Miracle-dz/UniFAR-FTUs huggingface dataset:
Antimicrobial effect of aqueous and ethanolic extracts Teucrium polium L. on Streptococcus pyogenes, Pseudomonas aeruginosa and Staphylococcus epidermidis

Teucrium polium L . (Labiatae) has long been recognized in folk medicine in the treatment of many pathophysiological implications, such as gastrointestinal disorders, inflammations, diabetes and rheumatism. In this study antimicrobial activity of two crude extracts obtained from Teucrium polium L . was tested against bacterial species. Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) were determined using a microdilution analysis method. The antimicrobial effects of extracts were evaluated on Streptococcus pyogenes PTCC 1447, Pseudomonas aeruginosa PTCC 1310 and Staphylococcus epidermidis PTCC 1435 by “using the method of Collins” and “disk agar diffusion method”. The results showed that aqueous and ethanolic extracts were quite effective in 2000 μg/ml concentration on Streptococcus pyogenes and Staphylococcus epidermidis and were prevented from growth them on medium, while both extracts have no certain antimicrobial effect on Pseudomonas aeruginosa. In “disk agar diffusion method”, 10, 20, 30 and 40 mg/ml aqueous and alcoholic extracts concentrations, was inhibition effect on Streptococcus pyogenes and Staphylococcus epidermidis , and 30 and 40 mg/ml aqueous and ethanolic extracts concentrations, has inhibition effect on Pseudomonas aeruginosa prevent them growing, but at 10 and 20 mg/ml concentrations, no inhibitory effect on Pseudomonas aeruginosa was observed. The results indicate that ethanolic and aqueous extracts of Teucrium polium L. have the greatest effect on gram-positive bacterium Streptococcus pyogenes (p<0.05). Results showed, aqueous and ethanolic extracts of Teucrium polium L. , have been strong antimicrobial activity against many food pathogen bacteria.
The impact of elevated CO 2 , increased nitrogen availability and biodiversity on plant tissue quality and decomposition

Elevated CO2, increased nitrogen (N) deposition and increasing species richness can increase net primary productivity (NPP). However, unless there are comparable changes in decomposition, increases in productivity will most likely be unsustainable. Without comparable increases in decomposition nutrients would accumulate in dead organic matter leading to nutrient limitations that could eventually prohibit additional increases in productivity. To address this issue, we measured aboveground plant and litter quality and belowground root quality, as well as decomposition of aboveground litter for one and 2-year periods using in situ litterbags in response to a three-way factorial manipulation of CO2 (ambient vs. 560 ppm), N deposition (ambient vs. the addition of 4 g N m! 2 yr! 1) and plant species richness (one, four, nine and 16 species) in experimental grassland plots. Litter chemistry responded to the CO2, N and plant diversity treatments, but decomposition was much less responsive. Elevated CO2 induced decreases in % N and % lignin in plant tissues. N addition led to increases in % N and decreases in % lignin. Increasing plant diversity led to decreases in % N and % lignin and an increase in % cellulose. In contrast to the litter chemistry changes, elevated CO2 had a much lower impact on decomposition and resulted in only a 2.5% decrease in carbon (C) loss. Detectable responses were not observed either to N addition or to species richness. These results suggest that global change factors such as biodiversity loss, elevated CO2 and N deposition lead to significant changes in tissue quality; however, the response of decomposition is modest. Thus, the observed increases in productivity at higher diversity levels and with elevated CO2 and N fertilization are not matched by an increase in decomposition rates. This lack of coupled responses between production and decomposition is likely to result in an accumulation of nutrients in the litter pool which will dampen the response of NPP to these factors over time.
A New Approach to Combine Classifiers Trained by NCL

In this paper we propose a new way to combine classifiers trained and diverged by NCL that leads to superior results in compare with averaging and DTs methods alone. In the proposed method after training classifiers by NCL, DTs and averaging are employed independently to combine them and then the outputs are combined again by averaging. For the second level combination, support vectors are scaled to the [0,1] interval. We show that each method used in the first level of combination yields a better performance in a different part of dataset so that they can complement each other. We did two sets of experiments, one on Satimage dataset and the other one on ORL dataset which showed a better performance for our method.
Correlates of Adolescent Cyberbullying in South Korea in Multiple Contexts: A Review of the Literature and Implications for Research and School Practice

ABSTRACT Cyberbullying is rapidly increasing in South Korea. The present article reviews research on factors associated with cyberbullying perpetration and victimization in South Korea. Study findings suggest a number of factors within individual, family, peer, and school levels. Relations with parents, parental verbal abuse, and a lack of attachment are related to perpetration. Delinquent peer association is positively associated with perpetration and victimization, and students’ school satisfaction is negatively associated with this victimization. Adolescents’ use of social networking sites and social media and lack of rules in cyberspace are found to increase perpetration and victimization. Research and practice implications are discussed.
An integrated distributed monitoring for mission-based systems: On the example of an autonomous unmanned helicopter

