gebhart/patrepeval huggingface dataset:
Deep Learning Feature Extraction for Brain Tumor Characterization and Detection (2021)

Deep Learning is a growing field of artificial intelligence that has become an operative research topic in a wide range of disciplines. Today we are witnessing the tangible successes of Deep Learning in our daily lives in various applications, including education, manufacturing, transportation, healthcare, military, and automotive, etc.&lt;strong&gt; &lt;/strong&gt;Deep Learning is a subfield of Machine Learning that stems from Artificial Neural Networks, where a cascade of layers is employed to progressively extract higher-level features from the raw input and make predictive guesses about new data. This paper will discuss the effect of attribute extraction profoundly inherent in training&lt;strong&gt; &lt;/strong&gt;approaches such as Convolutional Neural Networks (CNN). Furthermore, the paper aims to offer a study on Deep Learning techniques and attribute extraction methods that have appeared in the last few years. As the demand increases, considerable research in the attribute extraction assignment has become even more instrumental. Brain tumor characterization and detection will be used as a case study to demonstrate Deep Learning CNN's ability to achieve effective representational learning and tumor characterization.
Intramolecular quality control: HIV-1 Envelope gp160 signal-peptide cleavage as a functional folding checkpoint (2020)

Summary Removal of the membrane-tethering signal peptides that target secretory proteins to the endoplasmic reticulum is a prerequisite for proper folding. While generally thought to be removed well before translation termination, we here report two novel post-targeting functions for the HIV-1 gp120 signal peptide, which remains attached until gp120 folding triggers its removal. First, the signal peptide improves fidelity of folding by enhancing conformational plasticity of gp120 by driving disulfide isomerization through a redox-active cysteine, at the same time delaying folding by tethering the N-terminus to the membrane, which needs assembly with the C-terminus. Second, its carefully timed cleavage represents intramolecular quality control and ensures release and stabilization of (only) natively folded gp120. Postponed cleavage and the redox-active cysteine both are highly conserved and important for viral fitness. Considering the ∼15% secretory proteins in our genome and the frequency of N-to-C contacts in protein structures, these regulatory roles of the signal peptide are bound to be more common in secretory-protein biosynthesis.
Classification of surficial sediments: North-Central and Eastern Gulf of Mexico (2003)

Due to the character of the original source materials and the nature of batch digitization, quality control issues may be present in this document. Please report any quality issues you encounter to digital@library.tamu.edu, referencing the URI of the item.
Preparation and Characterization of Monoclonal Antibody Against Melatonin (2008)

Anti-melatonin monoclonal antibodies (MAb) were prepared following coupling melatonin to bovine serum albumin (BSA) by Mannich reaction. Balb/c mice were immunized via injection of the melatonin-BSA intraperitonally. The spleen cells producing high titer of antibody were fused with myeloma cells of SP2/0 origin. After two limiting dilutions, two stable clones (AS-H10 and AS-D26) exhibiting best properties were selected for further studies. The class and subclass of two MAbs were found to be IgG(1) and IgG(2a) with lambda and kappa light chains, respectively. Antibodies secreted by these two clones showed high affinity of about 10(9)M(1). Study of the specificity criteria showed that these clones had no cross reactivity with indolic, aromatic, and imidazole ring-containing compounds, and had high specificity towards melatonin. The calibration curve was constructed with a sensitivity range of 10 ng/mL to 10 microg/mL. In conclusion, these MAbs may be useful for immunoassay of melatonin.
Automation and management of scientific workflows in distributed network environments (2010)

Large-scale computation-intensive applications in various science fields feature complex DAG-structured workflows comprised of distributed computing modules with intricate inter-module dependencies. Supporting such workflows in heterogeneous network environments and optimizing their end-to-end performance are crucial to the success of large-scale collaborative scientific applications. We design and develop a generic Scientific Workflow Automation and Management Platform (SWAMP), which contains a set of easy-to-use computing and networking toolkits for application scientists to conveniently assemble, execute, monitor, and control complex computing workflows in distributed network environments. The current version of SWAMP integrates the graphical user interface of Kepler to compose abstract workflows and employs Condor DAGMan for workflow dispatch and execution. SWAMP provides a web-based user interface to automate and manage workflow executions and uses a special workflow mapper to optimize the end-to-end workflow performance. A case study of the workflow for Spallation Neutron Source datasets in real networks is presented to show the efficacy of the proposed platform.
Are Quantitative Measures of Academic Productivity Correlated with Academic Rank in Plastic Surgery? A National Study (2015)

