gebhart/patrepeval huggingface dataset:
Nascent prehormones are intermediates in the biosynthesis of authentic bovine pituitary growth hormone and prolactin. (1977)

Major translation products of bovine pituitary RNA in a wheat germ cell-free system were identified as larger forms (prehormones) of growth hormone and prolactin containing amino-terminal extensions of 26 or 27 and 30 amino acid residues, respectively. However, translation of bovine pituitary RNA in the wheat germ cell-free system in the presence of microsomal membranes prepared from canine pancreas or bovine pituitary yielded products that were of the same size as authentic growth hormone and prolactin; by partial amino-terminal sequence analysis they were shown to contain the correct unique amino-terminal sequence of prolactin and the two correct amino termini of authentic growth hormone; moreover, they were found to be segregated within the microsomal vesicles in that they were largely inaccessible to degradation by proteolytic enzymes. When microsomal membranes were present after rather than during translation, prehormones were neither cleaved nor segregated. These results strongly suggest that the synthesis and segregation of the authentic hormone observed in the presence of membranes proceeds via a nascent prehormone rather than a completed prehormone.
Learning the Structure of Biomedical Relationships from Unstructured Text (2015)

The published biomedical research literature encompasses most of our understanding of how drugs interact with gene products to produce physiological responses (phenotypes). Unfortunately, this information is distributed throughout the unstructured text of over 23 million articles. The creation of structured resources that catalog the relationships between drugs and genes would accelerate the translation of basic molecular knowledge into discoveries of genomic biomarkers for drug response and prediction of unexpected drug-drug interactions. Extracting these relationships from natural language sentences on such a large scale, however, requires text mining algorithms that can recognize when different-looking statements are expressing similar ideas. Here we describe a novel algorithm, Ensemble Biclustering for Classification (EBC), that learns the structure of biomedical relationships automatically from text, overcoming differences in word choice and sentence structure. We validate EBC's performance against manually-curated sets of (1) pharmacogenomic relationships from PharmGKB and (2) drug-target relationships from DrugBank, and use it to discover new drug-gene relationships for both knowledge bases. We then apply EBC to map the complete universe of drug-gene relationships based on their descriptions in Medline, revealing unexpected structure that challenges current notions about how these relationships are expressed in text. For instance, we learn that newer experimental findings are described in consistently different ways than established knowledge, and that seemingly pure classes of relationships can exhibit interesting chimeric structure. The EBC algorithm is flexible and adaptable to a wide range of problems in biomedical text mining.
Vulnerability Methods and Damage Scenario for Seismic Risk Analysis as Support to Retrofit Strategies: an European Perspective (2006)

The inherent seismic vulnerability of existing R.C. buildings, designed prior to the introduction of adequate seismic code provisions in the early/mid-1970s, has been dramatically confirmed by the catastrophic socio-economical consequences of earthquake events that have occurred worldwide in the past decade. The urgent need for the development of feasible and efficient structural mitigation strategies, and the&#13;\nimplementation of “standardized” retrofit solutions for intervention at urban or territorial scale, has received increasing recognition and attention. Damage scenario and seismic risk analysis, along with the use of a GIS-environment to represent the results, are considered as a helpful tool to support the decision making for planning and prioritizing seismic retrofit intervention programs at large scale. In this paper, after an overview of current vulnerability methods for seismic risk or damage scenario analysis at a territorial scale, tentative suggestions for possible refinements will be provided with particular focus on the vulnerability models for pre-1970 reinforced concrete buildings. Improvements should include the possibility to account for the peculiar alternative damage limit states and collapse mechanisms observed in real earthquakes and further confirmed by recent numerical and experimental investigations. Comparative evaluation of the reduced level of expected damage after alternative retrofit solutions will be carried&#13;\nout and described in terms of fragility curves. A damage scenario analysis, referred to a case study area in Italy, will be provided as further exemplification of the effects of implementing a multi-level retrofit strategy approach at territorial scale.
Self-Attentive Attributed Network Embedding Through Adversarial Learning (2019)

