Miracle-dz/UniFAR-FTUs huggingface dataset:
Assisting web search users by destination reachability

Search engine users are increasingly performing complex tasks based on the simple keyword-in document-out paradigm. To assist users in accomplishing their tasks effectively, search engines provide query recommendations based on the user's current query. These are suggestions for follow-up queries given the user-provided query. A large number of techniques have been proposed in the past on mining such query recommendations which include past user sessions (e.g., sequence of queries within a specified window of time) to identify most frequently occurring pairs, using click-through graphs (e.g., a bipartite graph of queries and the urls on which users clicked) and rank these suggestions using some form of frequency counts from the past query logs. Given the limited number of queries that are offered (typically 5) it is important to effectively rank them. In this paper, we present a novel approach to ranking query recommendations which not only consider relevance to the original query but also take into account efficiency of a query at accomplishing a user search task at hand. We formalize the notion of query efficiency and show how our objective function effectively captures this as determined by a human study and eliminates biases introduced by click-through based metrics. To compute this objective function, we present a pseudosupervised learning technique where no explicit human experts are required to label samples. In addition, our techniques effectively characterize preferred url destinations and project each query into a higher dimension space where each sub-spaces represents user intent using these characteristics. Finally, we present an extensive evaluation of our proposed methods against production systems and show our method to increase task completion efficiency by 15%.
TwiBiNG: A Bipartite News Generator Using Twitter

Online Journalism is being seen as future of Journalism. News Professionals are vying to capture newsworthy stories that emerge from crowd. Live Social Media especially Twitter is generating enormous volumes of data every minute. It becomes difficult to select credible and relevant tweets that may form quality news among others. The problem intensifies due to the freedom of Twitter being an informal language. Generating headlines by solving this problem may still not be relevant and may face the question of authenticity. Given a set of keywords and a time period this problem becomes manageable and can be solved efficiently. We propose a bipartite algorithm that clusters authentic tweets based on key phrases and ranks the clusters based on trends in each timeslot. Finally, we present an approach to select those topics which have sufficient content to form a story
Religion as Political Resource: Culture or Ideology?

While empirical studies of religion's involvement in political life abound, there remains a great deal of fuzziness about the concepts that best capture it. Two often-used approaches are "religion as culture" and "religion as ideology. " In some perspectives culture and ideology are treated as mutually exclusive modes of religio-political phenomena; in other perspectives the two concepts are conflated. This article argues for an analytic distinction between culture and ideology that still preserves their interactive and often complementary natures. Examples from empirical studies of religion in politics demonstrate the different ways in which religion acts as a political resource, and the usefulness of the proposed analytic distinction.
Inverse Rendering with a Morphable Model: A Multilinear Approach

In this paper, we present a complete framework to inverse render faces from single images using a 3D Morphable Model (3DMM). A 3DMM is a linear statistical model of 3D shape and texture [2]. In general, inverse rendering of faces from single photographs is ill-posed, as the same appearance can be obtained by different underlaying factors. For instance, a red pixel can be caused by skin colour, red illumination, or an increased camera sensitivity in the red channel. A combination of these factors is also possible. For an object of known shape under complex natural illumination, the well known work of Ramamoorthi [4] shows how the spherical harmonic domain can be used to estimate one or more of: illumination, surface texture and reflectance properties. We revisit this classical formulation in the context of 3DMMs. Previous methods for fitting a 3DMM based on analysis-by-synthesis recover all parameters in a single, nonconvex objective function [2, 3]. To reduce the threat of getting stuck in local minima, Romdhani introduced a fitting algorithm which incorporates features like edges and specular highlights into the cost function [5]. These fitting algorithms make limited assumptions about the illumination environment and only model ambient light and one directional light source. Zhang and Samaras [6] used spherical harmonics to model unconstrained illumination, although at the cost of assuming a simple Lambertian reflectance model.
Improved Write Access Control and Stronger Freshness Guarantee to Outsourced Data

In secure data outsourcing, even a single unauthorized write operation may heavily ruin the data owner's business operations. Another potential issue is that the untrusted service provider may return stale data to mislead the readers. Existing work on secure write access does not consider misbehavior by users with write authorization to the outsourced data files. The data owner may not wish to allow such users to modify their own written data files after a fixed amount of time. The other type of misbehavior is that a user with revoked access to a resource can modify corresponding latest versions of the resource written by him in collusion with the service provider. Also, the weak freshness guarantee (i.e., the < k, t >-staleness) is not appropriate in many time-sensitive applications. In this work, we address the misbehavior by users who attempt to modify the own written data files. Such misbehavior is detected by the data owner using an audit-based mechanism. The viability of the proposed mechanism is verified by implementing the proposed protocols in Microsoft's Azure platform. A strong freshness guarantee is addressed using proof messages from the service provider so that a read request will return the latest version of the data file at least until the time when the data file is sent from the service provider to a reader.
Robust estimation and inference for bivariate line‐fitting in allometry

