Miracle-dz/UniFAR-FTUs huggingface dataset:
Image vignetting reduction via a maximization of fuzzy entropy

In many computer vision applications, vignetting is an undesirable effect which must be removed in a pre-processing step. Recently, an algorithm for image vignetting correction has been presented by means of a minimization of log-intensity entropy. This method relies on an increase of the entropy of the image when it is affected with vignetting. In this paper, we propose a novel algorithm to reduce image vignetting via a maximization of the fuzzy entropy of the image. Fuzzy entropy quantifies the fuzziness degree of a fuzzy set and its value is also modified by the presence of vignetting. The experimental results show that this novel algorithm outperforms in most cases the algorithm based on the minimization of log-intensity entropy both from the qualitative and the quantitative point of view.
System identification and model predictive control design of toner supply system of photocopier

This paper deals with modeling and control systems design of a toner supply system of photocopiers. It is important to keep an image of the photocopier constant during printing. To realize the requirement, it is necessary to control the amount of the toner attracting to the paper. This paper proposes a design method of the toner supply control system. First, the printing process is divided to two components, that is, the toner supply system and development system. System identification method is applied to these systems in consideration of physical characteristics of the systems. Second, the toner supply control system is designed by model predictive control (MPC). Finally, the effectiveness of the proposed method is examined by using the experimental data using a photocopier.
Graph model selection using maximum likelihood

In recent years, there has been a proliferation of theoretical graph models, e.g., preferential attachment and small-world models, motivated by real-world graphs such as the Internet topology. To address the natural question of which model is best for a particular data set, we propose a model selection criterion for graph models. Since each model is in fact a probability distribution over graphs, we suggest using Maximum Likelihood to compare graph models and select their parameters. Interestingly, for the case of graph models, computing likelihoods is a difficult algorithmic task. However, we design and implement MCMC algorithms for computing the maximum likelihood for four popular models: a power-law random graph model, a preferential attachment model, a small-world model, and a uniform random graph model. We hope that this novel use of ML will objectify comparisons between graph models.
Multi-Population Cooperative GA and Multi-Objective Knapsack Problem

The knapsack problem (KP) is a classical NP problem. The multi-objective knapsack problem (MKP) is more difficult than KP. The fitness vector function is firstly introduced, that can solve the problem of non-convex solutions, which is difficult for the common aggregation function method. Then, with the master-slave multi-population cooperation method, the cooperation between the global exploration and local development is improved, so the multi-objective multi-population cooperative GA (MMGA) posed in this paper enhances also the optimization ability of GA. The experiment result shows, MMGA is superior to NSGAII for MKP. Furthermore, with the both of master-slave multi-population cooperation and the mechanism of holding non-dominate solutions, the premature and degradation phenomena are effectively prevent.
Journal of Graph Algorithms and Applications a Multilevel Algorithm for the Minimum 2-sum Problem

In this paper we introduce a direct motivation for solving the minimum 2-sum problem, for which we present a linear-time algorithm inspired by the Algebraic Multigrid approach which is based on weighted edge contraction. Our results turned out to be better than previous results, while the short running time of the algorithm enabled experiments with very large graphs. We thus introduce a new benchmark for the minimum 2-sum problem which contains 66 graphs of various characteristics. In addition, we propose the straightforward use of a part of our algorithm as a powerful local reordering method for any other (than multilevel) framework.
MPACT Family Trees: Quantifying Academic Genealogy in Library and Information Science

Academic genealogy is valuable because it provides context, history and has the potential to predict future trends in a particular discipline or field. However, it is most commonly done casually and without the rigor to provide a platform for discussion beyond the anecdote. This paper presents a novel technique for calculating genealogical scores for individuals and academic "families. " This data-driven technique provides a platform for greater contextualization and insight into an academic's legacy. Implemented widely, this technique could provide significant insight into mentorship as a valued addition to the traditional academic metrics of teaching, scholarship, and service.
Community Engagement: Talking about mathematics

