Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical, Electrocardiographic, and Angiographic Characteristics as Predictors of Procedural Success in Patients with Coronary Chronic Total Occlusions A Single-Center Experience

Department of Medicine College of Medicine University of Baghdad. challenge. Indeed, the most common reason for referral to bypass surgery or exclusion from clinical studies comparing outcomes of angioplasty to bypass surgery has been the presence of a CTO (1,2) . Anatomically, CTOs typically consist of a hard fibro-calcific proximal cap, a distal cap with generally less fibrotic material, and a central area of organized thrombus (3) . Indications for opening CTOs include relief of angina, evidence of ischemia in asymptomatic patients, to improve left ABSTRACT: BACKGROUND: Percutaneous coronary intervention for chronic total occlusion lesions is technically difficult despite equipment advances. Changes in electrocardiographic patterns such as Q wave during total occlusion can provide information about procedural success and myocardial viability. OBJECTIVE: The aims of study are to investigate clinical, electrocardiographic and procedural characteristics of chronic total occlusion and the relation of these variables to the procedural success rate. PATIENTS AND METHODS: In this study, clinical, electrocardiographic and coronary angiographic data of (100) patients with chronic total occlusion lesions who underwent percutanous coronary intervention between May 2010 and March 2011 at the Iraqi center for heart diseases were analyzed. The clinical data were collected using the patients’ files and angiographic data by the observation of their films. Chronic total occlusion was diagnosed from clinical events including myocardial infarction or worsening of their symptoms or previous angiography. RESULTS: There were 100 patients with chronic total occlusion. Successful recanalization with stent deployment was accomplished in 65 patients (65%), while unsuccessful recanalization was found in 35 patients (35%). No major cardiovascular events occurred among both groups. The success rate of PCI was significantly more in lesions shorter than 15 mm, presence of tapered stump, angulations less than 45 degree, duration less than 3 months and TIMI 1 flow grade (p values were significant). Presence of Q wave was associated with severe angina , decreased left ventricular ejection fraction, critical lesions other than chronic total occlusion, T wave inversion and more regional wall motion abnormalities ( p values were significant). The most common cause of procedural failure was inability of guide wire to cross through the totally occluded segment. CONCLUSION: Percutaneous coronary intervention is a safe and useful procedure for revascularization of coronary chronic total occlusion lesion. The procedural success rate was related to certain features of the totally occluded lesions.
Protein variety and functional diversity: UniProtKB/Swiss-Prot annotation in its biological context

We all know that the dogma ‘one gene, one protein’ is obsolete. A functional protein and, likewise, a protein’s ultimate function depend not only on the underlying genetic information but also on the ongoing conditions of the cellular system. Frequently the transcript, like the polypeptide, is processed in multiple ways but only one or a few out of a multitude of possible variants are produced at a time. An overview on processes that can lead to sequence variety and structural diversity in eukaryotes is given. The UniProtKB/Swiss-Prot protein knowledgebase provides a wealth of information regarding protein variety, function and associated disorders. Examples for such annotation are shown and further ones are available at http://www.expasy. org/sprot/tutorial/examples_CRB.
Optimal trajectory planning in partially observable environments under bounded actuation

—Optimal motion planning under uncertainty is a challenging problem, in particular if the optimization has to be performed on the belief space. One state of the art approach to this problem is an iterative version of the LQG algorithm. However, this method assumes unbounded actuation. This paper proposes a constrained version of this algorithm, designated here ciLQG, by integrating a Primal-dual interior-point method, to cope with arbitrary inequality constraints, such as bounded actuation, into an iterative LQG (iLQG) algorithm. As in iLQG, the locally optimal solution is computed using a continuous POMDP framework and the belief dynamics are computed using an EKF and approximate the user deﬁned value function to a quadratic function which is valid in the vicinity of a nominal trajectory. Simulation results illustrate the advantages of the proposed approach.
RADIO WAVE PROPAGATION IN URBAN ENVIRONMENTS

This work consists on the investigation and analysis of some aspects related to electromagnetic wave propagation in presence of the Earth and atmosphere. To accomplish that, MATLAB simulations are developed to allow a better comprehension of the different radio wave propagation phenomena that occur in certain environments. The simulations are based on the following features: representation of the electric field interference pattern due to ground reflection, representation of the electric field close to obstacles, ray tracing in a horizontally stratified atmosphere, visualization of the effects caused by the inversion of the refraction index in the atmosphere (mirages), and evolution of the electric field in an urban environment (mobile communications scenario), according to an empirical and theoretical model.
Valuing Health States using the MACBETH non-numerical approach

