Miracle-dz/UniFAR-FTUs huggingface dataset:
Inhalation Injury, Pulmonary Perturbations, and Fluid Resuscitation

Inhalation injury (INHI) associated with thermal injury has been shown to increase the rate of mortality. Several investigators have shown that patients with inhalation and burn injuries will require increased fluid volumes during acute resuscitation when compared with patients with burn injury alone. Other groups have examined the use of lung compliance and airway resistance as predictors of outcome in patients with INHI. We hypothesized that increased fluid requirements would more closely correlate with perturbations in pulmonary performance than with mere presence or absence of INHI or the degree of injury by bronchoscopic criteria. We performed a retrospective chart review during a period of 3 years. We identified 80 patients with suspected INHI that required intubation, mechanical ventilation, and fiber optic bronchoscopy in the first 24 hours of their admission. Variables collected included age, sex, weight and %TBSA burned, as well as blood alcohol level, the presence of head and neck burns and escharotomies, and admission carbon monoxide levels. Patients were classified into five groups according to a grading system of INHI (0, 1, 2, 3, and 4), derived from findings at initial bronchoscopy and based on AIS criteria. The following pulmonary parameters were noted at regular intervals: mode of ventilation, tidal volume, peak inspiratory pressures, mean airway pressures, and compliance. The P:F ratio also was recorded at regular intervals. Total fluid volume infused was noted at 0-, 24-, and 48-hour intervals, and was calculated as ml/kg/%TBSA. Outcomes were measured by in-hospital survival, ventilator days, intensive care unit days, and total length of stay. Patients were well matched for %TBSA among the different bronchoscopic grades of INHI, and those with grades 2, 3, and 4 injuries had a significantly worse survival than those with grades 0 or 1 (P = .03). However, grades 2, 3, and 4 did not have increased acute fluid requirements when compared with grades 1 and 2 injuries. Initial pulmonary compliance likewise did not correlate with acute fluid requirements. However, those patients with a P:F ratio less than 350 at presentation had a statistically significant increase in ml/kg/%TBSA compared with those with P:F >350 (P = .03). They did not have more ventilator days or a statistically worse survival. Fiber optic bronchoscopy is useful in the diagnosis of INHI, and overall survival is worse in those patients with worse grades of injury by bronchoscopic criteria. However, the P:F ratio may be a more accurate predictor of increased fluid requirements during the acute resuscitation.
Patient Discharge Instructions Completeness and Performance on a National Quality Measure A Quasi-Experimental Study

Objectives: To compare the completeness of Emergency Department (ED) discharge instructions before and after introduction of an electronic discharge instructions module by scoring compliance with the Centers for Medicare and Medicaid Services (CMS) Outpatient Measure 19 (OP-19). Methods: We performed a quasi-experimental study examining the impact of an electronic discharge instructions module in an academic ED. Three hundred patients discharged home from the ED were randomly selected from two time intervals: 150 patients three months before and 150 patients three to five months after implementation of the new electronic module. The discharge instructions for each patient were reviewed, and compliance for each individual OP-19 element as well as overall OP-19 compliance was scored per CMS specifications. Compliance rates as well as risk ratios (RR) and risk differences (RD) with 95% confidence intervals (CI) comparing the overall OP-19 scores and individual OP-19 element scores of the electronic and paper-based discharge instructions were calculated. Results: The electronic discharge instructions had 97.3% (146/150) overall OP-19 compliance, while the paper-based discharge instructions had overall compliance of 46.7% (70/150). Electronic discharge instructions were twice as likely to achieve overall OP-19 compliance compared to the paper-based format (RR: 2.09, 95% CI: 1.75 – 2.48). The largest improvement was in documentation of major procedures and tests performed: only 60% of the paper-based discharge instructions satisfied this criterion, compared to 100% of the electronic discharge instructions (RD: 40.0%, 95% CI: 32.2% – 47.8%). There was a modest difference in medication documentation with 92.7% for paper-based and 100% for electronic formats (RD: 7.3%, 95% CI: 3.2% – 11.5%). There were no statistically significant differences in documentation of patient care instructions and diagnosis between paper-based and electronic formats. Conclusions: With careful design, information technology can improve the completeness of ED patient discharge instructions and performance on the OP-19 quality measure. Research Article
Dual Learning-Based Safe Semi-Supervised Learning

