Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling of Evolving Knowledge Network with Node Deletion

A new type of knowledge evolving model which comprises knowledge-based local world preferential attachment and degree-based node preferential deletion is studied. A series of numerical simulations of the degree distribution of the knowledge networks are presented. The results indicate that the degree distribution of the knowledge networks at first has an approximate state of scale-invariant, and then it turns into an exponential distribution. Moreover, the truncation in p(k) increases as the adding probability pa decreases. In addition, the probability of the numbers having relatively more connections is greater when the adding probability is larger. Finally, we compare the effect of the size of local world on degree distribution. The results of simulations show that the probability of the numbers having relatively larger degree will increases as the size of local world increases which indicate that the connectivity is more and tighter as M increases.
Mining Web Activity Logs

Web mining has been a major research topic during the last decade. Traditional sources of information on the Web include the text of web pages, the structure of the pages as organized by the web page creators, as well as the link structure of the Web. Another emerging source of information is the tags for web pages as collected and organized by collaborative tagging systems (e.g. del.icio.us, StumbleUpon). Search engines are interested in organizing all the information provided by these sources so that they are able to respond accurately to different search tasks. However, the ample use of web search engines by billions of people worldwide has created another interesting source of information. The search and browsing activity of these users implicitly captures human knowledge and reveals the most interesting places on the web. By looking at the search queries people issue, we can extract a succinct, user-generated summary for pages appearing in the search results. For example, such a summary for Google’s main page could be: google, search engine, larry page, pagerank. These summaries tend to be accurate given the fact that web users have been trained all these years to formulate queries with an emphasis on selecting the least ambiguous and most meaningful words. In a way, in addition to requesting new information, search users are also revealing new knowledge (that perhaps does not even exist yet on the web) through the keywords they select for their queries and the navigational paths they follow in response. The paths users follow are also implicit votes on the interesting parts on the Web. Search engines are the first to record the users’ search history in order to be able to analyze it and improve their services in the future. These query logs contain the terms users issue in a search engine along with the search results people click on in response. In addition, through browser toolbars, search engines can record web activity logs that contain the history of pages a user visits. Although web activity and query logs contain invaluable information for the search engines, it is also the web users who can explicitly benefit from such data. However, we have to identify meaningful ways to mine the web activity logs and make them available back to the web users. The primary goal of my research has been to investigate novel uses of web activity logs in formulating and solving novel problems related to the Web. The research on query and web activity logs that we have performed, with collaborators from Yahoo! and Microsoft Research, apply to problems related to sponsored search, recommendation systems, web information extraction systems, and web navigation systems. Section 1 outlines the research I have performed to date, while Section 2 describes my current research and plans for the future.
Predictors of Antidepressant Nonadherence Among Older Veterans With Depression.

OBJECTIVE Most depression among older adults is treated in primary care, and many patients do not adhere to medication treatment. The U.S. Department of Veterans Affairs (VA) has recently introduced initiatives to address such treatment gaps. This study examined patient-reported antidepressant nonadherence during the acute treatment period (first four months after a prescription) and identified predictors of nonadherence in a sample of older veterans. METHODS This was a prospective, observational study of 311 participants ages 60 and older who received care at three VA medical centers and who had a diagnosis of clinically significant depression and were given a new outpatient antidepressant prescription. Participants completed an initial interview and a follow-up interview at four months after treatment recommendation. Antidepressant adherence was measured with a well-validated self-report measure. RESULTS At four months, 29% of participants reported nonadherence to their antidepressant medication. In unadjusted analyses, nonadherence was significantly associated with being African American, having no spouse or significant other, having greater general medical comorbidity, and receiving the prescription in a primary care setting (versus a specialty mental health setting). In logistic regression models controlling for several variables (demographic, illness, and functional status variables; type of antidepressant; contact with a therapist; medical setting; and site of recruitment), two predictors remained significantly associated with nonadherence: African-American race (odds ratio [OR]=4.23, p<.001) and general medical comorbidity (OR=1.33, p=.002). CONCLUSIONS The two main predictors of nonadherence among older adults with depression were African-American race and general medical comorbidity. Results suggest that significant needs remain for important patient subgroups to improve antidepressant adherence.
Ortorexia nervosa: cultural adaptation of ortho-15