Academic rank in plastic surgery is strongly correlated with several quantitative metrics of research productivity. Although academic promotion is the result of success in multiple different areas, bibliometric measures may be useful adjuncts for assessment of research productivity.
Collagenase-Inhibitory activity in deposit and resorption phases of guinea pig carrageenin granuloma (1992)

The levels of collagenase inhibitor, both free and bound to metalloproteinases, were evaluated at 7 days [deposit phase (DP)] and 14 days [resorptive phase (RP)] of evolution of the subcutaneous carrageenin-induced granuloma in the guinea pig. The level of free collagenase inhibitor was considerably higher in the supernatant of DP granulomas (7.95 +/- 1.53 U/mg protein) as compared to that of RP granulomas (2.53 +/- 0.41 U/mg protein). When the samples were heated at acid pH to release the inhibitor from metalloproteinase-inhibitor complexes, free inhibitor was recovered in both phases. However, the units of recovered collagenase inhibitor were several fold higher in all RP granulomas in comparison with DP granulomas (6.88 +/- 2.46 vs 1.5 +/- 0.53). Therefore, DP and RP tissues exhibited similar total amount of tissue inhibitor. By HPLC, collagenase inhibitor activity was localized in a fraction consistent with the size of TIMP. These results suggest a different balance of collagenase and collagenase inhibitor during the evolution of the granuloma; an excess of inhibitor over metalloproteinases appears to predominate during the phase of collagen accumulation contrasting with an inverse situation when the granuloma is healing.
Dynamic properties of imidazolium orthoborate ionic liquids mixed with polyethylene glycol studied by NMR diffusometry and impedance spectroscopy (2017)

We used <sup>1</sup> H pulsed field gradient nuclear magnetic resonance to study the self-diffusion of polyethylene glycol (PEG) with average molecular mass of 200 and ions in mixtures of PEG with imidazolium bis(mandelato)borate (BMB) and imidazolium bis(oxalato)borate ionic liquids (ILs). The IL was mixed with PEG in the concentration range of 0-100 wt%. Within the temperature range of 295 to 353 K, the diffusion coefficient of BMB is slower than that of the imidazolium cation. The diffusion coefficients of PEG, as well as the imidazolium cation and BMB anions, differ under all experimental conditions tested. This demonstrates that the IL in the mixture is present in at least a partially dissociated state. Generally, increasing the concentration of PEG leads to an increase in the diffusion coefficients of PEG and both the ions and decreases their activation energy for diffusion. Nuclear magnetic resonance chemical shift alteration analysis showed that the presence of PEG changes the chemical shifts of both ions but in different directions. Impedance spectroscopy was used to measure the ionic conductivity of the ILs mixed with PEG. Copyright © 2017 John Wiley & Sons, Ltd.
Design and Development of a Broiler Mortality Removal Robot (2022)

