Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterizing Tyrosine Phosphorylation Signaling in Lung Cancer Using SH2 Profiling

Background Tyrosine kinases drive the proliferation and survival of many human cancers. Thus profiling the global state of tyrosine phosphorylation of a tumor is likely to provide a wealth of information that can be used to classify tumors for prognosis and prediction. However, the comprehensive analysis of tyrosine phosphorylation of large numbers of human cancer specimens is technically challenging using current methods. Methodology/Principal Findings We used a phosphoproteomic method termed SH2 profiling to characterize the global state of phosphotyrosine (pTyr) signaling in human lung cancer cell lines. This method quantifies the phosphorylated binding sites for SH2 domains, which are used by cells to respond to changes in pTyr during signaling. Cells could be grouped based on SH2 binding patterns, with some clusters correlated with EGF receptor (EGFR) or K-RAS mutation status. Binding of specific SH2 domains, most prominently RAS pathway activators Grb2 and ShcA, correlated with EGFR mutation and sensitivity to the EGFR inhibitor erlotinib. SH2 binding patterns also reflected MET activation and could identify cells driven by multiple kinases. The pTyr responses of cells treated with kinase inhibitors provided evidence of distinct mechanisms of inhibition. Conclusions/Significance This study illustrates the potential of modular protein domains and their proteomic binding profiles as powerful molecular diagnostic tools for tumor classification and biomarker identification.
Investigation of Structure and Function of a Catalytically Efficient Variant of the Human Flavin-Containing Monooxygenase Form 3

To characterize the contribution of amino acid 360 to the functional activity of the human flavin-containing monooxygenase form 3 (FMO3) and form 1 (FMO1) in the oxygenation of drugs and chemicals, we expressed four FMO3 variants (i.e., Ala360-FMO3, His360-FMO3, Gln360-FMO3, and Pro360-FMO3) and one FMO1 variant (i.e., Pro360-FMO1) and compared them to wild-type enzymes (Leu360-FMO3 and His360-FMO1, respectively). The amino acid substitutions were introduced into wild-type FMO3 or FMO1 cDNA by site-directed mutagenesis. The thermal stability of variants of Leu360 FMO3 was also studied, and the thermal stability was significantly different from that of wild-type FMO3. The influence of different substrates to modulate the catalytic activity of FMO3 variants was also examined. Selective functional substrate activity was determined with mercaptoimidazole, chlorpromazine, and 10-[(N,N-dimethylaminopentyl)-2-(trifluoromethyl)]phenothiazine. Compared with wild-type FMO3, the Ala360-FMO3 and His360-FMO3 variants were less catalytically efficient for mercaptoimidazole S-oxygenation. N-Oxygenation of chlorpromazine was significantly less catalytically efficient for His360-FMO3 compared with wild-type FMO3. Human Pro360-FMO1 was significantly more catalytically efficient at S-oxygenating mercaptoimidazole and chlorpromazine compared with wild-type FMO1. The data support the mechanism that the Pro360 loci affect thermal stability of FMO3. Because different amino acids at position 360 affect substrate oxygenation in a unique fashion compared with that of FMO3 stimulation, we conclude that the mechanism of stimulation of FMO3 is distinct from that of enzyme catalysis. A molecular model of human FMO3 was also constructed to help explain the results. The increase in catalytic efficiency observed for Pro360 in human FMO3 was also observed when the His of FMO1 was replaced by Pro at loci 360.
Dual-arm framework for cooperative applications

This paper presents a framework schema that allows to bring simulation results obtained from different dual-arm robotic applications to executions in real environments. The framework uses the Robot Operating System (ROS) to communicate each component of the dual-arm, and the robotic software tool The Kautham Project for the computation of motion paths, inverse kinematics validations, collision checking and the graphical visualization of the simulated environment. The Anthropomorphic Dual Arm Robotic System (ADARS) was used in this work which is composed of two robotic arms of 6 degree of freedom, two anthropomorphic hands, and tactile sensors in the fingertips. The real execution of two different applications are presented to show the robustness of the framework. The resulting framework is general enough, allowing the reimplementation with minimum changes in any other dual-arm system.
BUILDING RECONSTRUCTION USING PLANAR FACES IN VERY HIGH DENSITY HEIGHT DATA

The point densities obtained by airborne laser scanner systems are increasing rapidly. When used for the 3D reconstruction of buildings the increasing amounts of points contain more and more information about the shape of buildings. Therefore methods for 3D reconstruction can be more data driven and need less specific object models. In this paper an approach is presented which is based on the detection and outlining of planar faces in dense height data. To avoid loss of information due to interpolation, all operations are performed on the Delaunay triangulation of the original height points. The planes of the faces are determined by clustering of the points. The outlines of the faces are determined by a connected component analysis on the triangles of the Delaunay triangulation. Only a limited amount of generic knowledge is used in the reconstruction. Apart from the assumption that a building can be described by planar faces, it is assumed that there exists a main orientation of the building and that all edges where discontinuities in height occur are either parallel or perpendicular to that orientation. Several results are presented and the pros and cons of the approach are discussed. The conclusion is that building reconstruction from laser altimetry data becomes a strong alternative for semi-automated mapping in images.
Autonomous Underwater Vehicle Motion Tracking using a Kalman Filter for Sensor Fusion

