Miracle-dz/UniFAR-FTUs huggingface dataset:
Emergency Endotracheal Intubation in Pediatric Trauma

The purpose of this study was to determine the effectiveness and associated problems of emergency intubation in 605 injured infants and children admitted to the Children's Hospital of Pittsburgh in 1987. We identified 63 patients (10.4%) undergoing endotracheal intubation at the scene of injury, at a referring hospital or in our emergency department. Injuries were to the head (90.5%), abdomen (12.7%), face (11.1%), chest (6.3%), neck (3.2%); or were orthopedic (19%) or multiple (39.7%). Indications for intubation included coma (74.6%), shock (28.6%), apnea (22.2%), and airway obstruction (3.2%). Of 16 complications (25.4%), 13 were immediately life threatening: right mainstem intubation (5), massive barotrauma (2), failure of adequate preoxygenation (2), esophageal intubation (1), attempt at nasotracheal intubation in an open facial fracture (1), and extubation during transport (1). Three were late complications: vocal cord paresis (2) and subglottic stenosis (1). Airway complications led to PO2 less than 90 mm Hg in 7 of 12 on first ABG, compared to 9 of 44 in uncomplicated cases (p less than 0.05). Intubation attempts at the scene of injury were more often multiple, unsuccessful, and associated with airway complications. All four complication-associated fatalities were life-threatening scene complications. Nearly one half (44.4%, 28 of 63) had one of the following problems in respiratory management: major airway complication, PaO2 less than 90, or PaCO2 greater than 45 on either the first or second ABG after arrival at our emergency department. Head injury with coma is the most common setting for emergency intubation. Airway complications are common, and are more frequent in treatment attempt at the scene. Despite endotracheal intubation, injured children in our series remain at high risk for hypoxemia, elevated arterial PCO2, and major airway complications, all of which contribute to secondary brain injury.
Recent Evolutions of Multiple Sequence Alignment Algorithms

An ever-increasing number of biological modeling methods depend on the assembly of an accurate multiple sequence alignment (MSA). These include phylogenetic trees, profiles, and structure prediction. Assembling a suitable MSA is not, however, a trivial task, and none of the existing methods have yet managed to deliver biologically perfect MSAs. Many of the algorithms published these last years have been extensively described [1–3], and this review focuses only on the latest developments, including meta-methods and template-based alignment techniques.
Path building in cellular partitioning networks

This paper presents a new method of obtaining couplings in networks. We begin by introducing a new class of networks which are structural extensions of triangular permuting networks. More, by using augmented cells, we increase the functionnal capability of such networks. Then we present an algorithm to solve the problem of constructing a complete coupling in such networks. This algorithm lends itself to a hardware implementation with partially distributed control.
An Overview on Recent Medical Case-Based Reasoning Systems

Case-based reasoning systems for medical application are increasingly applied to meet the challenges from the medical domain. This paper looks at the state of the art in case-based reasoning and some systems are classified in this respect. A survey is performed based on the recent publications and research projects in CBR in medicine. Also, the survey is based on e-mail questionnaire to the authors’ to complete the missing property information. Some clear trends in recent projects/systems have been identified such as most of the systems are multi-modal, using a variety of different methods and techniques to serve multipurpose i.e. address more than one task.
A Two-grid Finite Di erenceScheme for Non-linear ParabolicEquationsC

We present a two level nite diierence scheme for the approximation of nonlinear parabolic equations. Discrete inner products and the lowest order Raviart-Thomas approximating space are used in the expanded mixed method in order to develop the nite diierence scheme. Analysis of the scheme is given assuming an implicit time discretization. In this two level scheme, the full nonlinear problem is solved on a \coarse" grid of size H: The nonlinearities are expanded about the coarse grid solution and an appropriate interpolation operator is used to provide values of the coarse grid solution on the ne grid in terms of superconvergent node points. The resulting linear but nonsymmetric system is solved on a \\ne" grid of size h: Some a priori error estimates are derived which show that the discrete L 1 (L 2) and L 2 (H 1) errors are O(h 2 + H 4? d=2 + t), where d 1 is the spatial dimension.
Molecular mechanisms of translation initiation in eukaryotes

