Miracle-dz/UniFAR-FTUs huggingface dataset:
Sponsored Search Auctions: Research Opportunities in Marketing

We systematically overview the literature in keyword search and propose several promising research directions. The paper is organized by each agent in the search process; searchers, advertisers and the search engine and reviews the key research issues for each. For each group, we outline the decision process involved in keyword search. For searchers, this involves what to search, where to search, which results to click, and when to exit search. For advertisers, this involves where to bid and which word or words to bid on, and how searchers and auction mechanisms moderate these behaviors. The search engine faces choices on mechanism design, website design and how much information to share with its advertisers and searchers. These choices have implications for customer lifetime value and the nature of competition between advertisers. Overall, we list a number of potential areas of future research arising from the decision processes of these various agents.
Adherence to pediatric asthma treatment in economically disadvantaged African-American children and adolescents: an application of growth curve analysis.

OBJECTIVES The primary aims of the study were to: (a) describe the trajectories of adherence to daily inhaled corticosteroid (ICS) medication for a year in economically disadvantaged, African-American youth with asthma based on growth curve modeling; and (b) test the relationship of treatment adherence to symptom control, quick-relief medication, and healthcare utilization. METHODS This prospective study measured adherence to daily ICS treatment using electronic monitoring in 92 children and adolescents with moderate to severe asthma for 9-12 months and assessed clinical outcomes, including asthma-related symptoms, quick-relief medication, and healthcare utilization. RESULTS Youth showed a decrement in treatment adherence to less than half of prescribed corticosteroid treatment over the course of the study, which related to increased healthcare utilization (p < .04), but not to asthma symptoms or albuterol use. CONCLUSION Economically disadvantaged youth with asthma demonstrate high rates of chronic nonadherence that warrant identification and intervention to reduce asthma-related healthcare utilization.
Optimal Conditions for the Mycelial Growth of Coprinus comatus Strains

The principal objective of this study was to acquire basic data regarding the mycelial growth characteristics for the artificial cultivation of Coprinus comatus. 12 URP primers were employed to evaluate the genetic relationships of C. comatus, and the results were divided into three groups. Among six kinds of mushroom media, MYP medium was selected as the most favorable culture medium for C. comatus. The optimal temperature and pH ranges for the mycelial growth of C. comatus were 23~26°C and pH 6~8, respectively. The carbon and nitrogen sources for optimal mycelial growth were sucrose and tryptone, respectively.
Micronutrient quality of weight loss diets that focus on macronutrients: results from the A TO Z study

Information on diet quality of alternative weight loss diets is limited. Our objective was to compare nutrient intake among overweight/obese women randomly assigned to the Atkins (n=73), Zone (n=73), LEARN (n=72), or Ornish (n=73) diets. Diet data were collected by 3‐day, unannounced, 24‐hour recall at baseline and after 8 weeks of diet instruction. Nutrient intakes were compared between groups at 8 weeks, and within groups for changes in risk of micronutrient deficiency (<2/3 RDA) between baseline and 8 weeks. At 8 weeks there were significant differences among groups for all macronutrients and many micronutrients (p<0.0001). Energy intake decreased from baseline for all 4 groups but was similar among groups. The proportion of individuals at risk of deficiency increased significantly (p<0.05) in the Atkins group for thiamin, folate, vitamin C, iron, and magnesium; in the LEARN group for vitamin E and calcium; and in the Ornish group for vitamins E and B12 and zinc. In contrast, for the Zone group the risk of deficiencies significantly decreased for vitamins A, C, E and K (p<0.05) with no significant increases in risk of deficiency. Weight loss diets that emphasize macronutrient composition should consider not only the weight loss outcomes, but also the adequacy of micronutrient intakes. This research was supported by NIH and the Community Foundation of Southeastern Michigan.
Videolab: (De)construction of (un)real space

Within '[koligrica' Studio for Creative Education, Video-la-(b) project has been developing a series of video workshops for preschoolers since 1991. Its specific approach to media education was based on the use of CCTV (Closed Circuit Television) technique, enabling children to watch their own and others' activities on the screen as they perform them. This 'pseudo mirror' situation gives opportunity for organizing games of increasing complexity and opens interesting possibilities in two domains: media education and spatial cognition. As far as media education is concerned, the experience of partaking in the process of creating 'live pictures' counteracts the tendency of taking visual presentations for granted, contributing to the awareness of the mediatory and artificial nature of visual media. At the same time, it is possible that simultaneous presence in both actual and represented space, and the opportunity for their immediate comparison, might help the child to overcome the adherence to his/her own point of view and become capable of coordinating different perspectives. In Piagetian terms, as far as cognitive development is concerned, the described approach could turn out to have a stimulating effect on decentration, at least in the spatial domain.
Distance Transform for Images Represented by Quadtrees

