Miracle-dz/UniFAR-FTUs huggingface dataset:
Rescue of p53 Blockage by the A2A Adenosine Receptor via a Novel Interacting Protein, Translin-Associated Protein X

Blockage of the p53 tumor suppressor has been found to impair nerve growth factor (NGF)-induced neurite outgrowth in PC-12 cells. We report herein that such impairment could be rescued by stimulation of the A2A adenosine receptor (A2A-R), a G protein-coupled receptor implicated in neuronal plasticity. The A2A-R-mediated rescue occurred in the presence of protein kinase C (PKC) inhibitors or protein kinase A (PKA) inhibitors and in a PKA-deficient PC-12 variant. Thus, neither PKA nor PKC was involved. In contrast, expression of a truncated A2A-R mutant harboring the seventh transmembrane domain and its C terminus reduced the rescue effect of A2A-R. Using the cytoplasmic tail of the A2A-R as bait, a novel-A2A-R-interacting protein [translin-associated protein X (TRAX)] was identified in a yeast two-hybrid screen. The authenticity of this interaction was verified by pull-down experiments, coimmunoprecipitation, and colocalization of these two molecules in the brain. It is noteworthy that reduction of TRAX using an antisense construct suppressed the rescue effect of A2A-R, whereas overexpression of TRAX alone caused the same rescue effect as did A2A-R activation. Results of [3H]thymidine and bromodeoxyuridine incorporation suggested that A2A-R stimulation inhibited cell proliferation in a TRAX-dependent manner. Because the antimitotic activity is crucial for NGF function, the A2A-R might exert its rescue effect through a TRAX-mediated antiproliferative signal. This antimitotic activity of the A2A-R also enables a mitogenic factor (epidermal growth factor) to induce neurite outgrowth. We demonstrate that the A2A-R modulates the differentiation ability of trophic factors through a novel interacting protein, TRAX.
Proximity, Compatibility, and Noncomplementarity in Subjective Probability

Subjective probability judgments of two mutually exclusive and exhaustive events were investigated. Previous research has documented binary complementarity, that is, such judgments typically sum up to 1.00 in accordance with standard probability theories. However, I argue here that three hypotheses collectively specify conditions wherein systematic binary noncomplementarity is observed. Hypothesis 1 assumes that a possibility that an Example X does not belong to a Category C is assessed by dissimilarity calculation between X and C. According to Hypothesis 2, if X were both similar and dissimilar to C, then the probabilities that X belongs to C and that X does not belong to C would be judged high enough that their sum exceeds 1.00. Hypothesis 3 speculates that such normative contradiction occurs contingent upon task-dependent subjective weighting of relevant features. Experiments 1 through 5 confirmed Hypotheses 1 through 3. Analysis of subjective weight estimates revealed that the compatibility principle (Slovic, Griffin, & Tversky, 1990) provided a coherent account for such violation of probabilistic norms.
A New Approach to Modeling Choice with Limited Data

We visit the following problem: For a ‘generic’ model of consumer choice (namely, distributions over preference lists) and a limited amount of data on how consumers actually make decisions (such as marginal preference information), how may one predict revenues from offering a particular assortment of choices? This is a central problem in operations research and marketing. We present a framework to answer such questions and design a number of tractable algorithms from a data and computational standpoint for the same.
Recognition of Categorized Lists Positive and Negative Correlations Between Confidence and Accuracy for the Same Events in

Different researchers have reported positive, null, and negative relationships between confidence and accuracy in reports from memory. One possible reason for this paradox is the variety of materials used across experiments, but the two experiments reported in this article show that positive and negative confidence-accuracy correlations can be observed using a single procedure and the same materials. Subjects studied words from semantic categories and then took a recognition test while making confidence ratings. For previously studied items, positive correlations between confidence and accuracy were obtained using three different measures. Yet when confidence-accuracy correlations were assessed for unstudied items from studied categories, the correlations were zero or negative. The critical factors in determining when negative correlations will be found are the similarity of lures to presented items and the type of analysis used. These results indicate that one should be cautious about relying on confidence of recognition when rememberers must decide among highly similar events.
Effects of the Tip Location on Single Piles Subjected to Surcharge and Axial Loads

When applying axial load on piles subjected to negative skin friction (NSF), the yielded NSF is gradually eliminated. The process is notably influenced by the tip location (Y) and still a lack of understanding. This paper reports three-dimensional numerical simulations with tip locations Y = 1.00 pile diameter (D), 0.25D, 0.00D, and −1.00D. It is found that, against expectations, the dragload and NSF are not proportionally related to the tip location. When maximum dragload (P max) is eventually eliminated due to an axial load, there is also a negative crest of the skin friction, indicating that NSF still exists based on the criterion of the dragload reduction. The side resistance of the piles with Y = 1.00D and 0.25D is almost fully mobilised, which is demonstrated by the increment of end resistance that greatly increases with the larger axial loads. However, the side resistance of the piles with Y = 0.00D and −1.00D has a potential capacity to carry more loads with continued displacement since the increment of end resistance increases almost linearly with axial load. Therefore, when designing the pile foundation, the inclusion of the NSF should be governed by the amount of axial load to be resisted.
Political opportunity structures, democracy, and civil war