Highlights A broiler mortality removal robot was successfully developed. The broiler shank was the target anatomical part for detection and mortality pickup. Higher light intensities improved the performance of detection and pickup performance. The final success rate for picking up dead birds was 90.0% at the 1000-lux light intensity. Abstract. Manual collection of broiler mortality is time-consuming, unpleasant, and laborious. The objectives of this research were: (1) to design and fabricate a broiler mortality removal robot from commercially available components to automatically collect dead birds; (2) to compare and evaluate deep learning models and image processing algorithms for detecting and locating dead birds; and (3) to examine detection and mortality pickup performance of the robot under different light intensities. The robot consisted of a two-finger gripper, a robot arm, a camera mounted on the robot’s arm, and a computer controller. The robot arm was mounted on a table, and 64 Ross 708 broilers between 7 and 14 days of age were used for the robot development and evaluation. The broiler shank was the target anatomical part for detection and mortality pickup. Deep learning models and image processing algorithms were embedded into the vision system and provided location and orientation of the shank of interest, so that the gripper could approach and position itself for precise pickup. Light intensities of 10, 20, 30, 40, 50, 60, 70, and 1000 lux were evaluated. Results indicated that the deep learning model “You Only Look Once (YOLO)” V4 was able to detect and locate shanks more accurately and efficiently than YOLO V3. Higher light intensities improved the performance of the deep learning model detection, image processing orientation identification, and final pickup performance. The final success rate for picking up dead birds was 90.0% at the 1000-lux light intensity. In conclusion, the developed system is a helpful tool towards automating broiler mortality removal from commercial housing, and contributes to further development of an integrated autonomous set of solutions to improve production and resource use efficiency in commercial broiler production, as well as to improve well-being of workers. Keywords: Automation, Broiler, Deep learning, Image processing, Mortality, Robot arm.
Modulated adiabatic passage of oriented nuclei. I. The theory (1988)

The anisotropic \ensuremath{\gamma}-ray distribution from oriented nuclei (ON) may be used to detect changes in the ensemble spin polarization and, in particular, those changes arising from nuclear magnetic resonance (NMR ON). A feature of NMR ON of dilute nuclear impurities in ferromagnets is the severe inhomogeneous broadening resulting from a distribution of magnetic hyperfine fields over the nuclear ensemble. In conventional NMR ON spectroscopy fine details of the hyperfine interaction, such as the electric quadrupole interaction, are buried in the inhomogeneous broadening. It is shown here that the quadrupole splitting may, however, be directly measured if the rf field is amplitude modulated during an adiabatic passage. Such a modulation implies a three-level coupling which is sensitive to rank-2 terms in the hyperfine Hamiltonian, and the modulation frequency corresponds to the spectral domain of the quadrupole splitting. This theory is developed and applied to nuclear ensembles with integral and half-integral spins.
Localization and mapping for aerial manipulation based on range-only measurements and visual markers (2014)

This paper presents a new approach for aerial robots simultaneous localization and mapping (SLAM) oriented to aerial manipulation applications. The approach is based on the integration of range-only measurements and visual markers detected with the on-board camera. A multiple hypotheses framework is applied for range-only together with visual markers SLAM. This approach allows integrating two different types of sensors that are complementary for localization, mixing the stable and continuous estimation provided by range sensors with the precise but infrequent measurements from the visual markers. Real experiments involving an aerial robot and radio/visual markers have been used to validate the approach.
The inhaled corticosteroids questionnaire shortened version (ICQ-S): A brief patient-rated scale for monitoring inhaled corticosteroid side effects in clinical practice (2012)

Introduction : A shortened 15-item version (ICQ-S) of the validated 57-item Inhaled Corticosteroids (ICS) side effects Questionnaire (ICQ) was developed to enable monitoring/management of side effects in busy clinics. Aim : To determine the reliability, criterion validity and patient acceptability of the ICQ-S. Methods : At days 0 and 14, adults with doctor-diagnosed asthma and prescribed an ICS inhaler, completed the ICQ, ICQ-S, 6-item ACQ and AQLQ(s). The intraclass correlation coefficient (ICC) between day 0 and 14 ICQ-S assessed test-re-test reliability. Cronbach9s alpha (α) coefficient and item-total correlations tested the internal consistency of ICQ-S. Associations (Spearmans rho) between the ICQ and ICQ-S total score and relative associations of the ICQ and ICQ-S with the AQLQ(s) assessed criterion validity. Patients reported duration and perceived difficulty (1=very difficult, 5=very easy) of ICQ-S completion. Results : 62 patients (female 63%, mean age 54 (SD 13) yrs., mean ACQ 0.79 (SD 0.83), median ICS dose 1000µg (IQR 500,1000)) were eligible. The ICC between day 0 and 14 ICQ-S scores was 0.90, α coefficient was 0.90 and all item-total correlations were rho≥0.20. ICQ and ICQ-S were strongly associated (rho=0.86) and similarly associated with the AQLQ(s) (ICQ rho= -0.58, (ICQ-S rho= -0.62). 81% patients completed the ICQ-S within 5 minutes and 97% reported that it was not difficult to fill in. Conclusion : The ICQ-S is a patient-friendly tool which retains the reliability and validity of the original ICQ scale but is brief enough for monitoring/managing inhaled steroid side effects in clinical practice.
Differentiation of Human Induced Pluripotent Stem Cells from Patients with Severe COPD into Functional Airway Epithelium (2022)

