gebhart/patrepeval huggingface dataset:
Apolipoprotein B mRNA-editing protein induces hepatocellular carcinoma and dysplasia in transgenic animals. (1995)

Apolipoprotein (apo-) B mRNA editing is the deamination of cytidine that creates a new termination codon and produces a truncated version of apo-B (apo-B48). The cytidine deaminase catalytic subunit [apo-B mRNA-editing enzyme catalytic polypeptide 1 (APOBEC-1)] of the multiprotein editing complex has been identified. We generated transgenic rabbits and mice expressing rabbit APOBEC-1 in their livers to determine whether hepatic expression would lower low density lipoprotein cholesterol concentrations. The apo-B mRNA from the livers of the transgenic mice and rabbit was extensively edited, and the transgenic animals had reduced concentrations of apo-B100 and low density lipoproteins compared with control animals. Unexpectedly, all of the transgenic mice and a transgenic rabbit had liver dysplasia, and many transgenic mice developed hepatocellular carcinomas. Many of the mouse livers were hyperplastic and filled with lipid. Other hepatic mRNAs with sequence motifs similar to apo-B mRNA were examined for this type of editing (i.e., cytidine deamination). One of these, tyrosine kinase, was edited in livers of transgenic mice but not of controls. This result demonstrates that other mRNAs can be edited by the overexpressed editing enzyme and suggests that aberrant editing of hepatic mRNAs involved in cell growth and regulation is the cause of the tumorigenesis. Finally, these findings compromise the potential use of APOBEC-1 for gene therapy to lower plasma levels of low density lipoproteins.
Liquefaction of Victorian Brown Coal with Continuous Reactors. (IV). Effect of Preheating Conditions on Liquefaction Yields. (1998)

The effect of preheating conditions on the liquefaction reaction of Victorian brown coal (Yallourn) was investigated using a process development unit (PDU) with three stirred tank reactors and three preheaters connected in series. Four kinds of solvents (RS, RS +CLB, RS+HDAO and RS+CLB +HDAO) were used for liquefaction to examine the relationship between the solvent properties and the effect of the preheating conditions. RS, CLB, HDAO were the recycled solvent fraction (b. p.180-420°C), heavy liquefaction product derived from the brown coal (coal liquid bot-tom, b. p.>420°C) and coal liquid product further hydrogenated over Ni-Mo catalyst (b. p.<250°C), respectively. For all experiments, the liquefaction was carried out in the presence of iron-sulfur catalyst (Fe2O3, S/Fe atomic ratio 1.2) under the conditions of temperature 450°C and pressure 14.7 MPa.When the feed slurry was preheated up to 410°C for- 2 min. with hydrogen gas of 10 wt. % on daf coal, the distillate yield (b.p.<420°C) decreased 5-13 wt.% on daf coal for all kinds of the solvent in comparison with the case where reaction at the pre-heating stage was negligible. The decrease in the distillate yield resulted from the sup-pression of the conversion of the heavy fraction (CLB) into the solvent fraction (180-420°C). At the preheating stage, CO2 and H2O evolved and the coal of 20-30 wt % converted to preasphaltenes (benzene insoluble-pyridine solubles). The oxygen-contain-ing functional groups decomposed rapidly at more than 350°C, resulting in the formation of many radicals in the coal (Plorg.). Since the greater part of the coal remained as pyridine insolubles (Plorg.), the retrogressive reaction caused by the radicals in the Plorg. was considered to reduce the conversion of the heavy fraction into the distillate at the liquefaction stage.Based on these results, it is concluded that the usual preheating conditions of the liquefaction process decreased the liquedaction performance. This indicates that the distillate yield increases if the retrogressive reaction at the preheating stage is suppres-sed by controlling the preheating conditions and solvent quality such as hydrogen donor ability and catalyst activity.
Evaluation of a biodegradable synthetic hydrogel used as a guided bone regeneration membrane: an experimental study in dogs (2011)

