Miracle-dz/UniFAR-FTUs huggingface dataset:
Randomised controlled short-term intervention pilot study on rye bran bread in prostate cancer

The short-term effects of rye bran bread intake in prostate cancer were investigated. Ten men with conservatively treated prostate cancer were randomised to a daily supplement of 295 g of rye bran bread and eight men to 275 g of wheat bread (control) with similar fibre content for three weeks. Blood samples, ultrasound-guided core biopsies of the prostate, and urine samples were taken. In the rye group, there was a significant increase in plasma enterolactone, and the apoptotic index increased significantly from 2.1% (SD 1.3) to 5.9% (SD 1.8), P<0.005 as measured by a TUNEL index in four cases in the rye group and seven cases in the control group. Besides a significant decrease in weight in both groups, only small changes were observed in plasma concentrations of prostate specific antigen (PSA), circulating sex hormones, excreted oestrogens, insulin-like growth factor (IGF)-I, and in the endothelial fibrinolytical system. High intake of rye bran bread is suggested to increase apoptosis in prostate tumours.
The Impact of Feature Selection on Defect Prediction Performance: An Empirical Comparison

Software defect prediction aims to determine whether a software module is defect-prone by constructing prediction models. The performance of such models is susceptible to the high dimensionality of the datasets that may include irrelevant and redundant features. Feature selection is applied to alleviate this issue. Because many feature selection methods have been proposed, there is an imperative need to analyze and compare these methods. Prior empirical studies may have potential controversies and limitations, such as the contradictory results, usage of private datasets and inappropriate statistical test techniques. This observation leads us to conduct a careful empirical study to reinforce the confidence of the experimental conclusions by considering several potential source of bias, such as the noise in the dataset and the dataset types. In this paper, we investigate the impact of 32 feature selection methods on the defect prediction performance over two versions of the NASA dataset (i.e., the noisy and clean NASA datasets) and one open source AEEEM dataset. We use a state-of-the-art double Scott-Knott test technique to analyze these methods. Experimental results show that the effectiveness of these feature selection methods on defect prediction performance varies significantly over all the datasets.
Measuring inter-site engagement

Many large online providers offer a variety of content sites (e.g. news, sport, e-commerce). These providers endeavor to keep users accessing and interacting with their sites, that is to engage users by spending time using their sites and to return regularly to them. They do so by serving users the most relevant content in an attractive and enticing manner. Due to their highly varied content, each site is usually studied and optimized separately. However, these online providers aim not only to engage users with individual sites, but across all sites in their network. In these cases, site engagement should be examined not only within individual sites, but also across the entire content provider network. This paper investigates intersite engagement, that is, site engagement within a network of sites, by defining a global measure of engagement that captures the effect sites have on the engagement on other sites. As an application, we look at the effect of web page layout and structure, which we refer to as web page stylistics, on intersite engagement on Yahoo! properties. Through the analysis of 50 popular Yahoo! sites and a sample of 265,000 users and 19.4M online sessions, we demonstrate that the stylistic components of a web page on a site can be used to predict inter-site engagement across the Yahoo! network of sites. Intersite engagement is a new big data problem as overall it implies analyzing dozen of sites visited by hundreds of millions of people generating billions of sessions.
Factors Affecting Consumers' Value Creation in Online Group Buying

Drawing upon the social capital theory (SCT), this study integrates social capital factors with the perspectives of consumer hedonic participation and platform capability of online group buying sites to explore how they affect consumer value creation toward online group buying (OGB). Data from 663 valid responses were obtained using an online large-scale survey. The conceptual framework was validated by using the partial least squares (PLS) technique. The research findings show that 1) the consumers’ value created by engaging in OGB is contributed collectively by social capital factors (i.e., social interaction tie, trust, and shared value), hedonic participation and OGB platform capabilities; 2) the social capital enhances consumers’ value creation by increasing their hedonic participation; 3) The OGB platform capabilities has a positive impact on social capital, hedonic participation and value creation. The proposed research model explains 64.1 % of variance for consumers’ value creation, 52.6 % of variance for their hedonic participation and 46.1% of variance for social capital in OGB. Our findings provide insights into how OGB administrators can govern OGB initiatives to expand OGB members’ social capital and OGB platform capability, thereby leading to effective consumer value creation.
Protocol Coding through Reordering of User Resources, Part II: Practical Coding Strategies