The cult of body in modern society, seen as a vector of individuality, places beauty and aesthetics as happiness and wealth factors. With rigorous and unreachable established patterns, the number of people affected by food-related disorders and collective subjectivity increases. Orthorexia nervosa, a relatively recent eating disorder first described in 1997, is characterized by the obsession with what is normally seen as healthy food. Individuals affected by the disorder seek foods considered “pure”, spending time and effort in the pursuit of healthy food that is incompatible with everyday life and puts them away from social relations. Objective: This study was intended to translate and culturally adapt the Ortho-15 questionnaire, developed in 2005 as a tool of perception of orthorexia. Methodology: Translation of the Ortho-15 from Italian to Portuguese followed by discussion and implementation of pilot testing with a focal group to enable the questionnaire to be firstly used in a study with Technical Nutrition students in Brasilia, Federal District, Brazil, and eventually in other studies. Results: Ortho-15 was adapted for use in the target population. Conclusion: Translation and cultural adaptation of Ortho-15 is of great importance, since there are no published studies on the prevalence of orthorexia in Brazil. Further studies to determine the psychometric properties of the questionnaire are suggested
Invasive PUF Analysis

In this work we consider the suitability of Phyiscaly Unclonable Functions (PUFs) for high-security applications. For PUFs to be considered secure in such scenarios they must be resilient to both semi-invasive and fully-invasive attacks. We introduce a new failure analysis technique for semi-invasive, single-trace, backside readout of logic states. We apply this technique to characterize the unique physical response of a memory-based PUF. With these results we identify several weakness in current PUF schemes. We extend current PUF definitions to be resilient against such attacks by requiring that PUFs be implemented in a serialized manner. Finally, we improve already existing PUF architectures to include these concepts.
AN EFFECTIVE METHOD OF RNA ISOLATION FROM Fallopia multiflora TUBEROUS ROOTS

To isolate high-quality total RNA from Fallopia multiflora tuberous roots is difficult because of the presence of high levels of carbohydrates, phenolics, and other secondary metabolites. Since several procedures specialized for RNA isolation from polysaccharides and phenols rich tissues have resulted in poor yields, in this study, we developed a modified protocol that was derived from the traditional CTAB method. The protocol was able to produce high-quality and intact RNA from the tuberous roots of F. multiflora. The yield of total RNA was more than 0.15 mg/g fresh weight, with an A260/A280 ratio of 1.9–2.0. The obtained RNA was of sufficient quality and suitable for downstream application such as reverse-transcription polymerase chain reaction (RT-PCR), Northern hybridization, and cDNA library construction. The protocol may also have wider applicability for total RNA isolation from other plant species with tuberous roots.
Effect of green tea catechins on breast carcinogenesis: a systematic review of in-vitro and in-vivo experimental studies

Catechins (flavan-3-oils) are the main flavonoids present in green tea. The potential cancer chemopreventive and therapeutic properties of green tea catechins have been the focus of research efforts in the last two decades. This systematic review aims to generate in vitro and in vivo data on the effect of green tea catechins on breast carcinogenesis. Electronic databases were searched with the appropriate search terms. Existing evidence suggests that green tea catechins modulate breast cell carcinogenesis. The effect of green tea catechins on breast cell carcinogenesis has been investigated in different experimental models and under different experimental conditions, that is, carcinogen investigated, green tea catechin dosage regimen, treatment with green tea extract versus pure synthetic EGCG, and time point of treatment with green tea catechins in relation to the exposure to the carcinogen. Although the effect of green tea catechins was not always statistically significant, the protective effect of green tea catechins was demonstrated in all the trials, suggesting that treatment with green tea catechins should be further investigated in the clinical setting of chemoprevention of high-risk women. However, it should be emphasized that the reported actions of green tea catechins are observed in high concentrations that are difficult to achieve in the clinical setting. This drawback could be overcome by designing green tea catechins with better bioavailability and/or by cotreatment combining breast cancer endocrine treatment with green tea catechins.
Novel Network Intrusion Detection System using Hybrid Neural Network (Hopfield and Kohonen SOM with Conscience Function)

Summary Intrusion detection technology is an effective approach to dealing with the problems of network security. In this paper, it presents an intrusion detection model based on hybrid neural network and SVM. The key idea is to aim at taking advantage of classification abilities of neural network for unknown attacks and the expertbased system for the known attacks. We employ data from the third international knowledge discovery and data mining tools competition (KDDcup’99) to train and test the feasibility of our proposed neural network component. According to the results of our experiment, our model achieves 97.2 percent detection rate for DOS and Probing intrusions, and less than 0.04 percent false alarm rate. Expert system can detect R2L and U2R intrusions more accurately than neural network. Therefore, Hybrid model will improve the performance to detect intrusions.
Ecologically Sound Procedural Generation of Natural Environments