AUVs are ideal platforms for search and rescue operations. They can also be used for inspection of underwater terrains. These vehicles need to be autonomous and robust to cope with unpredictable current and high pressures. In this paper it will be shown how a Kalman filter is used to estimate the position of an autonomous vehicle in a three dimensional space. The Kalman filter is used to estimate movement and position using measurements from multiple sensors.
Spectrofluorometers Are Not Adequate for Aging Aedes and Culex (Diptera: Culicidae) Using Pteridine Fluorescence

Abstract Attempts were made to use pteridine fluorescence levels as a tool for aging individual Aedes polynesiensis Marks and Culex quinquefasciatus Say mosquitoes. Fluorescent pigments were extracted and quantified with techniques and apparatus (i.e., a spectrofluorometer) that can be used in developing countries or in field laboratories, and that has already given consistent results in similar studies on other insect groups. However, for Ae. polynesiensis as well as Cx. quinquefasciatus, individual fluorescence measurements were mostly below the spectrofluorometer white noise level. With batches of Aedes or Culex of the same age, significant fluorescence levels were recorded but not in relation to their calendar ages. The low content of pteridines in mosquitoes suggests that standard spectrofluorometry is not sufficiently sensitive for such studies.
Plasmonic and bolometric terahertz detection by graphene field-effect transistor

Polarization dependence analysis of back-gated graphene field-effect transistor terahertz responsivity at frequencies ranging from 1.63 to 3.11 THz reveals two independent mechanisms of THz detection by graphene transistor: plasmonic, associated with the transistor nonlinearity, and bolometric, caused by graphene sheet temperature increase due to THz radiation absorption. In the bolometric regime, electron and hole branches demonstrate a very different response to THz radiation, which we link to the asymmetry of the current-voltage characteristics temperature dependence with respect to the Dirac point. Obtained results are important for development of high-efficiency graphene THz detectors.
A real-time curb detection and tracking method for UGVs by using a 3D-LIDAR sensor

Environment perception is essential for autonomous driving technology. The curb is a prominent feature of urban roads and therefore is a significant part of environment perception. In this paper, a real-time curb detection and tracking method is proposed for Unmanned Ground Vehicles (UGVs). The proposed curb detection algorithm uses the the surrounding environment data provided by a 3D-LIDAR sensor to extract the curb position based on its spatial features. The curb tracking algorithm is proposed to predict and update the curb position with respect to the current vehicle states in real time. The performance of the proposed method is verified through extensive experiments with a UGV driving on campus roads. The experimental results demonstrate the accuracy and robustness of the proposed method.
The microbial ecology of anaerobic digestion: characterising novel biogas configurationsthrough molecular and statistical methods

Title The microbial ecology of anaerobic digestion: characterising novel biogas configurations through molecular and statistical methods Author(s) FitzGerald, Jamie A. Publication date 2018 Original citation FitzGerald, J. A. 2018. The microbial ecology of anaerobic digestion: characterising novel biogas configurations through molecular and statistical methods. PhD Thesis, University College Cork. Type of publication Doctoral thesis Rights © 2018, Jamie A. FitzGerald. http://creativecommons.org/licenses/by-nc-nd/3.0/
Partial Differential Equations to Diffusion-Based Population and Innovation Models

Multiple instances and diffusion mechanisms in biological and economic modeling involve partial differential equations (PDEs). Functional PDEs (with time delays) may be even more adequate to real world problems. In the modeling process, PDEs can also formalize behaviors, such as the logistic growth of populations with migrations, and the adopters’ dynamics of new products in innovation models. In biology, these events are then related to the variations in the environment, the population densities and overcrowding, the migrations and spreading of humans, animals, plants and other cells and organisms. In economics and management science, the diffusion processes of technological innovations in the marketplace (e.g. the mobile phone) is a major subject. Moreover, these innovation diffusion models refer mainly to epidemic models. This contribution introduces to this modeling process with PDEs and reviews the essential features of the dynamics in biological, ecological and economic modeling. The computations are carried out by using the software WolframMATHEMATICA® 7. Key-Words: Diffusion process, partial differential equation, reaction-diffusion equation, traveling wave solution, critical patch size, population dynamics, innovation diffusion.
Index-based model clone detection