Network embedding aims to learn the low-dimensional representations/embeddings of vertices which preserve the structure and inherent properties of the networks. The resultant embeddings are beneficial to downstream tasks such as vertex classification and link prediction. A vast majority of real-world networks are coupled with a rich set of vertex attributes, which could be potentially complementary in learning better embeddings. Existing attributed network embedding models, with shallow or deep architectures, typically seek to match the representations in topology space and attribute space for each individual vertex by assuming that the samples from the two spaces are drawn uniformly. The assumption, however, can hardly be guaranteed in practice. Due to the intrinsic sparsity of sampled vertex sequences and incompleteness in vertex attributes, the discrepancy between the attribute space and the network topology space inevitably exists. Furthermore, the interactions among vertex attributes, a.k.a cross features, have been largely ignored by existing approaches. To address the above issues, in this paper, we propose Nettention, a self-attentive network embedding approach that can efficiently learn vertex embeddings on attributed network. Instead of sample-wise optimization, Nettention aggregates the two types of information through minimizing the difference between the representation distributions in the low-dimensional topology and attribute spaces. The joint inference is encapsulated in a generative adversarial training process, yielding better generalization performance and robustness. The learned distributions consider both locality-preserving and global reconstruction constraints which can be inferred from the learning of the adversarially regularized autoencoders. Additionally, a multi-head self-attention module is developed to explicitly model the attribute interactions. Extensive experiments on benchmark datasets have verified the effectiveness of the proposed Nettention model on a variety of tasks, including vertex classification and link prediction.
Comparison and Validation of UV Dose Calculations for Low‐ and Medium‐Pressure Mercury Arc Lamps (2000)

A method for calculating UV dose for microbial disinfection that includes a measure of the wavelength‐dependent factors of UV lamp output, quartz sleeve UV transmission, microbial action spectra, and wastewater UV transmission is presented. The method is validated by comparing UV dose–response curves for the disinfection of a secondary effluent achieved using collimated beams of UV light generated from low‐ and medium‐pressure mercury arc lamps. The wastewater UV transmittance is artificially altered as part of the validation process. A simplified and practical method of UV dose calculation that relies only on a measure of the UV transmission at 254 nm is proposed for the disinfection of domestic wastewaters by mediumpressure lamps. The proposed method is validated using wastewater samples obtained from 21 wastewater treatment plants located across North America.
Translin associated protein X is essential for cellular proliferation (2004)

DNA vectors that express short hairpin RNAs (shRNAs) provide a new tool for reverse genetic analysis for selective long-term reduction of gene expression in mammalian cells. Using shRNA constructs with a cytomegalovirus promoter and an actin intron between the hairpins for stabilization, we reduce expression of an exogenously expressed gene, GFP and the endogenous protein, Translin-associated factor X (TRAX), in stably transfected Hela cell lines. The reduction of TRAX in Hela cells causes reduced cell proliferation. This decrease is specific as there is no equivalent reduction of the TRAX interacting protein, Testis brain RNA-binding protein, or any significant increase in a number of interferon-related target genes.
Survival after radical cystectomy of non‐bilharzial squamous cell carcinoma vs urothelial carcinoma: a competing‐risks analysis (2011)

• At RC, the rate of NOC BCa is higher in NBSCC patients than in their UC counterparts. • Despite a more advanced stage at surgery, NBSCC histological subtype is not associated with a less favourable CSM than UC histological subtype, after accounting for OCM and the extent of the disease (OC vs NOC).
Histone Methyltransferase DOT1L Is Involved in Larval Molting and Second Stage Nymphal Feeding in Ornithodoros moubata (2020)

Epigenetic mechanisms have not been characterized in ticks despite their importance as vectors of human and animal diseases worldwide. Our investigation identifies and functionally characterizes the orthologue of S-adenosylmethionine (SAM) binding methyltransferase enzyme, disruptor of telomeric silencing 1-like (DOT1L) in Ornithodoros moubata (OmDOT1L), a soft tick vector for the relapsing fever pathogen Borrelia duttonii and the African swine fever virus. The OmDOT1L tertiary structure was predicted and compared to the Homo sapiens DOT1L which had been co-crystalized with SGC0946, a DOT1L-specific inhibitor. The amino acid residues crucial for SAM and SGC0946 binding conserved in most DOT1L sequences available, are also conserved in OmDOT1L. Quantitative PCR of Omdot1l during O. moubata life stages showed that transcripts were significantly upregulated in first-stage nymphs. O. moubata larvae exposed to SGC0946 displayed high mortality during molting to first-stage nymphs. Furthermore, a significant decrease in weight was observed in second-stage nymphs fed on recombinant OmDOT1L-immunized rabbits. In contrast, artificial blood feeding supplemented with SGC0946 did not affect survival and reproductive performance of adult female ticks. We concluded that OmDOT1L plays an essential role in the regulation of larval molting and the feeding of O. moubata second-stage nymphs.
An Evaluation of Bayesian Methods for Bathymetry-based Localization of Autonomous Underwater Robots (2018)