Theories of mobilization suggest that groups are more likely to resort to violence in the presence of political opportunity structures that afford greater prospects for extracting concessions from the government or better opportunities to topple ruling governments. However, existing efforts to consider the possible influences of political opportunity structures on incentives for violence and civil war empirically have almost invariably relied upon measures of democracy to proxy for the hypothesized mechanisms, most notably the argument that the opposing effects of political accommodation and repression will give rise to an inverted U-shaped relationship between democracy and the risk of civil war. The authors detail a number of problems with measures of democracy as proxies for political opportunity structures and develop alternative measures based on the likely risks that political leaders will lose power in irregular challenges and their implications for the incentives for resort to violence. The authors evaluate empirically how the security with which leaders hold office influences the prospects of violent civil conflict. The findings indicate that recent irregular leader entry and transitions indeed increase the risk of conflict onset, while democratic institutions are found to decrease the risk of civil war, after controlling for the new measures of state weakness.
Virtual brain transplantation (VBT): a method for accurate image registration and parcellation in large cortical stroke.

OBJECTIVE The objective of the current study was to develop a semi-automated method to register and parcellate lesioned brains in a surface space with anatomical accuracy, facilitating group-level fMRI analyses in patients with large cortical strokes. METHODS Thirteen chronic patients with a single large left hemisphere stroke were included in the study. Our "virtual brain transplantation" (VBT) approach is based on pre-processing high resolution anatomical T1-weighted brain images by "filling in" the lesion with "transplanted virtual tissue" from the non-stroke hemisphere, providing "normal" anatomical landmarks for standard alignment and inflation algorithms developed for healthy individuals. Biological validation of the approach was performed by quantifying in Freesurfer space the areas of 12 hand-drawn sulci found inside and outside the stroke following "transplantation". RESULTS Our results show no difference in the Freesurfer parcellation of 12 different regions when comparing a lesioned hemisphere with the non-lesioned hemisphere, attesting for the validity of the anatomical classification in the stroke hemisphere. As consequence of the anatomical precision, this method permits a more detailed and quantifiable anatomical description of the regions affected directly by the stroke. CONCLUSIONS This method permits accurate surface reconstruction of the injured hemisphere after stroke by making it possible to extract the cortical surface from these images and to utilize this in software modules (FreeSurfer) specialized for aligning cortical surfaces using high-dimensionality warping algorithms. In addition, it permits quantifying, within bounds, the extent to which the lesion in question is associated with damage to particular regions of the cortical surface, information that is of explanatory value in models that attempt to explain brain-behavior relations using lesion analysis.
The Credit Suisse Meta-data Warehouse

This paper describes the meta-data warehouse of Credit Suisse that is productive since 2009. Like most other large organizations, Credit Suisse has a complex application landscape and several data warehouses in order to meet the information needs of its users. The problem addressed by the meta-data warehouse is to increase the agility and flexibility of the organization with regards to changes such as the development of a new business process, a new business analytics report, or the implementation of a new regulatory requirement. The meta-data warehouse supports these changes by providing services to search for information items in the data warehouses and to extract the lineage of information items. One difficulty in the design of such a meta-data warehouse is that there is no standard or well-known meta-data model that can be used to support such search services. Instead, the meta-data structures need to be flexible themselves and evolve with the changing IT landscape. This paper describes the current data structures and implementation of the Credit Suisse meta-data warehouse and shows how its services help to increase the flexibility of the whole organization. A series of example meta-data structures, use cases, and screenshots are given in order to illustrate the concepts used and the lessons learned based on feedback of real business and IT users within Credit Suisse.
PI4 Kinase Is a Prophylactic but Not Radical Curative Target in Plasmodium vivax-Type Malaria Parasites

ABSTRACT Two Plasmodium PI4 kinase (PI4K) inhibitors, KDU691 and LMV599, were selected for in vivo testing as causal prophylactic and radical-cure agents for Plasmodium cynomolgi sporozoite-infected rhesus macaques, based on their in vitro activity against liver stages. Animals were infected with P. cynomolgi sporozoites, and compounds were dosed orally. Both the KDU691 and LMV599 compounds were fully protective when administered prophylactically, and the more potent compound LMV599 achieved protection as a single oral dose of 25 mg/kg of body weight. In contrast, when tested for radical cure, five daily doses of 20 mg/kg of KDU691 or 25 mg/kg of LMV599 did not prevent relapse, as all animals experienced a secondary infection due to the reactivation of hypnozoites in the liver. Pharmacokinetic data show that LMV599 achieved plasma exposure that was sufficient to achieve efficacy based on our in vitro data. These findings indicate that Plasmodium PI4K is a potential drug target for malaria prophylaxis but not radical cure. Longer in vitro culture systems will be required to assess these compounds' activity on established hypnozoites and predict radical cure in vivo.
Geographic Variation in the Gender Differences in Test Scores