Translation initiation is a complex process in which initiator tRNA, 40S, and 60S ribosomal subunits are assembled by eukaryotic initiation factors (eIFs) into an 80S ribosome at the initiation codon of mRNA. The cap-binding complex eIF4F and the factors eIF4A and eIF4B are required for binding of 43S complexes (comprising a 40S subunit, eIF2/GTP/Met-tRNAi and eIF3) to the 5′ end of capped mRNA but are not sufficient to promote ribosomal scanning to the initiation codon. eIF1A enhances the ability of eIF1 to dissociate aberrantly assembled complexes from mRNA, and these factors synergistically mediate 48S complex assembly at the initiation codon. Joining of 48S complexes to 60S subunits to form 80S ribosomes requires eIF5B, which has an essential ribosome-dependent GTPase activity and hydrolysis of eIF2-bound GTP induced by eIF5. Initiation on a few mRNAs is cap-independent and occurs instead by internal ribosomal entry. Encephalomyocarditis virus (EMCV) and hepatitis C virus epitomize distinct mechanisms of internal ribosomal entry site (IRES)-mediated initiation. The eIF4A and eIF4G subunits of eIF4F bind immediately upstream of the EMCV initiation codon and promote binding of 43S complexes. EMCV initiation does not involve scanning and does not require eIF1, eIF1A, and the eIF4E subunit of eIF4F. Initiation on some EMCV-like IRESs requires additional noncanonical initiation factors, which alter IRES conformation and promote binding of eIF4A/4G. Initiation on the hepatitis C virus IRES is even simpler: 43S complexes containing only eIF2 and eIF3 bind directly to the initiation codon as a result of specific interaction of the IRES and the 40S subunit.
Topological charges for branes in M-theory

We propose a simple form for the superalgebra of M2 and M5-brane probes in arbitrary supersymmetric backgrounds of 11d supergravity, extending previous results in the literature. In particular, we identify the topological charges in the algebras and find BPS bounds for the energies. The charges are given by the integral over a brane's spatial worldvolume of a certain closed form built out of the Killing spinors and background fields. The existence of such closed forms for arbitrary supersymmetric backgrounds generalises the existence of calibration forms for special holonomy manifolds.
EEF: Exponentially Embedded Families With Class-Specific Features for Classification

In this paper, we present a novel exponentially embedded families (EEF) based classification method, in which the probability density function (PDF) on raw data is estimated from the PDF on features. With the PDF construction, we show that class-specific features can be used in the proposed classification method, instead of a common feature subset for all classes as used in conventional approaches. We apply the proposed EEF classifier for text categorization as a case study and derive an optimal Bayesian classification rule with class-specific feature selection based on the Information Gain score. The promising performance on real-life data sets demonstrates the effectiveness of the proposed approach and indicates its wide potential applications.
A Way To Reduce The Artifacts Caused By Intensely Absorbing Areas In Computed Tomography

Artifacts caused by intensely absorbing areas are encountered in computed tomography and may obscure or simulate pathology in medical applications, hide or mimic the cracks and cavities in the devices at industrial applications. We simulated sinograms with different levels of absorption to demonstrate the artifacts dynamics. If the analysis of the measured data shows the presence of strongly absorbing areas in the object under study we propose to use quadratic programming technique for solving the inverse problem. Although the technique is time-consuming it allows us to avoid the typical artifacts. We compare the images reconstructed with different techniques including the proposed one.
Using Ensemble Models to Classify the Sentiment Expressed in Suicide Notes

In 2007, suicide was the tenth leading cause of death in the U.S. Given the significance of this problem, suicide was the focus of the 2011 Informatics for Integrating Biology and the Bedside (i2b2) Natural Language Processing (NLP) shared task competition (track two). Specifically, the challenge concentrated on sentiment analysis, predicting the presence or absence of 15 emotions (labels) simultaneously in a collection of suicide notes spanning over 70 years. Our team explored multiple approaches combining regular expression-based rules, statistical text mining (STM), and an approach that applies weights to text while accounting for multiple labels. Our best submission used an ensemble of both rules and STM models to achieve a micro-averaged F1 score of 0.5023, slightly above the mean from the 26 teams that competed (0.4875).
Is privacy compatible with truthfulness?

In the area of privacy-preserving data mining, a differentially private mechanism intuitively encourages people to share their data because they are at little risk of revealing their own information. However, we argue that this interpretation is incomplete because external incentives are necessary for people to participate in databases, and so data release mechanisms should not only be differentially private but also compatible with incentives, otherwise the data collected may be false. We apply the notion of truthfulness from game theory to this problem. In certain settings, it turns out that existing differentially private mechanisms do not encourage participants to report their information truthfully. On the positive side, we exhibit a transformation that takes truthful mechanisms and transforms them into differentially private mechanisms that remain truthful. Our transformation applies to games where the type space is small and the goal is to optimize an insensitive quantity such as social welfare. Our transformation incurs only a small additive loss in optimality, and it is computationally efficient. Combined with the VCG mechanism, our transformation implies that there exists a differentially private, truthful, and approximately efficient mechanism for any social welfare game with small type space. We also study a model where an explicit numerical cost is assigned to the information leaked by a mechanism. We show that in this case, even differential privacy may not be strong enough of a notion to motivate people to participate truthfully. We show that mechanisms that release a perturbed histogram of the database may reveal too much information. We also show that, in general, any mechanism that outputs a synopsis that resembles the original database (such as the mechanism of Blum et al. (STOC '08)) may reveal too much information.
Rewiring and regulation of cross-compartmentalized metabolism in protists

