Miracle-dz/UniFAR-FTUs huggingface dataset:
Decision making behavior in a two-choice uncertain outcome situation.

The predictions people make when placed in a two-choice uncertain outcome situation have received considerable attention in recent years. In the classical situation, as first used by Humphreys (1939), S is asked to predict which of two events (e.g., illumination or nonillumination of a light) will occur after a signal stimulus. The two events occur with fixed but unequal probabilities, say TI and 7T2, in a random sequence for a number of trials, and the occurrence of either is not contingent on S's behavior. The S is instructed to do his best to predict which will occur. He is allowed to witness the event, and thus to determine for himself the correctness or incorrectness of his prediction. There are two theoretical models of interest here which yield predictions about S's behavior in a situation of this sort. One is Estes' (1950, 1954; Estes & Burke, 1953) statistical learning model which yields the prediction that Ss will learn to match their response ratios (the relative frequencies with which they predict each of the events) to the actual probabilities of occurrence of the events. The same prediction is yielded by the Bush-Mosteller (1955) model when certain restrictions are applied to the parameters of that model. A number of studies report findings in support of this prediction (Estes & Straughan,
Latina High School Leaving: Some Practical Solutions. ERIC Digest.

THIS DIGEST WAS CREATED BY ERIC, THE EDUCATIONAL RESOURCES INFORMATION CENTER. FOR MORE INFORMATION ABOUT ERIC, CONTACT ACCESS ERIC 1-800-LET-ERIC Leaving school early has a dramatic impact on Hispanic girls, because Latinas face greater barriers than males when seeking high-wage jobs and opportunities in postsecondary education. Recent census figures demonstrate the serious problem of Latinas leaving school before graduation. In 1995, both African Americans and
The divergent opinions of regulatory authorities on roflumilast are puzzling but we need new drugs for treating chronic obstructive pulmonary disease

A Food and Drug Administration (FDA) committee of experts in the USA has delivered a negative judgement on the approval of roflumilast, a once-daily phosphodiesterase (PDE)4 inhibitor that was reviewed as a maintenance treatment for chronic obstructive pulmonary disease (COPD) patients with chronic bronchitis at risk for exacerbations, because safety and efficacy data were not strong enough to approve the drug [Walker, 2010]. Moreover, according to several members, the benefits of the drug are modest and do not outweigh the risks. The agency has asked for ‘certain additional information and analyses’ but ‘no additional patient trials have been requested’ [Walker, 2010].
Expression analysis of DNA methyltransferases 1, 3A, and 3B in sporadic breast carcinomas.

PURPOSE Three genes, namely DNA methyltransferase (DNMT) 1, DNMT3A, and DNMT3B, coding for DNMTs that affect promoter methylation status are thought to play an important role in the development of cancers. Little is known of the biological and clinical significance of these genes in human breast cancer. EXPERIMENTAL DESIGN We used real-time reverse transcription-PCR assays to quantify the mRNA expression of the three DNMT genes in a series of 130 breast cancer patients. We also sought relationships between mRNA levels of the DNMTs and those of 20 target genes involved in the DNMT pathway (subgroup of 46 breast tumors). RESULTS The DNMT3B gene showed the highest range of expression (81.8 compared with 16.6 and 14 for DNMT1 and DNMT3A, respectively). DNMT3B was overexpressed in 30% of the patients (5.4 and 3.1% for DNMT1 and DNMT3A, respectively). DNMT3B overexpression was significantly related to Scarff, Bloom, and Richardson histopathological grade III (P = 0.002), ERalpha negativity (P = 0.0015), and strong MKI67 expression (P = 3 x 10(-6)). In univariate analysis, DNMT3B overexpression was associated with poor relapse-free survival in the subgroup of patients who received adjuvant hormone therapy (with or without chemotherapy; P = 0.0064). Although the poor prognosis associated with DNMT3B overexpression was confirmed by univariate analysis in an independent series of 98 postmenopausal women exclusively treated with adjuvant tamoxifen therapy (P = 0.0036), DNMT3B expression status did not persist as an independent prognostic factor in multivariate analysis. CONCLUSIONS Although we failed to identify underexpression of specific target genes associated with DNMT increasing expression, the frequent overexpression of DNMT3B in this breast tumor series points to DNMT3B as a potential new therapeutic target in breast cancer.
Relations Between the Timing of the Second Heart Sound and Aortic Blood Pressure

