Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization of Route of Administration for Coexposure to Ovalbumin and Particle Matter to Induce Adjuvant Activity in Respiratory Allergy in the Mouse

Epidemiological and experimental studies have not only shown that air pollution induces increased pulmonary morbidity, and mortality, but also that air pollution components may potentiate allergic responses. The respiratory allergy model to ovalbumin in the mouse has been shown a useful tool to characterize the adjuvant potency of air pollution components. However, the choice for the most effective route of administration for testing small amounts of air pollution component is hampered by the diversity of routes of administration used. To test the adjuvant activity of airborne particles (Ottawa dust EHC-93), we studied the optimal route of respiratory administration: intranasally (in) and aerosol (aero) in comparison with responses observed by intraperitoneal (ip) with diesel exhaust particles (DEP) as a positive control. Our results show that the combination of in/aero with ovalbumin caused almost similar immunoglobulin (Ig)E and inflammatory responses compared to the ip/aero. In/in application induced less responses for IgE, less inflammation in the lung, and less increased numbers of eosinophils in the bronchoalveolar lavage (BAL). This response increased dramatically when ovalbumin was coadministered with DEP. Subsequently, EHC-93, which is made up of airborne particles, was tested via the in/in route of administration. EHC-93 induced similar IgE responses, inflammation, and eosinophilic response in BAL compared to DEP. In addition, EHC-93 increased the airway responsiveness of the ovalbumin-sensitized mice measured in unrestrained condition and not in nonsensitized control mice. It is concluded that intranasal sensitization with intranasal challenge with airborne particles (EHC-93) is an effective route of administration to show potency of adjuvant activity of airborne particles.
Techniques for approximating a trigram language model

Several methods are proposed for reducing the size of a trigram language model (LM), which is often the biggest data structure in a continuous speech recognizer, without affecting its performance. The common factor shared by the different approaches is to select only a subset of the available trigrams, trying to identify those trigrams that mostly contribute to the performance of the full trigram LM. The proposed selection criteria apply to trigram contexts, both of length one or two. These criteria rely on information theory concepts, the back-off probabilities estimated by the LM, or on a measure of the phonetic/linguistic uncertainty relative to a given context. Performance of the reduced trigram LMs are compared both in terms of perplexity and recognition accuracy. Results show that all the considered methods perform better than the naive frequency shifting method. In fact, a 50% size reduction is obtained on a shift-1 trigram LM, at the cost of a 5% increase in word error rate. Moreover, the reduced LMs improve by around 15% the word error rate of a bigram LM of the same size.
Estimating the query difficulty for information retrieval

Many information retrieval (IR) systems suffer from a radical variance in performance when responding to users' queries. Even for systems that succeed very well on average, the quality of results returned for some of the queries is poor. Thus, it is desirable that IR systems will be able to identify "difficult" queries in order to handle them properly. Understanding why some queries are inherently more difficult than others is essential for IR, and a good answer to this important question will help search engines to reduce the variance in performance, hence better servicing their customer needs. The high variability in query performance has driven a new research direction in the IR field on estimating the expected quality of the search results, i.e. the query difficulty, when no relevance feedback is given. Estimating the query difficulty is a significant challenge due to the numerous factors that impact retrieval performance. Many prediction methods have been proposed recently. However, as many researchers observed, the prediction quality of state-of-the-art predictors is still too low to be widely used by IR applications. The low prediction quality is due to the complexity of the task, which involves factors such as query ambiguity, missing content, and vocabulary mismatch. The goal of this tutorial is to expose participants to the current research on query performance prediction (also known as query difficulty estimation). Participants will become familiar with states-of-the-art performance prediction methods, and with common evaluation methodologies for prediction quality. We will discuss the reasons that cause search engines to fail for some of the queries, and provide an overview of several approaches for estimating query difficulty. We then describe common methodologies for evaluating the prediction quality of those estimators, and some experiments conducted recently with their prediction quality, as measured over several TREC benchmarks. We will cover a few potential applications that can utilize query difficulty estimators by handling each query individually and selectively based on its estimated difficulty. Finally we will summarize with a discussion on open issues and challenges in the field.
Coordinating multi-layer MPC for complex water systems

In this paper, coordinating technique for the multi-layer model predictive control (MPC) of complex water network is proposed. A multi-layer topology structure resulting from a functional decomposition of water network is briefly presented. Inside each layer, a MPC based controller is used. Between the related two layers, a multi-layer coordinating mechanism is provided to generate control strategies which consider objectives and time scales of both layers. Optimal Path Method (OPM) is used to estimate aggregated water price for the whole layer. The case study is the Catalunya Regional Water Network. Simulation results based on an aggregate model of this network are provided.
Predictive and Prognostic Value of Von Willebrand Factor in Patients with Cirrhosis and Esophageal Varices

