Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation of the Predictive Validity of Implicit and Explicit Measures of Integrity

The present study examined the incremental predictive validity of two overt-based Implicit Association Tests (IATs) and three personality-based IATs for behavior related to integrity and character. The overt-based IATs assess attributes related to self and honesty. The personality-based IATs assess attributes related to the “dark triad” of personality – Machiavellianism, subclinical narcissism, and subclinical psychopathy. A temptation manipulation provided opportunities for subjects to lie, cheat, and steal on a number finding task, to receive a greater financial reward. In addition to the five IATs, subjects also completed five explicit (self-report) overt and personality-based integrity measures. Findings did not support the predictive power or the incremental validity of the IATs but the impression management subscale of the explicit personality-based Paulhus Deception Scale could predict the criterion behavior for only those who lied.
Specification, Semantics, and Enforcement of Dynamic Database Constraints

In older to specify dytxmi (' con-strc int? , we ~lrcsfnt * a siclplifjcd vel-sion of teopcltal lccic hasec! on the tenporal quarltjfjcrs " ~l\:eys " cind " so~c~:.ine " as well as their bcuncieii ve: s ions " always. .unt.i 1 " and " samet.ire. .hefore ". ! C rittor t::at , ! n rlcst practical cases, the Iloun-ded tecpol a1 quar:tifiers can be oxpresscd by np-propri att fotm~! las \:i th unhcundcc: tenpor; I q " ant ifiets. IJe t't.cn use special kinds of tt*mpcltal fcdrr-ctlas as a language to specify c'pIiiItYiC con-striiints. The problerr. of enfcBrcir.g st1c.h CLIP-strzints is t! ler; reduced to the l~rot! e~ cf cn-fz,rcirg dynoslic,ally changing sets cf two 1,irds of static c.onstt-hints, called universal ant1 ex-istertial constrafnts. Vhilc unicel sal con-strziats can t:c cpforced strict];. ir principle, vic;l? t ion of rsi.stent;'*l constraints cannot he detected in eac! ~ case ft tl:c. cr\rlif.:;t ;:or:ent. Ile give a sufficjcnt criterion fcr detcctin:; vicl;-tier 0C e> ist0t icl c.onstraints. i. It i5 \:jdel) recognized that t! re specificaticn aai enforcerlent of constraints for ciataboses is e. :. tten~l>-irlportilnt for the l'trt hct, devt~lopr.lent of database dcsipn and irlplementalion. In i.nfor-rat ictn noticl line, constrair4ts are u5ccl to cap-tulc the pecul;arities of reP1 world situations artI bebaviour by giving appropriate ~1~s. When runring ti:r datnhnse, these rules sbol Id be soclchow obeycci in order lo rec! uce the possitili-tjez fr,l incorrect data creeping ! n apd corrupting tlla ir! tcBgrity cf ttle ctata. There arc-numerous papers addressing protlens of jntrgrity constrairts for 63tc7bases, and it is Permission IO copy without fee all or parr of rhis maferial is granfed provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear. and notice is given that copying is by permission of the Very Large Dota Base Endowment. To copy otherwise. or to republish. requires a fee and/or special permission from the Endowment.
Improving the Efficiency of Approximate Inference for Probabilistic Logical Models by means of Program Specialization

We consider the task of performing probabilistic inference with probabilistic logical models. Many algorithms for approximate inference with such models are based on sampling. From a logic programming perspective, sampling boils down to repeatedly calling the same queries on a knowledge base composed of a static part and a dynamic part. The larger the static part, the more redundancy there is in these repeated calls. This is problematic since inefficient sampling yields poor approximations. We show how to apply logic program specialization to make sampling-based inference more efficient. We develop an algorithm that specializes the definitions of the query predicates with respect to the static part of the knowledge base. In experiments on real-world data we obtain speedups of up to an order of magnitude, and these speedups grow with the data-size.
Self-Mutilation in a Community Sample of Adolescents.

