Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhanced Chaos based Image Steganography using Edge Adaptive and Cat Mapping Techniques

is the science of hiding the messages in a medium. The existence of hidden messages remains imperceptible to the Intruders. The medium used for hiding the messages may be audio, video, text or images. The important goal of steganography is to protect the hidden message. There are many techniques to hide the payload in images. This will be achieved by applying different techniques in any medium. There are many techniques applied by the intruders to find the hidden information those techniques are called anti-steganalysis techniques. To provide the security to the payload after inserting the payload in to messages we need to do the anti steganalysis, if the hidden information is found then we need to provide the additional security. There is a need to build the system with highest security levels so that the anti steganalysis techniques can't find out the hidden information. In the proposed system there are certain areas which are suitable for hiding the payload are called Edges. Edges are good Regions of Interest or ROIs that are used for steganography. The proposed system uses edge adaptive image steganography (1) that uses the combinations of chaotic cat mapping (2) to provide additional security and matrix encoding (3) and LSBM (4) to embed the data in to image. The proposed mechanism guaranties the high imperceptibility and Fidelity which are the two important requirements for any Image steganography.
Purification and Characterization of a Novel NAD(P)+-Farnesol Dehydrogenase from Polygonum minus Leaves

Juvenile hormones have attracted attention as safe and selective targets for the design and development of environmentally friendly and biorational insecticides. In the juvenile hormone III biosynthetic pathway, the enzyme farnesol dehydrogenase catalyzes the oxidation of farnesol to farnesal. In this study, farnesol dehydrogenase was extracted from Polygonum minus leaves and purified 204-fold to apparent homogeneity by ion-exchange chromatography using DEAE-Toyopearl, SP-Toyopearl, and Super-Q Toyopearl, followed by three successive purifications by gel filtration chromatography on a TSK-gel GS3000SW. The enzyme is a heterodimer comprised of subunits with molecular masses of 65 kDa and 70 kDa. The optimum temperature and pH were 35°C and pH 9.5, respectively. Activity was inhibited by sulfhydryl reagents, metal-chelating agents and heavy metal ions. The enzyme utilized both NAD+ and NADP+ as coenzymes with K m values of 0.74 mM and 40 mM, respectively. Trans, trans-farnesol was the preferred substrate for the P. minus farnesol dehydrogenase. Geometrical isomers of trans, trans-farnesol, cis, trans-farnesol and cis, cis-farnesol were also oxidized by the enzyme with lower activity. The K m values for trans, trans-farnesol, cis, trans-farnesol and cis, cis-farnesol appeared to be 0.17 mM, 0.33 mM and 0.42 mM, respectively. The amino acid sequences of 4 tryptic peptides of the enzyme were analyzed by MALDI-TOF/TOF-MS spectrometry, and showed no significant similarity to those of previously reported farnesol dehydrogenases. These results suggest that the purified enzyme is a novel NAD(P)+-dependent farnesol dehydrogenase. The purification and characterization established in the current study will serve as a basis to provide new information for recombinant production of the enzyme. Therefore, recombinant farnesol dehydrogenase may provide a useful molecular tool in manipulating juvenile hormone biosynthesis to generate transgenic plants for pest control.
Non-Isomorphic Forest Pair Translation

This paper studies two issues, non-isomorphic structure translation and target syntactic structure usage, for statistical machine translation in the context of forest-based tree to tree sequence translation. For the first issue, we propose a novel non-isomorphic translation framework to capture more non-isomorphic structure mappings than traditional tree-based and tree-sequence-based translation methods. For the second issue, we propose a parallel space searching method to generate hypothesis using tree-to-string model and evaluate its syntactic goodness using tree-to-tree/tree sequence model. This not only reduces the search complexity by merging spurious-ambiguity translation paths and solves the data sparseness issue in training, but also serves as a syntax-based target language model for better grammatical generation. Experiment results on the benchmark data show our proposed two solutions are very effective, achieving significant performance improvement over baselines when applying to different translation models.
A Class of Frobenius Norm-Based Algorithms Using Penalty Term and Natural Gradient for Blind Signal Separation

We consider the blind signal separation (BSS) problem of instantaneous mixtures using penalty term and natural gradient. A class of Frobenius norm-based algorithms consisting of the offline/block processing (BP), online processing (OP) algorithms, and their normalized versions is proposed for separating nonstationary and nonwhite signals. The BP and OP algorithms, respectively, suitable for blind separation with offline and online data, are derived by using the nonstationarity and nonwhiteness of signals and the natural gradient method in conjunction with an appropriate penalty term. Associated with almost all algorithms employing a gradient method is a gradient noise problem. We thus develop, from BP and OP, their normalized versions in which the update of an unknown demixing matrix is based on the minimal disturbance principle. We show that the resulting updates are in the same direction as those of the original algorithms but with a scaling factor whose upper bound is unity. Algorithms using the nonstationarity and nonwhiteness properties have been proposed before but, due to the use of logarithms in their derivation, they are not capable of separating signals that are not persistently active and require regularization parameters to mitigate the problem. In this paper, the superior performance of the proposed algorithms to the previously proposed logarithm-based algorithms with and without regularization when separating nonpersistently active source signals is presented through some illustrative numerical experiments.
Toward Compassionate Action: Pragmatism and the Inseparability of Theory/Practice