In allometry, bivariate techniques related to principal component analysis are often used in place of linear regression, and primary interest is in making inferences about the slope. We demonstrate that the current inferential methods are not robust to bivariate contamination, and consider four robust alternatives to the current methods – a novel sandwich estimator approach, using robust covariance matrices derived via an influence function approach, Huber's M‐estimator and the fast‐and‐robust bootstrap. Simulations demonstrate that Huber's M‐estimators are highly efficient and robust against bivariate contamination, and when combined with the fast‐and‐robust bootstrap, we can make accurate inferences even from small samples.
In the wrong mood at the right time: Children’s acquisition of the Spanish subjunctive in temporal clauses

Abstract This study investigates the complexity of the mapping task in children’s acquisition of the Spanish subjunctive in temporal clauses. We consider that children’s difficulty with this task arises from the interaction between mood and other elements determining the evaluation of the temporal clause, such as semantic factors, tense, and cognition. Forty monolingual Spanish-speaking children first completed a cognitive assessment test, evaluating false belief understanding; this was followed by a linguistic prerequisite test assessing understanding of temporal connectors and knowledge of subjunctive morphology, and finally a temporal clause production task. Results reveal that mood selection in temporal clauses does not simply start with indicative followed by its replacement by subjunctive. On the contrary, the use of subjunctive temporal clauses involves a complex process for children in which tense corresponds to a fundamental source of bootstrapping. These results confirm the view that the acquisition of mood selection undergoes a protracted development. Spanish subjunctive meanings are not immediately accessible to children.
SERIES ( Statistics # 2007-2 ) Tail Index Estimation for Parametric Families Using Log Moments

For heavy-tailed econometric data it is of interest to estimate the tail index, a parameter that measures the thickness of the tails of the marginal distribution. Common models for such distributions include Pareto and t distributions, and in other applications (such as hydrology) stable distributions are popular as well. This paper constructs square root n consistent estimators of the tail index that are independent of the scale of the data, which are based on an assumed knowledge of the parametric family for the marginal distribution. Given the popularity of parametric modeling for economic time series, this method gives an appealing alternative to nonparametric tail index estimators – such as the Hill and Pickands estimators – that are appropriate when the modeler believes that the data belongs to a certain known parametric family of distributions. The method works fairly well for stationary time series with intermediate memory and infinite variance, and since it is parametric does not depend upon blocking or tuning parameters. Small sample results and full asymptotics are provided in this paper, and simulation studies on various heavy-tailed time series models are given as well.
Regularity effect in prospective memory during aging

Background Regularity effect can affect performance in prospective memory (PM), but little is known on the cognitive processes linked to this effect. Moreover, its impacts with regard to aging remain unknown. To our knowledge, this study is the first to examine regularity effect in PM in a lifespan perspective, with a sample of young, intermediate, and older adults. Objective and design Our study examined the regularity effect in PM in three groups of participants: 28 young adults (18–30), 16 intermediate adults (40–55), and 25 older adults (65–80). The task, adapted from the Virtual Week, was designed to manipulate the regularity of the various activities of daily life that were to be recalled (regular repeated activities vs. irregular non-repeated activities). We examine the role of several cognitive functions including certain dimensions of executive functions (planning, inhibition, shifting, and binding), short-term memory, and retrospective episodic memory to identify those involved in PM, according to regularity and age. Results A mixed-design ANOVA showed a main effect of task regularity and an interaction between age and regularity: an age-related difference in PM performances was found for irregular activities (older < young), but not for regular activities. All participants recalled more regular activities than irregular ones with no age effect. It appeared that recalling of regular activities only involved planning for both intermediate and older adults, while recalling of irregular ones were linked to planning, inhibition, short-term memory, binding, and retrospective episodic memory. Conclusion Taken together, our data suggest that planning capacities seem to play a major role in remembering to perform intended actions with advancing age. Furthermore, the age-PM-paradox may be attenuated when the experimental design is adapted by implementing a familiar context through the use of activities of daily living. The clinical implications of regularity effect are discussed.
Prediction of Brain States of Concentration and Relaxation in Real Time with Portable Electroencephalographs

