and context similarity to form an evolution graph of the topic. Experiments based on the official TDT4 corpus demonstrate that the generated temporal summaries present the storylines of topics in a comprehensible form. Moreover, in terms of content coverage, coherence, and consistency, the summaries are superior to those derived by existing summarization methods based on human-composed reference summaries.
A Fast Poisson Solver for 3-D Space Charge Calculations in a CPU+GPU Heterogeneous Routine

Space charge calculations play a key role in beam dynamics studies for particle accelerators and various other physical and technical fields. The major work is to solve Poisson's equation for numerous time steps. Therefore, it is important to solve Poisson's equation in a short time. In this paper, we present a CPU+GPU-based heterogeneous parallel computation routine with the compute unified device architecture platform in a normal PC. The new framework benefits from a novel efficient discrete cosine transform study using the classical Hockney and Eastwood's convolution routine rather than the former one with discrete Fourier transform. A model problem has been studied, which showed an efficiency improvement with the new heterogeneous routine.
Multimedia learning: Are we asking the right questions?

How can we help students to understand scientific explanations of cause-and-effect systems, such as how a pump works, how the human respiratory system works, or how lightning storms develop? One promising approach involves multimedia presentation of explanations in visual and verbal formats, such as presenting computer-generated animations synchronized with computer-generated narration or presenting illustrations next to corresponding text. In a review of eight studies concerning whether multimedia instruction is effective, there was consistent evidence for a multimedia effect: Students who received coordinated presentation of explanations in verbal and visual format (multiple representation group) generated a median of over 75% more creative solutions on problem-solving transfer tests than did students who received verbal explanations alone (single representation group). In a review of 10 studies; concerning when multimedia instruction is effective, there was consistent evidence for a contiguity effect: .
Exemplar-Based Inpainting from a Variational Point of View

Among all methods for reconstructing missing regions in a digital image, the so-called exemplar-based algorithms are very efficient and often produce striking results. They are based on the simple idea—initially used for texture synthesis—that the unknown part of an image can be reconstructed by simply pasting samples extracted from the known part. Beyond heuristic considerations, there have been very few contributions in the literature to explain from a mathematical point of view the performances of these purely algorithmic and discrete methods. More precisely, a recent paper by Levina and Bickel [Ann. Statist. , 34 (2006), pp. 1751–1773] provides a theoretical explanation of their ability to recover very well the texture, but nothing equivalent has been done so far for the recovery of geometry. Our purpose in this paper is twofold: (1) to propose well-posed variational models in the continuous domain that can be naturally associated to exemplar-based algorithms; (2) to investigate their ability to recons.
Forms of Adjustment

ABSTRACT In the increasingly competitive field of tertiary education in New Zealand, characterised by strong levels of institutional competition for a numerically limited pool of students, there has been an almost belated recognition of the importance of student retention strategies. In this context, the literature indicates that transition to the tertiary institute lifestyle can often result in a period of major personal re-adjustment for first year students, which sometimes manifests itself in early academic results that are below expectations-these twin factors can contribute to early perceptions of alienation and, in some instances, can result in unac-ceptably high dropout rates. This paper describes an intervention that attempted to increase rates of retention in a tourism study programme, through a process designed to facilitate easier assimilation into the tertiary education culture, and to consequently improve the academic results obtained in early course assessment. The nature of this approach, intended to alleviate adjustment problems and provide students with appropriate coping mechanisms, is described in outline, and the results of subsequent student evaluations discussed. The paper concludes by assessing the benefits of this intervention, and by highlighting the implications for future student intakes.
Multi-Stratum Networks: toward a unified model of on-line identities

