Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating an alternate form of the cognitive reflection test

Much research in cognitive psychology has focused on the tendency to conserve limited cognitive resources. The CRT is the predominant measure of such miserly information processing, and also predicts a number of frequently studied decision-making traits (such as belief bias and need for cognition). However, many subjects from common subject populations have already been exposed to the questions, which might add considerable noise to data. Moreover, the CRT has been shown to be confounded with numeracy. To increase the pool of available questions and to try to address numeracy confounds, we developed and tested the CRT-2. CRT-2 questions appear to rely less on numeracy than the original CRT but appear to measure closely related constructs in other respects. Crucially, substantially fewer subjects from Amazon’s Mechanical Turk have been previously exposed to CRT-2 questions. Though our primary purpose was investigating the CRT-2, we also found that belief bias questions appear suitable as an additional source of new items. Implications and remaining measurement challenges are discussed.
A Multimodal Predictive Model of Successful Debaters or How I Learned to Sway Votes

Interpersonal skills such as public speaking are essential assets for a large variety of professions and in everyday life. The ability to communicate in social environments often greatly influences a person's career development, can help resolve conflict, gain the upper hand in negotiations, or sway the public opinion. We focus our investigations on a special form of public speaking, namely public debates of socioeconomic issues that affect us all. In particular, we analyze performances of expert debaters recorded through the Intelligence Squared U.S. (IQ2US) organization. IQ2US collects high-quality audiovisual recordings of these debates and publishes them online free of charge. We extract audiovisual nonverbal behavior descriptors, including facial expressions, voice quality characteristics, and surface level linguistic characteristics. Within our experiments we investigate if it is possible to automatically predict if a debater or his/her team are going to sway the most votes after the debate using multimodal machine learning and fusion approaches. We identify unimodal nonverbal behaviors that characterize successful debaters and our investigations reveal that multimodal machine learning approaches can reliably predict which individual (~75% accuracy) or team (85% accuracy) is going to win the most votes in the debate. We created a database consisting of over 30 debates with four speakers per debate suitable for public speaking skill analysis and plan to make this database publicly available for the research community.
Analysis of circulating microRNA: preanalytical and analytical challenges.

BACKGROUND There is great interest in circulating microRNAs (miRNAs) as disease biomarkers. Translating promising miRNAs into validated clinical tests requires the characterization of many preanalytical and analytical parameters. METHODS miRNAs were extracted from serum and plasma samples of healthy volunteers, and miRNAs known to be present in serum and plasma (miR-15b, miR-16, miR-24, and miR-122) were amplified by reverse-transcription quantitative PCR. Stability and the effects of hemolysis were determined. Assay variation and its components, including the effect of adding control miRNA, were assessed by nested ANOVA. RESULTS miRNA concentrations were higher in plasma than in serum. Processing of plasma to remove subcellular/cellular components reduced miRNA concentrations to those of serum. The miRNAs analyzed were stable refrigerated or frozen for up to 72 h and were stable at room temperature for 24 h. Hemolysis increased the apparent concentration of 3 of the miRNAs. The total variability of replicate miRNA concentrations was <2.0-fold, with most of the variability attributable to the extraction process and interassay imprecision. Normalizing results to those of spiked exogenous control miRNAs did not improve this variability. CONCLUSIONS Detailed validation of the preanalytical steps affecting miRNA detection and quantification is critical when considering the use of individual miRNAs as clinical biomarkers. Unless these causes of imprecision are considered and mitigated, only miRNAs that are extremely up- or downregulated will be suitable as clinical biomarkers.
The impact of the unfolded protein response on human disease

A central function of the endoplasmic reticulum (ER) is to coordinate protein biosynthetic and secretory activities in the cell. Alterations in ER homeostasis cause accumulation of misfolded/unfolded proteins in the ER. To maintain ER homeostasis, eukaryotic cells have evolved the unfolded protein response (UPR), an essential adaptive intracellular signaling pathway that responds to metabolic, oxidative stress, and inflammatory response pathways. The UPR has been implicated in a variety of diseases including metabolic disease, neurodegenerative disease, inflammatory disease, and cancer. Signaling components of the UPR are emerging as potential targets for intervention and treatment of human disease.
On Fractional Instanton Numbers in Six Dimensional Heterotic E8 × E8 Orbifolds