The study demonstrates that the combination of the PEG membrane with DBBM maintains the bone graft volume over time better than controls. The PEG membrane with DBBM was also the most effective method to preserve the ridge contour.
Nucleic acid scavengers inhibit thrombosis without increasing bleeding (2012)

Development of effective, yet safe, antithrombotic agents has been challenging because such agents increase the propensity of patients to bleed. Recently, naturally occurring polyphosphates such as extracellular DNA, RNA, and inorganic polyphosphates have been shown to activate blood coagulation. In this report, we evaluate the anticoagulant and antithrombotic activity of nucleic acid-binding polymers in vitro and in vivo. Such polymers bind to DNA, RNA, and inorganic polyphosphate molecules with high affinity and inhibit RNA- and polyphosphate-induced clotting and the activation of the intrinsic pathway of coagulation in vitro. Moreover, [NH(2)(CH(2))(2)NH(2)](G = 3);dendri PAMAM(NH(2))(32) (PAMAM G-3) prevents thrombosis following carotid artery injury and pulmonary thromboembolism in mice without significantly increasing blood loss from surgically challenged animals. These studies indicate that nucleic acid-binding polymers are able to scavenge effectively prothrombotic nucleic acids and other polyphosphates in vivo and represent a new and potentially safer class of antithrombotic agents.
Supplementary Table 3 from Bevacizumab plus Ipilimumab in Patients with Metastatic Melanoma (2023)

&lt;p&gt;PDF file - 39K, Summary of grade 3 and grade 4 events incidence at each dose level for all events and those events possibly, probably, or definitively related.&lt;/p&gt;
Data Imputation for Symbolic Regression with Missing Values: A Comparative Study (2020)

Symbolic regression via genetic programming is considered as a crucial machine learning tool for empirical modelling. However, in reality, it is common for real-world data sets to have some data quality problems such as noise, outliers, and missing values. Although several approaches can be adopted to deal with data incompleteness in machine learning, most studies consider the classification tasks, and only a few have considered symbolic regression with missing values. In this work, the performance of symbolic regression using genetic programming on real-world data sets that have missing values is investigated. This is done by studying how different imputation methods affect symbolic regression performance. The experiments are conducted using thirteen real-world incomplete data sets with different ratios of missing values. The experimental results show that although the performance of the imputation methods differs with the data set, CART has a better effect than others. This might be due to its ability to deal with categorical and numerical variables. Moreover, the superiority of the use of imputation methods over the commonly used deletion strategy is observed.
Direct Circuit Formation Method on Aluminum Substrate by Electroless Nickel Plating. (1993)

Electroless nickel plating on aluminum substrates utilizing a nickel displacement process has been investigated.A zincate process is in general use before electroless nickel plating on aluminum substrates. It has been confirmed, however, that the film of deposited nickel exhibits higher adhesion strength if a nickel displacement process is used instead of the zincate process, and that adhesion strength depends on the rate of the displacement reaction, which can be controlled by changing the kind of complexing agent and the plating conditions in the displacement bath.In addition, fine bumps are required in the TAB or flip chip bonding methods and straight-walled bumps approximately 20μm wide and 15μm high can be formed by electroless nickel deposition utilizing the displacement process.
On Training-Symbol Design and Efficient Synchronization in OFDM Systems (2007)

We show the equivalence between the conventional frame synchronization in single-carrier systems and integer part estimation of frequency offset in OFDM systems and propose an efficient synchronization scheme. The proposed scheme achieves both OFDM symbol/frame timing and frequency offset estimation with only one well-designed OFDM training symbol, while previous synchronization algorithms need two OFDM training symbols at least. Numerical analysis shows that the proposed frequency estimator nearly achieves the Cramer-Rao lower bound for the variance of the frequency offset estimate, despite the reduction in the training sequence length.
Open-loop (feed-forward) and feedback control of coronary blood flow during exercise, cardiac pacing, and pressure changes (2016)