RESULTS. 43 DISCUSSION. 67 REFERENCES. 77 APPENDIX A: Consent F o r m . 86 APPENDIX B: FASM Motivational Groupings . 87 APPENDIX C: Measures . 88 V I T A . 106
Effects of a Patient-Provider, Collaborative, Medication-Planning Tool: A Randomized, Controlled Trial

Among patients with various levels of health literacy, the effects of collaborative, patient-provider, medication-planning tools on outcomes relevant to self-management are uncertain. Objective. Among adult patients with type II diabetes mellitus, we tested the effectiveness of a medication-planning tool (Medtable™) implemented via an electronic medical record to improve patients' medication knowledge, adherence, and glycemic control compared to usual care. Design. A multicenter, randomized controlled trial in outpatient primary care clinics. 674 patients received either the Medtable tool or usual care and were followed up for up to 12 months. Results. Patients who received Medtable had greater knowledge about indications for medications in their regimens and were more satisfied with the information about their medications. Patients' knowledge of drug indication improved with Medtable regardless of their literacy status. However, Medtable did not improve patients' demonstrated medication use, regimen adherence, or glycemic control (HbA1c). Conclusion. The Medtable tool supported provider/patient collaboration related to medication use, as reflected in patient satisfaction with communication, but had limited impact on patient medication knowledge, adherence, and HbA1c outcomes. This trial is registered with ClinicalTrials.gov NCT01296633.
MINNI: Micromouse Incorporating Neural Network Intelligence

MINNI is a system whereby a back propagation neural network is used to control the steering of a micromouse (small robot) in following a straight path. The neural network must be minimised to run on the hardware/software platform available on the Macquarie Micromouse. The development of the network follows intensive trials of algorithm and architecture variations in MATLAB. The implementation is programmed in ADA.
Evaluation of a Novel Array-Based Toxoplasma, Rubella, Cytomegalovirus, and Herpes Simplex Virus IgG Enzyme Linked Immunosorbent Assay and Its Comparison with Virion/Serion Enzyme Linked Immunosorbent Assays

Background The dramatic increase in use of the IgG test for toxoplasma, rubella, cytomegalovirus (CMV), and herpes simplex virus (HSV) [TORCH] has led to the requirement for a high-efficiency method that can be used in the clinical laboratory. This study aimed to compare the results of BGI-Array ELISA TORCH IgG (BGI-GBI, China) screening method to those of Virion/Serion TORCH IgG ELISA (Virion/Serion, Germany). Methods Serum specimens (n=400) submitted for routine IgG testing by Virion/Serion ELISA were also tested using the BGI-Array ELISA method. The agreements of these two kinds of method were analyzed by κ-coefficients calculation. Results Following repeat testing, the BGI-Array ELISA TORCH IgG assays demonstrated agreements of 99.5% (398/400 specimens), 98% (392/400 specimens), 99% (396/400 specimens), and 99.5% (398/400 specimens), respectively. The BGI-Array ELISA IgG assays provided results comparable to Virion/Serion ELISA results, with κ-coefficients showing near-perfect agreement for the HSV (κ=0.87), rubella (κ=0.92) and CMV (κ=0.93) and substantial agreement for the toxoplasma (κ=0.80) IgG assays. The use of the BGI-Array ELISA TORCH IgG assays could reduce the turnaround time (1.5 hr vs. 5 hr by Virion/Serion ELISA for 100 specimens) and were easy to use. Conclusions BGI-Array ELISA TORCH IgG shows a good agreement with Virion/Serion ELISA methods and is suitable for clinical application.
Phosphorylation of the MBF Repressor Yox1p by the DNA Replication Checkpoint Keeps the G1/S Cell-Cycle Transcriptional Program Active

