Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of impermeable covers for bedding in patients with allergic rhinitis.

BACKGROUND Encasing bedding in impermeable covers reduces exposure to house-dust mites, but the clinical benefit of this intervention as part of mite-avoidance measures for patients with allergic rhinitis is not known. We performed a multicenter, randomized, placebo-controlled trial of one year of use of impermeable bedding covers in the bedrooms of patients with rhinitis who were sensitized to house-dust mites to determine the effects on the signs and symptoms of disease. METHODS Three participating university medical centers enrolled 279 patients with allergic rhinitis who were randomly assigned to receive impermeable or non-impermeable (control) covers for their mattress, pillow, and duvet or blanket. At the start of the study, all participants received information on general allergen-avoidance measures. The severity of rhinitis was measured on a rhinitis-specific visual-analogue scale and by means of a daily symptom score and nasal allergen provocation testing. We also measured the concentrations of Dermatophagoides pteronyssinus (Der p1) and D. farinae (Der f1) in dust from patients' mattresses, bedroom floors, and living-room floors at base line and after 12 months as a measure of the efficacy of the intervention. RESULTS A total of 232 patients completed the study. There was a significant reduction in Der p1 and Der f1 concentrations in the mattresses of the impermeable-cover group, whereas there was no significant reduction in the control group. However, there was no significant effect on the clinical outcome measures. Analyses of subgroups defined according to age, level of exposure, type and severity of sensitization, or characteristics of the patient's home had similar results. CONCLUSIONS Mite-proof bedding covers, as part of a structured allergy-control program, reduced the level of exposure to mite allergens. Despite the success of the intervention, this single avoidance measure did not lead to a significant improvement of clinical symptoms in patients with allergic rhinitis.
Depression patient robot for diagnostic training in psychiatric education

In this paper, a depression patient robot by using the android robot SAYA is proposed as a practical application of android robot technologies. The purpose of the patient robot is to offer reproducible and realistic education and training to psychiatrist trainees. In particular, the patient robot treats unipolar depression, which is a typical psychiatric disease. The robot exhibits symptoms of unipolar depression by exploiting its communicative functions such as facial expressions, eye and head movements, and distinctive speech. In an interview with a psychiatrist, the robot's communicative functions are controlled by remote control, and the interview progresses according to a diagnosis scenario that was previously prepared. To evaluate its repeatability and educational effects, a field experiment was conducted in psychiatric education field.
Financial Globalisation and Exchange Rates

The founders of the Bretton Woods System sixty years ago were primarily concerned with orderly exchange rate adjustment in a world economy that was characterized by widespread restrictions on international capital mobility. In contrast, the rapid pace of financial globalization during recent years poses new challenges for the international monetary system. In particular, large gross cross-holdings of foreign assets and liabilities means that the valuation channel of exchange rate adjustment has grown in importance, relative to the traditional trade balance channel. Accordingly, this paper empirically explores some of the inter-connections between financial globalization and exchange rate adjustment and discusses the policy implications. Classification-
Treatment with Ca 2 1 ionophore improves embryo development and outcome in cases with previous developmental problems : a prospective multicenter study

T. Ebner1,2,*, P. Oppelt1,2, M. Wöber3, P. Staples4, R.B. Mayer1,2, U. Sonnleitner5, S. Bulfon-Vogl6, I. Gruber7, A.E. Haid1,2, and O. Shebl1,2 Department of Gynecological Endocrinology and Kinderwunsch Zentrum, Landes-Frauen-und Kinderklinik, Krankenhausstr. 26-30, A-4020 Linz, Austria Faculty of Medicine, Johannes Kepler University, 4020 Linz, Austria Kinderwunschzentrum Goldenes Kreuz, 1090 Vienna, Austria Medical University, 8010 Graz, Austria Babywunsch-Klinik Dr. Zajc, 5020 Salzburg, Austria Sterignost, Institut für Kinderwunschbehandlung, 9020 Klagenfurt, Austria Kinderwunschambulanz im Landesklinikum St Pölten, 3100 St Pölten, Austria
Growth Opportunities, Short-Term Market Pressure, and Dual-Class Share Structure

We test the hypothesis that dual-class shares can help managers focus on the implementation of long-term projects while avoiding short-term market pressure. Consistent with this idea, we find that dual-class firms face lower short-term market pressure (fewer transient or short-term institutional holdings, a lower probability of being taken over, and lower analyst coverage) than propensity-matched single-class firms. Dual-class firms also tend to have more growth opportunities (higher sales growth and R&D intensity). The dual-class share structure increases the market valuation of high growth firms, in contrast to the finding in the literature that dual-class firms trade at lower valuations. To address endogeneity concerns, we evaluate a sample of dual-class share unifications and find that growth opportunities decline while short-term market pressure increases after share unifications.
An improved IRLS algorithm with double-threshold sigmoid penalty