In many real-world applications, labeled instances are generally limited and expensively collected, while the most instances are unlabeled and the amount is often sufficient. Therefore, semi-supervised learning (SSL) has attracted much attention, since it is an effective tool to discover the unlabeled instances. However, how to safely make use of the unlabeled instances is an emerging and interesting problem in SSL. Hence, we propose DuAL Learning-based sAfe Semi-supervised learning (DALLAS), which employs dual learning to estimate the safety or risk of the unlabeled instances. To realize the safe exploitation of the unlabeled instances, our basic idea is to use supervised learning (SL) to analyze the risk of the unlabeled instances. First, DALLAS utilizes a primal model obtained by dual learning to classify each unlabeled instance and then uses a dual model to reconstruct the unlabeled instances according to the obtained classification results. The risk can be measured by analyzing the reconstruction error and predictions of the original and reconstructed unlabeled instances. If the error is small and the predictions are equal, the unlabeled instance may be safe. Otherwise, the instance may be risky and its output should be approach to be that obtained by SL. Finally, we embed a risk-based regularization term into SSL. Hence, the outputs of our algorithm are a tradeoff between those of SL and SSL. In particular, we utilize respectively regularized least squares (RLS) and Laplacian RLS for SL and SSL. To verify the effectiveness of the proposed safe mechanism in DALLAS, we carry out a series of experiments on several data sets by the comparison with the state-of-the-art supervised, semi-supervised, and safe semi-supervised learning methods and the results demonstrate that DALLAS can effectively reduce the risk of the unlabeled instances.
Alternative Iterations Based Registration for Contrast-Enhanced Multiphase Liver CT Images

Contrast-enhanced multiphase liver standard of practice in hepatic imaging for m liver diseases. The main contribution of this registration method which finds an accurate al phase and portal venous phase liver CT ima method combines global rigid registration nonrigid deformable registration (B-spline) alternative iterations, and extends tra registration to iterative multi-step registra registration, rigid and nonrigid registrations other by updating the transformed coordi Meanwhile, a composite optimization strateg tradeoff between the convergence and comput In our experiments, we derived the semi-au transformations from registering large volum return used these transformations to evalu Furthermore, experimental comparisons of our step methods were conducted. The correspond the proposed method is a promising sc registration in terms of accuracy and robustne Keywords-contrast-enhanced; abdominal alternative iteration; deformable registration
Optimized walking straight guidance system for visually impaired person that use Android smartphone

A person with visual organs problems whose often called visually impaired person, either total or partial blindness has obstacles in doing motor activities, especially activities that require a person to move from a place to another such as walking have a veering tendency. This problem can risk the safety of the visually impaired person when walking in public area. The need for a system that can help people with special needs is felt important enough to support ease of activity for these people. This research proposes a mobile app based system to guide someone to walk straight using the motion sensors on the smartphone and audio-based guidance. The low-pass filter was applied to magnetometer and accelerometer data to reduce noise that resulted when the user walks. The results of this study can be used to train the visually impaired person to reduce the veering habits.
Conserved Nonexonic Elements: A Novel Class of Marker for Phylogenomics

