Miracle-dz/UniFAR-FTUs huggingface dataset:
Semiparametric Efficiency Bound for Models of Sequential Moment Restrictions Containing Unknown Functions

This paper computes the semiparametric efficiency bound for finite dimensional parameters identified by models of sequential moment restrictions containing unknown functions. Our results extend those of Chamberlain (1992b) and Ai and Chen (2003) for semiparametric conditional moment restriction models with identical information sets to the case of nested information sets, and those of Chamberlain (1992a) and Brown and Newey (1998) for models of sequential moment restrictions without unknown functions to cases with unknown functions of possibly endogenous variables. Our bound results are applicable to semiparametric panel data models and semiparametric two stage plug-in problems. As an example, we compute the efficiency bound for a weighted average derivative of a nonparametric instrumental variables (IV) regression, and find that the simple plug-in estimator is not efficient. Finally, we present an optimally weighted, orthogonalized, sieve minimum distance estimator that achieves the semiparametric efficiency bound.
A Study on Static and Dynamic Behavior of Outrigger Structural System for Tall Buildings

In the present paper an investigation has been performed to examine the behavior of various alternative 3D models using ETABS software for reinforced concrete structure with central core wall with outrigger and without outrigger by varying the relative flexural rigidity from 0.25 to 2.0 with step of 0.25. Also the position of outrigger has been varied along the height of the building by considering a parameter relative height of outrigger from 0.975 to 0.4. The parameters discussed in this paper include variation of bending moments, shear force, lateral deflection, peak acceleration of the core; inter-storey drifts for static and dynamic analysis for a 3-dimensional model for various values of relative rigidity and relative height. From the analysis of the results obtained it has been found that performance of the outrigger is most efficient for relative height of the outrigger equal to 0.5.
The Green Bean Has to Be Longer than Your Thumb: An Observational Study of Preschoolers' Math and Science Experiences in a Garden.

School gardening has become increasingly popular as a context for learning in which children construct new knowledge, learn cultural and societal values related to ecological awareness, and develop and practice authentic or real world skills (Blair, 2009; Bowker & Tearle, 2007). The present research was a longitudinal case study of children’s gardening experiences at a Reggio -inspired preschool in the United States. Eleven children and their teacher were observed over nine days in various activities such as preparing the garden be ds, planting, and harvesting. Through sustained participation in a variety of gardening activities, preschoolers engaged in science rich dialogue utilizing complex and abstract science process skills such as observing, predicting, evaluating, and comparin g. Discussion of number -related concepts, spatial orientation, and size estimation and comparison was also recurrent during gardening activities. In addition, analyses of social interactions and dialogue related to gardening knowledge and ecological awaren ess indicated that working in the garden was an authentic context for enjoying, learning about, and valuing the natural world. The results of this study support the conclusion that with appropriate teacher guidance, a preschool garden affords myriad opport unities for young children to develop mathematical and scientific thinking, ecological awareness and positive affective responses to the natural world.
EFT (Emotional Freedom Techniques) Remediates PTSD and Psychological Symptoms in Veterans: A Randomized Controlled Replication Trial

Posttraumatic stress disorder (PTSD) is a common condition among veterans and is often regarded as treatment-resistant. Emotional Freedom Techniques (EFT) combines brief exposure therapy with acupressure and has demonstrated efficacy for PTSD in other trials and meta-analyses. This study recruited 58 veterans who scored 50 or greater on the military PTSD checklist (PCL-M), indicating clinical symptom levels. Participants were randomized into a Treatment As Usual (TAU) wait-list group (n = 26) and an experimental group (n = 32), which received six one-hour EFT sessions in addition to TAU. The mean pretreatment PCL-M score of participants was 66 ± 7.4, with no significant difference between groups. The EFT group demonstrated a significant reduction in PCL-M score from 65 ± 8.1 to 34 ± 10.3 (p < 0.001), while subjects in the TAU group showed no significant change. The TAU group was then treated with EFT and groups were combined for analysis using linear mixed effects modeling. In the combined EFT group, posttreatment PCL-M scores declined to a mean of 34 (–52%, p < 0.001). Participant gains were maintained at three and six-month follow-up, with mean six-month PCL-M scores of 34 (p < 0.001). Psychological conditions such as anxiety and depression also declined significantly, as did physiological markers of insomnia and pain. An effect size of Cohen’s d = 3.44 indicates a large treatment effect. These results replicate those obtained in an earlier investigation, and indicate that EFT is an evidence-based practice that is highly effective at reducing symptom severity in veterans with PTSD.
Improvement of Faba Bean Yield Using Rhizobium/Agrobacterium Inoculant in Low-Fertility Sandy Soil