Quality-adjusted life years (QALYs), a measure commonly used in health technology appraisals, incorporates in a summary index changes in quantity and in quality of life. The use of QALYs requires the modelling of individuals’ quality of life for distinct health states into utility-based QALY scores, with preference elicitation methods such as the Visual Analogue Scale, the Time Trade-Off (TTO) and the Standard Gamble. Given that these numerical elicitation methods may be associated with a high cognitive effort and their results may be differentiated by individual’s and population’s numeracy, in this study we explore the use of the MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) non-numerical approach to evaluate health states. A new protocol for preference elicitation based on the MACBETH approach (only requiring qualitative judgments) was developed and tested in a web survey alongside with TTO in a sample of the Portuguese general population (n=243). The web-survey asked individuals to value directly 25 different EQ-5D health states with the two methods, as well as for their preferred method. Individuals’ numeracy was also assessed. As key results, we found out that: the mean values derived from MACBETH and TTO are strongly correlated (Pearson r = 0.962); participants with higher and lower levels of numeracy preferred expressing value judgments with MACBETH; and mean values obtained differed on the basis of numeracy level. Results suggest that it is worth considering the use of non-numerical preference elicitation methods in health. Further research may be directed to understand eventual advantages of non-numerical methods in special disease populations, diseases states and across population from different countries.
Entity Triggers: Learning with Explanations for Named Entity Recognition

Training neural models for named entity recognition (NER) in a new domain often requires additional human annotations (e.g., tens of thousands of labeled instances) that are usually expensive and time-consuming to collect. Thus, a crucial research question is how to obtain supervision in a cost-eﬀective way. In this paper, we introduce “entity triggers”, an eﬀective proxy of human explanations for facilitating label-eﬃcient learning of NER models. An entity trigger is deﬁned as a group of words in a sentence that helps to explain why a human would recognize an entity in the sentence. Individual entity annotations provide limited explicit supervision. Entity-trigger annotations add in complementary supervision signals and thus helps the model to learn and generalize more eﬃciently. We crowd-sourced 14k entity triggers for two well-studied NER datasets and exploited these triggers to rapidly build high-performance neural NER models. We propose a novel framework, named Trigger Matching Network , which jointly learns trigger representations and soft matching module with self-attention such that can generalize to unseen sentences easily for tagging. Experiments show that our framework is signiﬁcantly more cost-eﬀective such that using 20% of the trigger-annotated sentences can result in a comparable performance of conventional supervised approaches using 70% training data. We will publicly release the collected entity triggers and our code 1 .
Analysis of Radio Repeaters in UMTS

This thesis analyses repeaters in UMTS and their impact on coverage, capacity and Quality of Service. For this purpose, a single user model was developed in order to calculate the maximum repeater radius. A more realistic approach was taken with the development of a multiple users simulator. Using these tools, the impact of the variation of several parameters was analysed. The single user results show that, in Release 99 and for a pedestrian environment, the increase in the repeater gain leads to an increase in the repeater radius of up to 2.2 times. In HSDPA and HSUPA this value is 2.8 and 3.5 times, respectively. The multiple users results show that, in Release 99, the repeater increases the number of covered users by 7.3%, in the most favourable conditions. In HSDPA this growth can go as far as 5.0%, and in HSUPA up to 20.0%. Results also show that the repeater has no impact on both capacity and Quality of Service.
Technology Dimensioning Model for an IP/MPLS NGN (Next Generation Networking)

Dimensioning models are essential for network providers with the objective of minimizing the CAPEX, increasing the network robustness in terms of resources and resilience to failures. The purpose of this work is to implement survivability to an existent dimensioning model. With this objective, the study of routing algorithms and mechanisms of survivability are in focus. It is approached the concept of Constraint-Routing that intends to introduce some limitations to the routing. The constraint in focus is the residual capacity of a network link. The algorithm for computing disjoint paths is important for survivability analysis. The survivability is implemented to guarantee end-to-end maximum bandwidth, obtaining a service path and a protection path that are able to carrier a certain traffic flux. The costs increase since it is dependent of the allocated load. The linear 1+1 path protection requires a huge investment by the service network provider. The 1:1 protection outputs the blocking ratio if it is intended to setup a path under capacity planning conditions. Keywords—Network planning, Backbone, Service network, Multi-Protocol Label Switching, Survivability, Routing algorithms
A hybrid gradient method for strictly convex quadratic programming