Existing algorithms for model clone detection operate in batch mode. Consequently, if a small part of a large model changes during maintenance, the entire detection needs to be recomputed to produce updated cloning information. Since this can take several hours, the lack of incremental detection algorithms hinders clone management, which requires up-to-date cloning information. In this paper we present an index-based algorithm for model clone detection that is incremental and distributable. We present a case study that demonstrates its capabilities, outline its current limitations and present directions for future work.
Treatment of psoriasis vulgaris with cyclo- sporine and methotrexate injections using the MMP® technique

Systemic oral medications – such as cyclosporine (CYA) or methotrexate (MTX) – for the treatment of psoriasis have limited bioavailability due to incomplete gastrointestinal absorption and first-pass hepatic metabolism. Moreover, they are associated with adverse effects. The application of CYA or MTX using the microinfusion of drugs into the skin method (MMP®) for the treatment of psoriasis vulgaris yielded a therapeutic response with significant reduction of lesions, and absence of side effects. In the present report, the authors describe 4 cases of psoriasis vulgaris treated using the MMP® method, with the application of CYA or MTX
swissPIT: a novel approach for pipelined analysis of mass spectrometry data

The identification and characterization of peptides from tandem mass spectrometry (MS/MS) data represents a critical aspect of proteomics. Today, tandem MS analysis is often performed by only using a single identification program achieving identification rates between 10-50% (Elias and Gygi, 2007). Beside the development of new analysis tools, recent publications describe also the pipelining of different search programs to increase the identification rate (Hartler et al., 2007; Keller et al., 2005). The Swiss Protein Identification Toolbox (swissPIT) follows this approach, but goes a step further by providing the user an expandable multi-tool platform capable of executing workflows to analyze tandem MS-based data. One of the major problems in proteomics is the absent of standardized workflows to analyze the produced data. This includes the pre-processing part as well as the final identification of peptides and proteins. The main idea of swissPIT is not only the usage of different identification tool in parallel, but also the meaningful concatenation of different identification strategies at the same time. The swissPIT is open source software but we also provide a user-friendly web platform, which demonstrates the capabilities of our software and which is available at http://swisspit.cscs. ch upon request for account.
ATF4 is an oxidative stress–inducible, prodeath transcription factor in neurons in vitro and in vivo

Oxidative stress is pathogenic in neurological diseases, including stroke. The identity of oxidative stress–inducible transcription factors and their role in propagating the death cascade are not well known. In an in vitro model of oxidative stress, the expression of the bZip transcription factor activating transcription factor 4 (ATF4) was induced by glutathione depletion and localized to the promoter of a putative death gene in neurons. Germline deletion of ATF4 resulted in a profound reduction in oxidative stress–induced gene expression and resistance to oxidative death. In neurons, ATF4 modulates an early, upstream event in the death pathway, as resistance to oxidative death by ATF4 deletion was associated with decreased consumption of the antioxidant glutathione. Forced expression of ATF4 was sufficient to promote cell death and loss of glutathione. In ATF4−/− neurons, restoration of ATF4 protein expression reinstated sensitivity to oxidative death. In addition, ATF4−/− mice experienced significantly smaller infarcts and improved behavioral recovery as compared with wild-type mice subjected to the same reductions in blood flow in a rodent model of ischemic stroke. Collectively, these findings establish ATF4 as a redox-regulated, prodeath transcriptional activator in the nervous system that propagates death responses to oxidative stress in vitro and to stroke in vivo.
The Impact of Incorrect Training Sets and Rolling Collections on Technology-Assisted Review.

Document classification and machine learning technology in electronic discovery (eDiscovery) are gaining attention under new names such as technology-assisted review (TAR), machineassisted review (MAR), computer-assisted review (CAR) and predictive coding [2]. Several judicial rulings have addressed typical legal concerns in relation to the quality of machine learning. In this paper, we address two of such concerns and investigate their relation with machine learning quality in more detail. The topics of interest of this paper are: (i) the impact of the quality of training documents on the overall classification results, which can be measured by investigating the impact of training supervised classifiers deliberately with wrong training samples and (ii) using machine learning in so-called rolling collections, which can be measured by investigating the quality of classification of new and unknown documents, which have not been used to extract or select machine-learning features, with existing classifiers. A machine learning pipeline with the most-common used document feature-extraction techniques known as a bag-of-word (BoW), and Term FrequencyInverse Document Frequency (TFIDF) is used [9]. For feature-selection, vector logarithmic normalization and cut-off of non-used or non-relevant dimensions has been selected. The resulting data was used to train binary classifiers for each category using Support Vector Machines (SVM). Documents for the experiments came from the Reuters RCV1 corpus. We found that in this model: (i) the impact of wrong training documents was smaller than expected: inserting up to 25% wrong training documents resulted only in 3-5% less classification quality, and (ii) that using BoW and TF-IDF based classifiers lost up to 50% in quality when used on completely new documents, such as in a rolling collection.
Exploiting item co‐utility to improve collaborative filtering recommendations