The thresholding methods based on the generalized IRLS iteration are discussed under the complex-valued condition in this paper. An improved IRLS algorithm with double-threshold sigmoid (DTHS) penalty are proposed herein. It is shown that the generalized IRLS algorithm is unbiased if the thresholding penalty can eliminate the undesired perturbation term added on the correlation matrix of the measurement matrix. The test show that the new algorithms are endowed with stability and insensitivity with respect to the regularization parameter by selecting some sound upper thresholds, which can eliminate the undesired perturbation term added on the correlation matrix of the measurement matrix. Further analyses show that the DTHS-1 algorithm is suitable to deal with both of the sparse and continuous problems for the i.i. d random. The noise performance of the DTHS-1 algorithm is always superior to that of the IRLS algorithm.
A Non Quasi-static Small Signal Model for Long Channel Symmetric DG MOSFET

We propose a compact model for small signal non quasi static analysis of long channel symmetric double gate MOSFET. The model is based on the EKV formalism and is valid in all regions of operation and thus suitable for RF circuit design. Proposed model is verified with professional numerical device simulator and excellent agreement is found well beyond the cut-off frequency.
Generation of dynamic process models for multi-metamodel applications

Multi-metamodel application development processes have to deal with specific needs including flexible support for structured artifacts like models, multi-layered modeling support and dynamic process updates. In order to deal with the requirements of dynamic process updates and multi-layered modeling support, we propose to model the processes in multiple abstraction levels. The use of conditions on structured artifacts, considered as models, allows enhanced activity interactions, specifically for iterative interactions. This endeavor presented as CAMA Process Modeling Framework (CPMF) counts towards the greater goal of automation of software development processes in the future.
The Chd1 chromatin remodeler shifts hexasomes unidirectionally

Despite their canonical two-fold symmetry, nucleosomes in biological contexts are often asymmetric: functionalized with post-translational modifications (PTMs), substituted with histone variants, and even lacking H2A/H2B dimers. Here we show that the Widom 601 nucleosome positioning sequence can be used to produce hexasomes in a specific orientation on DNA, which provide a useful tool for interrogating chromatin enzymes and allow for the generation of precisely defined asymmetry in nucleosomes. Using this methodology, we demonstrate that the Chd1 chromatin remodeler requires H2A/H2B on the entry side for sliding, and thus, unlike the back-and-forth sliding observed for nucleosomes, Chd1 shifts hexasomes unidirectionally. Chd1 takes part in chromatin reorganization surrounding transcribing RNA polymerase II (Pol II), and using asymmetric nucleosomes we show that ubiquitin-conjugated H2B on the entry side stimulates nucleosome sliding by Chd1. We speculate that biased nucleosome and hexasome sliding due to asymmetry contributes to the packing of arrays observed in vivo.
Unbundling the Effects of Reforms By

This paper investigates the effects of financial and trade reforms on manufacturing output performance in a large sample of developed and developing countries. To identify the channels through which reforms affect economic performance and to address endogeneity concerns, we estimate differential effects of reforms across various industries. We find that financial and trade reforms impact manufacturing output in a way that is consistent with standard theories of finance and trade. Specifically, reforms of the financial sector improve the efficiency of intermediation by reallocating capital towards sectors that need it most, and contribute in improving countries’ resilience to external shocks. Trade reforms foster output growth in export sectors that rely more intensively on imported intermediated goods. We also find that trade and financial sector reforms are more effective in countries with a better protection of property right. Our results are consistent across different empirical approaches. 1 Thierry Tressel in an Economist in the Research Department of the International Monetary Fund (email: ttressel@imf.org). Patricio Aros Valenzuela provided excellent research assistance in helping prepare the database.
An In Vivo Immunotherapy Screen of Costimulatory Molecules Identifies Fc-OX40L as a Potent Reagent for the Treatment of Established Murine Gliomas

Purpose: We tested the combination of a tumor lysate vaccine with a panel of costimulatory molecules to identify an immunotherapeutic approach capable of curing established murine gliomas. Experimental Design: Glioma-bearing mice were primed with a tumor lysate vaccine, followed by systemic administration of the following costimulatory ligands: OX40L, CD80, 4-1BBL, and GITRL, which were fused to the Fc portion of human immunoglobulin. Lymphocytes and mRNA were purified from the brain tumor site for immune monitoring studies. Numerous variations of the vaccine and Fc-OX40L regimen were tested alone or in combination with temozolomide. Results: Lysate vaccinations combined with Fc-OX40L led to the best overall survival, yielding cure rates of 50% to 100% depending on the timing, regimen, and combination with temozolomide. Cured mice that were rechallenged with glioma cells rejected the challenge, showing immunologic memory. Lymphocytes isolated from the draining lymph nodes of vaccine/Fc-OX40L–treated mice had superior tumoricidal function relative to all other groups. Vaccine/Fc-OX40L–treated mice exhibited a significant increase in proliferation of brain-infiltrating CD4 and CD8 T cells, as indicated by Ki67 staining. Fc-OX40L had single-agent activity in transplanted and spontaneous glioma models, and the pattern of inflammatory gene expression in the tumor predicted the degree of therapeutic response. Conclusions: These data show that Fc-OX40L has unique and potent activity against experimental gliomas and warrants further testing. Clin Cancer Res; 18(17); 4657–68. ©2012 AACR.
The flow fields involved in hydrodynamic imaging by blind Mexican cave fish (Astyanax fasciatus). Part I: open water and heading towards a wall