In this article, we present a reliable hybrid algorithm for solving convex quadratic minimization problems. At the kth iteration, two points are computed: first, an auxiliary point x˙k is generated by performing a gradient step using an optimal steplength, and second, the next iterate xk + 1 is obtained by means of weighted sum of x˙k with the penultimate iterate xk − 1. The coefficient of the linear combination is computed by minimizing the residual norm along the line determined by the previous points. In particular, we adopt an optimal, nondelayed steplength in the first step and then use a smoothing technique to impose a delay on the scheme. Under a modest assumption, we show that our algorithm is Q‐linearly convergent to the unique solution of the problem. Finally, we report numerical experiments on strictly convex quadratic problems, showing that the proposed method is competitive in terms of CPU time and iterations with the conjugate gradient method.
Communication Security in Wireless Sensor Networks

With the increasing usage of wireless sensor networks, it is necessary to ensure the basic security properties for the data communication, particularly in applications where the communication exchanged is sensitive. This work analyses the particular problem of communication security for a system that has several wireless sensor networks, and presents a solution for it. The proposed solu-tion is implemented and its operation analyzed.
Automatic Parameter Tuning of Algorithms using Optimization

The Adaptive Monte Carlo Localization algorithm is a well-known approach for performing the localization of a robot using a particle filter. The Adaptive Monte Carlo Localization have some parameters which boost the performance but at the expense of an increase in computational resources. In this thesis, the multi-objective optimization of the Adaptive Monte Carlo Localization algorithm parameters was performed, using a state of the art algorithm, the Predictive Entropy Search for Multi-objective Bayesian Optimization. In order to do so, a framework for single objective optimization was extended. The added output of this framework is a Pareto front where the user can select the desired resources and get the parameter set that is optimal for that particular setup. One of the objective functions used in the multi-objective optimization is the position error of the robot. Since its computation normally requires expensive tracking hardware, a method for estimating the robot’s two dimensional pose error using the Iterative Closest Point algorithm, is proposed and validated.
PCI Conﬂict and RSI Collision Detection in LTE Networks Using Supervised Learning Techniques

—This work tests three hypotheses regarding how well two distinct Long Term Evolution (LTE) network problems can be detected through supervised techniques with near real time performance. The tested network problems are Physical Cell Identity (PCI) conﬂicts and Root Sequence Index (RSI) collisions and were labeled through conﬁgured cell relations that veriﬁed these two conﬂicts. Furthermore, a real LTE network was used. The obtained results showed that both problems were best detected by using each Key Performance Indicator (KPI) measurement as an individual feature. The highest average Precision obtained for PCI conﬂict detection was 31% and 26% for the 800 MHz and 1800 MHz frequency bands, respectively. The highest average Precision obtained for RSI collision detection was 61% and 60% for the 800 MHz and 1800 MHz frequency bands, respectively.
Clustering of movement proﬁles of motor-impaired peoplefrom 2D image streams

—Ageing, motor disorders and accidents are some possible causes that lead people to require help from caregivers, being impossible for patients to have autonomy. Assistive robots have been developed to help them in tasks such as feeding. However, as each patient is a different case, so it is imperative to classify them and adapt the technology to better serve their needs. The aim of this work was a methodology which focused on classifying different subjects based on the manifestation of their disabilities in a speciﬁc setup. This would enable a better adaptation of robotic systems to adapt to each patient and consequently improve their performance. To achieve this result, a data set was created with recordings of people with and without physical limitations, while performing given tasks. Data from speciﬁc points was acquired from these videos using a facial landmark detector. Nevertheless, this data was incomplete, and so a matrix completion procedure with a Structure from Motion framework was used. Afterwards, the trajectories of the subjects were encoded onto two different features. These features were then used to build a classiﬁer, based on the Bag of Words model, aiming to discern the different types of subjects depending on their performance. During the clustering phase, it was possible to identify speciﬁc patterns associated to speciﬁc type of subjects. The results obtained were quite promising as they proved that the feasibility this study.
A VIDEO CHARGE-PUMP PHASE-LOCKED LOOP WITH LEAKAGE COMPENSATION IN 0.13µm CMOS TECHNOLOGY