Background and study aim: Von Willebrand factor (vWF) is released by activated endothelial cells and plays a crucial role in the development of portal hypertension. vWF levels correlate with liver function and venous hepatic pressure gradient (VHPG) and independently predict clinical outcome. The aim was to evaluate serum vWF levels as a predictor for esophageal varices and prognosis in patients with liver cirrhosis. Patients and Methods: Sixty two patients with liver cirrhosis, divided into two groups according to presence (group I) or absence (group II) of varices were included, In addition, twenty healthy persons served as control group (group III). All patients were submitted to full history taking, clinical examination, laboratory investigations and abdominal ultrasonography. The severity of liver disease was estimated by Modified Child-Pugh and Model for End Stage Liver Disease (MELD) scores. All patients were underwent upper gastrointestinal endoscopy and vWF assay. Results: vWF values were significantly higher in group I (p1=0.001), than controls (p2=0.000), but no significant difference between group II and control group (p3= 0.59). Receiver operating characteristics (ROC) curve analysis of vWF revealed that, vWF at cutoff value of 173.8 µg/ml; the sensitivity for detection of esophageal varices was 80.8%, specificity 76.0%, positive predictive value (PPV) was 93.9%, negative predictive value (NPV) was 55.6%; area under the curve was 86.6. There was significant positive correlation between vWF and Child, MELD, esophageal varices grade and severity of portal hypertensive gastropathy. Conclusion: vWF is a good predictor for development of esophageal varices and correlated well with prognosis in patients with cirrhosis.
How Symbolic Learning Can Help Statistical Learning (and vice versa)

We describe in this paper how different learning strategies can be applied on the same NLP task, namely chunking. The reference corpus is extracted from the French Treebank, the symbolic learning strategy used is grammatical inference and the statistical one is CRFs (Conditional Random Fields). As expected, the symbolic approach allows readability but is less effective than the statistical one. We then propose two distinct ways to combine both approaches and show that in both cases they benefit from one another.
Shipborne solar absorption measurements of CO 2 , CH 4 , N 2 O and CO and comparison with SCIAMACHY WFM-DOAS retrievals

CO, CH 4 , N 2 O and CO 2 were retrieved from high resolution solar absorption spectra obtained during a ship cruise from Capetown to Bremerhaven in January/February 2003 by Fourier Transform Infrared (FTIR) spectroscopy. Precisions of better than 0.5% for the column averaged volume mixing ratios (VMR) of CH 4 and CO 2 are achieved using of O 2 as a reference gas. Shipborne FTIR-measurements of CO and data from SCIAMACHY/ENVISAT retrieved by the Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS) retrieval algorithm show qualitatively the same latitudinal variations. WFM-DOAS data of CH 4 , N 2 O and CO 2 measured over sea exhibit a great spread. The spread is significantly reduced for satellite measurements over land and a reasonable agreement can be obtained if the shipborne data are compared with the closest SCIAMACHY measurements over land. The number of comparisons is too small to draw conclusions. However, by including only WFM-DOAS data with small errors the shipborne and WFM-DOAS data compare within 5% for CH 4 and CO 2 and within 30% for N 2 O.
Terms extraction from unstructured data silos

The major challenge that the big data era brings to the services computing landscape is debris of unstructured data. The high-dimensional data is in heterogeneous formats, schemaless, and requires multiple storage APIs is some cases. This situation has made it almost impractical to apply existing data mining techniques which are designed for schema-based data sources in a knowledge discovery in database (KDD) process. In this paper, a tool called TouchR is proposed which algorithmically relies on the Hidden Markov Model (HMM) to extract terms from data silos; specifically, distributed NoSQL databases- which we model as network graph. Our use case graph consists of storage nodes such as CouchDB, Neo4J, DynamoDB etc. The evaluation of TouchR shows high accuracy for terms extraction and organization.
Endocrine Function in Thalassemia Intermedia