This paper presents an evaluation of a number of probabilistic algorithms for localization of autonomous underwater vehicles (AUVs) using bathymetry data. The algorithms, based on the principles of the Bayes filter, work by fusing bathymetry information with depth and altitude data from an AUV. Four different Bayes filter-based algorithms are used to design the localization algorithms: the Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), Particle Filter (PF), and Marginalized Particle Filter (MPF). We evaluate the performance of these four Bayesian bathymetry-based AUV localization approaches under variable conditions and available computational resources. The localization algorithms overcome unique challenges of the underwater domain, including visual distortion and radio frequency (RF) signal attenuation, which often make landmark-based localization infeasible. Evaluation results on real-world bathymetric data show the effectiveness of each algorithm under a variety of conditions, with the MPF being the most accurate.
EEG feature extraction for classifying emotions using FCM and FKM (2008)

The Electroencephalogram (EEG) is one of the useful biosignals detect the human emotions. This paper discusses on a research conducted to determine the changes in the electrical activity of the human brain related to distinct emotions. We designed a competent acquisition protocol for acquiring the EEG signals under audio-visual induction environment. The EEG data has been collected from 6 healthy subjects with in an age group of 21-27 using 63 biosensors. From the subjective analysis on each emotion, three emotions have been identified with higher agreement. After preprocessing the signals, discrete wavelet transform is employed to extract the EEG parameters. The feature vectors derived from the above feature extraction method on 63 biosensors form an input matrix for emotion classification. In this work, we have used Fuzzy C-Means (FCM) and Fuzzy k-Means (FKM) clustering methods for classifying the emotions. We have also analyzed the performance of FCM and FKM on reduced number of 24 biosensors model. Finally, we compared the performance of clustering the discrete emotions using FCM and FKM on both 64 biosensors and 24 biosensors. Results confirm the possibility of using wavelet transform based feature extraction for assessing the human emotions from EEG signal, and of selecting a minimal number of channels for emotion recognition experiment.
A design of polygonal micro-ring cavities for photonic integrated circuits (1996)

Summary form only given. In this paper, we present a model of polygonal shaped ring cavities for reducing a scattering loss as well as for resonant mode control. An optimal cavity design will be discussed to realize a high finesse micro-ring semiconductor cavity.
Phase-transition induced giant negative electrocaloric effect in a lead-free relaxor ferroelectric thin film (2019)

Ferroelectric/antiferroelectric thin/thick films with large positive or negative electrocaloric (EC) effects could be very useful in designing commercial refrigeration devices.
CCDC 863202: Experimental Crystal Structure Determination (2012)

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Flypapers for Coral and Other Planktonic Larvae (1996)

any animals in the sea reproduce to yield vast numbers of minute, weakly swimming larvae that remain arrested in development while they are dispersed in the plankton. In many species, the larvae settle randomly and then continue to develop, but in other species the larvae emerge from developmental arrest only after settling in a particular microhabitat that is suitable for their postmetamorphic growth and survival to reproduction. What cues might indicate to such larvae that they have reached the appropriate environment? We and other investigators have found that these larvae recognize specific chemical signals from the environment that induce settlement from the plankton and metamorphosis to the adult form. This requirement helps ensure that the larvae settle and metamorphose selectively in the most suitable microhabitats.
Cocaine Use in the Past Year Is Associated With Altitude of Residence (2012)

This study demonstrates a significant correlation between altitude of substate region of residence and incidence of cocaine use. It is possible that stress response due to hypoxia is responsible; however, this requires further investigation. However, because other substance use was not assessed, specificity of this association is unknown. In addition, this correlation may help explain the increased rate of suicide in areas of higher elevation.
Architecture of Security Faults and Its Diagnosis in Connecting Electric Vehicle to the Charging Station (2018)

The charging infrastructure for electric vehicle plays significantly a crucial role in their development and substantial growth in the market. The configuration of a charging station may vary in different countries depending on its specifications, communication and connector standards, electrical grid etc. The electric vehicle standards are mentioned in many articles, but a limited information is available on security faults that may present in connecting electric vehicle to the charging station. Keeping this in view the present manuscript discusses the protocols and faults which may exist in connecting charger to electric vehicle and its diagnostic methods with the communication interface required between the charger, battery management system and electric vehicle.
Versatile vector suite for the extracytoplasmic production and purification of heterologous His-tagged proteins in Lactococcus lactis (2015)