We derive the precise relation between level matching condition and fractional instanton numbers in six dimensional, abelian and supersymmetric orbifolds of E8 x E8 heterotic string theory. The fractional part of the two E8 instanton numbers is explicitly calculated in terms of the gauge twist. This relation is then used to show that the classification of these orbifolds can be given in terms of flat bundles away from the orbifold singularities under the only constraint that the sum of the fractional parts of the gauge instanton numbers match the fractional part of the gravitational instanton number locally at every fixed point. This directly carries over to M-theory on S^1/Z_2
Northern Hemisphere Glaciation during the Globally Warm Early Late Pliocene

The early Late Pliocene (3.6 to ∼3.0 million years ago) is the last extended interval in Earth's history when atmospheric CO2 concentrations were comparable to today's and global climate was warmer. Yet a severe global glaciation during marine isotope stage (MIS) M2 interrupted this phase of global warmth ∼3.30 million years ago, and is seen as a premature attempt of the climate system to establish an ice-age world. Here we propose a conceptual model for the glaciation and deglaciation of MIS M2 based on geochemical and palynological records from five marine sediment cores along a Caribbean to eastern North Atlantic transect. Our records show that increased Pacific-to-Atlantic flow via the Central American Seaway weakened the North Atlantic Current and attendant northward heat transport prior to MIS M2. The consequent cooling of the northern high latitude oceans permitted expansion of the continental ice sheets during MIS M2, despite near-modern atmospheric CO2 concentrations. Sea level drop during this glaciation halted the inflow of Pacific water to the Atlantic via the Central American Seaway, allowing the build-up of a Caribbean Warm Pool. Once this warm pool was large enough, the Gulf Stream–North Atlantic Current system was reinvigorated, leading to significant northward heat transport that terminated the glaciation. Before and after MIS M2, heat transport via the North Atlantic Current was crucial in maintaining warm climates comparable to those predicted for the end of this century.
Exploiting Background Knowledge in Automated Discovery

Prior work in automated scientific discovery has been successful in finding patterns in data, given that a reasonably small set of mostly relevant features is specified. The work described in this paper places data in the context of large bodies of background knowledge. Specifically, data items are connected to multiple databases of background knowledge represented as inheritance networks. The system has made a practical impact on botanical toxicology research, which required linking examples of cases of plant exposures to databases of botanical, geographical, and climate background knowledge.
Controlling docking, altitude and speed in a circular high-roofed tunnel thanks to the optic flow

The new robot called BeeRotor we have developed is a tandem rotorcraft that mimicks optic flow-based behaviors previously observed in flies and bees. This tethered miniature robot (80g), which is autonomous in terms of its computational power requirements, is equipped with a 13.5-g quasi-panoramic visual system consisting of 4 individual visual motion sensors responding to the optic flow generated by photographs of natural scenes, thanks to the bio-inspired “time of travel” scheme. Based on recent findings on insects' sensing abilities and control strategies, the BeeRotor robot was designed to use optic flow to perform complex tasks such as ground and ceiling following while also automatically driving its forward speed on the basis of the ventral or dorsal optic flow. In addition, the BeeRotor robot can perform tricky manoeuvers such as automatic ceiling docking by simply regulating its dorsal or ventral optic flow in high-roofed tunnel depicting natural scenes. Although it was built as a proof of concept, the BeeRotor robot is one step further towards achieving a fully-autonomous micro-helicopter which is capable of navigating mainly on the basis of the optic flow.
Examining the Classification Accuracy of TSVMs with ?Feature Selection in Comparison with the GLAD Algorithm

