Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Oxidative DNA Damage Using an Alkaline Single Cell Gel Electrophoresis (SCGE) Comet Assay, and the Protective Effects of N-Acetylcysteine Amide on Zearalenone-induced Cytotoxicity in Chang Liver Cells

Zearalenone (ZEN) is a non-steroidal estrogenic mycotoxin produced by several species of Fusarium that are found in cereals and agricultural products. ZEN has been implicated in mycotoxicosis in farm animals and in humans. The toxic effects of ZEN are well known, but the ability of an alkaline Comet assay to assess ZEN-induced oxidative DNA damage in Chang liver cells has not been established. The first aim of this study was to evaluate the Comet assay for the determination of cytotoxicity and extent of DNA damage induced by ZEN toxin, and the second aim was to investigate the ability of N-acetylcysteine amide (NACA) to protect cells from ZEN-induced toxicity. In the Comet assay, DNA damage was assessed by quantifying the tail extent moment (TEM; arbitrary unit) and tail length (TL; arbitrary unit), which are used as indicators of DNA strand breaks in SCGE. The cytotoxic effects of ZEN in Chang liver cells were mediated by inhibition of cell proliferation and induction of oxidative DNA damage. Increasing the concentration of ZEN increased the extent of DNA damage. The extent of DNA migration, and percentage of cells with tails were significantly increased in a concentration-dependent manner following treatment with ZEN toxin ( p < 0.05). Treatment with a low concentration of ZEN toxin (25 μM) induced a relatively low level of DNA damage, compared to treatment of cells with a high concentration of ZEN toxin (250 μM). Oxidative DNA damage appeared to be a key determinant of ZEN-induced toxicity in Chang liver cells. Significant reductions in cytolethality and oxidative DNA damage were observed when cells were pre-treated with NACA prior to exposure to any concentration of ZEN. Our data suggest that ZEN induces DNA damage in Chang liver cells, and that the antioxidant activity of NACA may contribute to the reduction of ZEN-induced DNA damage and cytotoxicity via elimination of oxidative stress.
Modelling of cirrus clouds – Part 1a: Model description and validation

Abstract. A double-moment bulk microphysics scheme for modelling cirrus clouds including explicit impact of aerosols on different types of nucleation mechanism is described. Process rates are formulated in terms of generalised moments of the underlying a priori size distributions in order to allow simple switching between various distribution types. The scheme has been implemented into a simple box model and into the anelastic non-hydrostatic model EULAG. The new microphysics is validated against simulations with detailed microphysics for idealised process studies and for a well documented case of arctic cirrostratus. Additionally, the formation of ice crystals with realistic background aerosol concentration is modelled and the effect of ambient pressure on homogeneous nucleation is investigated in the box model. The model stands all tests and is thus suitable for cloud-resolving simulations of cirrus clouds.
Anatomically-based modeling and animation of human upper limbs

We propose an anatomically-based modeling and animation scheme for a human body model whose shape was created from 3-D scan data of a human body. The proposed human body model is composed of three layers: a skeleton layer, a muscle layer, and a skin layer. The skeleton layer, represented as a set of joints and bones, controls the animation of the human body model. The muscle layer deforms the skin layer realistically during animation. We create the muscles in that layer using soft objects, also known as blobby objects or metaballs, and deform them through the insertion/origin points of the muscles and the volume-preserving constraints. To deform the skin layer during animation, we bind the skin layer to both the skeleton layer and the muscle layer by finding corresponding joints and muscles of the vertices on the skin layer. We applied the proposed scheme for modeling the upper limb and shoulder of human body in this paper.
Intelligent Decision-Making System Based on Data Mining

With the development of the Web, more and more companies, governments and individuals publish their information on the Internet. Even very small companies are enabled to present their products and services in the World Wide Web. How could a company survive in this virtual world? How could it catch the first commercial opportunity? How could it find the best cooperative partner? How could it capture the clients? How could it earn the maximal profits? These are all urgent challenges to companies. So how to use the data inside and outside of company enough, to help the decision-maker make reasonable decision is becoming an urgent challenge. For this aim, we design a novel decision support system----WebCom Miner. This paper presents the design and implementation of the system in detail and demonstrates the key algorithms used in the system.
Adaptive Updating Algorithm of User Model Based on Interest Cycle