We use the term protocol coding to denote the communication strategies in which information is encoded through the actions taken by a certain communication protocol. In this work we investigate strategies for protocol coding via combinatorial ordering of the labelled user resources (packets, channels) in an existing, primary system. This introduces a new, secondary communication channel in the existing system, which has been considered in the prior work exclusively in a steganographic context. Instead, we focus on the use of secondary channel for reliable communication with newly introduced secondary devices, that are low-complexity versions of the primary devices, capable only to decode the robustly encoded header information in the primary signals. In Part I of the work we have characterized the capacity of the secondary channel through information-theoretic analysis. In this paper we consider practical strategies for protocol coding inspired by the information-theoretic analysis. It turns out that the insights from Part I are instrumental for devising superior design of error-control codes. This is demonstrated by comparing the error performance to the "na"{\i}ve" strategy which is presumably available without carrying out the analysis in Part I. These results are clearly outlining both the conceptual novelty behind the discussed concept of secondary channel as well as its practical applicability.
Impacts of extreme climatic events on the energetics of long-lived vertebrates: the case of the greater flamingo facing cold spells in the Camargue

Most studies analyzing the effects of global warming on wild populations focus on gradual temperature changes, yet it is also important to understand the impact of extreme climatic events. Here we studied the effect of two cold spells (January 1985 and February 2012) on the energetics of greater flamingos (Phoenicopterus roseus) in the Camargue (southern France). To understand the cause of observed flamingo mass mortalities, we first assessed the energy stores of flamingos found dead in February 2012, and compared them with those found in other bird species exposed to cold spells and/or fasting. Second, we evaluated the monthly energy requirements of flamingos across 1980–2012 using the mechanistic model Niche Mapper™. Our results show that the body lipids of flamingos found dead in 2012 corresponded to 2.6±0.3% of total body mass, which is close to results found in woodcocks (Scolopax rusticola) that died from starvation during a cold spell (1.7±0.1%), and much lower than in woodcocks which were fed throughout this same cold spell (13.0±2%). Further, Niche Mapper™ predicted that flamingo energy requirements were highest (+6–7%) during the 1985 and 2012 cold spells compared with ‘normal’ winters. This increase was primarily driven by cold air temperatures. Overall, our findings strongly suggest that flamingos starved to death during both cold spells. This study demonstrates the relevance of using mechanistic energetics modelling and body condition analyses to understand and predict the impact of extreme climatic events on animal energy balance and winter survival probabilities.
The nonchromatin substructures of the nucleus: the ribonucleoprotein (RNP)-containing and RNP-depleted matrices analyzed by sequential fractionation and resinless section electron microscopy