Gene expression data sets are used to classify and predict patient diagnostic categories. As we know, it is extremely difficult and expensive to obtain gene expression labelled examples. Moreover, conventional supervised approaches cannot function properly when labelled data (training examples) are insufficient using Support Vector Machines (SVM) algorithms. Therefore, in this paper, we suggest Transductive Support Vector Machines (TSVMs) as semi-supervised learning algorithms, learning with both labelled samples data and unlabelled samples to perform the classification of microarray data. To prune the superfluous genes and samples we used a feature selection method called Recursive Feature Elimination (RFE), which is supposed to enhance the output of classification and avoid the local optimization problem. We examined the classification prediction accuracy of the TSVM-RFE algorithm in comparison with the Genetic Learning Across Datasets (GLAD) algorithm, as both are semi-supervised learning methods. Comparing these two methods, we found that the TSVM-RFE surpassed both a SVM using RFE and GLAD.
Covinsky Individualized Decision Making Cancer Screening in Elderly Patients : A Framework for Correction

Correction Contact me if this article is corrected. Citations Contact me when this article is cited. This article has been cited 211 times. Topic collections Contact me when new articles are published in these topic areas. Aging/ Geriatrics; Screening the same issue Related Articles published in . 2001;285(21):2793. JAMA June 6, 2001 . 2001;285(21):2776. JAMA H. Gilbert Welch. Informed Choice in Cancer Screening
Incremental algorithms for fuzzy co-clustering of very large cooccurrence matrix

Handling very large data is an important issue in FCM-type clustering and several incremental algorithms have been proved to be useful in FCM clustering. In this paper, the incremental algorithms are extended to fuzzy co-clustering of cooccurrence matrices, whose goal is to simultaneously partition objects and items considering their cooccurrence information. Single pass and online approaches are applied to fuzzy clustering for categorical multivariate data (FCCM) and fuzzy CoDoK, which try to maximize the aggregation degrees of co-clusters adopting entropy-based and quadratic-based membership fuzziflcations. Several experimental results demonstrate the applicability of the incremental approaches to fuzzy co-clustering algorithms.
Are Cost Benefits of Anticoagulation for Stroke Prevention in Atrial Fibrillation Underestimated?

Background and Purpose— Stroke outcomes in patients with atrial fibrillation (AF) tend to be worse than those in patients without AF. The objective of this study was to evaluate whether the cost benefits of anticoagulation for stroke prevention in AF may currently be underestimated by existing economic models that do not distinguish between different stroke outcomes. Methods— A literature review was conducted in 3 areas: (1) studies comparing stroke outcomes in AF and non-AF patients; (2) studies providing long-term cost of stroke estimates; and (3) studies modeling the cost-effectiveness of anticoagulation with a vitamin K antagonist (eg, warfarin) in AF patients. Results— There is considerable evidence that stroke in AF patients has a worse outcome than in patients without AF, including higher mortality, severity, and recurrence rates, and greater functional impairment and dependency. Estimates of the long-term cost of stroke of different severities were between US $24 991 for a mild stroke over 5 years and US $142 251 for a major ischemic stroke over a lifetime (2004 prices). The cost of a severe ischemic stroke may typically be 3-times that of mild stroke. However, cost-effectiveness models for anticoagulation in patients with AF have used average (not AF-specific) cost-of-stroke data, and most have used stroke severity distributions derived from clinical trials, which may differ from those in clinical practice. Conclusions— Existing economic models underestimate the cost benefits of anticoagulation for stroke prevention because they do not adjust for poorer outcomes associated with cardioembolic strokes.
Intravenous immunoglobulin reduces serum tumor necrosis factor alpha in patients with Guillain-Barre syndrome.