Noncoding markers have a particular appeal as tools for phylogenomic analysis because, at least in vertebrates, they appear less subject to strong variation in GC content among lineages. Thus far, ultraconserved elements (UCEs) and introns have been the most widely used noncoding markers. Here we analyze and study the evolutionary properties of a new type of noncoding marker, conserved non-exonic elements (CNEEs), which consists of noncoding elements that are estimated to evolve slower than the neutral rate across a set of species. Although they often include UCEs, CNEEs are distinct from UCEs because they are not ultraconserved, and, most importantly, the core region alone is analyzed, rather than both the core and its flanking regions. Using a data set of 16 birds plus an alligator outgroup, and ~3600 - ~3800 loci per marker type, we found that although CNEEs were less variable than UCEs or introns and in some cases exhibited a slower approach to branch resolution as determined by phylogenomic subsampling, the quality of CNEE alignments was superior to those of the other markers, with fewer gaps and missing species. Phylogenetic resolution using coalescent approaches was comparable among the three marker types, with most nodes being fully and congruently resolved. Comparison of phylogenetic results across the three marker types indicated that one branch, the sister group to the passerine+falcon clade, was resolved differently and with moderate (> 70%) bootstrap support between CNEEs and UCEs or introns. Overall, CNEEs appear to be promising as phylogenomic markers, yielding phylogenetic resolution as high as for UCEs and introns but with fewer gaps, less ambiguity in alignments and with patterns of nucleotide substitution more consistent with the assumptions of commonly used methods of phylogenetic analysis.
SGBEM (Using Non-hyper-singular Traction BIE), and Super Elements, for Non-Collinear Fatigue-growth Analyses of Cracks in Stiffened Panels with Composite-Patch Repairs

Two-dimensional weakly-singular Symmetric Galerkin Boundary Elements (SGBEMs) are developed, following the work of [Han and Atluri (2003)], using non-hypersingular integral equations for tractions. Specifically, the present 2D SGBEM is used to compute the stress intensity factors for arbitrary-shaped line cracks, including embedded, edge, branching, and intersecting cracks. The computed stress intensity factors show high accuracy, even with very coarse meshes. The non-collinear mixed-mode fatigue growth analysis of cracks requires a very minimal effort—simply extending the cracks by adding an element to each crack tip, in the direction of the crack-growth as determined by a physics-based criterion. Moreover, by rearranging the symmetric Galerkin boundary integral equations, a Super Element containing the arbitrarily growing crack is developed. The Super Element is an arbitrarily-shaped domain with or without cracks inside it. Each Super Element has a stiffness matrix and a force vector, which have physical meanings similar to those by traditional finite elements.Likewise, the stiffness matrix of the Super Element is also positive semi-definite and has exactly three rigid body modes. Super Elements can therefore be directly coupled with traditional finite elements, using the simple assembly procedure. Super Elements are thus very suitable for analyzing large-scale structures and complex structures with cracks growing under fatigue. Fatigue analysis of cracked thin panels with stiffeners and composite patches are presented, showing the simplicity and efficiency of using SGBEM Super Elements to model cracked and repaired stiffened aircraft structures.
Degeneracy and Neuromodulation among Thermosensory Neurons Contribute to Robust Thermosensory Behaviors in Caenorhabditis elegans

Animals must ensure that they can execute behaviors important for physiological homeostasis under constantly changing environmental conditions. The neural mechanisms that regulate this behavioral robustness are not well understood. The nematode Caenorhabditis elegans thermoregulates primarily via modulation of navigation behavior. Upon encountering temperatures higher than its cultivation temperature (Tc), C. elegans exhibits negative thermotaxis toward colder temperatures using a biased random walk strategy. We find that C. elegans exhibits robust negative thermotaxis bias under conditions of varying Tc and temperature ranges. By cell ablation and cell-specific rescue experiments, we show that the ASI chemosensory neurons are newly identified components of the thermosensory circuit, and that different combinations of ASI and the previously identified AFD and AWC thermosensory neurons are necessary and sufficient under different conditions to execute a negative thermotaxis strategy. ASI responds to temperature stimuli within a defined operating range defined by Tc, and signaling from AFD regulates the bounds of this operating range, suggesting that neuromodulation among thermosensory neurons maintains coherence of behavioral output. Our observations demonstrate that a negative thermotaxis navigational strategy can be generated via different combinations of thermosensory neurons acting degenerately, and emphasize the importance of defining context when analyzing neuronal contributions to a behavior.
How are we improving the delivery to back of the eye? Advances and challenges of novel therapeutic approaches