One of the reasons behind the success of Social Network Analysis is its simple and general graph model made of nodes (representing individuals) and ties. However, when we focus on our daily on-line experience we must confront a more complex scenario: people inhabitate several on-line spaces interacting to several communities active on various technological infrastructures like Twitter, Facebook, YouTube or FourSquare and with distinct social objectives. This constitutes a complex network of interconnected networks where users’ identities are spread and where information propagates navigating through different communities and social platforms. In this article we introduce a model for this layered scenario that we call multi-stratum network. Through a theoretical discussion and the analysis of real-world data we show how not only focusing on a single network may provide a very partial understanding of the role of its users, but also that considering all the networks separately may not reveal the information contained in the whole multi-stratum model.
Postattachment Events Associated with Viral Entry Are Necessary for Induction of Interferon-Stimulated Genes by Human Cytomegalovirus

ABSTRACT Utilizing a human cytomegalovirus-specific fusion inhibitor and an antiglycoprotein H antibody, we studied the role of virion fusion in interferon-stimulated gene (ISG) induction. Our results indicate that ISG induction does not occur when virion-mediated, post-high-affinity attachment events are inhibited by either reagent. Thus, virion-mediated postattachment events, such as fusion, are required for ISG induction.
The Effects of Periodically Gapped Time Series on Cross-Correlation Lag Determinations

The three bright TeV blazars Mrk 421, Mrk 501, and PKS 2155-304 are highly variable in synchrotron X-ray emission. In particular, these sources can exhibit variable time lags between flux variations at different X-ray energy bands. However, there are a number of issues that may significantly bias lag determinations. Edelson et al. (2001) recently proposed that the lags on timescales of hours, discovered by ASCA and BeppoSAX, could be an artifact of periodic gaps in the light curves introduced by the Earth occultation every ~1.6 hr. Using Monte Carlo simulations, we show in this paper that the lags over timescales of hours cannot be the spurious result of periodic gaps, although periodic gaps do indeed introduce greater uncertainty than is present in the evenly sampled data. The results also show that time-lag estimates can be substantially improved by using evenly sampled light curves with large lag-to-bin-size ratios. Furthermore, we consider an XMM-Newton observation without interruptions and resample the light curves using the BeppoSAX observing windows, and then repeat the same cross-correlation-function (CCF) analysis on both the real and fake data. The results also show that periodic gaps in the light curves do not significantly distort the CCF characters, and indeed the CCF peak ranges of the real and fake data overlap. Therefore, the lags discovered by ASCA and BeppoSAX are not due to periodic gaps in the light curves.
MLFMA analysis of finite aperture arrays including reflector

An extended multilevel fast multipole algorithm (MLFMA) formulation is presented that includes magnetic surface current densities of radiating apertures and impedance relations containing modal excitation terms. The method-of-moment (MoM) solution is based on a combined field integral equation (CFIE) written in terms of mixed potential form. Aperture waveguide modal eigenvectors and Rao-Wilton-Glisson (RWG) functions for triangular patches are utilized for basis functions of the magnetic and electric surface current densities, respectively. The applicability of the method is demonstrated at the examples of a rectangular horn cluster in a finite screen and a finite circular horn cluster feeding a subreflector. Advantages and disadvantages of the MLFMA, when applied for aperture array problems, are discussed. The method is verified by available measurements and reference calculations.
Exploiting argument information to improve biomedical event trigger identification via recurrent neural networks and supervised attention mechanisms

In biomedical research, events revealing complex relations between entities play an important role. Event trigger identification is a crucial and prerequisite step in the pipeline process of biomedical event extraction. There exist two main problems in the previous work: (1) Traditional feature-based methods often rely on human ingenuity, which is a time-consuming process. Though most representation-based methods overcome this problem, these methods usually depend on local sentence representation features only within a window. (2) In current biomedical event trigger identification methods, arguments annotated in training set which can provide significant clues are completely ignored or exploited in an indirect manner. In this paper, we propose a Recurrent Neural Networks (RNN) based model considering argument information achieved via supervised attention mechanisms, which can automatically extract context features across the sentence and arguments clues. Meanwhile, we also introduce the dependency-based word embeddings in order to represent more dependency-based semantic information. Experimental results on the Multi Level Event Extraction (MLEE) corpus show that 1.14% improvement on F1-score is achieved by the proposed model when compared to the state-of-the-art approach, demonstrating the effectiveness of the proposed method.
MALDI-imaging reveals thymosin beta-4 as an independent prognostic marker for colorectal cancer