The concept of distance used in binary array representations of images is adapted to a quadtree representation. The chessboard distance metric is shown to be particularly suitable for the quadtree. A chessboard distance transform for a quadtree is defined as the minimum distance in the plane from each BLACK node to the border of a WHiTE node. An algorithm is presented which computes this transform by only examining the BLACK node's adjacent and abutting neighbors and their progeny. However, unlike prior work with quadtrees, computation of the distance transform requires a capability of finding neighbors in the diagonal direction rather than merely in the horizontal and vertical directions. The algorithm's average execution time is proportional to the number of leaf nodes in the quadtree.
Optimization Approaches for Learning with Low-rank Regularization

Low-rank modeling has a lot of important applications in machine learning, computer vision and social network analysis. As direct rank minimization is NP hard, many alternative choices have been proposed. In this survey, we first introduce optimization approaches for two popular methods on rank minimization, i.e., nuclear norm regularization and rank constraint. Nuclear norm is the tightest convex envelope of rank function, therefore low-rank optimization using nuclear norm regularization is a convex problem where many convex optimization approaches can be applied. When rank constraint is used, the resulting optimization problems become simpler but are generally non-convex. Thus, algorithms working for these problems are lack of global optimal and may suffer from slow convergence. Except above two common approaches, adaptive non-convex regularizers have recently been proposed, which can better fit singular values. The key idea behind these regularizers is that large singular values are more informative, and thus should be less penalized. The optimization problems are neither smooth nor convex, thus are harder than with nuclear norm regularization or rank constraint. Several algorithms are developed recently which can be applied on these problems, and they are introduced in this survey. Helpful remarks are given for algorithms working within same type of regularizer; and then experiments are performed with both synthetic and real data sets to compare above three different types of regularizers. Finally, we discuss some possible research issues.
Selection of 3PL service providers: a combined approach of AHP and Graph theory

3PL service provider helps the shippers in achieving their strategic objectives hence becoming vital in the logistics outsourcing. Shippers need to have a careful evaluation and selection before offering an important outsourcing contract. The selection process involves the identification of potential criteria and performance assessment of 3PL service providers with reference to selected criteria thus necessitates systematic methodology. The present work, proposes a methodology based on combined approach of Analytic Hierarchy Process (AHP) and Graph theory. A LSP selection index which evaluates and ranks the 3PL service providers have been derived to help shippers. The paper also proposes coefficients of similarity, coefficients of dissimilarity and the identification sets for further comparison of 3PL service providers. A real case problem of a MNC has been illustrated to help the logistics managers for their logistics outsourcing assignments.
Update of the cincinnati experience in pediatric laryngotracheal reconstruction

Surgical endeavors in the field of laryngotracheal reconstruction in children have received much interest in the past 15 years. A unique experience with laryngotracheal reconstruction in 203 children is reviewed. The majority (194) of the cases were classified as acquired; only nine were classified as congenital. Excluded from the study were those cases of stenoses managed en‐doscopically, all resections and end‐to‐end anastomoses, all anterior cricoid split procedures, and all cases of anterior glottic stenosis repaired by a laryngeal keel. The degree of stenosis was graded into four categories. Five different methods of laryngotracheal reconstruction were used depending on the pathologic lesion in the larynx and trachea. Of the 203 children, 186 (92%) were decannulated. The results support the use of laryngotracheal reconstruction in children with grades 2, 3, and 4 laryngeal stenosis.
Direction of arrival estimation using artificial neural networks

The maximum likelihood estimator is the optimal estimator of the direction of sources, but it requires the minimization of a complex, multimodal, multidimensional cost function. A neural optimization procedure is presented that does not require an initial estimate of the direction of the sources and offers the potential of real-time solutions to the direction of arrival problem by utilizing the fast relaxation properties of the Hopfield network. A modification based on an iterated descent procedure is introduced into the Hopfield model dynamic equation to increase the probability of convergence to the global optimum. The algorithms are implemented on an array of closely coupled transputers that perform the random asynchronous neural updates in parallel. The mapping is achieved using a technique called chaotic relaxation. Simulation results are presented to characterize the performance of the neural approach in terms of the variance of the estimates of source directions and the time required for the computation of the estimates. >
Modelling mid-Z element atmospheres for strongly magnetized neutron stars