The nonchromatin structure or matrix of the nucleus has been studied using an improved fractionation in concert with resinless section electron microscopy. The resinless sections show the nucleus of the intact cell to be filled with a dense network or lattice composed of soluble proteins and chromatin in addition to the structural nuclear constituents. In the first fractionation step, soluble proteins are removed by extraction with Triton X-100, and the dense nuclear lattice largely disappears. Chromatin and nonchromatin nuclear fibers are now sharply imaged. Nuclear constituents are further separated into three well-defined, distinct protein fractions. Chromatin proteins are those that require intact DNA for their association with the nucleus and are released by 0.25 M ammonium sulfate after internucleosomal DNA is cut with DNAase I. The resulting structure retains most heterogeneous nuclear ribonucleoprotein (hnRNP) and is designated the RNP-containing nuclear matrix. The proteins of hnRNP are those associated with the nucleus only if RNA is intact. These are released when nuclear RNA is briefly digested with RNAase A. Ribonuclease digestion releases 97% of the hnRNA and its associated proteins. These proteins correspond to the hnRNP described by Pederson (Pederson, T., 1974, J. Mol. Biol., 83:163- 184) and are distinct from the proteins that remain in the ribonucleoprotein (RNP)-depleted nuclear matrix. The RNP-depleted nuclear matrix is a core structure that retains lamins A and C, the intermediate filaments, and a unique set of nuclear matrix proteins (Fey, E. G., K. M. Wan, and S. Penman, 1984, J. Cell Biol. 98:1973- 1984). This core had been previously designated the nuclear matrix- intermediate filament scaffold and its proteins are a third, distinct, and nonoverlapping subset of the nuclear nonhistone proteins. Visualizing the nuclear matrix using resinless sections shows that nuclear RNA plays an important role in matrix organization. Conventional Epon-embedded electron microscopy sections show comparatively little of the RNP-containing and RNP-depleted nuclear matrix structure. In contrast, resinless sections show matrix interior to be a three-dimensional network of thick filaments bounded by the nuclear lamina. The filaments are covered with 20-30-nm electron dense particles which may contain the hnRNA. The large electron dense bodies, enmeshed in the interior matrix fibers, have the characteristic morphology of nucleoli. Treatment of the nuclear matrix with RNAase results in the aggregation of the interior fibers and the extensive loss of the 20-30-nm particles. (ABSTRACT TRUNCATED AT 400 WORDS)
Cohesin: It's Functions and Relevance to Cancer

Oncogene mutations, inactivation of tumor suppressor genes and chromosome instability are classic features of cancer. The sister chromatid cohesion complex, known as cohesin, is conserved among eukaryotes and is essential for efficient chromosome segregation. In this review, we focus on the key findings about cohesin biology and how cohesin misregulation can be deleterious.
Ensemble of One-Class Classifiers for Network Intrusion Detection System

To achieve high accuracy while lowering false alarm rates are major challenges in designing an intrusion detection system. In addressing this issue, this paper proposes an ensemble of one-class classifiers where each uses different learning paradigms. The techniques deployed in this ensemble model are; linear genetic programming (LGP), adaptive neural fuzzy inference system (ANFIS) and random forest (RF). The strengths from the individual models were evaluated and ensemble rule was formulated. Empirical results show an improvement in detection accuracy for all classes of network traffic; normal, probe, DoS, U2R and R2L. RF, which is an ensemble learning technique that generates many classification trees and aggregates the individual result was also able to address imbalance dataset problem that many of machine learning techniques fail to sufficiently address it.
Efficient registration via fingerprints combination

This is a novel system, for protecting fingerprint privacy by combining two different fingerprints into a new identity. Fingerprint registration is a critical step in fingerprint matching and validation. Fingerprint registration process, makes fingerprint combination template as new identity. In the enrollment phase or the registration phase of fingerprint combination registration, two fingerprints are captured from two different fingers. Then extract the minutiae features like ridge ending and bifurcation, from one fingerprint based on cross numbering method, orientation from other fingerprint using gradient method and the reference point from both fingerprints using complex filtering convolution operator. Based on these extracted information's and coding strategy 1, accompanied minutiae template is generated and stored in a database with the user information. By storing combined minutiae template, the complete minutiae features of a single fingerprint will not be compromised when the database is stolen. Because of the similarity in topology, it is difficult for attacker to distinguish a combined minutiae template from the original minutiae template. Then by using matching score estimation method calculate the matching score value between two templates. The experimental result shows correlation between same and different fingers and statistical measures of two fingerprints and combined minutiae template.
Reduction of genuine and imposter score overlapping based on intra-class variations and deviation of scores in a multimodal biometrie system