User model is the base of supporting personalized recommendation. It is not only able to represent user's interests, but also could reflect the change of user's interests over time. However, existing user model updating approaches have several disadvantages, such as unified interest update mode, the same interest category without considering interest cycle, which reduce the accuracy of user model representing and updating. To solve these problems, this paper introduces a method to discover interest cycle by cutting valid time of interest existing in the curve of interest changing, and divides the interests into three kinds of categories which are long-term interest, medium-term interest and short-term interest. Based on the different kinds of interest, the disparate interest update strategies are presented to make change of interest adaptive, especially adaptive forgetting functions with the factor of interest forgotten and adaptive incenting functions with the factor of interest incented are constructed, both of them could reflect the actual intention of interest changing over time. It is shown by the experiment that the application of the method presented in this paper is more effective and practicable than the method with adopting the unique forgetting and incenting function for all interests.
Advanced Research in Computer

— Outlier detection is currently very active area of research in data set mining community. Finding outliers in a collection of patterns is a very well-known problem in the data mining field. An outlier is a pattern which is dissimilar with respect to the rest of the patterns in the dataset. Proposed Method for outlier detection uses hybrid approach. Purpose of approach is first to apply clustering algorithm that is kmeans which partition the dataset into number of clusters and then find outliers from the each resulting clusters using distance based method. The principle of outliers finding depend on the threshold. Threshold is set by user. The main objective of the second stage is a finding out the objects, which are far away from their cluster centroids. In proposed approach, two techniques are combining to efficiently find the outlier from the data set. The experimental results using real dataset demonstrate that proposed method takes less computational cost and performs better than the distance based method. Proposed algorithm efficiently prunes of the safe cells (inliers) and save huge number of extra calculations.
The Ideological Foundations of Affective Polarization in the U.S. Electorate

Democratic and Republican partisans dislike the opposing party and its leaders far more than in the past. However, recent studies have argued that the rise of affective polarization in the electorate does not reflect growing policy or ideological differences between supporters of the two parties. According to this view, though Democratic and Republican elites are sharply divided along ideological lines, differences between the policy preferences of rank-and-file partisans remain modest. In this article, we show that there is a close connection between ideological and affective polarization. We present evidence from American National Election Studies surveys that opinions on social welfare issues have become increasingly consistent and divided along party lines and that social welfare ideology is now strongly related to feelings about the opposing party and its leaders. In addition, we present results from a survey experiment showing that ideological distance strongly influences feelings toward opposing party candidates and the party as a whole.
The global storage needs of a subcomputation

A defining characteristic of “functional” specifications is the absence of assignments: updates of tables and data structures are expressed by giving the relationship between the new and old values. An obvious implementation allocates separate space for new and old values and may consume a lot of storage. However, even when updates of attributes like symbol tables are expressed functionally, we would like to avoid making copies of the symbol table during attribute evaluation. In other words, if possible, the implementation should have a single global copy of the table that is updated using assignments. Since the value of the global copy changes during computation, the order of evaluation has to be chosen carefully. In this paper, we partition attributes into classes, the problem being to determine if there exists an evaluation order that allows each class to share a global storage area. The solution extends to handle symbol tables for block structured languages. More precisely, consider a directed acyclic graph D in which vertices represent attribute values to be computed. Associated with each vertex is a label indicating the storage area to be shared by the vertex. Storage used during the evaluation of D is studied by playing a pebble game on D with the following steps: (1) pebble (i.e. place a pebble) on a source; (2) pebble a vertex if all its successors have pebbles (a pebble may be moved to the vertex from one of its successors); (3) pick up a pebble. Each vertex must be pebbled exactly once. The use of global storage is formalized by defining single pebblings, in which at most one of the vertices with a given label has a pebble at any time. The results also apply to a form of pebbling, called chain pebbling, that allows symbol tables for block structured languages to be studied.
Health-promotion in the context of ageing and migration: a call for person-centred integrated practice

Objective For the aim of improving the implementation of a health-promoting intervention for older persons who are born abroad, this study aimed to explore health care professionals' experiences of facilitators and barriers for their possibilities to support a healthy ageing in the context of migration. Methods Qualitative data were collected from four focus groups with health professionals who all had experience of working with older persons who are born abroad. Data were analysed with the guidance from the method developed by Krueger and Casey, progressing from an empirical to an abstract level. Results Five different conditions were found to influence supporting healthy ageing in the context of migration: Sense of belonging through significant others, Emotional bonds to a place called home, Expectations on health and support during the ageing process, Mutual understanding as a means for communication and Heterogeneity as a point of departure. The one comprehensive theme complexity describes how those aspects are interrelated in a complex and unpredictable way. Conclusions The results point at the need for focusing on each person's experiences and health expectations, and the study provides a foundation for future research on the integration of whole-system and person-centred practice.
Attaining Single-Chip, High-Performance Computing through 3D Systems with Active Cooling