Soil fertility is one of the major limiting factors for crop’s productivity in Egypt and the world in general. Biological nitrogen fixation (BNF) has a great importance as a non-polluting and a cost-effective way to improve soil fertility through supplying N to different agricultural systems. Faba bean (Vicia faba L.) is one of the most efficient nitrogen-fixing legumes that can meet all of their N needs through BNF. Therefore, understanding the impact of rhizobial inoculation and contrasting soil rhizobia on nodulation and N2 fixation in faba bean is crucial to optimize the crop yield, particularly under low fertility soil conditions. This study investigated the symbiotic effectiveness of 17 Rhizobium/Agrobacterium strains previously isolated from different Egyptian governorates in improving the nodulation and N2 fixation in faba bean cv. Giza 843 under controlled greenhouse conditions. Five strains that had a high nitrogen-fixing capacity under greenhouse conditions were subsequently tested in field trials as faba bean inoculants at Ismaillia Governorate in northeast Egypt in comparison with the chemical N-fertilization treatment (96 kg N·ha−1). A starter N-dose (48 kg N·ha−1) was applied in combination with different Rhizobium inoculants. The field experiments were established at sites without a background of inoculation under low fertility sandy soil conditions over two successive winter growing seasons, 2012/2013 and 2013/2014. Under greenhouse conditions, inoculated plants produced significantly higher nodules dry weight, plant biomass, and shoot N-uptake than non-inoculated ones. In the first season (2012/2013), inoculation of field-grown faba bean showed significant improvements in seed yield (3.73–4.36 ton·ha−1) and seed N-yield (138–153 Kg N·ha−1), which were higher than the uninoculated control (48 kg N·ha−1) that produced 2.97 Kg·ha−1 and 95 kg N·ha−1, respectively. Similarly, in the second season (2013/2014), inoculation significantly improved seed yield (3.16–4.68 ton·ha−1) and seed N-yield (98–155 Kg N·ha−1) relative to the uninoculated control (48 kg N·ha−1), which recorded 2.58 Kg·ha−1 and 80 kg N·ha−1, respectively. Interestingly, faba bean inoculated with strain Rlv NGB-FR 126 showed significant increments in seed yield (35%–48%) and seed N-yield (34%–49%) compared to the inorganic N fertilizers treatment (96 kg N·ha−1) over the two cropping seasons, respectively. These results indicate that inoculation of faba bean with effective rhizobial strains can reduce the need for inorganic N fertilization to achieve higher crop yield under low fertility soil conditions.
FUNCTIONAL SUPERVISED CLASSIFICATION WITH WAVELETS

Let X be a random variable taking values in a Hilbert space and let Y be a random label with values in {0,1}. Given a collection of classification rules and a learning sample of independent, copies of the pair (X,Y), it is shown how to select optimally and consistently a classifier. As a general strategy, the learning sample observations are first expanded on a wavelet basis and the overall infinite dimension is reduced to a finite one via a suitable data-dependent thresholding. Then, a finite-dimensional classification rule is performed on the non-zero coefficients. Both the dimension and the classifier are automatically selected by data-splitting and empirical risk minimization. Applications of this technique to a signal discrimination problem involving speech recordings and simulated data are presented.
A novel zero-correlation zone sequence set with sequence subsets