Implementing assessment into early childhood (EC) undergraduate courses necessitates supporting learners in informed and intentional ways; since knowing how to teach comes from within the act of teaching itself. Consequently their practical knowledge builds through deliberate events which stimulate further insight and skill in what they do. Taken-for-granted assumptions that undergraduate students bring to the classroom can be challenged in such ways that they make implicit ideas explicit subsequently changing them to correspond with their new practices. Students can “test” out alternative approaches in real classroom contexts and then refine their own practical knowledge through reflection.
Representing information in patient reports using natural language processing and the extensible markup language.

OBJECTIVE To design a document model that provides reliable and efficient access to clinical information in patient reports for a broad range of clinical applications, and to implement an automated method using natural language processing that maps textual reports to a form consistent with the model. METHODS A document model that encodes structured clinical information in patient reports while retaining the original contents was designed using the extensible markup language (XML), and a document type definition (DTD) was created. An existing natural language processor (NLP) was modified to generate output consistent with the model. Two hundred reports were processed using the modified NLP system, and the XML output that was generated was validated using an XML validating parser. RESULTS The modified NLP system successfully processed all 200 reports. The output of one report was invalid, and 199 reports were valid XML forms consistent with the DTD. CONCLUSIONS Natural language processing can be used to automatically create an enriched document that contains a structured component whose elements are linked to portions of the original textual report. This integrated document model provides a representation where documents containing specific information can be accurately and efficiently retrieved by querying the structured components. If manual review of the documents is desired, the salient information in the original reports can also be identified and highlighted. Using an XML model of tagging provides an additional benefit in that software tools that manipulate XML documents are readily available.
Divergent evolution peaks under intermediate population bottlenecks during bacterial experimental evolution

There is growing evidence that parallel molecular evolution is common, but its causes remain poorly understood. Demographic parameters such as population bottlenecks are predicted to be major determinants of parallelism. Here, we test the hypothesis that bottleneck intensity shapes parallel evolution by elucidating the genomic basis of adaptation to antibiotic-supplemented media in hundreds of populations of the bacterium Pseudomonas fluorescens Pf0-1. As expected, bottlenecking decreased the rate of phenotypic and molecular adaptation. Surprisingly, bottlenecking had no impact on the likelihood of parallel adaptive molecular evolution at a genome-wide scale. However, bottlenecking had a profound impact on the genes involved in antibiotic resistance. Specifically, under either intense or weak bottlenecking, resistance predominantly evolved by strongly beneficial mutations which provide high levels of antibiotic resistance. In contrast with intermediate bottlenecking regimes, resistance evolved by a greater diversity of genetic mechanisms, significantly reducing the observed levels of parallel genetic evolution. Our results demonstrate that population bottlenecking can be a major predictor of parallel evolution, but precisely how may be more complex than many simple theoretical predictions.
Gene Overexpression Resources in Cereals for Functional Genomics and Discovery of Useful Genes

Identification and elucidation of functions of plant genes is valuable for both basic and applied research. In addition to natural variation in model plants, numerous loss-of-function resources have been produced by mutagenesis with chemicals, irradiation, or insertions of transposable elements or T-DNA. However, we may be unable to observe loss-of-function phenotypes for genes with functionally redundant homologs and for those essential for growth and development. To offset such disadvantages, gain-of-function transgenic resources have been exploited. Activation-tagged lines have been generated using obligatory overexpression of endogenous genes by random insertion of an enhancer. Recent progress in DNA sequencing technology and bioinformatics has enabled the preparation of genomewide collections of full-length cDNAs (fl-cDNAs) in some model species. Using the fl-cDNA clones, a novel gain-of-function strategy, Fl-cDNA OvereXpressor gene (FOX)-hunting system, has been developed. A mutant phenotype in a FOX line can be directly attributed to the overexpressed fl-cDNA. Investigating a large population of FOX lines could reveal important genes conferring favorable phenotypes for crop breeding. Alternatively, a unique loss-of-function approach Chimeric REpressor gene Silencing Technology (CRES-T) has been developed. In CRES-T, overexpression of a chimeric repressor, composed of the coding sequence of a transcription factor (TF) and short peptide designated as the repression domain, could interfere with the action of endogenous TF in plants. Although plant TFs usually consist of gene families, CRES-T is effective, in principle, even for the TFs with functional redundancy. In this review, we focus on the current status of the gene-overexpression strategies and resources for identifying and elucidating novel functions of cereal genes. We discuss the potential of these research tools for identifying useful genes and phenotypes for application in crop breeding.
A compositional, knowledge-based architecture for intelligent query user interfaces