Current techniques for the creation and exploration of virtual worlds are largely unable to generate sound natural environments from ecological data and to provide interactive web-based visualizations of such detailed environments. We tackle this challenge and propose a novel framework that (i) explores the advantages of landscape maps and ecological statistical data, translating them to an ecologically sound plant distribution, and (ii) creates a visually convincing 3D representation of the natural environment suitable for its interactive visualization over the web. Our vegetation model improves techniques from procedural ecosystem generation and neutral landscape modeling. It is able to generate diverse ecological sound plant distributions directly from landscape maps with statistical ecological data. Our visualization model integrates existing level of detail and illumination techniques to achieve interactive frame rates and improve realism. We validated with ecology experts the outcome of our framework using two case studies and concluded that it provides convincing interactive visualizations of large natural environments.
Antiviral activity of a Bacillus sp. P34 peptide against pathogenic viruses of domestic animals

P34 is an antimicrobial peptide produced by a Bacillus sp. strain isolated from the intestinal contents of a fish in the Brazilian Amazon basin with reported antibacterial activity. The aim of this work was to evaluate the peptide P34 for its in vitro antiviral properties against canine adenovirus type 2 (CAV-2), canine coronavirus (CCoV), canine distemper virus (CDV), canine parvovirus type 2 (CPV-2), equine arteritis virus (EAV), equine influenza virus (EIV), feline calicivirus (FCV) and feline herpesvirus type 1 (FHV-1). The results showed that the peptide P34 exhibited antiviral activity against EAV and FHV-1. The peptide P34 inhibited the replication of EAV by 99.9% and FHV-1 by 94.4%. Virucidal activity was detected only against EAV. When P34 and EAV were incubated for 6 h at 37 °C the viral titer reduced from 104.5 TCID50 to 102.75 TCID50, showing a percent of inhibition of 98.6%. In conclusion, our results demonstrated that P34 inhibited EAV and FHV-1 replication in infected cell cultures and it showed virucidal activity against EAV. Since there is documented resistance to the current drugs used against herpesviruses and there is no treatment for equine viral arteritis, it is advisable to search for new antiviral compounds to overcome these infections.
Identifying Gender Bias in College Culture: Descriptive and Prescriptive Stereotypes, Hostile and Benevolent Sexism, and Cognitive Justification

The concept of equality between men and women is a controversial and important subject for continued business and psychological research. This study aimed to gain greater insight into gender bias by surveying college students. Sexism has been thought to be manifested in two ways: hostile or benevolent. Hostile sexism pertains to overt discrimination against women for their sex. Benevolent sexism places females in a restrictive role like hostile sexism, but it does so in a nicer tone. Accordingly, some may not even recognize benevolent sexism to be an issue at all. Bias has also been thought to be manifested in a descriptive or prescriptive way. Descriptive bias assesses what people think women currently are like. On the other hand, prescriptive bias assesses how people believe women should be like. Constructs were used to assess hostile or benevolent sexism and descriptive or prescriptive bias, which have all been used in previously published research. Additional items were developed by the researcher to assess the possibility of stereotyping being followed up with rationalization. Results indicated that there was a difference in gender attitudes between men and women. Specifically, males displayed higher sexism overall and were more likely to associate benevolent sexism with hostile sexism than females were. The item developed by the researcher for the purposes of examining a potential rationalization for stereotyping exhibited a greater correlation for females pertaining to descriptive bias. Practical and theoretical implications and suggestions for future research are discussed.
Perceived Leader Effectiveness across Organizational Roles: Exploratory Evidence

SYMLOG methodology was used by a sample of respondents from Central Eurasia to rate their perceptions of the values shown in the behavior of leaders occupying three kinds of organizational roles: (1) chief executive officers of business enterprises, NGO's, or key governmental agencies; (2) immediate supervisors of the respondents in their respective organizations; and (3) country leaders or Heads of State (e.g., President, Prime Minister, etc.) of the respondents' home country. Respondents were participants who took part in a two-week leadership development program in their region. Respondents also rated the leaders' role performance and their satisfaction with the leaders. Respondents who categorized themselves as transformational leaders evaluated the supervisor role occupants as most effective while non-transformational leaders perceived the CEO role occupants to be most effective. The results are discussed in light of future needs for cross- cultural leadership research.
The absorbent's solution flow process, non-parametric identification into an absorption chiller for air conditioning

The lithium bromide chillers supplied from solar collectors are used to provide proper environmental conditions into industrial and civil buildings. To maintain the appropriate values for the temperature into the chiller's boiler, a control unit is introduced to avoid crystallization of the absorbent. The liquid flow process of the absorbent within the pipes of the chiller is a non-linear process. The paper focuses on the experimental identification techniques used to determine from measurements the nonlinear dynamic model of the flow process.
Bubble Treemaps for Uncertainty Visualization