DNA aneuploidy has been identified as a prognostic factor for epithelial malignancies. Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) is a powerful tool for direct analysis of multiple proteins in tissue sections while maintaining the cellular and molecular integrity. We compared diploid and aneuploid colon cancer tissues against normal mucosa of the colon by means of IMS. DNA image cytometry determined the ploidy status of tissue samples that were subsequently subjected to MALDI-IMS. After obtaining protein profiles through direct analysis of tissue sections, a discovery and independent validation set were used to predict ploidy status by applying proteomic classification algorithms [Supervised Neural Network (SNN) and Receiver Operating Characteristic (ROC)]. Five peaks (m/z 2,395 and 4,977 for diploid vs. aneuploid comparison as well as m/z 3,376, 6,663, and 8,581 for normal mucosa vs. carcinoma comparison) were significant in both SNN and ROC analysis. Among these, m/z 4,977 was identified as thymosin beta 4 (Tβ-4). Tβ-4 was subsequently validated in clinical samples using a tissue microarray to predict overall survival in colon cancer patients.
Treatment of infectious mastitis during lactation: antibiotics versus oral administration of Lactobacilli isolated from breast milk.

BACKGROUND Mastitis is a common infectious disease during lactation, and the main etiological agents are staphylococci, streptococci, and/or corynebacteria. The efficacy of oral administration of Lactobacillus fermentum CECT5716 or Lactobacillus salivarius CECT5713, two lactobacilli strains isolated from breast milk, to treat lactational mastitis was evaluated and was compared with the efficacy of antibiotic therapy. METHODS In this study, 352 women with infectious mastitis were randomly assigned to 3 groups. Women in groups A (n = 124) and B (n = 127]) ingested daily 9 log(10) colony-forming units (CFU) of L. fermentum CECT5716 or L. salivarius CECT5713, respectively, for 3 weeks, whereas those in group C (n =101) received the antibiotic therapy prescribed in their respective primary care centers. Results. On day 0, the mean bacterial counts in milk samples of the 3 groups were similar (4.35-4.47 log(10) CFU/mL), and lactobacilli could not be detected. On day 21, the mean bacterial counts in the probiotic groups (2.61 and 2.33 log(10) CFU/mL) were lower than that of the control group (3.28 log(10) CFU/mL). L. fermentum CECT5716 and L. salivarius CECT5713 were isolated from the milk samples of women in the probiotic groups A and B, respectively. Women assigned to the probiotic groups improved more and had lower recurrence of mastitis than those assigned to the antibiotic group. Conclusions. The use of L. fermentum CECT5716 or L. salivarius CECT5713 appears to be an efficient alternative to the use of commonly prescribed antibiotics for the treatment of infectious mastitis during lactation. ClinicalTrials.gov identifier. NCT00716183.
VNREAL: Virtual network resource embedding algorithms in the framework ALEVIN

Network virtualization is recognized as an enabling technology for the Future Internet that overcomes network ossification. However, it introduces a set of challenges. In any network virtualization environment, the problem of optimally mapping virtual resources to physical resources, known as virtual network embedding (VNE), is a critical challenge. Several algorithms attempting to solve this problem have been proposed in literature, so far. However, comparison of existing and new VNE algorithms is hard, as each algorithm focuses on different criteria. To that end, the VNREAL project introduces ALEVIN, a framework to compare different algorithms according to a set of metrics, easily incorporate new VNE algorithms, and evaluate these algorithms on a given scenario for arbitrary parameters.
Dirichlet Process based model for GWAS

Human population have large genetic variation. Genetic variations are usually characterized by Single Nucleotide Polymorphism (SNP). These are the location of variation in the genome sequence of two individuals. Identication of SNPs aecting human phenotype, especially leading to risks of complex disorders, is one of the key problems of medical genetics. In this project we build a probabilistic model which can determine the deleterious mutation which can lead to heart disease in humans.
STANDARDIZATION, RELIABILITY, AND VALIDITY OF OPTIMISM SCALE IN ESFAHAN AND A SURVEY OF RELATIONSHIP BETWEEN OPTIMISM, SELFMASTERY, AND DEPRESSION