A control system model was developed to analyze data on in vivo coronary blood flow regulation and to probe how different mechanisms work together to control coronary flow from rest to exercise, and under a variety of experimental conditions, including cardiac pacing and with changes in coronary arterial pressure (autoregulation). In the model coronary flow is determined by the combined action of a feedback pathway signal that is determined by the level of plasma ATP in coronary venous blood, an adrenergic open-loop (feed-forward) signal that increases with exercise, and a contribution of pressure-mediated myogenic control. The model was identified based on data from exercise experiments where myocardial oxygen extraction, coronary flow, cardiac interstitial norepinephrine concentration, and arterial and coronary venous plasma ATP concentrations were measured during control and during adrenergic and purinergic receptor blockade conditions. The identified model was used to quantify the relative contributions of open-loop and feedback pathways and to illustrate the degree of redundancy in the control of coronary flow. The results indicate that the adrenergic open-loop control component is responsible for most of the increase in coronary blood flow that occurs during high levels of exercise. However, the adenine nucleotide-mediated metabolic feedback control component is essential. The model was evaluated by predicting coronary flow in cardiac pacing and autoregulation experiments with reasonable fits to the data. The analysis shows that a model in which coronary venous plasma adenine nucleotides are a signal in local metabolic feedback control of coronary flow is consistent with the available data.
Binary Tissue Classification on Wound Images With Neural Networks and Bayesian Classifiers (2009)

A pressure ulcer is a clinical pathology of localized damage to the skin and underlying tissue caused by pressure, shear, or friction. Diagnosis, treatment, and care of pressure ulcers are costly for health services. Accurate wound evaluation is a critical task for optimizing the efficacy of treatment and care. Clinicians usually evaluate each pressure ulcer by visual inspection of the damaged tissues, which is an imprecise manner of assessing the wound state. Current computer vision approaches do not offer a global solution to this particular problem. In this paper, a hybrid approach based on neural networks and Bayesian classifiers is used in the design of a computational system for automatic tissue identification in wound images. A mean shift procedure and a region-growing strategy are implemented for effective region segmentation. Color and texture features are extracted from these segmented regions. A set of k multilayer perceptrons is trained with inputs consisting of color and texture patterns, and outputs consisting of categorical tissue classes which are determined by clinical experts. This training procedure is driven by a k-fold cross-validation method. Finally, a Bayesian committee machine is formed by training a Bayesian classifier to combine the classifications of the k neural networks. Specific heuristics based on the wound topology are designed to significantly improve the results of the classification. We obtain high efficiency rates from a binary cascade approach for tissue identification. Results are compared with other similar machine-learning approaches, including multiclass Bayesian committee machine classifiers and support vector machines. The different techniques analyzed in this paper show high global classification accuracy rates. Our binary cascade approach gives high global performance rates (average sensitivity =78.7% , specificity =94.7% , and accuracy =91.5% ) and shows the highest average sensitivity score ( =86.3%) when detecting necrotic tissue in the wound.
Environmental enteropathy and malnutrition: do we know enough to intervene? (2014)

Environmental enteropathy (EE) is a poorly defined state of intestinal inflammation without overt diarrhea that occurs in individuals exposed over time to poor sanitation and hygiene. It is implicated as a cause of stunting and malnutrition, oral vaccine failure and impaired development in children from low-income countries. The burden on child health of malnutrition alone, which affects 25% of all children and is estimated to result in more than a million deaths annually due to heightened susceptibility to infection, makes urgent a solution to EE. Efforts are thus underway to treat EE even while work continues to identify it through the use of non-invasive biomarkers, and delineate its pathogenesis. A recent study published in BMC Medicine reports the first randomized controlled phase I trial of an anti-inflammatory drug for EE. The aminosalicylate mesalazine was found to be safe in short-term treatment of a small number of severely malnourished children, although efficacy was not established. Whether such treatment trials are premature, or instead a way both to understand and intervene in EE, is the focus of this article. Please see related article: http://www.biomedcentral.com/1741-7015/12/133.
Giant Temperature Coefficient of Resistance in Carbon Nanotube/Phase‐Change Polymer Nanocomposites (2013)