The present paper introduces a new approach to the construction of a sequence set with a zero-correlation zone. The proposed sequences can be constructed from a pair of Hadamard matrices of the orders n<inf>0</inf> and n<inf>1</inf>. The constructed sequence set consists of n<inf>0</inf>n<inf>1</inf> ternary sequences, each of length n<inf>0</inf><sup>(m+2)</sup>(n<inf>1</inf>+2), for a non-negative integer m. The zero-correlation zone of the proposed sequences is |τ| ≤ n<inf>0</inf><sup>m+1</sup>− 1, where τ is the phase shift. The sequence member size of the proposed sequence set is equal to n<inf>1</inf> over n<inf>1</inf>+2 times that of the theoretical upper bound on the member size of a sequence set with a zero-correlation zone. The proposed sequence set consists of n<inf>0</inf> subsets, each of member size n<inf>1</inf>. The correlation function of the sequences of a pair of different subsets, refereed to as the inter-subset correlation function, has a zero-correlation zone with a width that is almost twice that of the correlation function of sequences of the same subset (intra-subset correlation function). This wider inter-subset zero-correlation contributes to the performance improvement of applications of the proposed sequence set. The proposed sequence set has a zero-correlation zone for both periodic and aperiodic correlation functions.
An Extensible Probabilistic Transformation-based Approach to the Third Recognizing Textual Entailment Challenge

We introduce a system for textual entailment that is based on a probabilistic model of entailment. The model is defined using some calculus of transformations on dependency trees, which is characterized by the fact that derivations in that calculus preserve the truth only with a certain probability. We also describe a possible set of transformations (and with it implicitly a calculus) that was successfully applied to the RTE3 challenge data. However, our system can be improved in many ways and we see it as the starting point for a promising new approach to textual entailment.
OF THE AMERICAN MATHEMATICAL SOCIETY Volume 33 , Number 2 , April 1996 Lectures on the geometry of Poisson manifolds

The discovery 18 years ago by Vaughan Jones of a powerful new polynomial invariant for knots and links began a revolution in knot theory. Of the nearly 8,000 Mathematical Reviews about knots, more than two thirds have appeared after 1985. Connections between knot theory and other areas of mathematics as well as physics are no longer surprising. Into this heady environment come two new publications, both revisions of important books on knots and links, both surveying knot theory from an earlier, mostly algebraic point of view. Knots, 2nd edition, by Gerhard Burde and Heiner Zieschang, revises and expands the first edition, which was published in 1985. In this book, which has a strongly group-theoretic flavor, links appear, but high-dimensional knots do not. Knots is intended as a textbook, and according to its authors, inspiration was derived from Dale Rolfson’s classic Knots and Links, Publish or Perish Press, published in 1976 and reprinted in 1990 (with corrections). Algebraic Invariants of Links, by Jonathan Hillman, is a greatly revised and expanded version of Hillman’s Alexander Ideals of Links, Springer-Verlag Lecture Notes in Mathematics, Volume 895, published in 1981. Intended more as a reference rather than a textbook, Algebraic Invariants of Links emphasizes links and highdimensional knots. It is more technical than Knots and requires a deeper algebraic background from the reader. Together these two books offer an algebraic view of knot theory that is both panoramic and penetrating. There are several superb surveys of knot theory ([G79], [KW79], [E99], [LO03], [L03], [T85] for example), and it is not our purpose to compete with them. Rather, we intend to describe some of the algebraic ideas that are central to the two books under review. Details about the books themselves will be found in the final section.
Fabrication and Room-Temperature Single-Charging Behavior of Self-Aligned Single-Dot Memory Devices

Self-aligned single-dot memory devices and arrays were fabricated based on arsenic-assisted etching and oxidation effects. The resulting device has a floating gate of about 5-10 nm, presenting single-electron memory operation at room temperature. In order to realize the final single-electron memory circuit, this paper investigates process repeatability, device uniformity in single-dot memory arrays, device scalability, and process transferability to an industrial application
Dissemination of the AHCPR clinical practice guideline in community health centres