This article explores the benefits and the challenges of 3D design and discusses novel techniques to integrate predictive cooling control with chip-level thermal-management methods such as job scheduling and voltage frequency scaling. Using 3D liquid-cooled systems with intelligent runtime management provides an energy-efficient solution for designing single-chip many-core architectures.
Process performance management: illuminating design issues through a systematic problem analysis

Business processes are the means by which organizations create value. Consequently, organizations need to continuously monitor and control their processes' performance so as to provide a consistent and predictable execution quality. A number of today's organizations, however, appear to encounter difficulties with measuring and improving their processes' performance. In this paper, we set out to identify the gap between how organizations currently approach process performance management (PPM) and what they are striving to realize in the future. The systematic gap analysis results in a set of design factors that are valuable in guiding future design efforts for useful and relevant PPM solutions.
Mutation and Analysis of Dan, the Founding Member of the Dan Family of Transforming Growth Factor β Antagonists

ABSTRACT The Dan family of transforming growth factor β antagonists is a large, evolutionarily conserved family of proteins. Little is known about either the specificity of these antagonists or the biological roles of these proteins. We have characterized Dan, the founding member of this family, with regard to both its biochemical specificity and its biological roles. Although DAN is not an efficient antagonist of BMP-2/4 class signals, we found that DAN was able to interact with GDF-5 in a frog embryo assay, suggesting that DAN may regulate signaling by the GDF-5/6/7 class of BMPs in vivo. Intriguingly, in developing neurons, Dan mRNA was localized to axons, suggesting a potential role for the DAN protein in axonal outgrowth or guidance. Mice lacking Dan activity were generated by gene targeting and displayed subtle, background-dependent defects.
Surface-enhanced Raman nanodomes

We demonstrate a surface-enhanced Raman scattering (SERS) substrate consisting of a closely spaced metal nanodome array fabricated on flexible plastic film. We used a low-cost, large-area replica molding process to produce a two-dimensional periodic array of cylinders that is subsequently overcoated with SiO2 and silver thin films to form dome-shaped structures. Finite element modeling was used to investigate the electromagnetic field distribution of the nanodome array structure and the effect of the nanodome separation distance on the electromagnetic field enhancement. The SERS enhancement from the nanodome array substrates was experimentally verified using rhodamine 6G as the analyte. With a separation distance of 17 nm achieved between adjacent domes using a process that is precisely controlled during thin film deposition, a reproducible SERS enhancement factor of 1.37 × 108 was demonstrated. The nanoreplica molding process presented in this work allows for simple, low-cost, high-throughput fabrication of uniform nanoscale SERS substrates over large surface areas without the requirement for high resolution lithography or defect-free deposition of spherical microparticle monolayer templates.
(Quasi-)Degeneration, Quantum Corrections and Neutrino Mixing

In the case of neutrinos having significant masses to be measured in direct search, there are sizeable corrections to the PMNS matrix. We show the universality of loop effects from any new physics sector and discuss the seesaw-extended MSSM as an example of a non-minimal flavour violating theory with non-decoupling effects.
International Journal of Innovative Research in Computer and Communication Engineering Hot Topics Perception in Social Network

Social Network have become a very big network where many people are discussing about the hot trends, events and everyday activities which they considered as important with their friends, families and many unknown people. Compare to media like Newspaper, Television the social network is spreading the latest news in a very fast manner and the original talk of the people is spread over the network. The proposed model is to identify the hot topics which is discussed in the social network. The previous methods of finding the hot topics in social network has some limitations like the performance of the model is low, the system detect the topic with high false positive rate. In the proposed model the posts that is shared by the people in social network with their friends by forwarding the posts is considered. The particular post which is forwarded by many people and irregular forwarding nature will be monitored and using change point detection technique and comparing the contents of the posts the perception of hot topic is done.
Effect of Genetic Diversity in Swine Leukocyte Antigen-DRA Gene on Piglet Diarrhea

The swine leukocyte antigens (SLAs) are the multigene families related to immune responses. Little is known about the effect of the DRA gene on diarrheal disease. This study reported the genetic diversity of the DRA gene in exons 1, 3 and 4 in 290 Chinese Yantai black pigs. No variation was identified in exon 3. In exon 1, three genotypes and two alleles were identified, generated by two single nucleotide polymorphisms (SNPs). In exon 4, there were eight genotypes and five alleles containing seven SNPs were detected with four SNPs being novel SNPs. The low polymorphism found in swine DRA is consistent with the concept that the DRA gene is highly conserved among all mammalian species. Statistical analyses indicated that the genotypes of exon 1 were not significantly associated with piglet diarrhea (p > 0.05); however, genotypes C4C4 (1.80 ± 0.33) and A4E4 (1.66 ± 0.25) of exon 4 were significantly susceptible to diarrhea (p < 0.01). These indicate that the particular genotypes of the DRA gene are susceptible to diarrheal disease, which provides valuable information for disease-resistance breeding in swine.
Using auto-associative neural networks to compress and visualize multidimensional data