Believing that the purpose of knowledge development and practice is compassionate action, in this article, we discuss how pragmatism can help us move toward that goal. Specifically, we show how pragmatic inquiry draws attention to the inseparability of practice/theory and the integral role practice experiences play in the ongoing development of theory. We demonstrate the utility of pragmatism to nursing by describing how we have explicitly approached theory development as a practical (and practice) activity of inquiry to attend to experiences of culture and diversity in family nursing.
Box consistency through adaptive shaving

The canonical algorithm to enforce box consistency over a constraint relies on a dichotomic process to isolate the leftmost and rightmost solutions. We identify some weaknesses of the standard implementations of this approach and review the existing body of work to tackle them; we then present an adaptive shaving process to achieve box consistency by tightening a domain from both bounds inward. Experimental results show a significant improvement over existing approaches in terms of robustness for difficult problems.
Phylogenetic Analysis of Astrovirus and Kobuvirus in Korean Dogs

ABSTRACT Astroviruses and kobuviruses are frequently found in mammalian feces, including that of humans. The present study examined fecal samples from 91 Korean dogs suffering from diarrhea. Canine astroviruses (CAstVs) and canine kobuviruses (CKoVs) were identified in 2 (2.1%) and 46 (50.6%) dogs, respectively. Nucleotide sequence analysis coupled with phylogenetic analysis using the neighbor-joining method showed that CAstVs clustered into four genetically diverse groups. Two Korean CAstVs belonged to group 2 alongside strains isolated in Italy and France. Twelve of the Korean CKoVs belonged to a single clade, along with strain UK003 identified in the UK and six CKoVs identified in the USA. Thus, the results suggest that the Korean strain of CAstV is closely related to strains isolated in Europe. Surely, CKoV in South Korea could identify the circulation among dogs population.
CmapTools: A Knowledge Modeling and Sharing Environment

Concept maps are an effective way of representing a person’s understanding of a domain of knowledge. Technology can further help by making it easy to construct and modify that representation, to manage large representations for complex domains, and to allow groups of people to share in the construction of the concept maps. CmapTools is a software environment developed at the Institute for Human and Machine Cognition (IHMC) that empowers users, individually or collaboratively, to represent their knowledge using concept maps, to share them with peers and colleagues, and to publish them. It is available for free for educational and not-for-profit organizations, and public servers have been established to promote the sharing of knowledge. The client-server architecture of CmapTools allows easy publishing of the knowledge models in concept map servers (CmapServers), and enables concept maps to be linked to related concept maps and to other types of media (e.g., images, videos, web pages, etc.) in other servers. The collaboration features enable remote users to asynchronously and/or synchronously collaborate in the construction of concept maps, and promote comments, criticism, and peer review. Public CmapServers have resulted in a large collection of knowledge models publicly available, constructed by users of all ages in a variety of domains of knowledge and from a large number of countries.
GENDER DIFFERENCES IN FACE RECOGNITION : THE ROLE

Women outperform men in face recognition and are especially good at recognizing other females’ faces. This may be caused by a larger female interest in faces. The aims of this study were to investigate if women were more interested in female faces and if depth of friendship was related to face recognition. Forty-one women and 16 men completed two face recognition tasks: one in which the faces shown earlier had been presented one at a time, and one where they had been shown two and two. The Network of Relationships Inventory was used to assess depth of friendships. As hypothesized, but not statistically significant, women tended to recognize more female faces when faces were presented two and two. No relationships were found between depth of friendships and face recognition. The results gave some support for the previously untested hypothesis that interest has importance in women’s recognition of female faces.
Effect of warming temperatures on US wheat yields