This paper presents a new approach of an integrated distributed monitoring system for an autonomous unmanned helicopter. The navigation mission consists of reaching areas of interest on a path composed of specific waypoints. The task of such a monitoring system is to determine whether the helicopter behaves as intended in order to detect faults in the mission execution early and to enable a re-planning of the mission or a failure recovery in due time. This is a very important issue for autonomous systems as they have to cope not only with ordinary subsystems failures, but also with unexpected situations which make the mission goals unattainable. The approach uses a special combination of Petri Nets and Monte Carlo Methods (particle filter) and integrates different layers of the system architecture such as control actions (path-planning, low-level control), environment perception (vision-based recognition of landmarks), state observation (estimation of speed, position, attitude) and decision making (mission planning and re-planning) in a unified model.
Intra-layered Multicast Based on Competition Probability

Intra-layered multicast uses fixed sending rate interval for each layer, and a delegate of the receivers is selected in the layer for adjusting the layer’s sending rate. Sender adjusts layer’s sending rate within the layer rate interval according to the delegate’s rate. A Scheme based on competition probability formula for delegate selection is proposed in this paper. Two factors determine whether the current feedback receiver can be selected as the delegate. One is the related difference between feedback rate and current layer’s sending rate, the other is the approximately rate distribution of receivers in the layer. The scheme can reduce layer’s sending rate drop when receivers with high available bandwidth are dominant in the layer. Simulation results show that the scheme can meet most of receivers’ demand within a layer, and is TCP friendly.
An Adaptive Occluded Region Detection and Interpolation for Robust Frame Rate Up-Conversion

FRUC (Frame Rate Up-Conversion) technique needs an effective frame interpolation algorithm using motion information between adjacent neighboring frames. In order to have good visual qualities in the interpolated frames, it is necessary to develop an effective detection and interpolation algorithms for occluded regions. For this aim, this paper proposes an effective occluded region detection algorithm through the adaptive forward and backward motion searches and also by introducing the minimum value of normalized cross-correlation coefficient (NCCC). That is, the proposed scheme looks for the location with the minimum sum of absolute differences (SAD) and this value is compared to that of the location with the maximum value of NCCC based on the statistics of those relations. And, these results are compared with the size of motion vector and then the proposed algorithm decides whether the given block is the occluded region or not. Furthermore, once the occluded regions are classified, then this paper proposes an adaptive interpolation algorithm for occluded regions, which still exist in the merged frame, by using the neighboring pixel information and the available data in the occluded block. Computer simulations show that the proposed algorithm can effectively classify the occluded region, compared to the conventional SAD-based method and the performance of the proposed interpolation algorithm has better PSNR than the conventional algorithms.
Shared control policies for safe wheelchair navigation of elderly adults with cognitive and mobility impairments: Designing a wizard of oz study

Older adults often lack the ability or strength to walk or to self-propel in manual wheelchairs. However, the need for a significant level of cognitive capacity to safely operate current powered wheelchair technology tends to exclude users with cognitive impairments. The resulting lack of mobility for a significant proportion of elderly residents in long term care leads to negative social, mental and physical outcomes. In this paper, we review shared (or collaborative) control policies implemented by smart wheelchair prototypes that have been tested by participants from their target populations, and highlight key usability findings and clinical insights. We discuss desirable features for control policies in new intelligent wheelchairs for cognitively impaired older adults. We then propose a method to evaluate these policies in a Wizard of Oz study conducted with cognitively impaired participants living in long term care facilities.
The Role of Thyroid Hormone Signaling in the Prevention of Digestive System Cancers

Thyroid hormones play a critical role in the growth and development of the alimentary tract in vertebrates. Their effects are mediated by nuclear receptors as well as the cell surface receptor integrin αVβ3. Systemic thyroid hormone levels are controlled via activation and deactivation by iodothyronine deiodinases in the liver and other tissues. Given that thyroid hormone signaling has been characterized as a major effector of digestive system growth and homeostasis, numerous investigations have examined its role in the occurrence and progression of cancers in various tissues of this organ system. The present review summarizes current findings regarding the effects of thyroid hormone signaling on cancers of the esophagus, stomach, liver, pancreas, and colon. Particular attention is given to the roles of different thyroid hormone receptor isoforms, the novel integrin αVβ3 receptor, and thyroid hormone-related nutrients as possible protective agents and therapeutic targets. Future investigations geared towards a better understanding of thyroid hormone signaling in digestive system cancers may provide preventive or therapeutic strategies to diminish risk, improve outcome and avert recurrence in afflicted individuals.
ON (m, n) –Upper Q-Fuzzy Soft Subgroups