Objective: To evaluate dissemination of the Agency for Health Care Policy and Research (AHCPR) Smoking cessation clinical practice guideline in community health centres. Design: Pre- and post-trial. Setting: Fourteen community health centres in Rhode Island. Subjects: Provider performance was assessed with 1798 and 1591 patient contacts, in pre-post cross sectional consecutive samples, respectively, and 891 contacts at one year follow up. Interventions: Three, one hour on-site provider training sessions, on review of effective tobacco interventions, use of office systems, and tobacco counselling skill building. Outcome measures: Chart documentation of four A’s (Ask, Advise, Assist, and Arrange follow up) at most recent primary care visit. Results: While average performance rates increased for Ask and Advise (from 30% to 44%, and 19% to 26%, pre-post, respectively), significant increases were found only for some visit types, with further differences by patient sex. There were significant increases for Ask for all except obstetric/gynaecological (ob/gyn) visit types. Patients at yearly physicals and first visits were more likely to be asked at all time points, while males were more likely to be asked at acute visits than were females. There were no significant increases for Advise, Assist, and Arrange across time, although female patients showed a differential increase in Advise post-training. Advise was significantly more likely in yearly physicals and first visits, and less likely in ob/gyn visits, at all time points. Conclusions: This guideline dissemination effort resulted in quite different provider counselling rates across patient sexes, and visit types. Guideline implementation may require more sustained efforts, with multiple strategies, which are reinforced at higher policy levels, to more fully integrate tobacco interventions into routine primary care practice with all patients who smoke.
On the Complexity of Fundamental Computational Problems in Pedigree Analysis

Pedigree analysis is a central component of many current efforts to locate genes that contribute to diseases or to valuable traits. The analysis usually involves solving one of two very computation-intense problems. We analyze the complexity of these two problems. Surprisingly, we show that both problems are NP-hard even for pedigrees that contain no inbreeding loops.
Fracture Resistance of Root Canals Obturated with Gutta-Percha versus Resilon with Two Different Techniques

Introduction Dentin removal during root canal instrumentation creates a weaker root structure and increases its potential to fracture. The aim of this in vitro experimental study was to compare fracture resistance of teeth filled with gutta-percha, and Resilon using two different techniques. Materials and Methods This study was performed on 105 single-canal extracted maxillary incisors. Samples were divided into seven groups of 15 each. Three groups were prepared with K-files; three groups with Race rotary files and in one group no preparation was carried out. Of all samples prepared either manually or with rotary instruments, 15 teeth were obturated using gutta-percha and AH26 sealer, 15 teeth were filled with Resilon and 15 teeth remained unfilled. Loading force to fracture was measured and ANOVA and Tukey tests were used for statistical analysis. Results No statistically significant differences were observed between different preparation techniques. The intact roots showed significantly greater fracture resistance compared to both instrumented groups (P<0.01). Resilon Group showed significantly higher resistance than gutta-percha Group (P<0.01); however the difference between Resilon and intact teeth was not statistically significant. Conclusion Accoding to the results of this in vitro study, root canal filling using Resilon may increase the fracture resistance of treated teeth.
Evaluating the Effectiveness of Reading Strategies for College Students: An Action Research Approach.

This study was an action research project evaluating the effectiveness of selected reading strategies on student learning. The action research was conducted in an undergraduate measurement course in a teacher preparation program. Students used a pre-selected reading strategy to read assigned readings then completed a quiz on the readings and a survey on their perception of the effectiveness of each reading strategy. A mixed-method approach was employed. Results indicated the active processing strategies were effective, with the “I” graphical organizer was perceived by most students as an efficient tool for quizzes and was also perceived as being more efficient than reflections.
Speeding up Convolutional Neural Networks with Low Rank Expansions

The focus of this paper is speeding up the application of convolutional neural networks. While delivering impressive results across a range of computer vision and machine learning tasks, these networks are computationally demanding, limiting their deployability. Convolutional layers generally consume the bulk of the processing time, and so in this work we present two simple schemes for drastically speeding up these layers. This is achieved by exploiting cross-channel or filter redundancy to construct a low rank basis of filters that are rank-1 in the spatial domain. Our methods are architecture agnostic, and can be easily applied to existing CPU and GPU convolutional frameworks for tuneable speedup performance. We demonstrate this with a real world network designed for scene text character recognition [15], showing a possible 2.5× speedup with no loss in accuracy, and 4.5× speedup with less than 1% drop in accuracy, still achieving state-of-the-art on standard benchmarks.
Motivation as a Lens to Understand Online Learners