Background: Chronic Obstructive Pulmonary Disease (COPD), a major cause of mortality and disability, is a complex disease with heterogeneous and ill-understood biological mechanisms. Human induced pluripotent stem cells (hiPSCs) are a promising tool to model human disease, including the impact of genetic susceptibility. Methods: We developed a simple and reliable method for reprogramming peripheral blood mononuclear cells into hiPSCs and to differentiate them into air−liquid interface bronchial epithelium within 45 days. Importantly, this method does not involve any cell sorting step. We reprogrammed blood cells from one healthy control and three patients with very severe COPD. Results: The mean cell purity at the definitive endoderm and ventral anterior foregut endoderm (vAFE) stages was >80%, assessed by quantifying C-X-C Motif Chemokine Receptor 4/SRY-Box Transcription Factor 17 (CXCR4/SOX17) and NK2 Homeobox 1 (NKX2.1) expression, respectively. vAFE cells from all four hiPSC lines differentiated into bronchial epithelium in air−liquid interface conditions, with large zones covered by beating ciliated, basal, goblets, club cells and neuroendocrine cells, as found in vivo. The hiPSC-derived airway epithelium (iALI) from patients with very severe COPD and from the healthy control were undistinguishable. Conclusions: iALI bronchial epithelium is ready for better understanding lung disease pathogenesis and accelerating drug discovery.
In vitro and in vivo proposal of an artificial esophagus (2006)

Artificial materials and autologous tissues used for esophageal reconstruction often induce complications like stenosis and leakage at long-term follow-up. This study evaluates the possibility to obtain in vitro an implantable tissue-engineered esophagus composed of homologous esophageal acellular matrix and autologous smooth muscle cells (SMCs). Acellular matrices obtained by detergent-enzymatic method did not present any major histocompatibility complex marker and expressed bFGF as protein, showing angiogenic activity in vivo on the chick embryo chorioallantoic membrane (CAM). Moreover, they supported cell adhesion, and inasmuch as just after 24 h from seeding, the scaffold appeared completely covered by SMCs. To verify the biocompatibility of our constructs, defects created in the porcine esophageal wall were covered using homologous acellular matrices with and without cultures of autologous SMCs. At 3 week from surgery, the patches composed of only acellular matrices showed a more severe inflammatory response and were negative for alpha-smooth muscle actin immunostaining. In contrast, the cell-matrix implants presented ingrowth of SMCs, showing an early organization into small fascicules. Collectively, these results suggest that patches composed of homologous esophageal acellular matrix and autologous SMCs may represent a promising tissue-engineering approach for the repair of esophageal injuries.
Signal recovery from level-crossing samples using projections onto convex sets (2016)

In this paper, a new method of recovery of a bandlimited signal from level-crossing samples is presented. In contrast to known methods, not only the level-crossing samples (explicit information) but also the fact that the signal does not cross the levels in the time intervals between the samples (implicit information) are used for the recovery. The reconstruction algorithm is iterative and adopts the framework of Projections onto Convex Sets (POCS). The projections are realized by alternating lowpass filtering and hardlimiting operations. Numerical experiments demonstrate the efficiency of the proposed recovery method.
Learning from Engineering Research (2007)

This chapter contains section titled: W. G. Vincenti, 1990: What Engineers Know and How They Know It: Analytical Studies from Aeronautical History
[Homogeneous synthesis of cellulose phenylcarbamates and evaluation of their enantioseparation capabilities]. (2020)