SUMMARY Blind Mexican cave fish (Astyanax fasciatus) sense the presence of nearby objects by sensing changes in the water flow around their body. The information available to the fish using this hydrodynamic imaging ability depends on the properties of the flow field it generates while gliding and how this flow field is altered by the presence of objects. Here, we used particle image velocimetry to measure the flow fields around gliding blind cave fish as they moved through open water and when heading towards a wall. These measurements, combined with computational fluid dynamics models, were used to estimate the stimulus to the lateral line system of the fish. Our results showed that there was a high-pressure region around the nose of the fish, low-pressure regions corresponding to accelerated flow around the widest part of the body and a thick laminar boundary layer down the body. When approaching a wall head-on, the changes in the stimulus to the lateral line were confined to approximately the first 20% of the body. Assuming that the fish are sensitive to a certain relative change in lateral line stimuli, it was found that swimming at higher Reynolds numbers slightly decreased the distance at which the fish could detect a wall when approaching head-on, which is the opposite to what has previously been expected. However, when the effects of environmental noise are considered, swimming at higher speed may improve the signal to noise ratio of the stimulus to the lateral line.
LOCATION-CONSTRAINED PARTICLE FILTER FOR RSSI-BASED INDOOR HUMAN POSITIONING AND TRACKING SYSTEM

This paper proposes a Location-Constrained Particle Filter (LC-PF) for Radio Signal Strength Indication (RSSI) based indoor localization system. Based on proposed LC-PF, the RSSI fluctuation problem can be restrained. The proposed methods include locationconstrained importance weight updating (LC-WU) and location-constrained propagation model (LC-model). LC-WU eliminates particles in prohibited regions based on the geolocation of the map. The LC-model propagates particles based on different turning probabilities in different regions. These two methods can be applied separately or jointly. The proposed LC-PF has 2.48m average accuracy improvement over basic PF with 68% error reduction, and results in 2.07m accuracy with 90% confidence.
Arginine Cofactors on the Polymerase Ribozyme

The RNA world hypothesis states that the early evolution of life went through a stage in which RNA served both as genome and as catalyst. The central catalyst in an RNA world organism would have been a ribozyme that catalyzed RNA polymerization to facilitate self-replication. An RNA polymerase ribozyme was developed previously in the lab but it is not efficient enough for self-replication. The factor that limits its polymerization efficiency is its weak sequence-independent binding of the primer/template substrate. Here we tested whether RNA polymerization could be improved by a cationic arginine cofactor, to improve the interaction with the substrate. In an RNA world, amino acid-nucleic acid conjugates could have facilitated the emergence of the translation apparatus and the transition to an RNP world. We chose the amino acid arginine for our study because this is the amino acid most adept to interact with RNA. An arginine cofactor was positioned at ten different sites on the ribozyme, using conjugates of arginine with short DNA or RNA oligonucleotides. However, polymerization efficiency was not increased in any of the ten positions. In five of the ten positions the arginine reduced or modulated polymerization efficiency, which gives insight into the substrate-binding site on the ribozyme. These results suggest that the existing polymerase ribozyme is not well suited to using an arginine cofactor.
Trust and Other Factors that Drive Students’ Self-Disclosure on Social Networking Sites (SNSs)

The aim of this study is to examine the factors that drive students’ self-disclosure on Social Networking Sites (SNSs). A total of 215 undergraduates from two public universities in East Malaysia were recruited as respondents. This study adapts self-disclosure model by Elmi, A.Iahad and Ahmed (2012), where the model proposed trust as one of the factors that complementing other existing factors in online self-disclosure. This study proved that privacy concerns (r = -.212, p < .01), perceived trust (r = .22, p < .01), perceived ease of use (r = .213, p < .01), and perceived enjoyment (r = .28, p < .01) are significantly related to students’ online self-disclosure on SNSs. In addition, as trust plays a vital role in moderating the users’ online self-disclosure behavior, this study formulated students’ trusts on SNSs based on three dimensions which are individual, institutional and online trust. Findings of study suggested that there is a significant difference between online trust based on male and female respondents.Keywords: Formulation of trust, online self-disclosure, privacy concern, perceived ease of use, perceived enjoyment, perceived trust
ElectroMagnetic analysis (EMA) of software AES on Java mobile phones