Open online learning environments attract an audience with diverse motivations who interact with structured courses in several ways. To systematically describe the motivations of these learners, we developed the Online Learning Enrollment Intentions (OLEI) scale, a 13-item questionnaire derived from open-ended responses to capture learners' authentic perspectives. Although motivations varied across courses, we found that each motivation predicted key behavioral outcomes for learners (N = 71, 475 across 14 courses). From learners' motivational and behavioral patterns, we infer a variety of needs that they seek to gratify by engaging with the courses, such as meeting new people and learning English. To meet these needs, we propose multiple design directions, including virtual social spaces outside any particular course, improved support for local groups of learners, and modularization to promote accessibility and organization of course content. Motivations thus provide a lens for understanding online learners and designing online courses to better support their needs.
Parenting factors related to asthma and anxiety in children

The present study examined the association between parenting style and anxiety in children with asthma. Participants included 60 children with asthma and 60 controls, aged 9-12 years. At least one of the children’s parents participated. The children and their parents completed self-report measures of anxiety and depressive symptoms. Children reported on their parent’s style of parenting, while parent’s reported on parent-child relationship quality. Parents and physicians completed asthma severity reports. Results partially replicated previous findings. In general, children with asthma obtained higher anxiety scores. Further, parenting style was associated with anxiety scores, with no difference between asthma and control groups. Parenting style did not differ between asthma and control groups. No differences were found between groups on parent child relationship variables.
A Robust Iterative Multiframe Super-Resolution Reconstruction using a Bayesian Approach with Tukey's Biweigth

Typically, the almost SRR (super-resolution reconstruction) estimations are based on L1 or L2 statistical norm estimation therefore these SRR methods are usually very sensitive to their assumed model of data and noise that limits their utility. This paper reviews some of these SRR methods and addresses their shortcomings. We propose a novel SRR approach based on the stochastic regularisation technique of Bayesian MAP estimation by minimizing a cost function. The Tukey's Biweigth norm (M.J Black et al., 1998) is used for measuring the difference between the projected estimate of the high-resolution image and each low resolution image, removing outliers in the data and Tikhonov regularisation is used to remove artifacts from the final answer and improve the rate of convergence. The experimental results confirm the effectiveness of our method and demonstrate its superiority to other super-resolution methods based on L1 and L2 norm for a several noise models such as noiseless, additive white Gaussian noise (AWGN) and salt & pepper Noise
Rb-RICH ASYMPTOTIC GIANT BRANCH STARS IN THE MAGELLANIC CLOUDS

We present high-resolution (R ∼ 60,000) optical spectra of a carefully selected sample of heavily obscured and presumably massive O-rich asymptotic giant branch (AGB) stars in the Magellanic Clouds. We report the discovery of strong Rb i lines at 7800 Å in four Rb-rich LMC stars at luminosities equal to or greater than the standard adopted luminosity limit for AGB stars (Mbol ∼ −7.1), confirming that “hot bottom burning” may produce a flux excess in the more massive AGB stars. In the SMC sample, just one of the five stars with Mbol < −7.1 was detected in Rb; the other stars may be massive red supergiants. The Rb-rich LMC AGB stars might have stellar masses of at least ∼6–7 M☉. Our abundance analyses show that these Rb-rich stars are extremely enriched in Rb by up to 103–105 times solar but seem to have only mild Zr enhancements. The high Rb/Zr ratios, if real, represent a severe problem for the s-process, even if the 22Ne source is operational as expected for massive AGB stars; it is not possible to synthesize copious amounts of Rb without also overproducing Zr. The solution to the problem may lie with an incomplete present understanding of the atmospheres of luminous AGB stars.