The second heart sound (S2) is triggered by an aortic valve closure as a result of the ventricular-arterial interaction of the cardiovascular system. The objective of this paper is to investigate the timing of S2 in response to the changes in hemodynamic parameters and its relation to aortic blood pressure (BP). An improved model of the left ventricular-arterial interaction was proposed based on the combination of the newly established pressure source model of the ventricle and the nonlinear pressure-dependent compliance model of the arterial system. The time delay from the onset of left ventricular pressure rise to the onset of S2 (RS2) was used to measure the timing of S2. The results revealed that RS2 bears a strong negative correlation with both systolic blood pressure and diastolic blood pressure under the effect of changing peripheral resistance, heart rate, and contractility. The results were further validated by a series of measurements of 16 normal subjects submitted to dynamic exercise. This study helps understand the relationship between the timing of S2 and aortic BP under various physiological and pathological conditions.
Metalloproteinases and their inhibitors in squamous cell carcinoma of the hypopharynx: indicators of individual tumor aggressiveness.

BACKGROUND Matrix metalloproteinases (MMP) are proteolytic enzymes capable of degrading connective tissue components. MMP activity is modulated by tissue inhibitors of metalloproteinases (TIMP). Imbalanced secretion of certain MMP or disturbances in the differential control of MMP by TIMP have been implicated in the invasive potential of malignant tumors. METHODS Thirty-nine surgically obtained specimens of the hypopharynx were immunohistochemically stained with antibodies against MMP-1, MMP-2, MMP-3, MMP-9 and their inhibitors, TIMP-1 and TIMP-2. Thirty-one samples derived from primary tumors (PT-group) and 8 samples from recurrent tumors (RT-group). RESULTS In the PT-group, MMP-1 was expressed in almost all tumors. Expression of TIMP-1 was rarer than of TIMP-2. Relapse occurred in 8/31 cases expressing MMP-1 or MMP-9 (4 cases each). Staining for TIMP-1 was negative in these patients, while TIMP-2 was expressed in most cases. In the RT-group, MMP-1 and MMP-9 stained positive in an almost equal number of cases. Only TIMP-1 was not expressed in any tumor. Patients who died of tumor were uniformly negative for TIMP-1. CONCLUSIONS The findings suggest that the presence of MMP-9 and concomitant lack of TIMP-1 serve as prognostic indicators of tumor aggressiveness and increased risk of relapse.
Robust voice conversion systems using MFDWC

Voice conversion is a method used to transform one speakerpsilas voice into another speakerpsilas voice. New modification approach for voice conversion is proposed in this paper. We take Mel-frequency Discrete Wavelet coefficients (MFDWC) as the basic feature. This feature copes well with small training sets of high dimension, which is a problem often encountered in voice conversion. The proposed voice conversion system assumes parallel training data from source and target speakers and uses the theory of wavelets in order to extract speaker feature information. The satisfactory performance of the voice conversion system can be confirmed through ABX listening test and MOS grade.
A Graph Mining Algorithm for Classifying Chemical Compounds

Graph data mining algorithms are increasingly applied to biological graph dataset. However, while existing graph mining algorithms can identify frequently occurring sub-graphs, these do not necessarily represent useful patterns. In this paper, we propose a novel graph mining algorithm, MIGDAC (Mining Graph DAta for Classification), that applies graph theory and an interestingness measure to discover interesting sub-graphs which can be both characterized and easily distinguished from other classes. Applying MIGDAC to the discovery of specific patterns of chemical compounds, we first represent each chemical compound as a graph and transform it into a set of hierarchical graphs. This not only represents more information that traditional formats, it also simplifies the complex graph structures. We then apply MIGDAC to extract a set of class-specific patterns defined in terms of an interestingness threshold and measure with residue analysis. The next step is to use weight of evidence to estimate whether the identified class-specific pattern will positively or negatively characterize a class of drug. Experiments on a drug dataset from the KEGG ligand database show that MIGDAC using hierarchical graph representation greatly improves the accuracy of the traditional frequent graph mining algorithms.
A Novel Statistical Thresholding in Edge Detection Using Laplacian Pyramid and Directional Filter Banks