Smartphones, whose market share has increased by 54% between 2009 and 2010, is one of the favored platform for “Convergence Computing”. Convergence Computing is a technology in which a single device can provide various services without any restrictions from external devices or networks. Today, smartphones as convergent single device have diverse functions and features such as calling, Internet surfing, game playing, banking, storage of personal and professional data, etc. Some of these use encryption algorithms such as AES (Advanced Encryption Standard). For example, this algorithm is used to authenticate server protocols or to encrypt confidential information. This paper shows that an Electromagnetic Analysis (EMA) on AES is possible on a Java mobile phone to extract secret keys. The latter can then be used for forensic purposes or to recover encrypted data stored in the device. Experiments involving two successful approaches are described and compared: Spectral Density based Approach (SDA) and Template based Resynchronisation Approach (TRA).
The SWO Project: A Case Study for Applying Agile Ontology Engineering Methods for Community Driven Ontologies

The Software Ontology Project (SWO) is a community effort to build an ontology that models software used in the generation and analy- sis of data for curation and preservation purposes in areas such as biomedicine. In community driven efforts, requirements are elicited from the members of these communities to help ensure the ontology is fit for purpose. This requires methods which are able to engage with users with a wide range of expertise, allow close collaboration between developers and users and that are able to respond rapidly to changing knowledge. We describe an Agile Ontology Engineering method for developing ontologies, adapted from modern Agile softw- are engineering methods. The approach was applied within the SWO project and demonstrated promising results in engaging a diverse set of community representatives and an objective measure of ontology success, of much relevance to the active community of bio-ontology developers and users.
Who caught a cold ? - Identifying the subject of a symptom

The development and proliferation of social media services has led to the emergence of new approaches for surveying the population and addressing social issues. One popular application of social media data is health surveillance, e.g., predicting the outbreak of an epidemic by recognizing diseases and symptoms from text messages posted on social media platforms. In this paper, we propose a novel task that is crucial and generic from the viewpoint of health surveillance: estimating a subject (carrier) of a disease or symptommentioned in a Japanese tweet. By designing an annotation guideline for labeling the subject of a disease/symptom in a tweet, we perform annotations on an existing corpus for public surveillance. In addition, we present a supervised approach for predicting the subject of a disease/symptom. The results of our experiments demonstrate the impact of subject identification on the effective detection of an episode of a disease/symptom. Moreover, the results suggest that our task is independent of the type of disease/symptom.
Determining car-park occupancy from single images

We propose a system to estimate the occupancy of a car-park using a single image of a single camera. Very often car-parks are already equipped with CCTV-cameras for surveillance purposes which may be used for automatic detection systems as well. Our system is targeted on cases where occupancy values are sought, but exact solutions like automatic gates or induction loops are too costly and where estimate values are acceptable for the operator. The image processing for the vehicle classification basically works by constructing a reference image of the empty car-park given in the input image and then comparing those two. The occupancy estimate is determined by the vehicle to car-park pixel area ratio, where perspective distortion and occlusion is compensated.
Comparison of different imputation methods from low- to high-density panels using Chinese Holstein cattle

Imputation of high-density genotypes from low- or medium-density platforms is a promising way to enhance the efficiency of whole-genome selection programs at low cost. In this study, we compared the efficiency of three widely used imputation algorithms (fastPHASE, BEAGLE and findhap) using Chinese Holstein cattle with Illumina BovineSNP50 genotypes. A total of 2108 cattle were randomly divided into a reference population and a test population to evaluate the influence of the reference population size. Three bovine chromosomes, BTA1, 16 and 28, were used to represent large, medium and small chromosome size, respectively. We simulated different scenarios by randomly masking 20%, 40%, 80% and 95% single-nucleotide polymorphisms (SNPs) on each chromosome in the test population to mimic different SNP density panels. Illumina Bovine3K and Illumina BovineLD (6909 SNPs) information was also used. We found that the three methods showed comparable accuracy when the proportion of masked SNPs was low. However, the difference became larger when more SNPs were masked. BEAGLE performed the best and was most robust with imputation accuracies >90% in almost all situations. fastPHASE was affected by the proportion of masked SNPs, especially when the masked SNP rate was high. findhap ran the fastest, whereas its accuracies were lower than those of BEAGLE but higher than those of fastPHASE. In addition, enlarging the reference population improved the imputation accuracy for BEAGLE and findhap, but did not affect fastPHASE. Considering imputation accuracy and computational requirements, BEAGLE has been found to be more reliable for imputing genotypes from low- to high-density genotyping platforms.