We present a novel type of circular treemap, where we intentionally allocate extra space for additional visual variables. With this extended visual design space, we encode hierarchically structured data along with their uncertainties in a combined diagram. We introduce a hierarchical and force-based circle-packing algorithm to compute Bubble Treemaps, where each node is visualized using nested contour arcs. Bubble Treemaps do not require any color or shading, which offers additional design choices. We explore uncertainty visualization as an application of our treemaps using standard error and Monte Carlo-based statistical models. To this end, we discuss how uncertainty propagates within hierarchies. Furthermore, we show the effectiveness of our visualization using three different examples: the package structure of Flare, the S&P 500 index, and the US consumer expenditure survey.
Behaviour control for a mobile robot by a structured neural network

We have been researching ways to use neurocomputers that have highly parallel data processing and learning functions for robot control. In this paper, a structured network model for robot control and its learning algorithm are presented. There are three requirements for the robots: (1) The robot must be easy to control but the neural network must be sophisticated enough to handle multiple sensor input. (2) The robot must be able to learn easily. (3) The robot must be able to adjust its own actions. We have developed a new mobile mechanism, created a network model, and increased the network learning speed. Sensor signals from the robot are input to the neural network. The network outputs a certain reaction pattern in response to the sensor input. Then the reaction is refined to an ideal one using training patterns. A robot can change its reaction pattern by changing the training pattern. We created two robots with different action patterns: one chases other robots and the other runs away from other robots.
The impact of entry modes on export knowledge resources and the international performance of SMEs

Cette etude explore le role que les modes d’entree – conceptualises en tant que formes d’experience internationale – jouent dans la creation des connaissances a l’export et dans le renforcement de la performance internationale des petites et moyennes entreprises (PME). Un modele causal developpe et teste sur la base d’un echantillon de 107 PME francaises de l’industrie des metaux, suggere que les modes d’entree ont un impact direct sur le niveau des connaissances explicites des PME a l’egard des marches etrangers ainsi qu’un impact indirect sur les connaissances tacites. Les connaissances tacites concernant les marches etrangers ameliorent la performance internationale des PME.
A Recombinant Rabies Virus Encoding Two Copies of the Glycoprotein Gene Confers Protection in Dogs against a Virulent Challenge

The rabies virus (RABV) glycoprotein (G) is the principal antigen responsible for the induction of virus neutralizing antibodies (VNA) and is the major modality of protective immunity in animals. A recombinant RABV HEP-Flury strain was generated by reverse genetics to encode two copies of the G-gene (referred to as HEP-dG). The biological properties of HEP-dG were compared to those of the parental virus (HEP-Flury strain). The HEP-dG recombinant virus grew 100 times more efficiently in BHK-21 cell than the parental virus, yet the virulence of the dG recombinant virus in suckling mice was lower than the parental virus. The HEP-dG virus can improve the expression of G-gene mRNA and the G protein and produce more offspring viruses in cells. The amount of G protein revealed a positive relationship with immunogenicity in mice and dogs. The inactivated HEP-dG recombinant virus induced higher levels of VNA and conferred better protection against virulent RABV in mice and dogs than the inactivated parental virus and a commercial vaccine. The protective antibody persisted for at least 12 months. These data demonstrate that the HEP-dG is stable, induces a strong VNA response and confers protective immunity more effectively than the RABV HEP-Flury strain. HEP-dG could be a potential candidate in the development of novel inactivated rabies vaccines
Molecular Modeling and Structure Analysis of S100 Calcium Binding Protein A14: Molecular Modeling and Structure Analysis of S100A14

S100 calcium binding protein A14 (S100A14), a new member of S100 calcium binding protein, has been rarely studied and its structure and function are still unclear. In this study, a credible model of human S100A14 (residues 12-102) was built based on the molecular structure of human S100A13 (Swiss-rot Q99584, PDB ID:1YUR_A). Protein sequence alignment showed some mutations in Ca-binding domain in the C-terminal, which suggested the C-terminal might not be able to bind Ca. While most of the Cu/ Zn binding sites of S100 protein family were conserved in S100A14, strongly suggesting its binding affinity to Cuand Zn. Compare to S100A13, the secondary structure showed there was a longer extension in the helix I and helix IV of S100A14. An unique site Trp (S100A13: W77), reported to play an important role in the interaction between S100A13 and cytoplasmic membrane, was also exist in S100A14 (W85), which suggested S100A13 and S100A14 might have common biological function. Though the monomer structures of S100A13 and S100A14 were quite similar, the strong difference between their C-terminals indicated S100A14 might have its functional uniqueness since the functional specificity of S100 proteins mainly attributes to the C-terminal sequence variation. Keywords-S100A14; molecular modeling; structure analysis
SemEval-2010 Task 13: TempEval-2

Tempeval-2 comprises evaluation tasks for time expressions, events and temporal relations, the latter of which was split up in four sub tasks, motivated by the notion that smaller subtasks would make both data preparation and temporal relation extraction easier. Manually annotated data were provided for six languages: Chinese, English, French, Italian, Korean and Spanish.