 Abstract— To achieve good localization and good detection of edges, a multi scale approach is required along with the direction of location of the edge. In this paper an edge detector is proposed which uses the Laplacian Pyramid for multi scale decomposition and a Directional Filter Bank to extract the direction. Furthermore, a thresholding based on statistical principles is used to validate the eligibility of a pixel to be an edge pixel. The results obtained from the proposed method are compared with the most popular Canny edge detector and are found to be appreciable. The results are also compared in terms of quantitative terms like psnr (dB) and Mean Square Error (MSE). The proposed method is found to performing better than the Canny edge detector both in terms of quantitative and qualitative evaluation.
Sex-based Association between Depression and Metabolic Syndrome in Korean Middle-aged and Older Adults

Objectives This study aimed to identify the sex-based association between depression and the development of metabolic syndrome (Mets) among middle-aged and older Korean adults. Methods A cross-sectional design was used for the secondary analysis of the 2010–2014 Korean National Health and Nutrition Examination Survey. Data from 1,938 men and 2,404 women were analyzed. Mets was defined in accordance with the criteria used for clinical diagnosis. Depression was assessed with a question about having clinical depression. The association between depression and the development of Mets with or without adjustment for covariates was identified by conducting logistic regression analysis on weighted data using a complex sample procedure. Results More women than men had depression. Before covariate adjustment, depression was significantly associated with the development of Mets among women (odds ratio [OR], 1.586; 95% confidence interval [CI], 1.152–2.183) and with a higher triglyceride level among men (OR, 1.679; 95% CI, 1.001–2.818). After covariate adjustment; depression was significantly associated with higher waist circumference among women (adjusted OR [AOR], 1.532; 95% CI, 1.046–2.245) and higher triglyceride level (AOR, 1.511; 95% CI, 1.029–2.219) than was Mets. Conversely, depression did not have significant effects on the development of Mets among men. Conclusion Depression was associated with the development of Mets among middle-aged and older Korean women. Healthcare providers in communities should assess women with depression for the presence of Mets components. Interventions for relieving depressive symptoms should also be provided to women at risk for Mets.
URank: formulation and efficient evaluation of top-k queries in uncertain databases

Top-k processing in uncertain databases is semantically and computationally different from traditional top-k processing. The interplay between query scores and data uncertainty makes traditional techniques inapplicable. We introduce URank, a system that processes new probabilistic formulations of top-k queries inuncertain databases. The new formulations are based on marriage of traditional top-k semantics with possible worlds semantics. URank encapsulates a new processing framework that leverages existing query processing capabilities, and implements efficient search strategies that integrate ranking on scores with ranking on probabilities, to obtain meaningful answers for top-k queries.
Transport of HIV Protease Inhibitors Through the Blood-Brain Barrier and Interactions With the Efflux Proteins, P-Glycoprotein and Multidrug Resistance Proteins

HIV protease inhibitors (HPIs) have limited penetration into the brain. This poor transport through the blood-brain barrier is mainly due to active efflux by proteins such as P-glycoprotein (P-gp) preventing drugs from clearing the brain of the virus. The present paper focuses on cerebral uptake of HPIs and interactions between HPIs and efflux proteins, either as substrates or modulators. Most of the studies described HPIs as P-gp substrates. Studies are more controversial when investigating HPIs as inhibitors of P-gp. HPIs seem to be able to inhibit efflux proteins of in vitro cell models but with limited consequences in vivo. Moreover, after repeated administrations of HPIs, most of them are also able to induce the expression and functionality of P-gp. For these reasons, certain combinations of HPIs may not efficiently increase brain uptake of HPIs as would combinations of more potent efflux inhibitors.
Practical attacks on proximity identification systems