We construct models for strongly magnetized neutron star atmospheres composed of midZ elements (carbon, oxygen and neon) with magnetic fields B = 10 12 ‐10 13 G and effective temperatures T eff = (1 ‐ 5) × 10 6 K; this is done by first addressing the physics relevant to strongly magnetized plasmas and calculating the equation of state and polarization-dependent opacities. We then obtain the atmosphere structure and spectrum by solving the radiative transfer equations in hydrostatic and radiative equilibrium. In contrast to hydrogen opacities at the relevant temperatures, mid-Z element opacities are dominated by numerous bound‐bound and bound‐free transitions. Consequently, temperature profiles are closer to grey profiles, and photosphere densities are lower than in the hydrogen case. Mid-Z element atmosphere spectra are significantly softer than hydrogen atmosphere spectra and show numerous absorption lines and edges. The atmosphere spectra depend strongly on surface composition and magnetic field but weakly on surface gravity. Absorption lines are primarily broadened by motional Stark effects and the (unknown) surface magnetic field distribution. When magnetic field variation is not severe, substructure in broad absorption features can be resolved by (phase-resolved) CCD spectroscopy from Chandra and XMM‐Newton. Given the multiple absorption features seen in several isolated neutron stars (INSs), it is possible to determine the surface composition, magnetic field, temperature and gravitational redshift with existing X-ray data; we present qualitative comparisons between our model spectra and the neutron stars 1E1207.4−5209 and RX J1605.3+3249. Future high-resolution X-ray missions such as Constellation-X will measure the gravitational redshift with high accuracy by resolving narrow absorption features; when combined with radius measurements, it will be possible to uniquely determine the mass and radius of INSs.
Analytical modeling of garbage collection algorithms in hotness-aware flash-based solid state drives

Garbage collection plays a central role of flash-based solid state drive performance, in particular, its endurance. Analytical modeling is an indispensable instrument for design improvement as it demonstrates the relationship between SSD endurance, manifested as write amplification, and the algorithmic design variables, as well as workload characteristics. In this paper, we improve recent advances in using the mean field analysis as a tool for performance analysis and target hotness-aware flash management algorithms. We show that even under a generic workload model, the system dynamics can be captured by a system of ordinary differential equations, and the steady-state write amplification can be predicted for a variety of practical garbage collection algorithms, including the d-Choice algorithm. Furthermore, the analytical model is validated by a large collection of real and synthetic traces, and prediction errors against these simulations are shown to be within 5%.
A retrospective review of clopidogrel as primary therapy for migraineurs with right to left shunt lesions

Background: The association of patient foramen ovale (PFO) and migraine headache (migraine) with aura (MA) is well established. Current research suggests a mechanistic link between platelet activation, paradoxical embolization and migraine in some patients. Methods: Clopidogrel, a platelet inhibitor, was added to existing migraine therapy, as a 4-week open-label trial in 15 women, aged 16–56 years, with severe migraine and documented right to left shunt (RLS). Results: 13/15 had >50% reduction or complete elimination of migraine symptoms. After completing the trial period, five responders remain on clopidogrel with ongoing benefit at 11.9 ± 4.5 months (6.5–20), one stopped clopidogrel because of side effects. Nine other responders underwent PFO closure and clopidogrel discontinuation. Eight of nine have had ongoing benefit. Conclusions: Clopidogrel may have a primary prophylactic role in migraine/RLS patients, but may also help select candidates who would benefit from PFO closure. A randomized clinical trial is being established.
Affect-expressive hand gestures synthesis and animation

Speech and hand gestures form a composite communicative signal that boosts the naturalness and affectiveness of the communication. We present a multimodal framework for joint analysis of continuous affect, speech prosody and hand gestures towards automatic synthesis of realistic hand gestures from spontaneous speech using the hidden semi-Markov models (HSMMs). To the best of our knowledge, this is the first attempt for synthesizing hand gestures using continuous dimensional affect space, i.e., activation, valence, and dominance. We model relationships between acoustic features describing speech prosody and hand gestures with and without using the continuous affect information in speaker independent configurations and evaluate the multimodal analysis framework by generating hand gesture animations, also via objective evaluations. Our experimental studies are promising, conveying the role of affect for modeling the dynamics of speech-gesture relationship.
Beyond Language Equivalence on Visibly Pushdown Automata

We study (bi)simulation-like preorder/equivalence checking on the class of visibly pushdown automata and its natural subclasses visibly BPA (Basic Process Algebra) and visibly one-counter automata. We describe generic methods for proving complexity upper and lower bounds for a number of studied preorders and equivalences like simulation, completed simulation, ready simulation, 2-nested simulation preorders/equivalences and bisimulation equivalence. Our main results are that all the mentioned equivalences and preorders are EXPTIME-complete on visibly pushdown automata, PSPACE-complete on visibly one-counter automata and P-complete on visibly BPA. Our PSPACE lower bound for visibly one-counter automata improves also the previously known DP-hardness results for ordinary one-counter automata and one-counter nets. Finally, we study regularity checking problems for visibly pushdown automata and show that they can be decided in polynomial time.
Expert Advice for Multiple Audiences with Conflicting Interests ∗