The causes and consequences of gender disparities in standardized test scores -- especially in the high tails of achievement -- have been a topic of heated debate. The existing evidence on standardized test scores largely confirms the prevailing stereotypes that more men than women excel in math and science while more women than men excel in tests of language and reading. We provide a new perspective on this gender gap in test scores by analyzing the variation in these disparities across geographic areas. We illustrate that male-female ratios of students scoring in the high ranges of standardized tests vary significantly across the United States. This variation is systematic in several important ways. In particular, states where males are highly overrepresented in the top math and science scores also tend to be states where women are highly overrepresented in the top reading scores. This pattern suggests that states vary in their adherence to stereotypical gender performance, rather than favoring one sex over the other across all subjects. Furthermore, since the genetic distinction and the hormonal differences between sexes that might affect early cognitive development (that is, innate abilities) are likely the same regardless of the state in which a person happens to be born, the variation we find speaks to the nature-versus-nurture debates surrounding test scores and suggests environments significantly impact gender disparities in test scores.
Mining social networks to discover ego sub-networks

A decade ago, no one would imagine that social networks would witness such rocket development to take part of our daily life. Within relatively short period of time, social networks gained global attention by a huge number of users. Since then, social networks grow bigger to accommodate millions of users. One challenge though is to automate the process of categorize friends into social. Therefore, several data mining solutions were introduced to automatically attempt to classify ego networks, however, issues related to categorization accuracy as well as the efficiency and effectiveness to classify ego networks are still lacking. In this paper, we propose a method that mainly utilizes features extracted from network topology and node profile to better identify social networks. We believe that extracting comprehensive and meaningful features to be used in conjunction with a roust classifier would increase the accuracy level of ego sub-networks detection. The proposed method was tested on a benchmarked data set and the performance was compared to two state-of-the-art methods namely Maximization Likelihood Like and Enhanced Link Clustering and showed valid improvement.
A time-frequency analysis of the dynamics of cortical networks of sleep spindles from MEG-EEG recordings

Sleep spindles are a hallmark of NREM sleep. They result from a widespread thalamo-cortical loop and involve synchronous cortical networks that are still poorly understood. We investigated whether brain activity during spindles can be characterized by specific patterns of functional connectivity among cortical generators. For that purpose, we developed a wavelet-based approach aimed at imaging the synchronous oscillatory cortical networks from simultaneous MEG-EEG recordings. First, we detected spindles on the EEG and extracted the corresponding frequency-locked MEG activity under the form of an analytic ridge signal in the time-frequency plane (Zerouali et al., 2013). Secondly, we performed source reconstruction of the ridge signal within the Maximum Entropy on the Mean framework (Amblard et al., 2004), yielding a robust estimate of the cortical sources producing observed oscillations. Lastly, we quantified functional connectivity among cortical sources using phase-locking values. The main innovations of this methodology are (1) to reveal the dynamic behavior of functional networks resolved in the time-frequency plane and (2) to characterize functional connectivity among MEG sources through phase interactions. We showed, for the first time, that the switch from fast to slow oscillatory mode during sleep spindles is required for the emergence of specific patterns of connectivity. Moreover, we show that earlier synchrony during spindles was associated with mainly intra-hemispheric connectivity whereas later synchrony was associated with global long-range connectivity. We propose that our methodology can be a valuable tool for studying the connectivity underlying neural processes involving sleep spindles, such as memory, plasticity or aging.
Detection Improvised Explosive Device (IED) Emplacement Using Infrared Image

This paper presents a method to detect an improvised explosive device (IED) by using infrared thermography (IRT) technology. The detection of IED will be done automatically and accurately even the IED detection expert is not present. Combining the advantage of IRT and image processing technique, the proposed method is very efficient and responsive to detect the existence of hidden IED. The captured images are filtered and segmented to extract the heat pattern before the decision is made. Based on the experimental result, the proposed system produced about 92 % of detection accuracy.
Evaluating Stress Distribution Pattern in Periodontal Ligament of Maxillary Incisors during Intrusion Assessed by the Finite Element Method