Abstract The temperature coefficient of resistance of a carbon nanotube nanocomposite with the non‐conductive phase‐change hydrogel Poly(N‐isopropylacrylamide) is studied. This nanocomposite is found to achieve the largest reported temperature coefficient of resistance, ≈−10%/°C, observed in carbon nanotube‐polymer nanocomposites to date. The giant temperature coefficients of resistance results from a volume‐phase‐transition that is induced by the humidity present in the surrounding atmosphere and that enhances the temperature dependence of the resistivity via direct changes in the tunneling resistance that electrons experience in moving between nearby carbon nanotubes. The bolometric photoresponses of this new material are also studied. The nanocomposite's enhanced responses to temperature and humidity give it great potential for sensor applications and uncooled infrared detection.
Current Status and the Future of Korean Biodiversity (2008)

While the number of the biological species in Korea is estimated to be 100,000 or more, only 29,916 species are identified (Ministry of Education, Science and Technology 2007), and 18,027 (60.26%) species are digitalized (Table 1), including 99.83% of insects recorded in Korea. Only 39.25% of spiders, 35.47% of fishes, and 6.98% of amphibians and reptiles are made into databases. However, the 18 taxa including arthropods, porifera, molluca, and bryozoa are not digitalized yet, which is the same for fungi, protista and prokaryotae (Paek and Lim 2008).
Aseptic loosening of the femoral component in cemented total hip replacement (1992)

The purpose of this study was to identify factors which predispose to aseptic loosening of the femoral component in cemented total hip replacement. Its design was based on rigid selection critria, so that successful and loose replacements which employed the same surgical technique were compared. Measurements of patient anatomy and of the insertion of the femoral component were made, by an accurate computer technique, on initial post-operative radiographs. Loosening was associated with heavier patients with a wider medullary canal which was flared proximally. This difference in anatomy led to differing distributions of cement in the successful and loose replacements. Medial cement-bone demarcation, at the mid-stem level, was also associated with loosening. These findings indicate the importance of optimizing the size of the prosthesis with respect to the femoral morphology.
Dynamic Continuous Cooling Transformation Behavior of A Novel Cu-bearing Pipeline Steel (2016)

Study on continuous cooling transformation (CCT) behavior is an essential issue before thermo-mechanical processing for a new steel. In this study, dynamic CCT characteristics and microstructural evolution of a novel Cu-bearing pipeline steel with different Cu content (1.06%, 1.46% and 2.00%) were investigated by means of a combined method of dilatometry and metallography. The microstructure developed at a cooling rate range of 0.05 to 30°C/s consisted of pearlite, polygonal ferrite, quasi-polygonal ferrite and acicular ferrite. More Cu addition could lower the transformation temperature for austenite to ferrite and lead to an increase in the driving force for the acicular ferrite transformation, resulting in a full acicular ferrite for 2.0 Cu steel at cooling rate above 2°C/s. The precipitation behavior of Cu-rich phase during continuous cooling showed that Cu precipitation could occur in the acicular ferrite, which made a hardness peak on the hardness vs cooling rate curve of 2.0Cu steel at the cooling rate of 2°C/s. However, no Cu precipitate was detected in the acicular ferrite at higher cooling rate for 2.0 Cu steel. Higher supersaturation of Cu in austenite and a short incubation period of Cu-rich phase precipitation were assumed to allow the Cu precipitation to occur in the auto-aging after acicular ferrite transformation.
Efficient entertainment services provision over a novel network architecture (2016)

The provision of entertainment services through current network infrastructures generates a significant part of global Internet traffic. Such traffic is created by users who are interconnected through social media networks, distributing multimedia content, as well as through their online games interaction, leading to a significant increase in data traffic demands. At the same time, users demand the high-quality content delivery necessary for such multimedia-based services and applications. In this article, a novel network architecture is proposed that exploits a resource prediction engine to predict the upcoming demands on resources for the optimal distribution of streaming data among content delivery networks, emerging mobile networks, cloudbased providers, and home media gateways. Performance evaluation experiments carried out under controlled conditions verify the validity of the proposed network architecture and establish its effectiveness for efficient resources prediction during the provision of entertainment services.
High power pulsed accelerators with potential industrial applications (1984)