Recent studies have shown that the Gram-positive bacterium Lactococcus lactis can be exploited for the expression of heterologous proteins; however, a versatile set of vectors suitable for inducible extracellular protein production and subsequent purification of the expressed proteins by immobilized metal affinity chromatography was so far lacking. Here we describe three novel vectors that, respectively, facilitate the nisin-inducible production of N- or C-terminally hexa-histidine (His6)-tagged proteins in L. lactis. One of these vectors also encodes a tobacco etch virus (TEV) protease cleavage site allowing removal of the N-terminal His6-tag from expressed proteins. Successful application of the developed vectors for protein expression, purification and/or functional studies is exemplified with six different cell wall-bound or secreted proteins from Staphylococcus aureus. The results show that secretory production of S. aureus proteins is affected by the position, N- or C-terminal, of the His6-tag. This seems to be due to an influence of the His6-tag on protein stability. Intriguingly, the S. aureus IsdB protein, which is phosphorylated in S. aureus, was also found to be phosphorylated when heterologously produced in L. lactis, albeit not on the same Tyr residue. This implies that this particular post-translational protein modification is to some extent conserved in S. aureus and L. lactis. Altogether, we are confident that the present vector set combined with the L. lactis expression host has the potential to become a very useful tool in optimization of the expression, purification and functional analysis of extracytoplasmic bacterial proteins.
Direct Electrophilic Monofluoromethylation (2008)

Monofluoromethyl derivatives of various nucleophiles have been synthesized using a new electrophilic monofluoromethylating reagent developed. The S-(monofluoromethyl)diarylsulfonium tetrafluoroborate has been shown to be effective for the introduction of an electrophilic monofluoromethyl group into C, S, O, N, and P nucleophiles. This methodology has been expanded for the synthesis of various biologically important compounds.
Meu10 is required for spore wall maturation in Schizosaccharomyces pombe (2002)

Meu10 is a spore wall component and plays a pivotal role in the formation of the mature spore wall structure.
Robust scheduling and disruption recovery for airlines (2009)

Airline planning include complex and structured operations that must be planned in advance in order to exploit the available resources, provide a reliable and competitive service and forecast system's performances. Decisions regarding operations are based on data which is frequently due to uncertainty. Moreover, unpredicted events may disrupt the current schedule and force managers to take reactive decisions to recover to an operational state. On the other hand, proactive decisions, i.e. decisions which take into account the uncertainty of the data, tend to robust solutions which are able to absorb data deviation and small disruptions. In this talk we address the aircraft routing problem from both reactive and proactive point of view and suggest ways to integrate the two approaches to reach what we call a robust recoverable approach for aircraft routing, i.e. a proactive strategy which accounts for the presence of a disruption recovery strategy. We validate our ideas with a computational study based on real world data provided by a major european airline.
Experimental Validation of Ultrasonic Imaging Using Topological Derivative (2022)

We investigated an array ultrasonic imaging method using the topological derivative. The topological derivative is formulated based on the sensitivity of the cost functional associated with the inverse scattering problem due to the creation of an infinitesimal rigid inclusion. To calculate the topological derivative, time convolutions of a free field and a supplementary adjoint field are required. In this study, scattered waves from flaws were received with an array transducer, then the supplementary adjoint field using the measured waves was calculated in the framework of the finite integration technique (EFIT). Finally, flaw imaging was performed by plotting the obtained topological derivative in the target region.
TIEMPO: temporal modeling and authoring of interactive multimedia (2002)

Future multimedia titles will provide many ways to interact with the presented information. When creating an interactive multimedia title, the author has to specify the temporal layout and the interaction elements, However, this part of the authoring process is not trivial as the temporal layout and the interaction forms are not independent because some interaction forms affect the presentation schedule of the title. The paper identifies various temporal interaction forms and their temporal dependencies, an integrated model for time and interaction is proposed, and we show how this model is applied to ease rapid authoring of multimedia titles.
Metastable Ge1–xCx Alloy Nanowires (2011)

Carbon-containing alloy materials such as Ge(1-x)C(x) are attractive candidates for replacing silicon (Si) in the semiconductor industry. The addition of carbon to diamond lattice not only allows control over the lattice dimensions, but also enhances the electrical properties by enabling variations in strain and compositions. However, extremely low carbon solubility in bulk germanium (Ge) and thermodynamically unfavorable Ge-C bond have hampered the production of crystalline Ge(1-x)C(x) alloy materials in an equilibrium growth system. Here we successfully synthesized high-quality Ge(1-x)C(x) alloy nanowires (NWs) by a nonequilibrium vapor-liquid-solid (VLS) method. The carbon incorporation was controlled by NW growth conditions and the position of carbon atoms in the Ge matrix (at substitutional or interstitial sites) was determined by the carbon concentration. Furthermore, the shrinking of lattice spacing caused by substitutional carbon offered the promising possibility of band gap engineering for photovoltaic and optoelectronic applications.