Statement of the Problem The use of miniscrews has expedited the true maxillary incisor intrusion and has minimized untoward side effects such as labial tipping. Purpose The aim of this study was to assess the stress distribution in the periodontal ligament of maxillary incisors when addressed to different models of intrusion mechanics using miniscrews by employing finite element methods. The degree of relative and absolute intrusion of maxillary incisors in different conditions was also evaluated. Materials and Method Finite element model of maxillary central incisor to first premolar was generated by assembling images obtained from a three-dimensional model of maxillary dentition. Four different conditions of intrusion mechanics were simulated with different placement sites of miniscrews as well as different points of force application. In each model, 25-g force was applied to maxillary incisors via miniscrews. Results In all four models, increased stress values were identified in the apical region of lateral incisor. Proclination of maxillary incisors was also reported in all the four models. The minimum absolute intrusion was observed when the miniscrew was placed between the lateral incisor and canine and the force was applied at right angles to the archwire, which is very common in clinical practice. Conclusion From the results yield by this study, it seems that the apical region of lateral incisor is the most susceptible region to root resorption during anterior intrusion. When the minimum flaring of maxillary incisors is required in clinical situations, it is suggested to place the miniscrew halfway between the roots of lateral incisor and canine with the force applied to the archwire between central and lateral incisor. In order to achieve maximum absolute intrusion, it is advised to place miniscrew between the roots of central and lateral incisors with the force applied at a right angle to the archwire between these two teeth.
A Novel Dynamic and Scalable Caching Algorithm of Proxy Server for Multimedia Objects

This paper presents a novel dynamic and scalable caching algorithm of proxy server with a finite storage size for multimedia objects. Among the multimedia such as text, image, audio and video, video is a dominant component in terms of the performance of proxy server due to its traffic characteristics. For the fast caching process, caching sequences for videos are obtained to decrease both the buffer size and the required bandwidth and saved into metafiles in advance. Then, we present a novel caching and replacing algorithms for multimedia objects based on the metafiles. Finally, experimental results are provided to show the superior performance of the proposed algorithm.
Proposal : Learning to make decisions from large data sets

The ability to store and process large amounts of data in computers has increased enormously in the last decade. This has opened up the possibility of analyzing very large data sets gathered from a particular domain of interest to obtain useful knowledge about that domain, in a process known as data mining. Useful knowledge is a very broad concept, and indeed, there are many flavors of data mining that aim to extract different types of knowledge from different types of data. In some domains, the data can be organized into a set of examples, each represented by a feature vector. One type of useful knowledge that may be extracted in this case is a model that predicts one of the feature values when given the values of the other features for one particular example. The usefulness of such a model is directly related to its prediction accuracy on examples that were not used in the model construction. Predictive models are often used for decision-making, that is, for choosing which action to perform in a particular state described by the feature values. This is straightforward if we have examples of the form s a , where s is a state and a is the optimal action for state s. For example, in character recognition, s is the image of a character and a is the character. The optimal action for a system that receives s as input is to output a . Using this type of data we can construct a model to predict a given s. However, in many real-world applications, the data consists of a set of examples of the form s a r , where s is a state, a is an action executed in the state and r is a reward associated with the action. The reward is a real number that indicates the desirability of action a in state s and it is, in general, stochastic. The optimal action is the one that yields the largest expected reward. Since the optimal action associated with a state is not written explicitly in the data, we cannot predict it directly. Furthermore, the state space is often large (or infinite) so we cannot expect to have data describing each possible action in each possible state.
Dietary Intakes of Antioxidant Vitamins and Mortality From Cardiovascular Disease: The Japan Collaborative Cohort Study (JACC) Study

Background and Purpose— Only a few reports have dealt with the association of antioxidant vitamin intakes with mortality or morbidity from cardiovascular disease in Asia. We investigated the relation of dietary vitamins A, E, and C intake with mortality from cardiovascular disease for Japanese men and women. Methods— The subjects were 23 119 men and 35 611 women aged 40 to 79 years without a history of cardiovascular disease or cancer who responded to the food frequency questionnaire as part of the Japan Collaborative Cohort Study for Cancer Risk (JACC) Study. They were followed up for a median period of 16.5 years. Hazard ratios were calculated per quintile of dietary vitamins A, E, and C intake by using Cox proportional hazard model. Results— During the 859 962 person-year follow-up, there were 2690 deaths (1343 men and 1347 women) from cardiovascular disease, comprising 1227 (607 men and 620 women) from stroke and 557 (311 men and 246 women) from coronary heart disease. The multivariable hazard ratios (95% CI) associated with the highest versus lowest quintiles of vitamin C intake were 0.70 (0.54 to 0.92) for total stroke, 0.63 (0.41 to 0.97) for coronary heart disease, and 0.79 (0.66 to 0.94) for total cardiovascular disease for women, but the inverse associations observed were weak and did not reach statistical significance for men. No significant association was observed between vitamins A or E intake and risk of mortality for either men or women. Conclusions— Vitamin C intake is inversely associated with mortality from cardiovascular disease for Japanese women.