Abstract Radiation processing sources fall into two categories, electron beams and nuclear decay products (gamma rays). Applications requiring high average power ( > 100 kW), high dose rate, or limited deposition depth are performed with electrons. Typically, the electron sources that are used for radiation processing are either DC accelerators or linacs with peak powers in the 50 to 200 kW regime. Recent advances have made the development of pulsed electron sources in this parameter range attractive as well. Pulsed sources operate with space charge limited “cold cathode” emission on the microsecond or submicrosecond time scale. As a result, the dose rates are much higher than currently available. This paper will describe a design for a 10 MV, 100 kW or greater accelerator for large area electron beam irradiation or for bremsstrahlung conversion. The design is based on pulse transformers to generate megavolt, microsecond pulses, saturable magnetic core switching to compress to shorter pulse lengths, pulse-forming line adder techniques to transform to 10 MV, and a magnetically insulated cold cathode diode for electron beam formation. The status of these various technologies is reviewed.
Multivalued associative memories based on recurrent networks (1993)

A multivalued neural associative memory model based on a recurrent network structure is proposed. This model adopts the same principle proposed in the authors' previous work, the exponential correlation associative memories (ECAM). The model also has a very high storage capacity and strong error-correction capability. The major components of the new model include a weighted average process and some similarity-measure computation. As in ECAM, in order to enhance the differences among the weights and make the largest weights more overwhelming, the new model incorporates a nonlinear function in the calculation of weights. Several possible similarity measures suitable for this model are suggested. Simulation results of the performance of the new model with different measures show that, loaded with 500 64-component patterns, the model can sustain noise with power about one fifth to three fifths of the average signal power.
Applying experimental data to protein fold prediction with the genetic algorithm (1997)

Specific residue interactions as revealed from a few and readily available experiments can be quite important in shaping a protein's tertiary topology by complementing basic and general folding principles. This experimental information is employed in structure prediction (mainchain topology) based on sequence knowledge and the genetic algorithm with its ability to optimize simultaneously many parameters. Examples investigated include the distribution of cysteinyl S-S bonds, protein side-chain ligands to iron-sulfur cages, cofactor-ligands, crosslinks amongst side-chains, and conserved hydrophobic and catalytic residues. Such interactions yield an improvement in the predicted topology (0.4-6.6 A root mean square deviation in the positions of the backbone C alpha-atoms relative to those observed) compared with those resulting from simulations relying only on basic protein folding principles. For several examples the resultant topology depended critically on knowledge of the few and specific interactions such that the relationship between predicted and observed C alpha-positions was near random without their use. The combined methodology (experimental data and the genetic algorithm) should prove helpful in settings where experiment and theory can cooperate in successive steps to elucidate an unknown structure.
Automatic nipple detection on 3D images of an automated breast ultrasound system (ABUS) (2014)

Recent studies have demonstrated that applying Automated Breast Ultrasound in addition to mammography in women with dense breasts can lead to additional detection of small, early stage breast cancers which are occult in corresponding mammograms. In this paper, we proposed a fully automatic method for detecting the nipple location in 3D ultrasound breast images acquired from Automated Breast Ultrasound Systems. The nipple location is a valuable landmark to report the position of possible abnormalities in a breast or to guide image registration. To detect the nipple location, all images were normalized. Subsequently, features have been extracted in a multi scale approach and classification experiments were performed using a gentle boost classifier to identify the nipple location. The method was applied on a dataset of 100 patients with 294 different 3D ultrasound views from Siemens and U-systems acquisition systems. Our database is a representative sample of cases obtained in clinical practice by four medical centers. The automatic method could accurately locate the nipple in 90% of AP (Anterior-Posterior) views and in 79% of the other views.