BACKGROUND Tumor necrosis factor a TNF-alpha has a possible role in the pathogenesis of the Guillain-Barre syndrome (GBS). AIMS To study the effect of intravenous immunoglobulin (IVIg) on serum TNF-alpha concentrations in patients with GBS. MATERIAL AND METHODS The effect of IVIg on TNF-alpha was evaluated in 36 patients with GBS. Serum TNF-alpha concentration was measured by enzyme-linked immunosorbent assay (ELISA). The sera of 22 (61%) patients with GBS showed elevated concentrations of TNF-alpha (35-182 pg/ml) and these sera were individually incubated in vitro with IVIg (0.25 mg/ml) at 37 degrees C for 24 hours. RESULTS The serum TNF-alpha concentrations in the 22 GBS patients with elevated levels showed a steady decline (60.34-19.78 pg/ml) following incubation with IVIg. These 22 patients also received IVIg therapy, and serum TNF-alpha concentrations showed a significant decline (65.5-9.75 pg/ml) at the end of the therapy. At the time of discharge from the hospital, there was a positive correlation between neurological recovery and decline in TNF-alpha concentrations in these 22 GBS patients. CONCLUSIONS The results of this study indicate that elevated levels of TNF-alpha occur in a proportion of patients with GBS and in these patients elevated serum TNF-alpha levels decline with IVIg therapy.
Mechanically Coupled Contour Mode Piezoelectric Aluminum Nitride MEMS Filters

A new class of mechanically coupled contour mode MEMS filters is demonstrated using a thin film piezoelectric aluminum nitride (AlN) process. The use of contour modes, whose frequencies are set by lithographically defined dimensions, permits the co-fabrication of multiple filters at arbitrary frequencies on the same chip. The stronger electromechnical coupling of the thin film piezoelectric structural material vis-à-vis electrostatically transduced devices results in lower insertion losses (as low as 1.5 dB) with termination values of 1 to 2.5 kΩ. Finally, filters synthesized using mechanically coupled resonators are fundamentally capable of wider bandwidths than electrically coupled ladder filters without requiring external tuning elements. Two designs for bandpass filters are analyzed, fabricated, and tested. The filters have center frequencies of 40 and 100 MHz.
Towards Realism in Facial Image Prototyping: Results of a Wavelet MRF Method

The ability to combine multiple images to produce a composite that is representative of the set has applications in psychology research, medical imaging and entertainment. Current techniques using a combination of image warping and blending suffer from a lack of realism due to unrealistic or inappropriate textures in the output images. This paper describes a new method for improving the representation of textures when blending multiple facial images. We select the most likely value for each pixel, given the values of the neighbouring pixels, by learning from the corresponding values in the training set i.e. we use a Markov Random Field (MRF) texture model. We use a multi-scale neighbourhood and separate low and high frequency information using a wavelet transform. This ensures proper correlations of values across spatial scales and allows us to bias the global appearance to the mean for the set, while selecting more specific texture components at higher resolutions. We validate our results using perceptual testing that shows that the new prototypes improve realism over previous techniques.
A compressive sensing-based technique for ISAR imaging

In the process of the traditional method for ISAR imaging, the produced data is extremely huge, so storage and transmission are both big problems. This paper successfully solves the problems by using compressive sensing theory. After the complete motion compensation to the radar echoes, the method of compressive sensing will be used to dispose the range cells before the imaging. It can reduce the required data quantity and satisfy the demand of the imaging quality. This characteristic is helpful to overcome the mainly disadvantage of traditional methods. At the latter part of this paper, the results of the measured data of Yak-42 airplane manifest that the method can markedly reduce the amount of data in the case of the decent imaging.
Experiments with the cascade-correlation algorithm

A series of experiments with the cascade-correlation algorithm (CCA) and some of its variants on a number of real-world pattern classification tasks are described. Some of the experiments investigated the effect of different design parameters on the performance of the CCA. Parameter settings that consistently yield good performance on different data sets were identified. The performance of the CCA is compared with that of the backpropagation algorithm and the perceptron algorithm. Preliminary results obtained from some variants of CCA and some directions for future work with CCA-like neural network learning methods are discussed. <<ETX>>
The Relationship of Protestant Ethic Beliefs and Values to Achievement

