Miracle-dz/UniFAR-FTUs huggingface dataset:
Avirulence Genes in Cereal Powdery Mildews: The Gene-for-Gene Hypothesis 2.0

The gene-for-gene hypothesis states that for each gene controlling resistance in the host, there is a corresponding, specific gene controlling avirulence in the pathogen. Allelic series of the cereal mildew resistance genes Pm3 and Mla provide an excellent system for genetic and molecular analysis of resistance specificity. Despite this opportunity for molecular research, avirulence genes in mildews remain underexplored. Earlier work in barley powdery mildew (B.g. hordei) has shown that the reaction to some Mla resistance alleles is controlled by multiple genes. Similarly, several genes are involved in the specific interaction of wheat mildew (B.g. tritici) with the Pm3 allelic series. We found that two mildew genes control avirulence on Pm3f: one gene is involved in recognition by the resistance protein as demonstrated by functional studies in wheat and the heterologous host Nicotiana benthamiana. A second gene is a suppressor, and resistance is only observed in mildew genotypes combining the inactive suppressor and the recognized Avr. We propose that such suppressor/avirulence gene combinations provide the basis of specificity in mildews. Depending on the particular gene combinations in a mildew race, different genes will be genetically identified as the “avirulence” gene. Additionally, the observation of two LINE retrotransposon-encoded avirulence genes in B.g. hordei further suggests that the control of avirulence in mildew is more complex than a canonical gene-for-gene interaction. To fully understand the mildew–cereal interactions, more knowledge on avirulence determinants is needed and we propose ways how this can be achieved based on recent advances in the field.
Tentativas de suicídio e suicídios na atenção pré-hospitalar

Objetivo Caracterizar as tentativas de suicidio e suicidios ocorridos em um municipio do noroeste do Estado do Parana, atendidos em servico pre-hospitalar. Metodos Estudo descritivo, transversal, dos registros de atendimentos pre-hospitalares de 257 vitimas de tentativa de suicidio e suicidio, no periodo de 2005 a 2012, por meio de analise bidimensional por qui-quadrado. Resultados Ocorreram 180 tentativas de suicidio e 76 suicidios. A idade variou de 13 a 93 anos, com media de 33,5 ± 15,1 anos e maior prevalencia na populacao jovem do sexo masculino. As ocorrencias se concentraram nos meses da primavera e verao, na zona urbana. O uso de objeto cortante foi o metodo mais empregado, seguido por intoxicacao e precipitacao de locais elevados. Conclusao Conhecer caracteristicas, metodos e fatores agravantes fornecem subsidios para implementacao de medidas de prevencao.
Automatic Facial Image Annotation and Retrieval by Integrating Voice Label and Visual Appearance

Annotation is important for managing and retrieving a large amount of photos, but it is generally labor-intensive and time-consuming. However, speaking while taking photos is straightforward and effortless, and using voice for annotation is faster than typing words. To best reduce the manual cost of annotating photos, we propose a novel framework which utilizes the scarce spoken annotations recorded while capturing as voice labels and automatically label every facial image in the photo collection. To accomplish this goal, we employ a probabilistic graphical model which integrates voice labels and visual appearances for inference. Combined with group prior estimation and gender attribute association, we can achieve an outstanding performance on the proposed synthesized group photo collections.
Vision-based drowsiness detector for a realistic driving simulator

This paper presents a nonintrusive approach for monitoring driver drowsiness, based on computer vision techniques, installed in a realistic driving simulator. An IR stereo camera is placed in from of the driver in order to obtain PERCLOS, the most confident drowsiness parameter [1], in real-time and in a robust and automatic way. Our proposal doesn't need a calibration process and includes three main stages. The first is the pre-processing stage, which includes face and eye detection based on appearance strategy using the Viola and Jones algorithm, and the equalization of the eyes using a Hat transformation. An eye tracking strategy in a sequence of image frames is then carried out. The second stage executes the pupil position extraction and its characterization using integral projection techniques and a Gaussian model. The final stage executes the PERCLOS estimation, depending on the eyes closed rate on duration of time interval and fusing information obtained for each eye in the two images of the stereo camera. For evaluation of the proposed system several experiments have been designed by psychologists and carried out. A preliminary study about the performance of the proposal, based on confusion matrixes, is presented.
Functional approaches to generating orderings for efficient symbolic representations

The authors present a functional approach to generating orderings for representing functions. They develop a cost function which closely mimics the ordered binary decision diagram operations and can be quickly computed. Using the cost as a metric for an ordering, an annealing procedure was used to arrive at good variable orderings. The results obtained by simulated annealing are compared to orderings generated from heuristics that use circuit topology to arrive at a variable ordering. <<ETX>>
Embarrassingly Parallel Variational Inference in Nonconjugate Models