Plastid acquisition, endosymbiotic associations, lateral gene transfer, organelle degeneracy or even organelle loss influence metabolic capabilities in many different protists. Thus, metabolic diversity is sculpted through the gain of new metabolic functions and moderation or loss of pathways that are often essential in the majority of eukaryotes. What is perhaps less apparent to the casual observer is that the sub-compartmentalization of ubiquitous pathways has been repeatedly remodelled during eukaryotic evolution, and the textbook pictures of intermediary metabolism established for animals, yeast and plants are not conserved in many protists. Moreover, metabolic remodelling can strongly influence the regulatory mechanisms that control carbon flux through the major metabolic pathways. Here, we provide an overview of how core metabolism has been reorganized in various unicellular eukaryotes, focusing in particular on one near universal catabolic pathway (glycolysis) and one ancient anabolic pathway (isoprenoid biosynthesis). For the example of isoprenoid biosynthesis, the compartmentalization of this process in protists often appears to have been influenced by plastid acquisition and loss, whereas for glycolysis several unexpected modes of compartmentalization have emerged. Significantly, the example of trypanosomatid glycolysis illustrates nicely how mathematical modelling and systems biology can be used to uncover or understand novel modes of pathway regulation.
Improving Tumor Identification by Using Tumor Markers Classification Strategy

Tumor markers are substances, usually proteins that can be found in the blood, urine, stool, tumor tissue and more recently DNA changes, which are produced by the body in response to cancer growth. Thus far, more than 20 different tumor markers have been identified where some of them are specific for a particular type of cancer, while others are associated with several cancer types. The problem of tumor profiling has been extensively studied by the bioinformatics community. Although tumor classification has improved nowadays, there has been no general approach for identifying new cancer classes or for assigning tumors to known classes. In this paper we describe a novel strategy for tumor classification by using Growing Hierarchical Self-Organizing map (GHSOM) since it is able to weigh the contribution of each marker according to its relatedness with other tumor markers as well as handles highly skewed tumor marker expressions well. In the end, experiments are conducted to further demonstrate the feasibility and efficiency of tumor classification approach which provide valuable contribution in the field of oncology and cancer diseases and will be as a guide for the identification of these diseases.
Prediction of Forest Vegetation Shift due to Different Climate-Change Scenarios in Slovenia

By using an empirical GIS model, the potential spatial changes of forest vegetation driven by expected climate change have been analysed. Based on the three different scenarios predicting climate warming in Slovenia (the mean, pessimistic and optimistic scenarios), the simulation showed that the share of vegetation types will be altered under the impacts of climate change, and the shift of vegetation belts upwards might be expected. By the year 2100, the share of mesic beech forests is likely to decrease. From ecological, – nature-conservation – and forest-management points of view, the predicted decrease of the share of Dinaric fir-beech forests is especially important. The model predicts an increase of the share of thermophilous forests from the present 14% to a range between 50% (according to the optimistic scenario) and 87% (according to the pessimistic scenario). A significant part of the coniferous forest with Picea abies and Abies alba predominating might be converted to deciduous forests. K e y w o rd s : climate change, forest vegetation, model, simulation, climate scenarios
Sudden Infant Death Syndrome and the time of death: factors associated with night-time and day-time deaths.

OBJECTIVE To investigate the diurnal occurrence of Sudden Infant Death Syndrome (SIDS) and interaction with established risk factors in the infant sleeping environment. METHODS A 3 year population-based case-control study, in five English Health Regions. Parentally defined day-time or night-time deaths of 325 SIDS infants and reference sleep of 1300 age-matched controls. RESULTS The majority of SIDS deaths (83%) occurred during night-time sleep, although this was often after midnight and at least four SIDS deaths occurred during every hour of the day. The length of time from last observed alive until the discovery of death ranged from <l to 14 h but was not significantly different from the corresponding sleep period amongst the controls. Amongst the day-time deaths, 38% of the infants were observed alive 30 min prior to discovery and 9% within 10 min. The risk of placing infants asleep on their side was more marked for day-time deaths (interaction: P = 0.0001) nearly half of whom were found prone, while the risk associated with paternal smoking [OR = 3.25 (95%CI: 1.88-5.62)] was more marked for night-time deaths (interaction: P = 0.02). The adverse effect of unsupervised sleep recognized for night-time practice [OR = 5.38 (95%CI: 2.67-10.85)] was also significant for day-time sleep [OR = 10.57 (95%CI: 1.47-75.96)]. Significantly more (P = 0.002) unobserved SIDS infants (24.8%) were found with bedclothes over the head compared with those SIDS infants where a parent was present in the room (11.3%). CONCLUSIONS SIDS can happen at any time of the day and relatively quickly. Parents need to be made aware that placing infants supine and keeping them under supervision is equally important for day-time sleeps.
Vision-Based Detection and Distance Estimation of Micro Unmanned Aerial Vehicles