The purpose of this research was standardization, reliability, and validity of optimism scale (LOT) between citizens of Esfah n. 120 citizens of Esfah n city selected by cluster sampling method. Optimism, self mastery, depression scale, and personal characteristics form were administered to them. This research was a survey that encompasses descriptional, evaluation, comparison, and correlation method. Finding of research revealed percentiles and standardized (T) scores as the norms of optimism scale. Cut-off point of standardized (T) test for males were ascertained 32 and 13 and 30 and 16 for females. The results of scale’s item analysis showed that all of the scales items had a significant and positive relationship with total scores of the scale. Reliability coefficient was computed 0.74 and 0.87 using Cronbach’s Alpha reliability test and test-retest method respectively . validity coefficient of optimism was computed by criteria related approach. Validity coefficient between optimism, depression, and self mastery were -0.649 and 0.725 respectively. Factor analysis revealed two dominant factors that called positive attitude toward event and hope for future. Other findings showed that there was significant relationship between optimism, self mastery, age, depression, income, mother’s age, and season of birth, (P < 0.05). Results showed that gender is not an influential factor on optimism, selfmastery, and depression. With respect to finding it was concluded that optimism scale can be used to test people’s optimism.
MOLECULAR PHARMACOLOGY IN CHINA Megakaryocytic Smad 4 Regulates Platelet Function through Syk and ROCK 2 Expression s

Smad4, a key transcription factor in the transforming growth factor-b signaling pathway, is involved in a variety of cell physiologic and pathologic processes. Here, we characterized megakaryocyte/platelet-specific Smad4 deficiency in mice to elucidate its effect on platelet function. We found that megakaryocyte/platelet-specific loss of Smad4 caused mild thrombocytopenia and significantly extended first occlusion time and tail bleeding time in mice. Smad4-deficient platelets showed reduced agonist-induced platelet aggregation. Further studies showed that a severe defect was seen in integrin aIIbb3-mediated bidirectional (inside-out and outside-in) signaling in Smad4deficient platelets, as evidenced by reduced fibrinogen binding and a-granule secretion, suppressed platelet spreading and clot retraction. Microarray analysis showed that the expression levels of multiple genes were altered in Smad4-deficient platelets. Among these genes, spleen tyrosine kinase (Syk) and Rhoassociated coiled-coil containing protein kinase 2 (ROCK2) were downregulated several times as confirmed by quantitative reverse-transcription polymerase chain reaction and immunoblotting. Further research showed that Smad4 directly regulates ROCK2 transcription but indirectly regulates Syk. Megakaryocyte/platelet-specific Smad4 deficiency caused decreased expression levels of Syk and ROCK2 in platelets. These results suggest potential links among Smad4 deficiency, attenuated Syk, and ROCK2 expression and defective platelet activation.
Hybrid Technique for Java Code Complexity Analysis

Software complexity can be defined as the degree of difficulty in analysis, testing, design and implementation of software. Typically, reducing model complexity has a significant impact on maintenance activities. A lot of metrics have been used to measure the complexity of source code such as Halstead, McCabe Cyclomatic, Lines of Code, and Maintainability Index, etc. This paper proposed a hybrid module which consists of two theories which are Halstead and McCabe, both theories will be used to analyze a code written in Java. The module provides a mechanism to better evaluate the proficiency level of programmers, and also provides a tool which enables the managers to evaluate the programming levels and their enhancements over time. This will be known by discovering the various differences between levels of complexity in the code. If the program complexity level is low, then of the programmer professionalism level is high, on the other hand, if the program complexity level is high, then the programmer professionalism level is almost low. The results of the conducted experiments show that the proposed approach give very high and accurate evaluation for the undertaken systems.