The design of a user interface to intelligently intermediate between the user and a DB query system, based on a modular, knowledge-based generic architecture is to be discussed. The main principles concerning the user interface design are: identification of the essential (1) tasks of intelligent intermediation and (2) (meta-)knowledge as the basis of performing these tasks, but also (3) active role for the user in the strategic decisions of the tasks. The resulting user interface architecture is transparent, easily adaptable, and makes it possible to model strategic interaction with the user as well.
Explicit verses implicit: an analysis of a multiple search result visualization

When searching on the Web, users often reformulate their queries after viewing the results and viewing some of the pages. After one or two reformulations the user may implicitly realize patterns and relationships between the multiple search results. We believe that these patterns can be used to identify interesting results. We have developed the prototype Search Engine Similarity (SES) tool which explicitly visualizes the similarity between multiple searches. We describe an experiment to determine whether explicitly visualizing the relationships between multiple searches will let users browse more effectively. Our results show that explicit difference visualizations can enhance the search process for some tasks.
Plasma Membrane Ca2+-ATPase 4 in Murine Epididymis: Secretion of Splice Variants in the Luminal Fluid and a Role in Sperm Maturation1

ABSTRACT Plasma membrane Ca2+-ATPase isoform 4 (PMCA4) is the primary Ca2+ efflux pump in murine sperm, where it regulates motility. In Pmca4 null sperm, motility loss results in infertility. We have shown that murine sperm PMCA4b interacts with Ca2+/CaM-dependent serine kinase (CASK) in regulating Ca2+ homeostasis and motility. However, recent work indicated that the bovine PMCA4a splice variant (missing in testis) is epididymally expressed, along with 4b, and may be transferred to sperm. Here we show, via conventional and in situ RT-PCR, that both the splice variants of Pmca4 mRNA are expressed in murine testis and throughout the epididymis. Immunofluorescence localized PMCA4a to the apical membrane of the epididymal epithelium, and Western analysis not only confirmed its presence but showed for the first time that PMCA4a and PMCA4b are secreted in the epididymal luminal fluid (ELF), from which epididymosomes containing PMCA4a were isolated. Flow cytometry indicated the presence of PMCA4a on mature caudal sperm where it was increased ∼5-fold compared to caput sperm (detected by Western blotting) and ∼2-fold after incubation in ELF, revealing in vitro uptake and implicating PMCA4a in epididymal sperm maturation. Coimmunoprecipitation using pan-PMCA4 antibodies, revealed that both variants associate with CASK, suggesting their presence in a complex. Because they have different kinetic properties for Ca2+ transport and different abilities to bind to CASK, our study suggests a mechanism for combining the functional attributes of both PMCA4 variants, leading to heightened efficiency of the pump in the maintenance of Ca2+ homeostasis, which is crucial for normal motility and male fertility.
Relapse after cognitive behavior therapy of depression: potential implications for longer courses of treatment.