ABSTRACT Introduction: Drug delivery to the back of the eye requires strategic approaches that guarantee the long-term therapeutic effect with patient compliance. Current treatments for posterior eye diseases suffer from significant challenges including frequent intraocular injections of anti-VEGF agents and related adverse effects in addition to the high cost of the therapy. Areas covered: Treatment challenges and promising drug delivery approaches for posterior segment eye diseases, such as age-related macular degeneration (AMD) are summarized. Advances in the development of several nanotechnology-based systems, including stimuli-responsive approaches to enhance drug bioavailability and overcome existing barriers for effective ocular delivery are discussed. Stem cell transplantation and encapsulated cell technology (ECT) approaches to treat posterior eye diseases are elaborated. Expert opinion: There are several drug delivery systems demonstrating promising results. However, a better understanding of ocular barriers, disease pathophysiology, and drug clearance mechanisms is required for better therapeutic outcomes. The stem cell transplantation strategy and ECT approach provide positive results in AMD therapy, but there are a number of challenges that must be overcome for long-term efficiency. Ultimately, there are numerous multidimensional challenges to cure vision problems and a collaborative approach among scientists is required.
Aggregating Sparse Binarized Local Features by Summing for Efficient 3D Model Retrieval

An effective and widespread approach for shape-based 3D model retrieval (3DMR) is to use a feature vector per 3D model obtained by aggregating, or pooling, a set of local features extracted from the 3D model. State-of-the-art feature aggregation algorithms, such as Fisher Vector (FV) coding [7] or Super Vector (SV) coding [22], used in the approach is not spatially efficient, however. The FV or SV, for example, typically encodes a local feature into a very high-dimensional (e.g., 300k-dimensional) vector. For a database containing a large number of 3D models, the spatial cost of storing all the aggregated feature vectors for the database becomes very high. In this paper, we propose a novel, spatially efficient yet accurate feature aggregation algorithm called Sum of Sparse Binary codes (SSB) aggregation. The SSB first encodes a local feature into a highly sparse binary code. Then, a set of sparse binary codes are aggregated efficiently by simple summing into a compact feature vector. We also propose fast SSB (fSSB) aggregation, which is a computationally efficient approximation of the SSB. Experiments using a 3DMR scenario show that the proposed algorithms are significantly more efficient than the state-of-the-art feature aggregation algorithms we have compared against. At the same time, retrieval accuracies of the proposed algorithms are equal or better than the state-of-the-art aggregation algorithms.
Skin exposure to aliphatic polyisocyanates in the auto body repair and refinishing industry: a qualitative assessment.

OBJECTIVES Although respiratory exposures have been the primary concern with isocyanates, skin exposure also can occur and may contribute to sensitization and asthma. Methodologies to assess isocyanate skin exposure in the workplace are limited and skin exposure data scarce. The goals of this study were (i) to evaluate and validate the isocyanate colorimetric indicators against a quantitative assay, (ii) to evaluate the extent of isocyanate surface contamination and skin exposure among auto body shop workers and (iii) to evaluate isocyanate skin exposure determinants. METHODS The colorimetric indicators were compared with a high-performance liquid chromatography (HPLC) quantitative assay based on the National Institute for Occupational Safety and Health Method 5525 using paired laboratory sampling. The colorimetric indicators were then used to assess surface contamination and skin exposure to aliphatic isocyanates in 35 auto body shops and 124 workers as part of an epidemiologic study. The positive sample rate was calculated for various surfaces, body parts and tasks. The color intensity of the colorimetric indicators was rated on a scale 0 (yellow color) to 5 (deep red). Side-by-side comparisons of the qualitative method with the quantitative HPLC assay were also performed in the field using paired samples. RESULTS Laboratory and field evaluation validated use of the colorimetric indicators. The rate of positive surface samples for isocyanates was 46% (n = 145/313). Thirty-four percent (73/216) of samples were positive for unprotected skin and 20% (n = 22/111) for skin under latex gloves. The highest positive rate observed on skin samples was obtained after paint mixing and spraying tasks. The colorimetric indicators were highly specific for isocyanates, but false negatives occurred when compared with the more sensitive HPLC quantitative assay. The presence of surface contamination and the performance of paint-related tasks were the major determinants of isocyanate skin exposure. CONCLUSIONS This study documents extensive surface contamination and skin exposure, including under gloves, to aliphatic polyisocyanates during painting and paint mixing tasks in auto body shop workers. Contaminated surfaces and aerosol deposition during spray painting may both contribute to skin exposure. The colorimetric indicator is a quick, practical and low-cost, but not highly sensitive, industrial hygiene tool to detect isocyanate surface contamination and skin exposures following the use of isocyanate-containing products.
A Computationally Inexpensive Optimal Guidance via Radial-Basis-Function Neural Network for Autonomous Soft Landing on Asteroids

