Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive inexact Newton methods for discretizations of nonlinear diffusion PDEs. II. Applications

We consider nonlinear algebraic systems resulting from numerical discretizations of nonlinear partial differential equations of diffusion type. In order to solve them, some iterative nonlinear solver, and, on each step of this solver, some iterative linear solver are used. In Part I of this work, we have developed a general abstract framework hinging on equilibrated flux reconstructions to derive stopping criteria for both iterative solvers and to control the size and distribution of the overall approximation error. In this Part II, we apply this framework to various discretization schemes like finite elements, nonconforming finite elements, discontinuous Galerkin, finite volumes, and lowest-order mixed finite elements; to different linearizations like fixed point and Newton; and to arbitrary iterative linear solvers. This leads to new guaranteed and robust a posteriori error estimates for nonlinear diffusion problems in the presence of linearization and algebraic errors. Moreover, for many discretization schemes, we improve on, or derive new, flux equilibration techniques.
Longitudinal Study of Informed Consent in Innovative Therapy Research: Experience and Provisional Recommendations from a Multicenter Trial of Intracerebral Grafting

Background There is an urgent need to assess and improve the consent process in clinical trials of innovative therapies for neurodegenerative disorders. Methods We performed a longitudinal study of the consent of Huntington’s disease patients during the Multicenter Fetal Cell Intracerebral Grafting Trial in Huntington’s Disease (MIG-HD) in France and Belgium. Patients and their proxies completed a consent questionnaire at inclusion, before signing the consent form and after one year of follow-up, before randomization and transplantation. The questionnaire explored understanding of the protocol, satisfaction with the information delivered, reasons for participating in the trial and expectations regarding the transplant. Forty-six Huntington’s disease patients and 27 proxies completed the questionnaire at inclusion, and 27 Huntington’s disease patients and 16 proxies one year later. Results The comprehension score was high and similar for Huntington’s disease patients and proxies at inclusion (72.6% vs 77.8%; P > 0.1) but only decreased in HD patients after one year. The information satisfaction score was high (73.5% vs 66.5%; P > 0.1) and correlated with understanding in both patients and proxies. The motivation and expectation profiles were similar in patients and proxies and remained unchanged after one year. Conclusions Cognitively impaired patients with Huntington’s disease were capable of consenting to participation in this trial. This consent procedure has presumably strengthened their understanding and should be proposed before signing the consent form in future gene or cell therapy trials for neurodegenerative disorders. Because of the potential cognitive decline, proxies should be designated as provisional surrogate decision-makers, even in competent patients.
Draft Genome Sequences of 11 Staphylococcus epidermidis Strains Isolated from Wild Mouse Species

ABSTRACT We report here the draft genome sequences of 11 strains of Staphylococcus epidermidis, a common bacterium inhabiting the skin of humans and other animals. These isolates, obtained from five mouse species, provide valuable information on the native Staphylococcus spp. of this important model organism and form a basis for studying host-bacterial interactions in their natural environment.
Microanalysis in Music Therapy: Introduction and Theoretical basis

Abstract: In the context of music therapy, microanalysis is the detailed analysis of that short period of time during a music therapy session during which some kind of significant change takes place. These moments are crucial to the therapeutic process, and there is increasing interest amongst music therapists in understanding how they come about and whether there are ways of initiating them. The contributors to this groundbreaking book look at methods of micro process analyses used in a variety of music therapy contexts, both clinical and research-based. They outline their methods, which include using video and audio materials, interviewing, and monitoring the client's heart rate, and also give examples of the practical application of microanalysis from their clinical experience, including work with clients who have psychiatric illness, autism and other conditions. Microanalyses in Music Therapy provides a wealth of important theoretical and practical information for music therapy clinicians, educators and students.
Influence of Transportation Cost on Combinatorial Auctions

Although combinatorial auctions have been extensively studied, the factor of transportation cost for delivering goods from the seller to the winners (buyers) is ignored in most of the existing literature. The existence of transportation cost may not only influence decision making but also may lead to suboptimal solutions. Furthermore, ignoring transportation cost may result in discrepancy between the expected revenue and the actual revenue of the seller. Motivated by the discussion above, the goals of this paper are to propose a decision support model that considers transportation cost in combinatorial auctions, develop an associated solution methodology with and study the influence of transportation cost on combinatorial auctions. To achieve these goals, we propose two models for handling transportation cost in combinatorial auctions, one model considers transportation cost in determining the winners whereas the other does not take transportation cost into account in determining winners but calculates the transportation cost based on the solution obtained. We formulate the problems for these two models, develop solution algorithms and compare the two models by conducting an experiment based on our proposed algorithm.
Vanin-1 licenses inflammatory mediator production by gut epithelial cells and controls colitis by antagonizing peroxisome proliferator-activated receptor γ activity