Significance This study provides insights for wheat breeding efforts, public policy, and agricultural decision making related to climate change. Our findings provide opportunities for the international wheat breeding community to intensify research efforts to increase resistance to heat stress during focused developmental stages. These efforts could result in net positive warming effects since reduced exposure to freeze was found to be a yield-enhancing benefit of warming. Our results indicate that advancements in heat resistance could come at the expense of higher average yields, and that there is currently limited scope for producer adaptation through alternative variety selection. Our results also suggest that irrigation could help mitigate the effects of warming, which has implications for policies focused on the conservation of increasingly scarce water resources. Climate change is expected to increase future temperatures, potentially resulting in reduced crop production in many key production regions. Research quantifying the complex relationship between weather variables and wheat yields is rapidly growing, and recent advances have used a variety of model specifications that differ in how temperature data are included in the statistical yield equation. A unique data set that combines Kansas wheat variety field trial outcomes for 1985–2013 with location-specific weather data is used to analyze the effect of weather on wheat yield using regression analysis. Our results indicate that the effect of temperature exposure varies across the September−May growing season. The largest drivers of yield loss are freezing temperatures in the Fall and extreme heat events in the Spring. We also find that the overall effect of warming on yields is negative, even after accounting for the benefits of reduced exposure to freezing temperatures. Our analysis indicates that there exists a tradeoff between average (mean) yield and ability to resist extreme heat across varieties. More-recently released varieties are less able to resist heat than older lines. Our results also indicate that warming effects would be partially offset by increased rainfall in the Spring. Finally, we find that the method used to construct measures of temperature exposure matters for both the predictive performance of the regression model and the forecasted warming impacts on yields.
From Genotype × Environment Interaction to Gene × Environment Interaction

Historically in plant breeding a large number of statistical models has been developed and used for studying genotype × environment interaction. These models have helped plant breeders to assess the stability of economically important traits and to predict the performance of newly developed genotypes evaluated under varying environmental conditions. In the last decade, the use of relatively low numbers of markers has facilitated the mapping of chromosome regions associated with phenotypic variability (e.g., QTL mapping) and, to a lesser extent, revealed the differetial response of these chromosome regions across environments (i.e., QTL × environment interaction). QTL technology has been useful for marker-assisted selection of simple traits; however, it has not been efficient for predicting complex traits affected by a large number of loci. Recently the appearance of cheap, abundant markers has made it possible to saturate the genome with high density markers and use marker information to predict genomic breeding values, thus increasing the precision of genetic value prediction over that achieved with the traditional use of pedigree information. Genomic data also allow assessing chromosome regions through marker effects and studying the pattern of covariablity of marker effects across differential environmental conditions. In this review, we outline the most important models for assessing genotype × environment interaction, QTL × environment interaction, and marker effect (gene) × environment interaction. Since analyzing genetic and genomic data is one of the most challenging statistical problems researchers currently face, different models from different areas of statistical research must be attempted in order to make significant progress in understanding genetic effects and their interaction with environment.
Impacts of Atmospheric Nitrogen Deposition and Coastal Nitrogen Fluxes on Oxygen Concentrations in Chesapeake Bay

Although rivers are the primary source of dissolved inorganic nitrogen (DIN) inputs to the Chesapeake Bay, direct atmospheric DIN deposition and coastal DIN concentrations on the continental shelf can also significantly influence hypoxia; however, the relative impact of these additional sources of DIN on Chesapeake Bay hypoxia has not previously been quantified. In this study, the estuarine-carbonbiogeochemistry model embedded in the Regional-Ocean-Modeling-System (ChesROMS-ECB) is used to examine the relative impact of these three DIN sources. Model simulations highlight that DIN from the atmosphere has roughly the same impact on hypoxia as the same gram-for-gram change in riverine DIN loading, although their spatial and temporal distributions are distinct. DIN concentrations on the continental shelf have a similar overall impact on hypoxia as DIN from the atmosphere (~0.2 mg L ); however, atmospheric DIN impacts dissolved oxygen (DO) primarily via the decomposition of autochthonous organic matter, whereas coastal DIN concentrations primarily impact DO via the decomposition of allochthonous organic matter entering the Bay mouth from the shelf. The impacts of atmospheric DIN deposition and coastal DIN concentrations on hypoxia are greatest in summer and occur farther downstream (southern mesohaline) in wet years than in dry years (northern mesohaline). Integrated analyses of the relative contributions of all three DIN sources on summer bottomDO indicate that impacts of atmospheric deposition are largest in the eastern mesohaline shoals, riverine DIN has dominant impacts in the largest tributaries and the oligohaline Bay, while coastal DIN concentrations are most influential in the polyhaline region. Plain Language Summary Most organisms living in the Chesapeake Bay, like fish, crabs, and oysters, need adequate oxygen concentrations to survive. However, general increases in the supply of nutrients to estuaries always enhance the production of algae, and the decomposition of these algae takes away oxygen from other organisms, resulting in hypoxic (low-oxygen) conditions or what is commonly referred to as a “dead zone. ” Generally, researchers focus on how terrestrial nutrients entering the bay, for example, from fertilizer, wastewater treatment, or sewer runoff, produce the Chesapeake Bay dead zone, since they account for most of the nutrients entering the bay. However, the atmospheric and oceanic nutrients directly impacting the bay are often not accurately considered. In this study the impacts of nutrients from the atmosphere and the open ocean on Chesapeake Bay hypoxia are quantified via the application of a three-dimensional ecosystemmodel. Atmospheric deposition of nitrate is found to have the same gram-for-gram impact on hypoxia as terrestrial nitrate entering via rivers. Overall, these two sources of nutrients have the greatest impact in the summer and have similar impacts on dissolved oxygen, reducing oxygen concentrations by up to 0.2 mg L 1 in the mid-Chesapeake Bay region where oxygen concentrations are lowest.
Integrating a Wiki in an Ontology Driven Web Site: Approach, Architecture and Application in the Archaeological Domain