Many score normalization and transformation techniques [2, 4, 13] have been introduced in score level fusion of multimodal biometric traits for enhanced authentication and security. Such normalization techniques help in fusing heterogeneous scores at matching score level. This paper represents a novel approach which produces distributed scores without application of normalization and quantization techniques thus eliminating the overhead of such algorithms. The proposed method considers real time face vibrations and intra-class variations in face modality. It has been observed that standard deviation of genuine scores and standard deviation of imposter scores for continuous stream of face inputs distributes the scores and eliminates the problem of overlapping. Standard deviation of genuine scores and standard deviation of imposter scores are sufficient for face modality and can be scaled to a new score by scalar weight multiplication for further fusion with other biometric trait scores. The proposed algorithm of standard deviation algorithm improves GAR significantly and reduces FAR to an extremely mitigated value as desired.
Immobilization and stabilization of papain on chelating sepharose: a metal chelate regenerable carrier

A method for immobilization of papain has been selected based on the interaction between its histidine, cysteine and tryptophan residues with the immobilized metal ion (IMI) carrier for maximum binding on a small volume of the carrier. The immobilized papain retained high activity has improved thermal stability and the carrier could be recovered from the spent bound enzyme, to be reused. Reimmobilization of papain on the regenerated matrix was equally effective with the retention of maximum enzyme activity.
The role of self-disclosure in human-robot interaction

The act of revealing personal information, thoughts, and feelings is known as self-disclosure. Self-disclosure represents an important determinant of liking and is central to the development of close relationships among humans. The present study aimed to investigate the role of self-disclosure in human-robot interaction (HRI). 81 participants were randomly assigned to one of four experimental conditions in which they interacted with the humanoid robot NAO. We manipulated whether the robot disclosed personal information or whether the robot asked personal questions to the human interaction partner, so that the participant had to self-disclose. In two control conditions the robot either made factual statements or the robot asked factual questions. Contrary to the hypotheses, the results indicated no immediate statistically significant effects of self-disclosure on the dependent variables robot likability, human-robot interaction quality, future contact intentions, and mind attribution. However, when taking into account participants' tendency to anthropomorphize technology, nature, and the animal world as a covariate, self-disclosure was found to significantly affect participants' tendency to attribute mind to NAO. Furthermore, the results indicate that the form of engagement and dominance in an interaction (i.e., being in the role of a passive listener vs. conversing actively) may affect perceived HRI more than does the content of the verbal exchange. Thus, the paper highlights the importance of considering covariates (i.e., interindividual differences in the tendency to anthropomorphize nonhuman entities) in HRI analyses and points out possible relevant moderators of self-disclosure in HRI.
Human p53 Is Phosphorylated on Serines 6 and 9 in Response to DNA Damage-inducing Agents*

To characterize the sites in human p53 that become phosphorylated in response to DNA damage, we have developed polyclonal antibodies that recognize p53 only when it is phosphorylated at specific sites. Several attempts to generate an antibody to p53 phosphorylated at Ser6 using a phosphoserine-containing peptide as an immunogen were unsuccessful; however, phosphorylation-specific antibodies were produced by using the phosphoserine mimetic,l-2-amino-4-phosphono-4,4-difluorobutanoic acid (F2Pab), in place of phosphoserine. Fmoc-F2Pab was prepared by an improved synthesis and chemically incorporated using solid phase peptide synthesis. Affinity-purified antibodies elicited by immunizing rabbits with an F2Pab peptide coupled to keyhole limpet hemocyanin recognized a p53(1–39) peptide phosphorylated only at Ser6 but not the unphosphorylated peptide or the same peptide phosphorylated at Ser9, Ser15, Ser20, Ser33, or Ser37. Untreated A549 cells exhibited a background of constitutive phosphorylation at Ser6 that increased approximately 10-fold upon exposure to either ionizing radiation or UV light. Similar results were obtained for Ser9 using antibodies raised against a conventional phosphopeptide. Ser9 was phosphorylated by casein kinase 1in vitro in a phosphoserine 6-dependent manner. Our data identify two additional DNA damage-induced phosphorylations in human p53 and show that F2Pab-derivatized peptides can be used to develop phosphorylation site-specific polyclonal antibodies.
Healthcare Quality: A Concept Analysis