Weber's Protestant ethic thesis is more concerned with a person's beliefs and values than his affiliation per se. To test the thesis, an index of Calvinist beliefs and values was constructed and administered to a randomly selected sample of 252 males in a midwestern rural city. The index was found to correlate positively with both occupational status and educational achievement. But when religious affiliation was used as an independent variable, its relationship to occupational status was found to be minimal. These results suggest that religious affiliation is a less adequate measure of the independent variable in assessing religion's effect upon secular behavior than the religious beliefs suggested by Weber's analysis.
Subtractive fuzzy C-means clustering approach with applications to fuzzy predictive control

To identify T-S models, this paper presents a so-called "subtractive fuzzy C-means clustering" approach, in which the results of subtractive clustering are applied to initialize clustering centers and the number of rules in order to perform adaptive clustering. This method not only regulates the division of fuzzy inference system input and output space and determines the relative member function parameters, but also overcomes the impacts of initial values on clustering performance. Additionally, the orthogonal least square algorithm is employed to identify the parameters of consequents and linearize the systems over every sample time, ultimately resulting in the entire T-S fuzzy models. With this approach available, a fuzzy model predictive control system is established, along with corresponding control algorithms derived, as well as control system simulations carried out which explicitly demonstrate the effectiveness of the proposed method.
Mechanism of Cellular Oxidation Stress Induced by Asymmetric Dimethylarginine

The mechanism by which asymmetric dimethylarginine (ADMA) induces vascular oxidative stress is not well understood. In this study, we utilized human umbilical vein endothelial cells (HUVEC) to examine the roles of ADMA cellular transport and the uncoupling of endothelial nitric oxide synthase (eNOS) in contributing to this phenomenon. Dihydroethidium (DHE) fluorescence was used as an index of oxidative stress. Whole cells and their isolated membrane fractions exhibited measureable increased DHE fluorescence at ADMA concentrations greater than 10 μM. ADMA-induced DHE fluorescence was inhibited by co-incubation with L-lysine, tetrahydrobiopterin (BH4), or L-nitroarginine methyl ester (L-NAME). Oxidative stress induced in these cells by angiotensin II (Ang II) were unaffected by the same concentrations of L-lysine, L-NAME and BH4. ADMA-induced reduction in cellular nitrite or nitrite/nitrate production was reversed in the presence of increasing concentrations of BH4. These results suggest that ADMA-induced DHE fluorescence involves the participation of both the cationic transport system in the cellular membrane and eNOS instead of the Ang II-NADPH oxidase pathway.
User-Generated Video Gaming

Digital technology users are growingly involved in what has been described as convergence culture or participatory cultures. In this context, a major role is played by user-generated content. This article focuses on the participatory practices related to Little Big Planet (LBP) 1, a PlayStation platform video game that encourages users to create and share their own gaming levels. Our theoretical framework refers both to convergence culture and to a specific perspective of game studies that focuses on the cultural and social dimensions that are to be found in gaming and modding practices. A total of 8,829 Italian PlayStation Network (PSN) users were surveyed regarding their gaming practices, their attitude toward digital technology, and their LBP usage experiences. The results show that familiarity with digital technology and a socially oriented attitude to digital technology are clearly related to “active LBP engagement. ” Moreover, PSN users are more likely than other digital platforms users to create their own content.
The Pretest in Survey Research: Issues and Preliminary Findings

Despite their widely recognized importance in survey research, pretests have received little methodological attention. The authors summarize the current state of the art and report results from an empirical investigation of the effectiveness of respondent verbalizations in pretesting. The results suggest that pretesting is effective in identifying some types of problem questions but not others.
Dynamic Properties of a WDM Switching Module Based on Active Microring Resonators

The switching properties of a resonator consisting of two serially cascaded active microrings (MRs) are reported. The switching is achieved through the variation of the refractive index and the losses of the MRs with current injection, which alters the overall output spectral response. The switch is suitable for optical burst switching systems and metro architectures as it provides fast optical switching in the nanosecond scale with contrast ratio higher than 30 dB for 10-Gb/s intensity modulated signals. The capacity of the switch can be remarkably increased if multiwavelength switching is employed.