Thalassemias are the most common genetic disorder on a wordwide basis. β-thalassemia is a severe hemolytic anemia which results from genetic defects in the synthesis of the hemoglobin β-chain. Various endocrine abnormalities have been described in patients with thalassemia major. Endocrine disturbances have also been observed in patients with thalassemia intermedia (TI). In this study endocrine functions were investigated in TI and here the frequency of different abnormalities is reported. Ninety-three patients (40 males, 53 females) with thalassemia intermedia, 11-40 years old (mean 19.4 yr) were studied. Medical history was obtained and a complete physical examination was done for each patient. The age, sex, weight, height and serum ferritin levels were recorded using a questionnaire. Growth Hormone (GH) secretion, thyrotropin (TSH), T4, parathyroid hormone (PTH) and cortisole levels were determined in these patients. The mean ± Standard Deviation (SD) serum ferritin level was 452.4 ± 312.60 μg/L. Mean ± SD hemoglobin concentration was 9 ± 1 g/dl. Short stature was present in 46% of patients. Growth hormone deficiency was one of the most frequent (31%) endocrine abnormalities in these patients. Primary hypothyroidism was observed in 21.5% of patients. Hypoparathyroidism was found in one patient (1%). Failure of puberty was present in 2% of patients, secondary ammenorrhea was observed in 6.4% of patients and diabetes mellitus (DM) in 2% of patients. Conclusion: Growth retardation and GH deficiency should be considered as common finding in TI. Therefore endocrine evaluation of these patients is suggested to prevent complications and to improve the overall quality of life.
Dantrolene Inhibition of Sarcoplasmic Reticulum Ca2+Release by Direct and Specific Action at Skeletal Muscle Ryanodine Receptors*

The skeletal muscle relaxant dantrolene inhibits the release of Ca2+ from the sarcoplasmic reticulum during excitation-contraction coupling and suppresses the uncontrolled Ca2+ release that underlies the skeletal muscle pharmacogenetic disorder malignant hyperthermia; however, the molecular mechanism by which dantrolene selectively affects skeletal muscle Ca2+ regulation remains to be defined. Here we provide evidence of a high-affinity, monophasic inhibition by dantrolene of ryanodine receptor Ca2+ channel function in isolated sarcoplasmic reticulum vesicles prepared from malignant hyperthermia-susceptible and normal pig skeletal muscle. In media simulating resting myoplasm, dantrolene increased the half-time for45Ca2+ release from both malignant hyperthermia and normal vesicles approximately 3.5-fold and inhibited sarcoplasmic reticulum vesicle [3H]ryanodine binding (K i ∼150 nm for both malignant hyperthermia and normal). Inhibition of vesicle [3H]ryanodine binding by dantrolene was associated with a decrease in the extent of activation by both calmodulin and Ca2+. Dantrolene also inhibited [3H]ryanodine binding to purified skeletal muscle ryanodine receptor protein reconstituted into liposomes. In contrast, cardiac sarcoplasmic reticulum vesicle 45Ca2+ release and [3H]ryanodine binding were unaffected by dantrolene. Together, these results demonstrate selective effects of dantrolene on skeletal muscle ryanodine receptors that are consistent with the actions of dantrolene in vivo and suggest a mechanism of action in which dantrolene may act directly at the skeletal muscle ryanodine receptor complex to limit its activation by calmodulin and Ca2+. The potential implications of these results for understanding how dantrolene and malignant hyperthermia mutations may affect the voltage-dependent activation of Ca2+release in intact skeletal muscle are discussed.
Consensus-based Distributed Total Least-squares Estimation Using Parametric Semidefinite Programming

We propose a new distributed algorithm to solve the total least-squares (TLS) problem when data are distributed over a multi-agent network. To develop the proposed algorithm, named distributed ADMM TLS (DA-TLS), we reformulate the TLS problem as a parametric semidefinite program and solve it using the alternating direction method of multipliers (ADMM). Unlike the existing consensus-based approaches to distributed TLS estimation, DA-TLS does not require careful tuning of any design parameter. Numerical experiments demonstrate that the DA-TLS converges to the centralized solution significantly faster than the existing consensus-based TLS algorithms.
Magnetic Field Produced by a Parallelepipedic Magnet of Various and Uniform Polarization

This paper deals with the modeling of parallelepipedic magnets of various polarization directions. For this purpose, we use the coulombian model of a magnet for calculating the magnetic potential in all points in space. Then, we determine the three components of the magnetic fleld created by a parallepiped magnet of various polarization direction. These three components and the scalar magnetic potential are also expressed in terms of fully analytical terms. It is to be noted that the formulas determined in this paper are more general that the ones established in the literature and can be used for optimization purposes. Moreover, our study is carried out without using any simplifying assumptions. Consequently, these expressions are accurate whatever the magnet dimensions. This analytical formulation is suitable for the design of unconventional magnetic couplings, electric machines and wigglers.
Cooperative Intelligent Software Agents.