Optimal guidance is essential for the soft landing task. However, due to its high computational complexities, it is hardly applied to the autonomous guidance. In this paper, a computationally inexpensive optimal guidance algorithm based on the radial basis function neural network (RBFNN) is proposed. The optimization problem of the trajectory for soft landing on asteroids is formulated and transformed into a two-point boundary value problem (TPBVP). Combining the database of initial states with the relative initial co-states, an RBFNN is trained offline. The optimal trajectory of the soft landing is determined rapidly by applying the trained network in the online guidance. The Monte Carlo simulations of soft landing on the Eros433 are performed to demonstrate the effectiveness of the proposed guidance algorithm.
Effects of Hermetic Storage on Adult Sitophilus oryzae L. (Coleoptera: Curculionidae) Acoustic Activity Patterns and Mortality

Abstract Hermetic storage is of interest to farmers and warehouse managers as a method to control insect pests in small storage facilities. To develop improved understanding of effects of hermetic storage on insect pest activity and mortality over time, oxygen levels, acoustic signals, and observations of visual movement were recorded from replicates of 25, 50, and 100 adult Sitophilus oryzae (L.) (Coleoptera: Curculionidae) hermetically sealed in 500- and 1,000-ml glass jars. Recordings were done for 28 d; twice daily for the first 6 d and twice weekly thereafter. Insect sounds were analyzed as short bursts (trains) of impulses with spectra that matched average spectra (profiles) of previously verified insect sound impulses. Oxygen consumption was highest in treatments of 100 insects/500-ml jar and lowest in 25/1000-ml jars. The rates of bursts per insect, number of impulses per burst, and rates of burst impulses per insect decreased as the residual oxygen levels decreased in each treatment. Activity rates <0.02 bursts s–1, the acoustic detection threshold, typically occurred as oxygen fell below 5%. Mortality was observed at 2% levels. The time to obtain these levels of insect activity and oxygen depletion ranged from 3–14 d depending on initial infestation levels. Acoustic detection made it possible to estimate the duration required for reduction of insect activity to levels resulting in negligible damage to the stored product under hermetic conditions. Such information is of value to farmers and warehouse managers attempting to reduce pest damage in stored crops.
Luhn Revisited: Significant Words Language Models

Users tend to articulate their complex information needs in only a few keywords, making underspecified statements of request the main bottleneck for retrieval effectiveness. Taking advantage of feedback information is one of the best ways to enrich the query representation, but can also lead to loss of query focus and harm performance in particular when the initial query retrieves only little relevant information when overfitting to accidental features of the particular observed feedback documents. Inspired by the early work of Luhn [23], we propose significant words language models of feedback documents that capture all, and only, the significant shared terms from feedback documents. We adjust the weights of common terms that are already well explained by the document collection as well as the weight of rare terms that are only explained by specific feedback documents, which eventually results in having only the significant terms left in the feedback model. Our main contributions are the following. First, we present significant words language models as the effective models capturing the essential terms and their probabilities. Second, we apply the resulting models to the relevance feedback task, and see a better performance over the state-of-the-art methods. Third, we see that the estimation method is remarkably robust making the models in- sensitive to noisy non-relevant terms in feedback documents. Our general observation is that the significant words language models more accurately capture relevance by excluding general terms and feedback document specific terms.