This paper examines a simple (repeated) cheap talk game between a single expert and two audiences with conflicting interests. The expert, who is informed about a payoff relevant parameter, sends an unverifiable message to the receivers. Conditional on the message they observe, the receivers simultaneously choose their actions, which collectively determine the payoffs of all three. The paper answers the following questions: How valuable and informative are the expert’s advice? Under what conditions is deception consistent with equilibrium? Furthermore, if the expert is a long-lived agent who also cares about the reliability of her messages in the long-term, then what makes the expert more or less deceptive?
A Preliminary Study on the Learning Informativeness of Data Subsets

Estimating the internal state of a robotic system is complex: this is performed from multiple heterogeneous sensor inputs and knowledge sources. Discretization of such inputs is done to capture saliences, represented as symbolic information, which often presents structure and recurrence. As these sequences are used to reason over complex scenarios, a more compact representation would aid exactness of technical cognitive reasoning capabilities, which are today constrained by computational complexity issues and fallback to representational heuristics or human intervention. Such problems need to be addressed to ensure timely and meaningful human-robot interaction. Our work is towards understanding the variability of learning informativeness when training on subsets of a given input dataset. This is in view of reducing the training size while retaining the majority of the symbolic learning potential. We prove the concept on human-written texts, and conjecture this work will reduce training data size of sequential instructions, while preserving semantic relations, when gathering information from large remote sources.
The Measurement of Student Ability in Modern Assessment Systems

Economists often use test scores to measure a student’s performance or an adult’s human capital. These scores reflect non-trivial decisions about how to measure and scale student achievement, with important implications for secondary analyses. For example, the scores computed in several major testing regimes, including the National Assessment of Educational Progress (NAEP), depend not only on the examinees’ responses to test items, but also on their background characteristics, including race and gender. As a consequence, if a black and white student respond identically to questions on the NAEP assessment, the reported ability for the black student will be lower than for the white student—reflecting the lower average performance of black students. This can bias many secondary analyses. Other assessments use different measurement models. This paper aims to familiarize applied economists with the construction and properties of common cognitive score measures and the implications for research using these measures.
Loved to Death

incentives for mutative change in our patients and our own practice. By inviting us into her open-mindedness and readiness to engage with new perspectives—interpersonal, intersubjective, relational, dynamic systems theory—Kieffer makes example of her own efforts toward mutual recognition and the confrontation of ideas and practice in contemporary psychoanalysis. Her credo might be, as Samuel Beckett (1992) put it, “Ever tried. Ever failed. No matter. Try again. Fail again. Fail better” (p. 101).
Mapping accretion and its variability in the young open cluster NGC 2264: a study based on u-band photometry

Context. The accretion process has a central role in the formation of stars and planets. Aims. We aim at characterizing the accretion properties of several hundred members of the star-forming cluster NGC 2264 (3 Myr). Methods. We performed a deep ugri mapping as well as a simultaneous u-band+r-band monitoring of the star-forming region with CFHT/MegaCam in order to directly probe the accretion process onto the star from UV excess measurements. Photometric properties and stellar parameters are determined homogeneously for about 750 monitored young objects, spanning the mass range ~0.1–2 M_⊙. About 40% of the sample are classical (accreting) T Tauri stars, based on various diagnostics (H_α, UV and IR excesses). The remaining non-accreting members define the (photospheric + chromospheric) reference UV emission level over which flux excess is detected and measured. Results. We revise the membership status of cluster members based on UV accretion signatures, and report a new population of 50 classical T Tauri star (CTTS) candidates. A large range of UV excess is measured for the CTTS population, varying from a few times 0.1 to ~3 mag. We convert these values to accretion luminosities and accretion rates, via a phenomenological description of the accretion shock emission. We thus obtain mass accretion rates ranging from a few 10^(-10) to ~10^(-7) M_⊙/yr. Taking into account a mass-dependent detection threshold for weakly accreting objects, we find a >6σ correlation between mass accretion rate and stellar mass. A power-law fit, properly accounting for censored data (upper limits), yields Ṁ_(acc) ∝ M_*^(1.4±0.3). At any given stellar mass, we find a large spread of accretion rates, extending over about 2 orders of magnitude. The monitoring of the UV excess on a timescale of a couple of weeks indicates that its variability typically amounts to 0.5 dex, i.e., much smaller than the observed spread in accretion rates. We suggest that a non-negligible age spread across the star-forming region may effectively contribute to the observed spread in accretion rates at a given mass. In addition, different accretion mechanisms (like, e.g., short-lived accretion bursts vs. more stable funnel-flow accretion) may be associated to different Ṁ_(acc) regimes. Conclusions. A huge variety of accretion properties is observed for young stellar objects in the NGC 2264 cluster. While a definite correlation seems to hold between mass accretion rate and stellar mass over the mass range probed here, the origin of the large intrinsic spread observed in mass accretion rates at any given mass remains to be explored.