This paper describes an approach to the design and implementation of ontology driven dynamic web sites combining ontologies and wiki technologies. The core of the architectural solution proposed is completely based on ontologies rather than on more traditional forms of persistent data storage facilities, such as relational databases. This approach provides a flexible support to the design and implementation of web portals in which navigation schemes are not entirely predetermined but are instead influenced by actual relationships among the contents of the ontology, that are used to generate web pages as well as hyperlinks. A wiki technology is integrated with this approach in order to create pages not directly derived by elements of the ontology, but also to enrich the textual contents with suitable formatting, images and hyperlinks. The application of this approach to the realization of a web portal is also described; the portal is devoted to enable a number of scientific communities to share archaeological knowledge about the Silk Road domain.
Evaluation of Recombinant Cytochrome P450 Enzymes as an in Vitro System for Metabolic Clearance Predictions

The aim of this study was to explore the potential of recombinant cytochrome P450 (P450) enzymes for human metabolic clearance prediction. The relative abundance and relative activity approaches were compared as methods to bridge the gap between catalytic activities in recombinant P450 enzymes and human liver microsomes (HLMs). Relative activity factors were measured by determining the intrinsic clearance (CLint) of probe substrates (bufuralol-CYP2D6, diclofenac-CYP2C9, midazolam-CYP3A4, and phenacetin-CYP1A2) in recombinant P450s and 16 HLM donors. Simultaneous determination of drug depletion and metabolite formation profiles has enabled a direct comparison of these methods for CLint determination. Of the 110 drugs tested, 66% were metabolized by one or more P450 enzymes; of these 44% of were metabolized by CYP3A4 (0.3–21 μl/min/pmol of P450), 41% by CYP2D6 (0.6–60 μl/min/pmol of P450), 26% by CYP2C19 (0.4–8.1 μl/min/pmol of P450), 9% by CYP1A2 (0.4–2.5 μl/min/pmol of P450), and 4% by CYP2C9 (0.9–6.4 μl/min/pmol of P450). Recombinant enzymes demonstrated improved prediction reliability relative to HLMs and hepatocytes. The most reliable correlations in terms of lowest bias and highest precision were observed by comparing in vivo CLint, calculated using the parallel-tube model and incorporating fraction unbound in blood, with in vitro CLint determined using relative activity factors and adjusted for nonspecific binding. Predictions were less reliable using the relative abundance approach. For these drugs, recombinant P450 enzymes offer improved assay sensitivity compared with HLMs and cryopreserved hepatocytes for CLint determination using the drug depletion method.
Implementing Scrum in a Distributed Software Development Organization

This paper describes the start of the implementation of Scrum within BMC Software (Identity Management business unit). It describes the project, the project structure and the first 18 months of the project with the impediments and solutions. The specific attention points addressed are around the work with distributed teams (team members of a single team in multiple countries, as well as whole teams in different countries). The size of the project at hand is significant: 50 people are involved, and the initial duration is estimated at 18 months.
Very short utterances in conversation

Faced with the difficulties of finding an operationalized definition of backchannels, we have previously proposed an intermediate, auxiliary unit ‐ the very short utterance (VSU) ‐ which is defined operationally and is automatically extractable from recorded or ongoing dialogues. Here, we extend that work in the following ways: (1) we test the extent to which the VSU/NONVSU distinction corresponds to backchannels/non-backchannels in a different data set that is manually annotated for backchannels ‐ the Columbia Games Corpus; (2) we examine to the extent to which VSUS capture other short utterances with a vocabulary similar to backchannels; (3) we propose a VSU method for better managing turn-taking and barge-ins in spoken dialogue systems based on detection of backchannels; and (4) we attempt to detect backchannels with better precision by training a backchannel classifier using durations and inter-speaker relative loudness differences as features. The results show that VSUS indeed c apture a large proportion of backchannels ‐ large enough that VSUs can be used to improve spoken dialogue system turntaking; and that building a reliable backchannel classifier working in real time is feasible.