In this paper we shall study some properties for upper Q- fuzzy subgroups, some lemma and theorem for this subject. We shall study the upper Q- fuzzy index with the upper fuzzy sub groups; also we shall give some new definitions for this subject. On the other hand we shall give the definition of the upper normal fuzzy subgroups, and study the main theorem for this. We shall also give new results on this subject.
Black-Scholes equation from Gauge Theory of Arbitrage

We apply Gauge Theory of Arbitrage (GTA) {hep-th/9710148} to derivative pricing. We show how the standard results of Black-Scholes analysis appear from GTA and derive correction to the Black-Scholes equation due to a virtual arbitrage and speculators reaction on it. The model accounts for both violation of the no-arbitrage constraint and non-Brownian price walks which resemble real financial data. The correction is nonlocal and transform the differential Black-Scholes equation to an integro-differential one.
Structural Composition Attacks on Anonymized Data

Anonymized releases of databases are increasingly available in public. The composition of two releases does not necessarily fulfil any anonymity notion, even if the individual releases do fulfil that anonymity notion on their own. In this paper, we study composition scenarios and provide formalizations. We introduce a formal framework to study the composition of databases on a structural level and show the equivalence of the composition scenarios used in the literature. We show that known attacks on anonymity notions can be reduced to two simple properties and only need limited side information. keywords: database anonymization, data composition, anonymity notions
REENGINEERING AND REFACTORING LARGE-SCALE SCIENTIFIC PROGRAMS WITH THE UNIFIED PROCESS: A CASE STUDY WITH OSIRIS PIC PROGRAM

OSIRIS is a large-scale particle-in-cell (PIC) code which was developed at Particle Beam Physics Laboratory (PBPL) in UCLA for researches of laser- plasma interactions. OSIRIS was reengineered and documented in UML by our group and ported to Linux cluster machine of 8 nodes. We report our current status of developing the extended version of OSIRIS, which was named as OSIRIS-X and maintained and developed with the Unified Process. Some guidelines in designing and refactoring large-scale scientific codes are presented and discussed. A design model of numerically intensive programs for large-scale computing is suggested, and it is discussed how we can use it for rapid development and prototyping of scientific programs. We also discuss future challenges and prospects in OSIRIS-X development.
The Role of End User in E-Government Application Development: A Conceptual Model in the Agricultural Context

This paper describes a new conceptual approach of e-government application development in which end users such as government managers, responsible officials and citizens at different levels can engage in effective service delivery, particularly in the agricultural sector. This approach provides end-user specific customizable provisions in which responsible government officials can design public services for the target end-user groups/local citizens such as primary producers. In the G2C Government to Citizen dimension, the author focuses on a hypothetical case of an e-government solution that provides various agricultural extension services such as training, awareness, consultation services, and knowledge sharing services provision, according to individual or farming requirements. This initiative reinforces a shift from the traditional information portal process to a new provision where citizens/primary producers can actively contribute in designing their useful services from the relevant government agencies. This paper presents a generic process model and identifies the critical interplaying roles between the end-user groups. The study argues that the process model may be operationalized in various other government service sectors.
Financial crisis, monetary policy reform and the monetary transmission mechanism in Turkey

Turkey experienced a financial crisis in 2000–2001, which led to significant financial reforms. The reforms resulted in a switch to a floating exchange rate, granted greater central bank independence and pursuit of a more credible monetary policy. Investigation of the channels of monetary policy in both periods finds that monetary policy's output effects have been strengthened considerably by the reforms. In the pre-crisis period, monetary policy was highly inflationary, while in the post-crisis period, monetary policy targets low inflation and has become a tool for output stabilization. These results support the importance of central bank independence and a credible policy.
Constrained optimal control problems of nonlinear systems based on improved Newton algorithms

In this paper, we consider an optimal control problem of constrained nonlinear systems. By standard optimization methods, it is difficult to solve the problem, since such constraints are very complex. To overcome this difficulty, by a smoothing technique and a penalty function method, an improved Newton algorithm is developed for solving the problem. Convergence results indicate that the proposed methods is globally convergent with quadratic rate. Finally, numerical results indicate that our method is effective compared to existing methods.
Changing prevalence of overweight children and adolescents at onset of insulin-treated diabetes.