Colitis involves immune cell–mediated tissue injuries, but the contribution of epithelial cells remains largely unclear. Vanin-1 is an epithelial ectoenzyme with a pantetheinase activity that provides cysteamine/cystamine to tissue. Using the 2,4,6-trinitrobenzene sulfonic acid (TNBS)-colitis model we show here that Vanin-1 deficiency protects from colitis. This protection is reversible by administration of cystamine or bisphenol A diglycidyl ether, a peroxisome proliferator-activated receptor (PPAR)γ antagonist. We further demonstrate that Vanin-1, by antagonizing PPARγ, licenses the production of inflammatory mediators by intestinal epithelial cells. We propose that Vanin-1 is an epithelial sensor of stress that exerts a dominant control over innate immune responses in tissue. Thus, the Vanin-1/pantetheinase activity might be a new target for therapeutic intervention in inflammatory bowel disease.
Secret Sharing vs . Encryption-based Techniques For Privacy Preserving Data Mining 1

Privacy preserving querying and data publishing has been studied in the context of statistical databases and statistical disclosure control. Recently, large-scale data collection and integration efforts increased privacy concerns which motivated data mining researchers to investigate privacy implications of data mining and how data mining can be performed without violating privacy. In this paper, we first provide an overview of privacy preserving data mining focusing on distributed data sources, then we compare two technologies used in privacy preserving data mining. The first technology is encryptionbased, and it is used in earlier approaches. The second technology is secret-sharing which is recently being considered as a more efficient approach.
Technology and Management in Mauritanian Cephalopod Fisheries

If the technology in a multi-species fishery is such that there is jointness in inputs and non-separability between inputs and outputs, then management on a species-by-species basis may lead to unintended outcomes, including over-exploitation of the resource. This study investigates the nature of the technical and economic relationships underlying the 1989-90 Mauritanian cephalopod fishery by estimating a system of dual output supply functions derived from a generalized Leontief revenue function. Model results indicate the existence of jointness in inputs and non-separability between inputs and outputs in the fishery. Cross-price elasticities indicated a number of substitute and complementary relationships, with these relationships changing in magnitude across years. Taken together, the results suggest that any attempts to economically manage the resource should be based on multi-product production theory, not single-species biological response functions. Besides ruling out single-species management, the dominance of substitute relationships in the Mauritanian cephalopod fishery precludes the use of "key species" management of the entire resource.
Exact clustering in linear time

The time complexity of data clustering has been viewed as fundamentally quadratic, slowing with the number of data items, as each item is compared for similarity to preceding items. Clustering of large data sets has been infeasible without resorting to probabilistic methods or to capping the number of clusters. Here we introduce MIMOSA, a novel class of algorithms which achieve linear time computational complexity on clustering tasks. MIMOSA algorithms mark and match partial-signature keys in a hash table to obtain exact, error-free cluster retrieval. Benchmark measurements, on clustering a data set of 10,000,000 news articles by news topic, found that a MIMOSA implementation finished more than four orders of magnitude faster than a standard centroid implementation.
Paleoclassical transport in low-collisionality toroidal plasmas

Radial electron heat transport in a low-collisionality, current-carrying resistive plasma confined in an axisymmetric toroidal magnetic field is hypothesized to be caused by the paleoclassical collisional processes of parallel electron heat conduction and radial magnetic-field diffusion. The electron distribution is Maxwellianized and the electron temperature equilibrated over a long length L (⪢ the poloidal periodicity half-length πR0q) along helical magnetic-field lines that are diffusing radially with the resistivity-induced magnetic-field diffusivity Dη≡η‖nc∕μ0≃νe(c∕ωp)2. This produces a paleoclassical radial electron heat diffusivity χepc that is a multiple M≃L∕(πR0q)∼10⪢1 of the magnetic-field diffusivity: χepc≃(3∕2)MDη. New paleoclassical model developments in this paper include full axisymmetric toroidal magnetic-field geometry, evolution of toroidal, poloidal, and helical magnetic fluxes, effects of temporally varying magnetic fluxes, introduction of electron guiding center radial diffusion effec.
Sequencing of tsunami waves: why the first wave is not always the largest