In this article we study the extent to which the interplay between recommended items affect recommendation effectiveness. We introduce and formalize the concept of co‐utility as the property that any pair of recommended items has of being useful to a user, and exploit it to improve collaborative filtering recommendations. We present different techniques to estimate co‐utility probabilities, all of them independent of content information, and compare them with each other. We use these probabilities, as well as normalized predicted ratings, in an instance of an NP ‐hard problem termed the Max‐Sum Dispersion Problem (MSDP). A solution to MSDP hence corresponds to a set of items for recommendation. We study one heuristic and one exact solution to MSDP and perform comparisons among them. We also contrast our solutions (the best heuristic to MSDP) to different baselines by comparing the ratings users give to different recommendations. We obtain expressive gains in the utility of recommendations and our solutions also recommend higher‐rated items to the majority of users. Finally, we show that our co‐utility solutions are scalable in practice and do not harm recommendations' diversity.
Lean Thinking Process in the Determination of Design Suggestions to Optimize Treatment of WEEE

This work proposes a set of actions to assist redesign procedure in existing products of Electric and Electronic Equipment (EEE). The aim is to improve their environmental behavior after their withdrawal in the End-of-Life (EOL) phase. In the beginning data collection takes place. Then follows selection and implementation of the optimal EOL Treatment Strategy (EOL_TS) and its results’ evaluation concerning the environment. In parallel, product design characteristics that can be altered are selected based on their significance for the environment in the EOL stage. All results from the previous stages are combined and possible redesign actions are formulated for further examination and afterwards configuration in the design stage. The applied method to perform these tasks is Lean Thinking (LT). At the end, results concerning the application of the proposed method on a distribution transformer are presented. Keywords—End-of-life treatment, Lean thinking, WEEE
Demystifying Content Analysis

Objective. In the course of daily teaching responsibilities, pharmacy educators collect rich data that can provide valuable insight into student learning. This article describes the qualitative data analysis method of content analysis, which can be useful to pharmacy educators because of its application in the investigation of a wide variety of data sources, including textual, visual, and audio files. Findings. Both manifest and latent content analysis approaches are described, with several examples used to illustrate the processes. This article also offers insights into the variety of relevant terms and visualizations found in the content analysis literature. Finally, common threats to the reliability and validity of content analysis are discussed, along with suitable strategies to mitigate these risks during analysis. Summary. This review of content analysis as a qualitative data analysis method will provide clarity and actionable instruction for both novice and experienced pharmacy education researchers.
Long-Term Outcome after Local Intra-Arterial Fibrinolysis of Basilar Artery Thrombosis

Thrombolytic therapy of acute basilar artery (BA) thrombosis has been shown to reduce mortality and avoid a fatal outcome. Objective of this study was to investigate the long-term clinical outcome following intra-arterial fibrinolysis of occlusions of the BA. We retrospectively analyzed the clinical records and neuroradiologic results of 20 consecutive patients who had intra-arterial fibrinolysis of acute occlusions of the BA between 1982 and 1990. All patients were followed neurologically for a period of up to 12 years, including assessment of the Barthel index (BI) and brain CT or MRI studies. At the time of treatment, 6 patients were somnolent and 14 comatose, and tetraparesis was present in 15. The time between the onset of symptoms and treatment ranged from 1 to 48 h. The mortality rate was 35% (7/20 patients). Functional outcome was excellent in 9, 78%, of 13 survivors (BI <85). During the cumulative follow-up period (125 patient years) there was 1 death from myocardial infarction and 1 death from pneumonia. Vascular events during follow-up were myocardial infarction (n = 3) and a single cerebral transient ischemic attack. Despite the fact that our series was biased towards patients with severe symptoms, 65% (13/20) survived, and 78% of the survivors reached independence in daily life. These results provide evidence that local fibrinolysis of BA occlusion reduces mortality, and the long-term prognosis of the survivors is better than previously thought. None of our patients had a further stroke during the follow-up period, which indicates that acute BA occlusion is not a strong indicator for advanced arteriosclerotic disease.
Model predictive current control of a grid connected converter with LCL-filter

A method to control the output current of a three-phase grid-tied inverter is presented. An LCL-filter is used to reduce the current distortion injected into the grid. The objective is to minimise current distortion and switching frequency to reduce losses. The control approach is based on finite control set model predictive control with sphere decoding to make the problem computationally tractable for long horizons. A mathematical model was derived that extends on previous work by incorporating the effect of a grid-voltage to the system. The control strategy was evaluated through simulation. The results indicate that this control strategy can achieve the objectives for its application mentioned in the paper.