OBJECTIVE The aim of this study was to compare the prevalence of being overweight in black and white children and adolescents at onset of insulin-treated diabetes during two time periods: 1979-1989 (period I) and 1990-1998 (period II). RESEARCH DESIGN AND METHODS All black children <19 years of age diagnosed with diabetes and treated with insulin at onset admitted to the Children's Hospital of Pittsburgh between January 1979 and December 1998 were matched with white children by sex, age at onset, and year of diagnosis. Data were obtained from a review of medical records. Overweight was defined as BMI >or=85th percentile for age and sex. Islet cell autoantibodies were measured. RESULTS The prevalence of being overweight increased from 12.6% (period I) to 36.8% (period II) (P = 0.0003); in whites from 2.9 to 16.6% (P = 0.04) and in blacks from 22 to 55% (P = 0.001); and in the age-group <11 years from 7.3 to 22.2% (P = 0.04) and age 11-18 years from 20 to 50% (P = 0.006). In children with at least one antibody, the prevalence of being overweight increased from 5.1 to 24.4% (P = 0.001). In the multivariate logistic regression, period of diagnosis (period II), race (black), age at onset (>or=11 years old), and absence of autoimmunity were associated with being overweight. CONCLUSIONS At onset of the disease, the prevalence of being overweight has tripled from the 1980s to the 1990s, following the trend in the general population. Weight gain may be an accelerating factor for onset of insulin-treated diabetes and may have contributed to the increased incidence of diabetes in youth seen in some populations.
The Roles of Religiosity and Affluence for Adolescents’ Family Orientation : Multilevel Analyses of 18 Cultures

Recent sociological and psychological debates concern the nature of the relation between changing religious beliefs and changing significance of the family. The current study analyzes multilevel relations between religiosity (personal and culture-level) and several aspects of family orientation for n = 4902 adolescents from 18 nations/areas from diverse cultural contexts covering a number of religious denominations with data from the Value-of-Children-Study (Trommsdorff & Nauck, 2005). In addition, cultural values from the World Values Survey representing religious versus secular values as well as survival versus self- expression values are examined at the cultural level of analysis as a joint effect with nation-level economic development. Results showed that religiosity/religious values were positively related to all aspects of adolescents’ family orientation at the individual as well as the cultural level, while societal affluence was only related to a loss of importance of the traditional and hierarchical aspects of family orientation. Postmaterialist self-expression values were unrelated to adolescents’ family orientation.
Evaluation of studies of causation (aetiology)

You have been appointed as the Nurse Manager of a nursing home that provides long term care for older people and have become aware that a large proportion of residents have pressure ulcers. You know that many preventive measures, such as special beds and mattresses, are promoted, but feel unsure as to which residents are most at risk and which characteristics predict those most likely to develop pressure ulcers. Although you know there are some pressure ulcer risk prediction tools available, you are not sure that these would apply to your residents and so would like to read some original research on the topic. Your long term goal is to ensure that care is targeted at those residents at highest risk so that preventable ulcers are avoided. Your focused clinical question is which characteristics of nursing home residents place them at higher risk of pressure ulcer development? You begin by searching Evidence-Based Nursing Online (www.evidencebasednursing.com) using the search term “pressure ulcer*”. This search identifies 8 abstracts, none of which address questions of risk factors. Similarly, a search of Evidence-Based Medicine finds no relevant studies. You try PubMed (www.ncbi.nlm.nih.gov), which is freely available online. You select the Clinical Queries search option, and the “Etiology” search because you are looking for articles concerned with the causation of pressure ulcers. You decide that your search should emphasise sensitivity over specificity so that you can minimise the risk of missing relevant articles. Your search terms are “pressure ulcer*” AND “nursing home*”. This search identifies 32 abstracts, one of which, “A longitudinal study of risk factors associated with the formation of pressure ulcers in nursing homes” sounds relevant.1 Studies that consider risk factors (often referred to as exposures) for certain diseases (often referred to as outcomes) are generally called analytical observational studies. They are …
Latent Low-Rank Transfer Subspace Learning for Missing Modality Recognition

We consider an interesting problem in this paper that uses transfer learning in two directions to compensate missing knowledge from the target domain. Transfer learning tends to be exploited as a powerful tool that mitigates the discrepancy between different databases used for knowledge transfer. It can also be used for knowledge transfer between different modalities within one database. However, in either case, transfer learning will fail if the target data are missing. To overcome this, we consider knowledge transfer between different databases and modalities simultaneously in a single framework, where missing target data from one database are recovered to facilitate recognition task. We referred to this framework as Latent Low-rank Transfer Subspace Learning method (L2TSL). We first propose to use a low-rank constraint as well as dictionary learning in a learned subspace to guide the knowledge transfer between and within different databases. We then introduce a latent factor to uncover the underlying structure of the missing target data. Next, transfer learning in two directions is proposed to integrate auxiliary database for transfer learning with missing target data. Experimental results of multi-modalities knowledge transfer with missing target data demonstrate that our method can successfully inherit knowledge from the auxiliary database to complete the target domain, and therefore enhance the performance when recognizing data from the modality without any training data.