Background In fission yeast Schizosaccharomyces pombe G1/S cell-cycle regulated transcription depends upon MBF. A negative feedback loop involving Nrm1p and Yox1p bound to MBF leads to transcriptional repression as cells exit G1 phase. However, activation of the DNA replication checkpoint response during S phase results in persistent expression of MBF-dependent genes. Methodology/Principal Findings This report shows that Yox1p binding to MBF is Nrm1-dependent and that Yox1p and Nrm1p require each other to bind and repress MBF targets. In response to DNA replication stress both Yox1p and Nrm1p dissociate from MBF at promoters leading to de-repression of MBF targets. Inactivation of Yox1p is an essential part of the checkpoint response. Cds1p (human Chk2p) checkpoint protein kinase-dependent phosphorylation of Yox1p promotes its dissociation from the MBF transcription factor. We establish that phosphorylation of Yox1p at Ser114, Thr115 is required for maximal checkpoint-dependent activation of the G1/S cell-cycle transcriptional program. Conclusions/Significance This study shows that checkpoint-dependent phosphorylation of Yox1p at Ser114, Thr115 results in de-repression of the MBF transcriptional program. The remodeling of the cell cycle transcriptional program by the DNA replication checkpoint is likely to comprise an important mechanism for the avoidance of genomic instability.
Association Between the Use of 4 Recommended Drug Categories and Patient Perceptions of Health Status Following an ACS Event

BACKGROUND: Four categories of medication have been shown to reduce mortality following an acute coronary syndrome (ACS) event: (a) antiplatelets, (b) beta-blockers, (c) statins, and (d) angiotensin-converting enzyme (ACE) inhibitors or angiotensin II receptor blockers (ARBs). OBJECTIVES: To determine the association between use of 1 or more of 4 categories of evidence-based medications and patient-perceived health status. METHODS: Data from the registry of a large university-based health system were used for an analysis of prescribing at discharge following an inpatient hospitalization for ACS. Use of evidence-based medications and patient perceived health status were measured in a telephone survey administered 6 to 12 months (mean [SD]=10 [3.5] months) after hospital discharge. Surveys were conducted from January 2002 through March 2005. Subjects were included in the survey if they were prescribed at least 1 of the 4 evidence-based drug categories at the time of discharge. Each patient was assigned to 1 of 5 groups (range: 0 to 4) based on the number of drug categories self-reported by the patient as current at the time of the survey. Patient-perceived health status was assessed using the question “How would you rate your health at the present time? ” using a 5-point scale from excellent (1) to poor (5). Mean perceived health status scores for each of the 4 evidence-based medication categories were compared using Analysis of Variance (ANOVA). Multivariate logistic regression determined the association between patient-perceived health status—dichotomized to excellent/ very good/good versus fair/poor—and the evidence-based medication group, controlling for patient demographics and comorbidities. P values of less than 0.05 were considered statistically significant. RESULTS: A total of 393 of 1,206 patients (32.6%) responded to the survey between 6 and 12 months after discharge for an ACS event. The mean (SD) patient-perceived health status ranged from 3.3 (1.1) for patients with no (0) self-reported evidence-based medications (n=14) to 2.5 (1.0) for patients with 4 evidence-based medications (n=130, P=0.028), indicating higher self-perceived health status for patients who were taking more of the evidence-based medications. Using patients with no (0) evidence based medications as the comparator, the odds of higher patient-perceived health status were multiplied by 8.2 (95% confidence interval [CI]=1.7- 37.9, P=0.007) for those with 4 medications, 9.3 (95% CI=2.0-43.4, P=0.004) for those with 3 medications, 4.9 (95% CI=1.1-22.6, P=0.041) for those with 2 medications, and not significantly different for those with 1 medication (odds ratio=2.5, 95% CI=0.4-14.4, P=0.316). Younger age, prior myocardial infarction, and recurrent ACS events occurring between discharge and the survey date were significantly associated with poorer perceived health status. CONCLUSIONS: Better patient-perceived health status was associated with use of a greater number of evidence-based medications for patients with ACS.
Design and implementation of a Greek text-to-speech system based on concatenative synthesis