Understanding the structure-property relationship of polysaccharide derivatives is of great significance toward the development of novel chiral stationary phases. In this work, we used an ionic liquid, 1-allyl-3-methylimidazolium chloride (AmimCl), as the solvent and introduced phenyl isocyanates with various substituents into cellulose to obtain a series of cellulose phenylcarbamates. The effects of the degree of substitution (DS), as well as the type and position of the substituents, on the chiral separation capability of the cellulose phenylcarbamates were researched in detail. With an increase in the DS, the chiral recognition capability of the cellulose phenylcarbamates improved dramatically for most of the chiral analytes. Fully substituted cellulose phenylcarbamates showed the best enantioseparation capabilities. In addition, the type and position of the substituents on the benzene ring significantly influenced the chiral separation capabilities of the cellulose phenylcarbamates. Cellulose 3-methyl-4-chlorophenylcarbamate, 3,5-dichlorophenylcarbamate, and 2-methyl-5-chlorophenylcarbamate had better chiral recognition capabilities than cellulose 3,5-dimethylphenylcarbamate for some chiral analytes.
Clinical Value of Soluble IgG Fc Receptor Type III in Plasma From Patients With Chronic Idiopathic Neutropenia (1998)

Previous studies have shown that the plasma level of soluble IgG Fc receptor type III (sFcγRIII) is a measure of the total body neutrophil mass. The aim of this study was to determine whether the plasma level sFcγRIII is associated with the risk of contracting bacterial infections in patients with neutropenia. We collected blood from 66 patients suffering from acquired idiopathic neutropenia, whose blood was sent to our laboratory for diagnostic evaluation of neutropenia (neutrophil count &lt;1,500 cells/μL). Soluble FcγRIII levels were measured in plasma. Genotype distibutions of FcγR polymorphisms were determined. Clinical data were obtained from the patient files. Patients were assessed as to whether or not they had suffered from a bacterial infection 3 months before to 3 months after a single sFcγRIII measurement. In addition, longitudinal data were obtained from 21 patients. Of the 66 neutropenic patients who were included, 15 had suffered from a bacterial infection in the period 3 months before to 3 months after sFcγRIII measurement. The age and sex distribution was equal among the groups with and without infections, as were the genotype frequencies of neutrophil FcγR polymorphisms. Both neutrophil count and plasma level sFcγRIII were significantly lower in the patient group with infections, compared with the noninfected group (P = .03 and P &lt; .0001, respectively). No infections were reported for patients who had plasma sFcγRIII levels above 100 arbitrary units (AU; normal value, 30 to 200). After matching each infected patient with two noninfected patients having the same neutrophil count, sFcγRIII plasma levels remained significantly lower in the group with infections (P = .0001). For the patients who were followed in time, no infections were reported when sFcγRIII levels were above 100 AU. In conclusion, our population of patients with chronic idiopathic neutropenia with plasma sFcγRIII levels above 100 AU did not show an increased risk of contracting bacterial infections.
An Adaptive Prediction-Based Approach to Lossless Compression of Floating-Point Volume Data (2012)

In this work, we address the problem of lossless compression of scientific and medical floating-point volume data. We propose two prediction-based compression methods that share a common framework, which consists of a switched prediction scheme wherein the best predictor out of a preset group of linear predictors is selected. Such a scheme is able to adapt to different datasets as well as to varying statistics within the data. The first method, called APE (Adaptive Polynomial Encoder), uses a family of structured interpolating polynomials for prediction, while the second method, which we refer to as ACE (Adaptive Combined Encoder), combines predictors from previous work with the polynomial predictors to yield a more flexible, powerful encoder that is able to effectively decorrelate a wide range of data. In addition, in order to facilitate efficient visualization of compressed data, our scheme provides an option to partition floating-point values in such a way as to provide a progressive representation. We compare our two compressors to existing state-of-the-art lossless floating-point compressors for scientific data, with our data suite including both computer simulations and observational measurements. The results demonstrate that our polynomial predictor, APE, is comparable to previous approaches in terms of speed but achieves better compression rates on average. ACE, our combined predictor, while somewhat slower, is able to achieve the best compression rate on all datasets, with significantly better rates on most of the datasets.