We develop a parallel variational inference (VI) procedure for use in data-distributed settings, where each machine only has access to a subset of data and runs VI independently, without communicating with other machines. This type of "embarrassingly parallel" procedure has recently been developed for MCMC inference algorithms; however, in many cases it is not possible to directly extend this procedure to VI methods without requiring certain restrictive exponential family conditions on the form of the model. Furthermore, most existing (nonparallel) VI methods are restricted to use on conditionally conjugate models, which limits their applicability. To combat these issues, we make use of the recently proposed nonparametric VI to facilitate an embarrassingly parallel VI procedure that can be applied to a wider scope of models, including to nonconjugate models. We derive our embarrassingly parallel VI algorithm, analyze our method theoretically, and demonstrate our method empirically on a few nonconjugate models.
Modernization of Confucianism: An Ethnographic Observation of Cultural Promoting Community

Abstract China is becoming one of the super powers in the world and the Chinese government is trying to promote Confucianism, the core philosophy of East Asia to the rest of the world in order to strengthen its soft power. As modernization is becoming the global process since the Cold War, the modernization of Confucianism is as well under process to fit in the new era. This article is based on a case of Confucianism promoting project to study the process and effect of cultural modernization and test how modernization helps the promotion of traditional Chinese culture. Such as, 1. The modernization will trigger voluntary and involuntary changes of the culture. 2. Cultural modernization will create a common language with other culture background people that are helpful in order to better understand Chinese traditional culture. 3. Different cultural background people are more sensitive to their own cultural elements even modernization combines various factors of traditional and modern culture or foreigner and local culture.
Integrating T race Logic and Petri Nets Speci

This paper presents an experience in formal meth ods integration for the speci cation and validation of distributed fault tolerant systems The speci cation formalisms we deal with are the trace logic based on the CSP theory and stochastic Petri nets Their inte gration allows to combine the power of event traces to specify the behaviour of a system in an intuitive and modular way and the power of Petri nets for the analy sis of concurrent systems The integrated speci cation technique is discussed by applying it to a real industrial control system which uses redundant modules to guar antee given operational conditions despite failures and incorporates a voting algorithm for arbitration over the replicated units
Developing a GIS-based Fuzzy AHP Model for Selecting Solar Energy Sites in Shodirwan Region in Iran

The objective of this study is to use a Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and geographical mapping models using Geographical Information System (GIS) to locate the most appropriate sites for solar energy farms in Shodirwan region in Iran. GIS interpolation showed that annual solar insolation in Shodirwan is very good and can be used for potential solar farm locations. The average of solar insolation in the region is 5.12 kWh/m2/day annually. Results showed that 18.25% of the Shodirwan area is exploitable as solar farms. With a conversion efficiency of 10% and area factor of 70%, annual electricity production for the exploitable area is roughly 16100 GWh. Land suitability analysis for solar farms implementation was carried out and overlay results obtained from the analysis of the resultant maps showed that 13.98% and 3.79% of the total land area demonstrate high and good suitability levels, respectively. The total electricity generation potential from both highly and good suitability levels in Shodirwan region was about 15,690 GWh annually.
Growing Up African-American and Female: The Relationship Between Racial Socialization and Self-Esteem of African-AmericanFemale Adolescents.

DAVIS, CARMEN PYLES. Growing up African-American and Female: The Relationship Between Racial Socialization and Self-esteem of African-American Female Adolescents. (Under the direction of Dr. Stanley B. Baker.) Dominant discourse in American society has posed a problem for minority populations because social and identity constructs, such as race, gender, and class, have created a society that has not been fair for less dominant groups. Growing up in the United States as an African-American female adolescent poses particular challenges because these girls contend with typical pre-adolescent and adolescent developmental tasks along with how to negotiate their multiple identities (i.e., being Black and female). For these reasons, developmental issues for African-American adolescent girls are best understood using a multiple-lens paradigm inclusive of gender, race, ethnicity, and social class. Across disciplines, most empirical studies of African-American adolescent girls have emphasized atrisk themes, frequently neglecting normative developmental concerns. The present study explored African-American female adolescents across three socioeconomic (SES) groups to learn how girls from different backgrounds respond to racial socialization as it relates to selfesteem. Ninety-five African-American girls completed questionnaires related to SES, racial socialization experiences, and self-esteem. Correlational (Pearson product-moment) and comparison (ANOVA) statistics indicated no significant relationships between racial socialization and self-esteem, racial socialization and SES, or self-esteem and SES. A significant difference was found in racial socialization frequency scores for the middle SES group compared to the high SES group. Significant differences were also found in racial socialization agreement where the high SES group had lower scores than the low and middle SES group. The finding that more than 85% of the participants in all three SES groups had higher than average self-esteem scores supports those of prior studies that African-American girls do not experience the same declines in self-esteem during adolescence as do girls from other racial/cultural groups. This research adds to existing literature about this population and may assist counseling professionals and others in understanding the normative development of African-American female adolescents and how race, gender, and socioeconomics play a part in this development. Growing up African-American and Female: The Relationship Between Racial Socialization and Self-esteem of African-American Female Adolescents
Fluoxetine elevates allopregnanolone in female rat brain but inhibits a steroid microsomal dehydrogenase rather than activating an aldo-keto reductase