S U M M A R Y This paper examines the factors contributing to the ‘sequencing’ of tsunami waves in the far field, that is, to the distribution of the maximum sea surface amplitude inside the dominant wave packet constituting the primary arrival at a distant harbour. Based on simple models of sources for which analytical solutions are available, we show that, as range is increased, the wave pattern evolves from a regime of maximum amplitude in the first oscillation to one of delayed maximum, where the largest amplitude takes place during a subsequent oscillation. In the case of the simple, instantaneous uplift of a circular disk at the surface of an ocean of constant depth, the critical distance for transition between those patterns scales as r3 0 /h 2 where r0 is the radius of the disk and h the depth of the ocean. This behaviour is explained from simple arguments based on a model where sequencing results from frequency dispersion in the primary wave packet, as the width of its spectrum around its dominant period T0 becomes dispersed in time in an amount comparable to T0, the latter being controlled by a combination of source size and ocean depth. The general concepts in this model are confirmed in the case of more realistic sources for tsunami excitation by a finite-time deformation of the ocean floor, as well as in real-life simulations of tsunamis excited by large subduction events, for which we find that the influence of fault width on the distribution of sequencing is more important than that of fault length. Finally, simulation of the major events of Chile (2010) and Japan (2011) at large arrays of virtual gauges in the Pacific Basin correctly predicts the majority of the sequencing patterns observed on DART buoys during these events. By providing insight into the evolution with time of wave amplitudes inside primary wave packets for far field tsunamis generated by large earthquakes, our results stress the importance, for civil defense authorities, of issuing warning and evacuation orders of sufficient duration to avoid the hazard inherent in premature calls for all-clear.
Random matrix theory over finite fields: a survey

First we survey generating function methods for obtaining useful probability estimates about random matrices in the finite classical groups. Then we describe a probabilistic picture of conjugacy classes which is coherent and beautiful. Connections are made with symmetric function theory, Markov chains, potential theory, Rogers-Ramanujan type identities, quivers, and various measures on partitions.
An automatically-generated run-time instrumenter to reduce coverage testing overhead

Coverage testing is often used as a quantified measurement of testing progress. One important issue of code coverage testing is the overhead of program execution monitoring that inserts probes into programs, either at run-time or off-line, to record program execution code coverage information (e.g., "1" for covered and "0" for not-covered). For time sensitive systems, such overhead may alter the program execution behavior or impact its performance, which is an even more critical problem for embedded systems where memory and CPU resources are limited. This paper proposes a new Super Nested Block (SNB) method to reduce instrumentation run-time overhead. The method improves upon two existing technologies: 1) program analysis for selecting instrumentation points, and 2) on-line run-time instrumentation eliminating repeated probes. We implemented the SNB method on an automatic generated on-line instrumenter of a code coverage testing tool and found that the instrumentation overhead was minor, less than 1% of overall execution time, and all real-time execution external behaviors were preserved.
Automatic segmentation of basal ganglia iron deposits from structural MRI

Brain iron deposits have recently been suggested as biomarkers for small brain vessel diseases. Here, we present a novel, automated method for segmenting brain iron deposits in the basal ganglia from structural MRI data. It is based on minimum-variance clustering of intensities from T1and T2∗-weighted volumes, and a supervised cluster selection algorithm. This method was evaluated with MR data from 24 subjects and compared with iron deposit masks segmented manually by an experienced rater. A median Jaccard similarity index of 0.64 between manual and automatically generated segmentation masks is promising and encourages further investigations to improve the computing speed and accuracy of the method.
Assessing and Predicting Small-Group Literacy Instruction in Early Childhood Classrooms

ABSTRACT Research Findings: The present study assessed the extent to which early childhood educators utilized small-group literacy instruction and explored factors potentially associated with the use of this evidence-based practice. The classroom activities of 83 early childhood educators were observed in the fall and spring, and videos were coded to calculate time spent in small-group literacy instruction. Educators completed questionnaires indicating classroom adult:child ratios, literacy beliefs, and feelings of self-efficacy. Classroom Assessment Scoring System scores for classroom organization and instructional support measured the quality of classroom management and instructional interactions, respectively. On average, educators provided 11.4 min (SD = 10.6) of small-group literacy instruction a day. It is notable that many educators provided little or no small-group literacy instruction. Negative binomial regression analyses indicated that educators with better classroom management, higher quality instructional interactions, and lower adult:child ratios were more likely to use small-group literacy instruction. Educators’ beliefs and feelings of self-efficacy were not associated with the use of small-group literacy instruction. Practice or Policy: Educators may be better able to provide small-group literacy instruction in contexts affording low adult:child ratios and high levels of classroom management and instructional support, all of which are malleable factors that can be changed via policy or professional development.
Conditional Random Fields combined FSM stemming method for Uyghur

This paper presents the generation of Uyghur Noun Suffix DFA combined with Conditional Random Fields (CRF) for stemming algorithm. Because of the agglutinative nature of Uyghur language, stemming is an essential task for Uyghur language processing applications. We generate Uyghur noun inflectional suffixes finite state machines (FSMs) by using the morphotactic rules in reverse order. But there are eight suffixes which is similar to the ending part of some words. These suffixes make the FSM ambiguous. We apply the CRF model to resolve ambiguity of the FSM. This paper describes the steps of generating the FSM, building the CRF suffix identifying model and combination of CRF with FSM.
Overexpression of the Starch Phosphorylase-Like Gene (PHO3) in Lotus japonicus has a Profound Effect on the Growth of Plants and Reduction of Transitory Starch Accumulation