Abstract : The availability of network-based information sources and services, along with the wide use of of World Wide Web, presents a great opportunity for enhanced problem solving support that incorporates information gathering into the problem solving framework. The concept of an intelligent information agent has been explored for information accessing and filtering tasks (e.g., filtering of newsgroup information). To provide support for more complex tasks that involve information gathering along with decision making capabilities, an agent must communicate and cooperate with other agents. One of the main issues is how to structure a multi-agent architecture that will allow access, filtering and fusing of information from many sources and services, integrated with flexible decision support. In this paper we present such an architecture. It has two layers: The top layer consists of task-specific software agents which help users perform tasks by formulating problem solving plans and carrying out these plans through querying and exchanging information with other software agents. The bottom layer consists of information-specific agents which provide intelligent access to a heterogeneous collection of information sources. The layered architecture has been implemented in the domain of everyday organizational tasks (e.g., hosting visitors, finding information about persons on the internet, managing personal calendars) at Carnegie Mellon. We illustrate this architecture and the agent coordination protocols in the hosting visitor domain.
Building the genetic, agronomic and economic foundations for expansion of oat cultivation in western Washington

by Louisa Rosemarie Winkler, Ph.D. Washington State University May 2017 Chair: Kevin M. Murphy Oats (Avena sativa L.) are a versatile crop with diverse genetic resources. A study of population structure in a collection of oat genotypes relatively unaffected by recent breeding activity identified an under-utilized area of genetic diversity which could be a source of novel alleles for agronomic traits and disease resistance. Association mapping in the collection generates the first molecular evidence for genetic architecture of traits including awn frequency and hull color. The history of oats in western Washington reveals an evolution away from regional self-sufficiency and towards greater integration with national and global markets. Recently, growth of interest in and demand for local and regional agriculture are fostering a more purposeful approach to regionality, and will be integral to reinvented roles for oats in western Washington. One opportunity for oats is the milling (food) oat market. To address a lack of regionally specific information on production practices and variety choice, two years of oat variety tests were carried out on organic and conventional farms in four counties. Estimated revenues based on
Time-lapse imaging of self- and cross-pollinations in Brassica rapa.

BACKGROUND AND AIMS Pollination is an important process in the life cycle of plants and is the first step in bringing together the male and female gametophytes for plant reproduction. While pollination has been studied for many years, accurate knowledge of the morphological aspects of this process is still far from complete. This study therefore focuses on a morphological characterization of pollination, using time-series image analysis of self- and cross-pollinations in Brassica rapa. METHODS Time-lapse imaging of pollen behaviour during self- and cross-pollinations was recorded for 90 min, at 1 min intervals, using a stereoscopic microscope. Using time-series digital images of pollination, characteristic features of pollen behaviours during self- and cross-pollinations were studied. KEY RESULTS Pollen exhibited various behaviours in both self- and cross-pollinations, and these were classified into six representative patterns: germination, expansion, contraction, sudden contraction, pulsation and no change. It is noteworthy that in 'contraction' pollen grains shrunk within a short period of 30-50 min, and in 'pulsation' repeated expansion and contraction occurred with an interval of 10 min, suggesting that a dehydration system is operating in pollination. All of the six patterns were observed on an individual stigma with both self- and cross-pollinations, and the difference between self- and cross-pollinations was in the ratios of the different behaviours. With regard to water transport to and from pollen grains, this occurred in multiple steps, before, during and after hydration. Thus, pollination is regulated by a combination of multiple components of hydration, rehydration and dehydration systems. CONCLUSIONS Regulated hydration of pollen is a key process for both pollination and self-incompatibility, and this is achieved by a balanced complex of hydration, dehydration and nutrient supply to pollen grains from stigmatic papilla cells.
Progress in automatic meeting transcription

In this paper we report recent developments on the meeting transcription task, a large vocabulary conversational speech recognition task. Previous experiments showed this is a very challenging task, with about 50% word error rate (WER) using existing recognizers. The difficulty mostly comes from highly disfluent/conversational nature of meetings, and lack of domain specific training data. For the first problem, our SWB(Switchboard) system — a conversational telephone speech recognizer — was used to recognize wide-band meeting data; for the latter, we leveraged the large amount of Broadcast News (BN) data to build a robust system. This paper will especially focus on two experiments in the BN system development: model combination and HMM topology/duration modeling. Model combination can be done at various stages of recognition: post-processing schemes such as ROVER can lead to significant improvements; to reduce computation we tried model combination at acoustic score level. We will also show the importance of temporal constraints in decoding, present some HMM topology/duration modeling experiments. Finally, the meeting browser system and meeting room setup will be reviewed.