The goal of this paper is to present the work carried out up to now for the development of the Greek Text-To-Speech (GRTTS) system by NTUA. The system under consideration is based on the method of concatenative synthesis and follows the Bell Labs approach to this technique. In order that the input text to the GRTTS is translated into continuous synthetic speech the following modules have already been studied and implemented: (i) module for the linguistic analysis of the input text; (ii) the acoustic inventory module. On the same time it is under development the duration module of the GRTTS, for the computation of the appropriate temporal structure of synthesized speech. The objectives of the above studies, in combination with the concatenative synthesis technique, which is one of the simplest methods for speech synthesis, are to bypass most of the problems encountered by other synthesis methods such as articulatory and formant synthesis systems. The major objective is to minimize abrupt discontinuities and thus maximize the naturalness of the synthesized utterances.
Automatic recognition of spontaneous speech for access to multilingual oral history archives

Much is known about the design of automated systems to search broadcast news, but it has only recently become possible to apply similar techniques to large collections of spontaneous speech. This paper presents initial results from experiments with speech recognition, topic segmentation, topic categorization, and named entity detection using a large collection of recorded oral histories. The work leverages a massive manual annotation effort on 10 000 h of spontaneous speech to evaluate the degree to which automatic speech recognition (ASR)-based segmentation and categorization techniques can be adapted to approximate decisions made by human annotators. ASR word error rates near 40% were achieved for both English and Czech for heavily accented, emotional and elderly spontaneous speech based on 65-84 h of transcribed speech. Topical segmentation based on shifts in the recognized English vocabulary resulted in 80% agreement with manually annotated boundary positions at a 0.35 false alarm rate. Categorization was considerably more challenging, with a nearest-neighbor technique yielding F=0.3. This is less than half the value obtained by the same technique on a standard newswire categorization benchmark, but replication on human-transcribed interviews showed that ASR errors explain little of that difference. The paper concludes with a description of how these capabilities could be used together to search large collections of recorded oral histories.
A Neurocomputational Model of Figure-ground Discrimination by Relative Motion

A neurocomputational model is presented for gure-ground discrimination by relative motion. In the model, the correlation type of elementary motion detectors (EMDs), an oscillatory neural network for motion perception and a selective attention module are involved. It is shown that through the oscillatory amplitude and frequency encoding and selective synchronization of phase oscillators, a perfectly camou-aged textured gure can be successfully discriminated from its identically textured background by relative motion alone. network (ONN), multilayer network of phase oscillators.
On the optimality of K longest path generation algorithm under memory constraints

Adequate coverage of small-delay defects in circuits affected by statistical process variations requires identification and sensitization of multiple paths through potential defect sites. Existing K longest path generation (KLPG) algorithms use a data structure called path store to prune the search space by restricting the number of sub-paths considered at the same time. While this restriction speeds up the KLPG process, the algorithms lose their optimality and do not guarantee that the K longest sensitizable paths are indeed found. We investigate, for the first time, the effects of missing some of the longest paths on the defect coverage. We systematically quantify how setting different limits on the path-store size affects the numbers and relative lengths of identified paths, as well as the run-times of the algorithm. We also introduce a new optimal KLPG algorithm that works iteratively and pinpointedly addresses defect locations for which the path-store size limit has been exceeded in previous iterations. We compare this algorithm with a naïve KLPG approach that achieves optimality by setting the path-store size limit to a very large value. Extensive experiments are reported for 45nm-technology data.
Development of ICTL module-based on suitable teaching methodology for Orang Asli (ICTL-TeMfOA): The preliminary study of suitable teaching strategy

Orang Asli (aborigines) are the indigenous people of Peninsular Malaysia. They have diverse cultures, traditions and ways of living, beliefs and language. The Malaysian government is providing assistance in developing Orang Asli education by preparing certain educational assistance for the Orang Asli to remain in schools. In general, there has been significant improvements in the overall school attendance of the Orang Asli. Research done in 2007 by UNICEF shows dropout has decreased over the past 15 years; however 80 percent from of the Orang Asli children still do not complete their secondary school. This problem may be due to the teaching strategy in classroom which may not fit the students' cultures, traditions, ways of living, beliefs and language. This also may apply to the ICTL subject. In Malaysia, the importance of ICT in the education system has been realized as one way to achieve the 2001–2010 education Development Plan [1]. Since the Orang Asli have their own paradigm of education, there should be special teaching methodologies to attract the students' interest, attention and focus in the ICTL subject. In order to achieve this, the teacher should build the ICT program by selecting content and adapting the curricula to address students' learning needs, interest and prior knowledge. They should guides and facilitate learning with a suitable methodology in the classroom. To carry out this study, the ADDIE model is used as a methodology. The aim of this study is to investigate and identify suitable teaching strategy for Orang Asli towards learning ICTL subjects. Based on the identified teaching methodology for Orang Asli, the researchers will develop an ICTL module which suits them.
Human Motion Data Definition for 3D Characters