Two isoforms of starch phosphorylase (PHO; EC 2.4.1.1), plastidic PHO1 and cytosolic PHO2, have been found in all plants studied to date. Another starch phosphorylase-like gene, PHO3, which is an ortholog of Chlamydomonas PHOB, has been detected in some plant lineages. In this study, we identified three PHO isoform (LjPHO) genes in the Lotus japonicus genome. Expression of the LjPHO3 gene was observed in all tissues tested in L. japonicus, and the LjPHO3 protein was located in the chloroplast. Overexpression of LjPHO3 in L. japonicus resulted in a drastic decline in starch granule sizes and starch content in leaves. The LjPHO3 overexpression transgenic seedlings were smaller, and showed decreased pollen fertility and seed set rate. Our results suggest that LjPHO3 may participate in transitory starch metabolism in L. japonicus leaves, but its catalytic properties remain to be studied.
Using Prominence and Phrasing Predictions to Improve Weighted Dictionary Pronunciation Models

Prosody impacts the pronunciation of lexical items in a number of ways. Accented syllables tend to be pronounced with their canonical (dictionary) vowel. Deaccented vowels are more likely to be reduced. Coarticulatory influences rarely span intonational phrase boundaries. In this work, we investigate the use of automatically generated prosodic hypotheses to improve a weighted dictionary pronunciation model. We use the phonemically transcribed, Buckeye Corpus for this investigation. We find that predictions of pitch accent and intonational phrase boundaries can be used to lower pronunciation model perplexity.
An Expert System Based Process Control System for Silicon Steel Mill Furnace of Rourkela Steel Plant

An intriguing problem faced in Industrial Process Control is unavailability of exact mathematical co-relations, which can define the process behavior. Such cases are most appropriate application areas of Artificial Intelligence and more particularly Expert Systems. A close loop Expert System based heating control system has been developed for Decarburization-Annealing Furnace of Tandem Annealing Line at Silicon Steel Mill of Rourkela Steel Plant. The mill produces electrical grade steel used for various electrical and electromagnetic applications. One of the key factors responsible for achieving desired electromagnetic and mechanical quality of steel is selection of optimum temperature ranges inside the furnace and its accurate control. However exact co-relation, which can determine these temperature values for different steel grades, line speed and other steel sheet parameters are not known. The concepts of Expert System have been used to resolve this indeterminate issue of process control. The Expert System predicts most appropriate set temperatures for different zones of furnace based on steel grade, line speed and other steel coil parameters. The knowledge base and inference rules have been prepared utilizing years of experience and expertise of shop floor operation engineers, researchers and quality control agencies. To make it truly a close loop control, Expert System also configures the control function blocks of a Level-I automation PLC using COM based protocol "OPC". PLC controls the furnace temperature as per set points given by Expert System and communicates the actual process variables back to Expert System. The system has rendered significant improvement in plants performance with respect to improvement in product quality and reduction in energy consumption. It also exemplifies an Industrial demonstration of concepts of Artificial Intelligence for enhancing the efficiency of a plant.
Behavioural Biases and Contract Theory

This thesis studies how concepts of behavioural biases and bounded rationality affect classical results in contract theory and industrial organization. Chapter 2 studies the concept of naïveté (Strotz, 1956) in a principal agent model. Agents are assumed to be unaware of their true type, and form biased (naïve) beliefs about it. The latter depend on the actual type of the agent. Results show how the information about agents’ true nature, that can be elicited from their beliefs, plays a crucial role in the principal’s optimal contracting strategy. In particular, the principal faces a trade-off between exploiting the agent with the most naïve beliefs and designing efficient contracts for the most widespread type of agent, according to her posteriors. Chapter 3 and Chapter 4 analyse models where agents suffer from temptation and self-control problems (à la Gul and Pesendorfer, 2001). Chapter 3 presents a new justification for loyalty schemes in the retailing industry. In the literature, loyalty schemes have been mostly studied as competition devices (Caminal and Claici, 2007) or as ways to increase consumers’ lifetime value (Caminal, 2012). This work focuses on how a seller can use loyalty schemes to acquire information about consumers’ preferences and gain the ability to perform individual pricing. Finally, Chapter 4 presents a two-period mechanism design problem with no commitment. It shows how the presence of consumers that suffer from self-control problems can explain the existence of entry bonuses paid by the seller to the consumer, regardless of whether the latter makes the purchase or not.