Detection and distance estimation of micro unmanned aerial vehicles (mUAVs) is crucial for (i) the detection of intruder mUAVs in protected environments; (ii) sense and avoid purposes on mUAVs or on other aerial vehicles and (iii) multi-mUAV control scenarios, such as environmental monitoring, surveillance and exploration. In this article, we evaluate vision algorithms as alternatives for detection and distance estimation of mUAVs, since other sensing modalities entail certain limitations on the environment or on the distance. For this purpose, we test Haar-like features, histogram of gradients (HOG) and local binary patterns (LBP) using cascades of boosted classifiers. Cascaded boosted classifiers allow fast processing by performing detection tests at multiple stages, where only candidates passing earlier simple stages are processed at the preceding more complex stages. We also integrate a distance estimation method with our system utilizing geometric cues with support vector regressors. We evaluated each method on indoor and outdoor videos that are collected in a systematic way and also on videos having motion blur. Our experiments show that, using boosted cascaded classifiers with LBP, near real-time detection and distance estimation of mUAVs are possible in about 60 ms indoors (1032×778 resolution) and 150 ms outdoors (1280×720 resolution) per frame, with a detection rate of 0.96 F-score. However, the cascaded classifiers using Haar-like features lead to better distance estimation since they can position the bounding boxes on mUAVs more accurately. On the other hand, our time analysis yields that the cascaded classifiers using HOG train and run faster than the other algorithms.
Health Belief Model and Healer Choice in a Medically Pluralistic Society: A Study on Urban Youths

The choice of a healer in a medically pluralistic society is a complex process. This paper examined the usefulness of Health Belief Model (HBM) and other confounding factors in determining healer choice of the urban youths and tested four components of HBM in relation to socio-demographic characteristics and preferred treatment mode of the respondents. The study revealed that socio-demographic characteristics - sex, years of schooling, household income, marital status, occupation, listening to radio, watching television have been found significantly associated with preferred treatment choice of the respondents. Perceived Severity is moderately associated with the preferred treatment mode (p<0.05). In addition, respondents with higher levels of education and income are more likely to have higher levels of Perceived Susceptibility, Severity and Benefits. The study findings indicate that youths with greater economic vulnerability tend to choose traditional healer for receiving treatment. Background Adolescents and youths comprise the biggest segment of the population of Bangladesh. Nearly one-third (32%) of the country's population is composed of adolescents and youth (10-24 years) (BBS, 2008). Despite this huge population of this category very little is known about their treatment choice behaviour. The choice of a healer in a medically pluralistic society is a complex process. It depends on a great variety of conditions such as the severity of the disease, patient’s perceived risk of the disease, relative proximity of the healer, cost of health care, transportation facilities, gender of the patient, patient’s attitude toward different systems of medicine, past experience of the patients, perception on illness, belief system on disease causation and the like (Helman, 1995; Kleinman, 1980; Ahmed, F.H. et. al., 2010). Every society has its own beliefs and practices regarding health and disease. Perception of illness, customs and practices shape and direct health seeking behaviour of the community. Socio-cultural pattern of the community is one of the major factors towards the availability and use of different kinds of treatment. Health and disease are related to sociological and cultural resources of a community in a specific environment. The treatment of disease in any particular society depends on the world view of the people concerned- it is directly related to the attitude of the general public in respect of looking at the universe.
Let’s Twist Again: A High-Frequency Event-Study Analysis of Operation Twist and Its Implications for QE2

This paper undertakes a modern event-study analysis of Operation Twist and uses its estimated effects to assess what should be expected for the recent policy of quantitative easing by the Federal Reserve, dubbed “QE2. ” The paper first shows that Operation Twist and QE2 are similar in magnitude. It then identifies six significant, discrete announcements in the course of Operation Twist that could have had a major effect on financial markets and shows that four did have statistically significant effects. The cumulative effect of these six announcements on longer-term Treasury yields is highly statistically significant but moderate, amounting to about 15 basis points (bp). This estimate is consistent both with time-series analysis undertaken not long after the event and with the lower end of empirical estimates of Treasury supply effects in the literature. The effects of Operation Twist on long-term agency and corporate bond yields are also statistically significant but smaller, about 13 bp for agency securities and 2 to 4 bp for corporates. Thus, the effects of Operation Twist seem to diminish substantially as one moves from Treasury securities toward private sector credit instruments.