We define a human motion data format for providing a character model with motion so that any motion capture data can be used to generate exchangeable human animation sequences through networks of heterogeneous computer systems. We have extended the ISO/IEC 19774 H-Anim specification to include motion definition in order to meet this objective. A character model can be prepared with any general graphics tool according to the hierarchical structure defined in the extended H-Anim specification. We can provide the character model with any captured motion data using the interfaces for motion parameters defined in the extended H-Anim specification, even when the data is not relevant to the character model initially. Several kinds of motion capture data can be applied to generate animation sequences for a character model; conversely, one kind of motion capture data can be applied to several different character models. New Joint and Motion nodes are defined for animation exchange in the H-Anim specification. Schema expansion and validation are also included.
Decoherent histories and quantum state diffusion.

We demonstrate a close connection between the decoherent histories approach to quantum mechanics and the quantum state diffusion picture, for open quantum systems described by a master equation of Lindblad form. The (physically unique) set of variables that localize in the quantum state diffusion picture also define an approximately decoherent set of histories in the decoherent histories approach. The degree of localization is related to the degree of decoherence, and the probabilities for histories prescribed by each approach are essentially the same.
An Antibody Targeted to VEGFR-2 Ig Domains 4-7 Inhibits VEGFR-2 Activation and VEGFR-2–Dependent Angiogenesis without Affecting Ligand Binding

Inhibition of VEGFR-2 signaling reduces angiogenesis and retards tumor growth. Current biotherapeutics that inhibit VEGFR-2 signaling by either sequestering VEGF ligand or inhibiting VEGF binding to VEGFR-2 may be compromised by high VEGF concentrations. Here we describe a biotherapeutic that targets VEGFR-2 signaling by binding to Ig domains 4-7 of VEGFR-2 and therefore has the potential to work independently of ligand concentration. 33C3, a fully human VEGFR-2 antibody, was generated using XenoMouse technology. To elucidate the mechanism of action of 33C3, we have used a number of competition and binding assays. We show that 33C3 binds VEGFR-2 Ig domains 4-7, has no impact on VEGF-A binding to VEGFR-2, and does not compete with an antibody that interacts at the ligand binding site. 33C3 has a high affinity for VEGFR-2 (KD < 1 nmol/L) and inhibits VEGF-A induced phosphorylation of VEGFR-2 with an IC50 of 99 ± 3 ng/mL. In vitro, in a 2D angiogenesis assay, 33C3 potently inhibits both tube length and number of branch points, and endothelial tubule formation in a 3D assay. In vivo, 33C3 is a very effective inhibitor of angiogenesis in both a human endothelial angiogenesis assay and in a human skin chimera model. These data show targeting VEGFR-2 outside of the ligand binding domain results in potent inhibition of VEGFR-2 signaling and inhibition of angiogenesis in vitro and in vivo. Mol Cancer Ther; 10(5); 770–83. ©2011 AACR.
The limitation of the SVD for latent semantic indexing

Latent semantic indexing (LSI) is an indexing method for improving retrieval performance of an information retrieval system by grouping related documents to the same clusters so that each of these documents indexes the same (or almost the same) words, and unrelated documents index (relatively) different words. The de facto standard method for LSI is the truncated singular value decomposition (SVD). In this paper, we show that the LSI capability of the truncated SVD is not as conclusive as previously reported; rather it is a conditional aspect and when the condition is not met, then the truncated SVD can fail in recognizing the related documents resulting in a poor retrieval performance.