OBJECTIVE The authors studied the risk of relapse among depressed patients after cognitive behavior therapy in order to document the need and potential indications for longer-term models of treatment. METHOD Forty-eight patients with major depression who responded during a 16-week course of cognitive behavior therapy entered a 1-year prospective follow-up study, as did two patients who received 20 weeks of therapy. Standardized, independent clinical assessments were completed 1, 3, 6, 9, and 12 months after treatment. Relapse was defined as, at minimum, a 2-week period in which the subject met the DSM-III-R criteria for major depression and had a Hamilton depression scale score of 15 or more. RESULTS Sixteen patients (32%) relapsed during the 1-year follow-up. Correlates of relapse included a history of depressive episodes, higher levels of depressive symptoms and dysfunctional attitudes, slower response to therapy, and being unmarried. Patients who fully recovered during therapy (Hamilton depression score of 6 or less for 8 weeks or more) were at significantly lower risk for relapse than those who partially recovered (9% and 52%, respectively). Slower response to therapy, unmarried status, and high residual scores on the Dysfunctional Attitudes Scale were independently and additively related to increased risk of relapse. CONCLUSIONS These findings provide further evidence of a relation between residual symptoms and relapse after cessation of active treatment. The authors strongly recommend that models of longer-term psychotherapy be developed for depressed patients who do not recover fully during time-limited cognitive behavior therapy.
Multiclass On-demand routing in heterogeneous ad hoc networks

In this article, Ad hoc On-demand Distance Vector (AODV) routing protocol is modified to introduce a multiclass on-demand routing mechanism for ad hoc networks. The proposed protocol supports two distinct traffic classes, realtime traffic and non-realtime traffic. The anticipated protocol also takes into account the heterogeneity of the network while making the routing decisions, i.e. the yielded routes may comprise of dissimilar link layers. These modifications are implemented and evaluated on an actual ad hoc network testbed comprising of eight mobile nodes.
Vascular Smooth Muscle Cell Apoptosis Induces Interleukin-1–Directed Inflammation: Effects of Hyperlipidemia-Mediated Inhibition of Phagocytosis

Rationale: Atherosclerosis is characterized by lipid accumulation in the vessel wall, inflammation, and both macrophage and vascular smooth muscle cell (VSMC) apoptosis. However, whereas VSMC apoptosis in mice with established atherosclerotic plaques or hyperlipidemia increases serum levels of the proatherogenic cytokines monocyte chemotactic protein (MCP)-1, tumor necrosis factor &agr;, and interleukin (IL)-6, the link between hyperlipidemia, apoptosis and inflammation, and the mechanisms by which apoptotic cells promote inflammation in atherosclerosis are unknown. Objective: To determine whether hyperlipidemia affects apoptotic cell clearance, and identify the molecular pathways downstream of VSMC apoptosis that may promote inflammation. Methods and Results: We find that human VSMCs are potent and efficient phagocytes of apoptotic human VSMCs, but phagocytosis is significantly reduced by oxidized low-density lipoprotein in vitro or hyperlipidemia in vivo. Necrotic human aortic VSMCs release IL-1&agr;, which induces IL-6 and MCP-1 production from viable human VSMCs in vitro. In contrast, secondary necrotic VSMCs release both IL-1&agr; and caspase-activated IL-1&bgr;, augmenting IL-6 and MCP-1 production. Conditionally inducing VSMC apoptosis in situ in hyperlipidemic SM22&agr;-hDTR/ApoE−/− mice to levels seen in human plaques increases serum MCP-1, tumor necrosis factor &agr;, and IL-6, which is prevented by blocking IL-1. Conclusions: We conclude that VSMC necrosis releases IL-1&agr;, whereas secondary necrosis of apoptotic VSMCs releases both IL-1&agr; and &bgr;. IL-1 from necrotic VSMCs induces the surrounding viable VSMCs to produce proinflammatory cytokines. Thus, failed clearance of apoptotic VSMCs caused by hyperlipidemia in vivo may promote the increased serum cytokines and chronic inflammation associated with atherosclerosis.
Angiogenesis in salivary gland tumors: from clinical significance to treatment