Fluoxetine, a selective serotonin reuptake inhibitor, elevates brain concentrations of the neuroactive progesterone metabolite allopregnanolone, an effect suggested to underlie its use in the treatment of premenstrual dysphoria. One report showed fluoxetine to activate the aldo‐keto reductase (AKR) component of 3α‐hydroxysteroid dehydrogenase (3α‐HSD), which catalyses production of allopregnanolone from 5α‐dihydroprogesterone. However, this action was not observed by others. The present study sought to clarify the site of action for fluoxetine in elevating brain allopregnanolone.
Exploring views on heritage language use and bilingual acquisition: quantitative and qualitative evidence from teachers and immigrant students in the Greek context

ABSTRACT In this paper, we present a synthesis of a series of studies, carried out by our research groups, from the Greek educational context on teachers’ and immigrant students’ views on issues of bilingual acquisition and of heritage language learning and teaching. Albeit including heterogeneous samples and employing quantitative and qualitative instruments, our data functioned in a complementary way, forming a converging ‘picture’ about the status of heritage language and immigrant students in the Greek educational context. From the total of our studies, it was revealed that both teachers and immigrant students oscillate between the opposing forces of assimilation and acceptance of the ‘other’/resistance to assimilation.
Towards Video Management over Relational Database

Video has become popular in our daily life for both professional and consumer applications. Both low level video processing and high level semantic video analysis are critically computational tasks in application domains. Most of current video computing tools are developed for specific analytic tasks, they are lack higher level interoperability with database and treat database merely as a relational data storage engine rather than an analytic platform, which causes inefficient data access and massive amount of data movement. In this paper, we study how to support video data management over relational database, and present our initial solutions of video data storage mechanism, video data access method and efficient video analytics. We also illustrate our ongoing prototype system HybVideo that developed in a novel architecture. It integrates above solutions to tackle the major challenges of providing a platform for both storage and analysis of video data.
Network Security Evaluation Algorithm Based on Access Level Vectors

The attack graph, a typical model-based method, is widely used in the field of network security evaluation. The biggest disadvantage of attack graph method is its exponential growth of the state space. This paper presents an efficient algorithm based on the malefactorpsilas access level vector in every host of the network to generate a reduced attack graph in polynomial compute complexity. In this algorithm, the state space is reduced to O(nm), where n is the number of nodes and m is the whole number of vulnerabilities in the network. We also present a standard method to generate attack templates from the vulnerabilities.
Microwave Characterization of Carbon Nanotube Yarns For UWB Medical Wireless Body Area Networks

Carbon nanotube (CNT) yarns are novel CNT-based materials that extend the advantages of CNT from the nanoscale to macroscale applications. In this study, we have modeled CNT yarns as potential data transmission lines. Test structures have been designed to measure electrical properties of CNT yarns, which are attached to these test structures using gold paste. DC testing and microwave S-parameter measurements have been conducted for characterization. The observed frequency independent resistive behavior of the CNT yarn is a very promising indicator that this material, with its added values of mechanical resilience and thermal conductivity, could be invaluable for a range of applications such as body area networks. A model is developed for the CNT yarn, which fits the measured data collected and agrees in general with similar data for non-yarn CNTs.
Modana: An Integrated Framework for Modeling and Analysis of Energy-Aware CPSs

Cyber-Physical Systems (CPSs) as advanced embedded systems integrating computation with physical process are increasingly penetrating into our life. Modeling and analysis for such systems closely involved with us are actively researched. A current challenging problem is how to take advantages of existing technologies like SysML/MARTE, Modelica and Statistical Model Checking (SMC) through effective integration. Moreover, the lack of efficient methodologies or tools for modeling and analysis of CPSs makes the gap between design and analysis models hard to bridge. To solve these problems, we present a framework named Modana to achieve an integrated process from modeling with SysML/MARTE to analysis with SMC for CPSs in terms of Non Functional Properties (NFP) such as time, energy, etc. Functional Mock-up Interface (FMI), as a connecting link between modeling and analysis, plays a major role in coordinating various tools for co-simulation to generate traces as the input of statistical model checker. To demonstrate the capability of Modana framework, we model energy-aware buildings as a case study, and discuss the analysis on energy consumption in different scenarios.
A population-based study of hospital length of stay and emergency readmission following surgery for non-small-cell lung cancer