The number of RFID devices used in everyday life has increased, along with concerns about their security and user privacy. This paper describes our initial findings on practical attacks that we implemented against 'proximity' (ISO 14443 A) type RFID tokens. Focusing mainly on the RF communication interface we discuss the results and implementation of eavesdropping, unauthorized scanning and relay attacks. Although most of these attack scenarios are regularly mentioned in literature little technical details have been published previously. We also present a short overview of mechanisms currently available to prevent these attacks
Sinus rate in acute myocardial infarction.

The clinical course of sinus bradycardia and sinus tachycardia has been studied in 735 patients owith acute myocardial infarction admitted to a coronary care unit. Sinus bradycardia was considered to have occurred when two or more records showed sinus rhythm with a rate below 6o a minute, and sinus tachycardia when a sinus rate over 0OO a minute occurred in two or more records. Hospital mortality of patients having sinus bradycardia was significantly lower (6%) and of those with sinus tachycardia was significantly higher (26%) than of those who had neither bradycardia nor tachycardia (i5%). Major ventricular arrhythmias were no more common in patients having sinus bradycardia and when they did occur did not usually do so at the time ,'that the bradycardia was present. Sinus bradycardia was more common in cases of posterior and subendocardial infarction without radiological evidence of cardiac failure, while sinus tachycardia was frequent in patients with anterior transmural infarction complicated by heart failure. The benign course of sinus bradycardia is surprising because experimental evidence suggests that slow heart rates after infarction favour the occurrence of ventricular arrhythmias. Further work is necessary to correlate heart rate with prognosis, particularly in patients seen at the onset ,. f infarction, and before admission to a coronary care unit.
Rapid and Simultaneous Detection of Major Drug Resistance Mutations in Reverse Transcriptase Gene for HIV-1 CRF01_AE, CRF07_BC and Subtype B in China Using Sequenom MassARRAY® System

The development of a rapid, high-throughput and cost-effective HIV-1 drug resistance (HIV-DR) testing system is a challenge for areas consisting different HIV-1 strains. In this study, we established a broadly reactive multiplex assay that could simultaneously detect major drug resistance mutations at 8 loci, which are associated with resistance to commonly used nucleoside reverse transcriptase inhibitors (NRTIs) and Non-nucleoside reverse transcriptase inhibitors (NNRTIs), in specimens of HIV-1 CRF01_AE, CRF07_BC and subtype B, the three major circulating strains in China, using the matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) provided by Sequenom MassARRAY® system. To establish the assay, pol gene fragments were prepared from the plasma viral RNA of 159 patients by nested PCR and the presence of wild type and mutant alleles at the 8 loci were analyzed by MALDI-TOF MS. In terms of loci, the detection rate of the alleles was greater than 97% for M41L, K65R, M184V and G190A, 91.2% for K101E/Q/P, 91.2% for T215F/Y, 89.9% for K103N/S and 80.5% for L210W. In terms of individuals, 80% of the alleles were detected in 95.4% CRF01_AE patients, 100% CRF07_BC patients and 83.3% subtype B patients. Importantly, the MALDI-TOF MS results were concordant to the drug resistance profiles of patients obtained from conventional sequencing analysis after excluded the failed detections. Using plasmid templates, the assay was estimated to be sensitive to detect drug resistant variants at level about 20% of the circulating viral population. The capability of this assay to detect mixed viral populations was further verified by two different patient specimens. In conclusion, this study evaluated the use of Sequenom MassARRAY® system for high-throughput detection of HIV-DR mutations towards the commonly used reverse transcriptase inhibitors in China.
Reducing manual labeling in singing voice detection: An active learning approach