Introduction: Salivary gland tumors (SGTs) represent a rare cancer entity, consisting of various morphological features that complicate diagnosis. Their diversity in terms of morphology and clinical course makes defining risk factors difficult, while the molecular steps responsible for SGT development remain unclear. Angiogenesis, a hallmark of cancer development, is considered as an attractive target. Areas covered: This review aims to summarize the available research regarding angiogenesis in SGTs from clinical significance to treatment options. Expert opinion: The available data suggest that microvessel density (MVD) evaluation may be capable of discriminating between benign and malignant SGTs, while the use of CD105 antibody seems to be the most suitable. Substantial evidence also suggests that MVD and VEGF expression could be used as prognostic factors in malignant SGTs. Although several agents have shown antiangiogenic activities in adenoid cystic carcinoma cells and xenograft tumors, limited effectiveness in the existing clinical trials was noted. Further studies are strongly recommended for the validation of already well-known and the identification of novel prognostic and predictive angiogenic markers. There is also a strong demand for relatively larger cohorts, homogenous samples referring to same histological SGT subtypes and including an equivalent number of low- and high-grade SGTs.
Insights from ecological niche modeling on the taxonomic distinction and niche differentiation between the black-spotted and red-spotted tokay geckoes (Gekko gecko)

The black-spotted tokay and the red-spotted tokay are morphologically distinct and have largely allopatric distributions. The black-spotted tokay is characterized by a small body size and dark skin with sundry spots, while the red-spotted tokay has a relatively large body size and red spots. Based on morphological, karyotypic, genetic, and distribution differences, recent studies suggested their species status; however, their classifications remain controversial, and additional data such as ecological niches are necessary to establish firm hypotheses regarding their taxonomic status. We reconstructed their ecological niches models using climatic and geographic data. We then performed niche similarity tests (niche identity and background tests) and point-based analyses to explore whether ecological differentiation has occurred, and whether such differences are sufficient to explain the maintenance of their separate segments of environmental ranges. We found that both niche models of the black- and the red-spotted tokay had a good fit and a robust performance, as indicated by the high area under the curve (AUC) values (“black” = 0.982, SD = ± 0.002, “red” = 0.966 ± 0.02). Significant ecological differentiation across the entire geographic range was found, indicating that the involvement of ecological differentiation is important for species differentiation. Divergence along the environmental axes is highly associated with climatic conditions, with isothermality being important for the “black” form, while temperature seasonality, precipitation of warmest quarter, and annual temperature range together being important for the “red” form. These factors are likely important factors in niche differentiation between the two forms, which result in morphological replacement. Overall, beside morphological and genetic differentiation information, our results contribute to additional insights into taxonomic distinction and niche differentiation between the black- and the red-spotted tokay.
Evaluation of Correlation Measures for Computationally-Light vs . Computationally-Heavy Centrality Metrics on Real-World Graphs

We identify three different levels of correlation (pairwise relative ordering, network-wide ranking and prediction through linearity) that could be assessed between a computationally-light centrality metric and a computationally-heavy centrality metric for real-world networks. The Kendall's concordance-based correlation measure could be used to quantitatively assess how well we could consider the relative ordering of two vertices vi and vj with respect to a computationally-light centrality metric as the relative ordering of the same two vertices with respect to a computationally-heavy centrality metric. We hypothesize that the pair-wise relative ordering (concordance)-based assessment of the correlation between centrality metrics is the strictest of all three levels of correlation and claim that the Kendall's concordance-based correlation coefficient will be lower than the correlation coefficient observed with the more relaxed levels of correlation measures (prediction through linearity-based Pearson's product-moment correlation coefficient and the network wide ranking-based Spearman's correlation coefficient). We validate our hypothesis by evaluating the three correlation coefficients between two sets of centrality metrics: the computationally-light degree and local clustering coefficient complement-based degree centrality metrics and the computationally-heavy eigenvector centrality, betweenness centrality and closeness centrality metrics for a diverse collection of 50 real-world networks.