To interpret the information hidden in multidimensional data can be considered as challenging and complicated task. Usually, dimension reduction or data compression is considered as the first step to data analysis and exploration of multidimensional data. Here, the focus is given to study Auto-Associative Neural Networks (AANNs) technique for data compression and visualization. AANNs have the ability to deal with linear and nonlinear correlation among variables. This technique is often referred to as nonlinear Principal Component Analysis (NLPCA) or could also be known as Bottleneck Neural Networks (BNNs) due to their specific structures that consist of combination of compression and decompression networks. The trained AANNs can reduce high dimensional data onto lower dimensional data by compressing them on its bottleneck layer that later can be used for data visualization. In this paper, the technique of AANNs are described, developed using high level computer language and applied on two different multidimensional datasets. The results have shown that AANNs are able to compress multidimensional data into only two non linear principal components at its bottleneck layer and these compressed data can provide visualization of different clusters of data.
A Multi-Service Bit and Power Allocation in WiMAX Networks

WiMAX, as a key standard in last-mile access, is expected to support QoS guarantees for multi-services. Developing adaptive bit and power allocation according to quality of service (QoS) requirements is important to different services. In this paper, an adaptive multi-service bit and power allocation based on game theory is proposed for orthogonal frequency division multiplexing (OFDM) WiMAX networks. Considering QoS abilities that each sub-channel could support, the allocation is described as non-cooperation games between sub-channels. Meanwhile, the optimal power is derived. The limitation of traditional approach and its discreteness are improved. Simulation results indicate that the multi-service adaptive bit and power allocation makes WiMAX networks support more users of multi-service on the basis of meeting QoS.
Determinants of educational attainment among adolescents in Egypt: Does school quality make a difference?

The paper explores the relationship between school quality in Egyptian preparatory (middle) schools and the likelihood of school dropout either during preparatory school or before the completion of secondary school. Despite strong empirical evidence for the many positive social and economic returns associated with more years of schooling there has been little research exploring how the quality of particular schools might influence grade levels attained. The authors address this research gap using detailed data on Egyptian preparatory schools (grades 6-8 the last 3 years of the 8 years of basic schooling) that are linked with a national survey of Egyptian adolescents. The results confirm that school quality is associated with grade levels attained. For both boys and girls the elements of school quality that matter include traditional elements such as time available for learning and material resources including teacher quality as well as some aspects of school and classroom dynamics in particular treatment by teachers and teacher attitudes. A comparison of these results with a similarly designed study in Kenya by some of the same authors suggests that the specific features of school quality that matter for educational outcomes are context specific and differ between boys and girls. Gender roles in society as well as school quality and teacher attitudes about the academic capabilities of adolescent boys and girls shape the ways in which schools influence boys and girls in a particular setting. At the same time as schools empower young people with knowledge and skills they also reflect and reinforce norms including norms about gender roles. (authors)
Cell-free eukaryotic systems for the production, engineering, and modification of scFv antibody fragments

Open cell‐free translation systems based on Escherichia coli cell lysates have successfully been used to produce antibodies and antibody fragments. In this study, we demonstrate the cell‐free expression of functional single‐chain antibody variable fragments (scFvs) in a eukaryotic and endotoxin‐free in vitro translation system based on Spodoptera frugiperda (Sf21) insect cell extracts. Three scFv candidates with different specificities were chosen as models. The first scFv candidate SH527‐IIA4 specifically discriminates between its phosphorylated (SMAD2‐P) and nonphosphorylated antigens (SMAD2) (where SMAD is mothers against decapentaplegic homolog 2), whereas the second scFv candidate SH527‐IIC10 recognizes both, SMAD2‐P and SMAD2. The third scFv candidate SH855‐C11 binds specifically to a linear epitope of the CXC chemokine receptor type 5. The translocation of antibody fragments into the lumen of endogenous microsomal vesicles, which are contained in the lysate, was facilitated by fusion of scFv genes to the insect cell specific signal sequence of honeybee melittin. We compared the binding capabilities of scFv fragments with and without melittin signal peptide and detected that translocated scFv fragments were highly functional, whereas scFvs synthesized in the cytosol of the cell extract showed strongly decreased binding capabilities. Additionally, we describe a cell‐free protein synthesis method for the incorporation of noncanonical amino acids into scFv molecules in eukaryotic cell lysates. We demonstrate the successful cotranslational labeling of de novo synthesized scFv molecules with fluorescent amino acids, using residue‐specific as well as site‐specific labeling.