In our research, we attempt to help people recognize their brain state of concentration or relaxation more conveniently and in real time. Considering the inconvenience of wearing traditional multiple electrode electroencephalographs, we choose Muse to collect data which is a portable headband launched lately with a number of useful functions and channels and it is much easier for the public to use. Besides, traditional online analysis did not focus on the synchronism between users and computers and the time delay problem did exist. To solve the problem, by building the Analytic Hierarchy Model, we choose the two gamma wave channels of F7 and F8 as the data source instead of using both beta and alpha channels traditionally.Using the Common Space Pattern algorithm and the Support Vector Machine model, the channels we choose have a higher recognition accuracy rate and smaller amount of data to be dealt with by the computer than the traditional ones. Furthermore, we make use of the Feedforward Neural Network Model to predict subjects'brain states in half a second. Finally, we design a plane program in Python where a plane can be controlled to go up or down when users concentrate or relax. The SVM model and the Feedforward Neural Network model have both been tested by 12 subjects and they give an evaluation ranging from 1 to 10 points. The former gets 7.58 points while the latter gets 8.83, which proves that the time delay problem is improved once more.
Validation of dietary reference intake equations for estimating energy requirements in Korean adults by using the doubly labeled water method

BACKGROUND/OBJECTIVES The doubly labeled water (DLW) method is considered the gold standard for the measurement of total energy expenditure (TEE), which serves to estimate energy requirements. This study evaluated the accuracy of predictive dietary reference intake (DRI) equations for determining the estimated energy requirements (EER) of Korean adults by using the DLW as a reference method. SUBJECTS/METHODS Seventy-one participants (35 men and 36 women) aged between 20 and 49 years were included in the study. The subjects' EER, calculated by using the DRI equation (EERDRI), was compared with their TEE measured by the DLW method (TEEDLW). RESULTS The DRI equations for EER underestimated TEE by -36.3 kcal/day (-1.3%) in men and -104.5 kcal/day (-4.9%) in women. The percentages of accurate predictions among subjects were 77.1% in men and 62.9% in women. There was a strong linear correlation between EERDRI and TEEDLW (r=0.783, P<0.001 in men and r=0.810, P<0.001 in women). CONCLUSIONS The present study supports the use of DRI prediction equations to determine EER in Korean adults. More studies are needed to confirm our results and to assess the validity of these equations in other population groups, including children, adolescents, and older adults.
Short Paper: On High-Assurance Information-Flow-Secure Programming Languages

We argue that high-assurance systems require high-assurance information-flow-secure programming languages. As a step towards such languages, we present the, to our knowledge, first concurrent theory of information flow security that supports (1) compositional reasoning under dynamic assumptions, and (2) value-dependent classification, to handle the dynamism inherent in modern high-assurance systems. We sketch out our vision and a roadmap for building self-certifying information-flow-secure programming languages.
Brain Injury after Perinatal Hypoxia-Ischemia Is Exacerbated in Copper/Zinc Superoxide Dismutase Transgenic Mice

The role of superoxide radical formation in the pathogenesis of perinatal hypoxic-ischemic injury was examined using transgenic (Tg) mice expressing three times normal amounts of copper/zinc-superoxide dismutase (CuZn/SOD). Fourteen litters of postnatal d 7 strain 218/3 mice were subjected to right common carotid artery ligation followed by 90 min of hypoxia in an 8% oxygen/humidified chamber maintained at 37°C. Both Tg mice (n = 32) and their nontransgenic (nTg) littermates (n = 30) survived the injury equally. Evaluation of infarcted brain areas measured by video image analysis of three coronal brain sections through the anterior hippocampus from each animal revealed that the Tg animals suffered brain infarction more frequently than did nTg mice. Blinded histologic scoring of cerebral cortex and striatum 5 d after injury revealed that Tg mice were more likely to have higher histologic severity scores than their nTg littermates (p = 0.0463, Mann-Whitney U test). These findings suggest that brain injury in perinatal hypoxia-ischemia may be mediated in part by free radical formation from excessive hydrogen peroxide or nitric oxide production.
Peering at the Past Century's Corporate Strategy Through the Looking Glass of Time‐Series Analysis: Extrapolating from Chandler's Classic Mid‐Century American Firms?