OBJECTIVES We conducted a population-based analysis of time trends in length of stay (LOS), predictors of prolonged LOS and emergency readmission following resection for non-small-cell lung cancer (NSCLC). METHODS Incident lung cancers (ICDO2:C34), diagnosed between 2002 and 2008, were identified from the National Cancer Registry (NCR) of Ireland, and linked to hospital in-patient episodes (HIPE). For those with NSCLC who underwent lung resection, the associated hospital episode was identified. Factors predicting longer LOS (upper quartile, >20 days), and emergency readmission within 28 days of the index procedure (IP) were investigated using Poisson regression. RESULTS A total of 1284 patients underwent resection. Eighty-four (7%) subsequently died in hospital and 1200 (93%) were discharged. Hundred and nineteen of 1200 (10%) were readmitted as an emergency within 28 days of discharge. Median LOS after the IP was 13 days (inter-decile range: 7–35). Risk of prolonged LOS was significantly greater in patients >75 years, resident in an area of highest deprivation, with 2+ comorbidities, who had undergone surgery in a lower-volume hospital, and died in hospital subsequent to the IP. Emergency readmission was significantly more likely in patients who were resident in an area of highest deprivation, with 2+ comorbidities, and had Stage III disease or worse. The main reasons for emergency readmission were: pulmonary complications (29%), cardio/cerebrovascular events (21%) or infection (20%). CONCLUSIONS Half of the patients had a LOS in excess of 13 days, which was longer than any other country with published data. Patient and health-service factors were associated with prolonged LOS, while patient and tumour characteristics were associated with risk of emergency readmission. Deprivation was a conspicuous determinant of both LOS and readmission.
Instance Search Experiment for TRECVID 2010

1. Briefly, what approach or combination of approaches did you test in each of your submitted runs?  KB_lab : This system extracts the facial image from each cut scene frame using the Haar-like operator, and then eliminates noise images (non-facial image) using SVM. Next, SIFT features are detected from the true facial image, and the similarity of the facial image is calculated using the SIFT features. 2. What if any significant differences (in terms of what measures) did you find among the runs? none. 3. Based on the results, can you estimate the relative contribution of each component of your system/approach to its effectiveness? Estimation is the same as above.
Inverse Singular Value Method for Enforcing Passivity in Reduced-Order Models of Distributed Structures for Transient and Steady-State Simulation

Reduced-order modeling of distributed structures for transient and steady-state circuit simulation transforms discrete frequency-domain network parameters to a set of rational functions. The models are ideally causal and passive with passivity being the most difficult property to assure, especially when the distributed structures incorporate propagation delay effects or the available network parameters have limited bandwidth. Small errors in the frequency-domain network parameters, or out-of-band assumptions, can yield models that result in unstable transient simulations. Here, an inverse singular value method is developed that imposes the smallest perturbation required to simultaneously modify the residues, poles, and coupling coefficients of the rational function-based model to achieve passivity. The process enables selection of the frequency ranges for which the model is required to be most accurate. The method is based on the observation that a macromodel is passive if the singular values of the scattering parameter matrix are less than unity at all frequencies.
Noise properties of low-dose CT projections and noise treatment by scale transformations

Projection data acquired for image reconstruction of low-dose computed tomography (CT) are degraded by many factors. These factors complicate noise analysis on the projection data and render a very challenging task for noise reduction. In this study, we first investigate the noise property of the projection data by analyzing a repeatedly acquired experimental phantom data set, in which the phantom was scanned 900 times at a fixed projection angle. The statistical analysis shows that the noise can be regarded as normally distributed with a nonlinear signal-dependent variance. Based on this observation, we then utilize scale transformations to modulate the projection data so that the data variance can be stabilized to be signal independent. By analyzing the relationship between the data standard deviation and the data mean level, we propose a segmented logarithmic transform for the stabilization of the non-stationary noise. After the scale transformations, the noise variance becomes approximately a constant. A two-dimensional Wiener filter is then designed for an analytical treatment of the noise. Experimental results show that the proposed method has a better noise reduction performance without circular artifacts, by visual judgment, as compared to conventional filters, such as the Harming filter.