Worsening quality indicators of health care shake public trust. Although safety and quality of care in hospitals can be improved, healthcare quality remains conceptually and operationally vague. Therefore, the aim of this analysis is to clarify the concept of healthcare quality. Walker and Avant's method of concept analysis, the most commonly used in nursing literature, provided the framework. We searched general and medical dictionaries, public domain websites, and 5 academic literature databases. Search terms included health care and quality, as well as healthcare and quality. Peer-reviewed articles and government publications published in English from 2004 to 2016 were included. Exclusion criteria were related concepts, discussions about the need for quality care, gray literature, and conference proceedings. Similar attributes were grouped into themes during analysis. Forty-two relevant articles were analyzed after excluding duplicates and those that did not meet eligibility. Following thematic analysis, 4 defining attributes were identified: (1) effective, (2) safe, (3) culture of excellence, and (4) desired outcomes. Based on these attributes, the definition of healthcare quality is the assessment and provision of effective and safe care, reflected in a culture of excellence, resulting in the attainment of optimal or desired health. This analysis proposes a conceptualization of healthcare quality that defines its implied foundational components and has potential to improve the provision of quality care. Theoretical and practice implications presented promote a fuller, more consistent understanding of the components that are necessary to improve the provision of healthcare and steady public trust.
Calcitonin-specific transcription and splicing targets gene-directed enzyme prodrug therapy to medullary thyroid carcinoma cells.

Recurrent and metastatic medullary thyroid carcinoma (MTC) remains difficult to treat due to its limited responsiveness to chemotherapy, radiotherapy, and imaging. To investigate an alternative therapeutic approach, we examined the feasibility of targeting gene-directed enzyme/prodrug therapy delivered by adenoviral vectors to MTC. We previously described a modified human calcitonin (CT)/CT gene-related peptide promoter that produced increased expression while maintaining specificity for MTC cells. In this study, we introduced an additional level of specificity by using cell-specific splicing and examined whether the selectivity of the gene-directed enzyme/prodrug therapy for MTC was enhanced when both the promoter and splicing features were combined in a single transcription unit. Two replication-defective adenoviruses were constructed that expressed the Escherichia coli purine nucleoside phosphorylase (PNP) gene under the transcriptional control of a modified T2 promoter (Ad.T2-PNP) or the T2 promoter in combination with a CT minigene cassette in which the PNP gene was imbedded within the CT gene exon 4 (Ad.T2-CT/PNP). The specificity of PNP expression by Ad.T2-PNP, Ad.T2-CT/PNP, and control viruses in the MTC cell line, TT, and in a panel of non-MTC cell lines was evaluated. The highest level of PNP gene expression and the most effective cell killing in the presence of prodrug occurred in TT cells infected with Ad.T2-PNP, followed by Ad.T2-CT/PNP. Infection of most non-MTC cell lines, even with high multiplicities of Ad.T2-PNP, produced only low-level PNP expression that resulted in minimal cell killing in the presence of prodrug. High-level expression of PNP and effective cell killing was observed with both adenoviral gene constructs. The highest level of cell specificity was achieved with the combined use of promoter and splicing regulation in the Ad.T2-CT/PNP virus.
Submodular Function Minimization under Covering Constraints

This paper addresses the problems of minimizing nonnegative submodular functions under covering constraints, which generalize the vertex cover, edge cover, and set cover problems. We give approximation algorithms for these problems exploiting the discrete convexity of submodular functions. We first present a rounding 2-approximation algorithm for the submodular vertex cover problem based on the half-integrality of the continuous relaxation problem, and show that the rounding algorithm can be performed by one application of submodular function minimization on a ring family. We also show that a rounding algorithm and a primal-dual algorithm for the submodular cost set cover problem are both constant factor approximation algorithms if the maximum frequency is fixed. In addition, we give an essentially tight lower bound on the approximability of the submodular edge cover problem.