This study has a dual thrust. "Substantively", it revisits Chandler's pragmatic fit-performance directive (Chandler's 'efficiency thesis') or his assertion that firms whose structure matches their strategy become more effective than mismatched firms. It is important to revisit the empirical origin of this result in view of its gradual international extrapolation beyond the time and place in which it originated. By gathering the financial data relevant to the firms cited as examples by Chandler, we identify whether the change to the multidivisional structure did indeed lead to improved financial performance in the mid-twentieth century American firms he described. "Methodologically", it explores a novel approach to the empirical validation of basic theories. Using historical replication, it undertakes a longitudinal, time-series analysis of a classic theory based on twentieth-century data, and thus investigates the testing of classic data with a modern tool. We undertake multiple replications. Three separate longitudinal studies are performed, consisting of two forecasting methods applied to 11 individual time series, and a comparison technique applied to the same. These are used with the three most common measures of performance at the time of Chandler's writing. All three methods reveal that the differences predicted by his theory are not borne out by the longitudinal analysis of a core group of Chandler's own exemplary firms. The three sets of longitudinal analyses we present raise some substantive questions regarding this cornerstone of classical theory, and carry positive methodological portents regarding the use of "historical replication" as a stepping-stone for twenty-first-century research. Copyright Blackwell Publishing Ltd 2003.
Vascular Relaxation, Antihypertensive Effect, and Cardioprotection of a Novel Peptide Agonist of the Mas Receptor

Mas stimulation with angiotensin (Ang)-(1-7) produces cardioprotective effects and vasorelaxation. Using a computational discovery platform for predicting novel naturally occurring peptides that may activate G protein–coupled receptors, we discovered a novel Mas agonist peptide, CGEN-856S. An endothelium- and NO-dependent vasodilating effect was observed for CGEN-856S in thoracic aorta rings of rats (maximal value for the relaxant effect: 39.99±5.034%), which was similar to that produced by Ang-(1-7) (10−10 to 10−6 mol/L). In addition, the vasodilator activity of this peptide depended on a functional Mas receptor, because it was abolished in aorta rings of Mas-knockout mice. CGEN-856S appears to bind the Mas receptor at the same binding domain as Ang-(1-7), as suggested by the blocking of its vasorelaxant effect with the Ang-(1-7) analogue d-Ala7-Ang-(1-7), and by its competitive inhibition of Ang-(1-7) binding to Mas-transfected cells. The effect of CGEN-856S on reperfusion arrhythmias and cardiac function was studied on ischemia reperfusion of isolated rat hearts. We found that picomolar concentration of CGEN-856S (0.04 nmol/L) had an antiarrhythmogenic effect, as demonstrated by a reduction in the incidence and duration of reperfusion arrhythmias. Furthermore, acute infusion of CGEN-856S produced a shallow dose-dependent decrease in mean arterial pressure of conscious spontaneously hypertensive rats. The maximum change during infusion was observed at the highest dose. Strikingly, blood pressure continued to drop in the postinfusion period. The results presented here indicate that the novel Mas agonist, CGEN-856S, might have a therapeutic value, because it induces vasorelaxing, antihypertensive, and cardioprotective effects.
Theorem Proving and the Real Numbers : Overview and Challenges

One of the first achievements in automated theorem proving was Jutting's construction of the real numbers using AUTOMATH [14]. But for years after-wards, formal proofs focused on problems from functional programming and elementary number theory. In the early 90s, John Harrison revived work on the reals by formalising their construction using HOL [8] and by undertaking an extensive programme of research into verifying floating point arithmetic, including the exponential and trigonometric functions [9–11]. MetiTarski represents a different approach to theorem proving about the reals. Reducing everything to first principles is rigorous, but makes proofs of the simplest statements extremely time-consuming. Many other automatic theorem provers are confined to linear arithmetic, or at best, polynomial comparisons. MetiTarski can prove complicated assertions involving transcendental functions. It takes many of their properties as axioms, and reasons from these properties using sophisticated decision procedures. MetiTarski has recently been integrated with other powerful reasoning tools, including KeYmaera [19] and PVS [17]. With this power, proofs involving such things as aircraft manoeuvres and the stability of hybrid systems can be undertaken, even when the dynamics are described by complicated formulas involving many special functions. Examples of this research can be found in these proceedings, for example, Denman's work on qualitative abstraction of hybrid systems [6]. This very success raises the question of how to recover the rigour of LCF-style theorem proving without losing the power of MetiTarski. The standard answer to this question (used by Isabelle's Sledgehammer for example [18]) is for the external prover to generate some sort of certificate that can be checked rigorously. The point is that the expensive proof search does not need to be checked, but only the proof that was actually found. Checking a certificate using a separate theorem prover, such as Isabelle, requires machine formalisations of all the underlying mathematics. Since Harri-son's work mentioned above, researchers worldwide have formalised substantial chunks of real analysis, including measure theory and probability theory [12, 16]. Independently, from the 1960s onwards, computer algebra systems enjoyed rapid development, as did decision procedures for real arithmetic. Much recent work has focused on formalising computer algebra algorithms within theorem provers, especially Coq [2, 15]. Investigations into special function inequalities have been conducted using PVS [5]. Nevertheless, the mathematics needed to certify the sort of proofs found by MetiTarski does not appear to have been formalised as yet. MetiTarski relies on an external decision procedure for real-closed …