In order to solve the bottleneck of tedious and time-consuming manual labeling in singing voice detection, in this paper we integrate the active learning mechanism into the conventional SVM-based supervised learning algorithm. By selecting most informative unlabeled samples and asking for human annotation, active learning substantially reduces the number of training samples to be labeled and meanwhile obtains almost the same frame-level vocal/non-vocal classification performance. Experiments on the public MIR-1K database demonstrate the effectiveness of active learning in the task of singing voice detection.
Examining child restraint use and barriers to their use: lessons from a pilot study

Objective: To determine the suitability of four research methods to measure the rate of child restraint device (CRD) use and incorrect use in New Zealand and obtain data on barriers to CRD use. Design and setting: To assess the rates of CRD use among vehicles carrying children 8 years of age and under, two methods were piloted—namely, an unobtrusive observational survey and a short interview and close inspection. A self administered questionnaire and focus group interviews were also piloted to assess CRD use, reasons for use and non-use, and to obtain information on barriers to their use. Respondents to all methods except the focus groups were approached in supermarket car park sites at randomly selected times. Focus groups were established with parents identified through early childhood organisations. All methods were assessed on criteria related to efficiency, representativeness, and ability to obtain the necessary data. Results: The observational survey provided a simple method for identifying rates of CRD use, while the self administered questionnaire obtained data on demographic characteristics and reported the installation and use/non-use of CRDs. The interview/inspection addressed all the questions of both the above methods and enabled incorrect CRD use to be examined. The focus groups provided the most meaningful information of all methods on barriers to CRD use. Discussion and conclusion: Advantages and limitations of these methods are discussed and some refinements of the original instruments are proposed. The interview/inspection and focus group methods were identified as being more appropriate for efficiently obtaining reliable data on CRD use and identification of barriers to CRD use.
Imidazopyridazine derivatives as Gabaa receptor modulators

Compound. The present invention relates to imidazopyridazine derivatives. More particularly, the invention is a compound of the Formula a salt thereof of 4- (biphenyl-3-yl)-7H-imidazo [4,5-c] pyridazine derivatives and the pharmaceutically acceptable formula (I), R Imidazopyridazine derivatives of the invention modulate the activity of GABA These will be useful in the treatment of many conditions, including pain. [Formula 1]
Automating the Administration and Analysis of Psychiatric Tests: The Case of Attachment in School Age Children

This article presents the School Attachment Monitor, a novel interactive system that can reliably administer the Manchester Child Attachment Story Task (a standard psychiatric test for the assessment of attachment in children) without the supervision of trained professionals. Attachment problems in children cause significant mental health issues and costs to society which technology has the potential to reduce. SAM collects, through instrumented doll-play games, enough information to allow a human assessor to manually identify the attachment status of children. Experiments show that the system successfully does this in 87.5% of cases. In addition, the experiments show that an automatic approach based on deep neural networks can map the information collected into the attachment condition of the children. The outcome SAM matches the judgment of expert human assessors in 82.8% of cases. This is the first time an automated tool has been successful in measuring attachment. This work has significant implications for psychiatry as it allows professionals to assess many more children cost effectively and to direct healthcare resources more accurately and efficiently to improve mental health.
Cognition–emotion interactions in schizophrenia: Emerging evidence on working memory load and implicit facial-affective processing

Although much is known about working memory (WM) and emotion perception deficits in schizophrenia, little is known of how these deficits interact. We sought to address this gap by conducting a narrative review of relevant literatures and distilling core themes. First, people with schizophrenia have difficulty with high load and during initial phases of WM (e.g., encoding, early rehearsal), yet are able to activate WM-related prefrontal brain regions to the same maximal degree as comparison controls under certain circumstances. Second, people with schizophrenia have difficulty identifying and expressing facial emotions, yet demonstrate heightened automatic/implicit processing of facial emotions. Third, people with schizophrenia behaviourally demonstrate intact cognition–emotion interactions on laboratory tasks wherein emotional processing is automatic/implicit, yet demonstrate cognition–emotion disconnections in other levels of analysis. Insights are drawn from basic science showing interdependency between WM load and implicit emotion. Future research questions are raised regarding interactions between WM load and implicit facial-affective processing in schizophrenia.