—In deep sub-micrometer CMOS processes the leakage currents have become an issue in the design of analog integrated circuits. This is due to the thin gate oxide and small subthreshold voltages of transistors. PLLs are not exception, since leakage currents are the main causers of jitter in the output signal of these systems. With the goal of reducing the jitter caused by leakage currents, a new compensation system is proposed, that is based on a conventional video CPLL. The proposed solution is composed by the CPLL’s main and feedback loops, as well as a new compensation loop formed by a CP, an integrated capacitor and an OTA. This compensation loop measures the phase error between the input and feedback signals of the PLL, which is proportional to the value of the leakage currents in the main loop. Next, from the phase error it produces a current that equals the leakage currents, then being injected in the loop filter to reestablish its charge. The new system works with external or integrated loop filter CPLL’s topologies, decreasing its output RMS jitter up to 50 times, when compensating the effects of the leakage currents with a value up to 2,5µA. The proposed system occupies a die area of only 20% more than the original system, when using an external loop filter.
Learning to Rank under Evolving Consumer Reviews

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Mitigation of Unintended Biases against Non-Native English Texts in Sentiment Analysis

Currently the demand for text analytics grows due to the fact that textual data is being created online in large amounts. A number of tools are available for various tasks related to natural language processing such as sentiment analysis and text pre-processing. The majority of these tools are trained using unrepresentative data, which may lead to unintended biases altering the results. Previous research indicates that sentiment analysis tools show gender and race biases, and word embed-dings discriminate against women. This research investigates previously undeﬁned non-native speaker bias in sentiment analysis, i.e. unintended discrimination against English texts written by non-native speakers of English. Non-native speakers of English tend to use cognates, English words that have origin in the speaker’s language. To measure the non-native speaker bias in 4 lexicon-based sentiment analysis systems, a new Cognate Equity Evaluation Corpus was created, based on previous work in the literature for measuring racial and gender biases. The tools gave signiﬁcantly diﬀerent scores to English texts with features of non-native speakers. The bias discovered in lexicon-based tools was mitigated by updating 4 lexicons for English cognates in 3 languages. This paper proposes a generalisable framework for measuring and mitigating non-native speaker bias.
ePaga – Electronic Payment System

The possibility of using mobile devices for payments promises greater speed, convenience and ubiquity when compared with current payment methods. Hence the large potential demonstrated by the mobile payments market. However, the lack of interoperability between payment systems, along with the absence of suitable technologies, has delayed the progress in the field of mobile payments. This project’s goal is to develop a support system for electronic payments, with a special focus on mobile payments, which takes advantage of multiple payment protocols installed on the same device. The application derived by this multiprotocol support achieves higher universality, efficiency and interoperability, when compared to a single protocol application. The proposed system is based on NFC (Near Field Communication) technology. This document also describes the prototype developed with the purpose of demonstrating the system’s behavior, as well as its evaluation.
Significant others, patient outcomes and maintenance of symptoms in chronic fatigue syndrome

15 Declaration . 16 Alternative thesis format . 16 Copyright. 17 Acknowledgements . 18 Context . 19 Chapter 1: Literature Review . 22 1.1 Overview . 22 1.2 Chronic Fatigue Syndrome (CFS/ME). 22 1.3 Theoretical models of chronic fatigue syndrome.23 1.3.1 Cogntive Behavioural models.23 1.4 The Rationale for Examining Significant Other Factors in CFS/ME . 25 1.5 Patient outcomes in association with Significant Other responses to CFS/ME: A systematic review of the literature . 27 1.5. 1 Abstract . 29 1.5. 2 Background . 30 1.5. 2.1 Aims . 32 1.5. 3 Method . 33 1.5. 3.1 Search Procedure . 33
MD-assisted refinement of X-ray coordinates

We have developed a software solution to refine crystallographic protein structures using experimental diffraction data in conjunction with state-of-the-art MD modeling setup. For this purpose, a special module to calculate structure factors has been implemented within AMBER16 [1] biomolecular simulations package. The refinement is conducted in a form of a short MD simulation that models the entire unit crystal cell complete with interstitial solvent. The structure-factor-based restraints are imposed in a form of maximum likelihood potential [2], which is balanced against the regular force-field potential. To evaluate the performance of the new refinement protocol, we tested it on a set of 84 protein structures. As a first step, we conducted the refinement of relatively poor initial structural models (average deviation from the target 0.75 Å). It has been found that in 83% of the cases our protocol outperformed the refinement procedures available in Phenix [3] as judged by the lower resultant R free factors. Furthermore, our protocol consistently led to better geometries, as indicated by superior MolProbity scores [4]. As a second step, we refined the coordinates that are deposited in the PDB databank. We found that in 38% of the cases our protocol achieved improvements over both the original PDB depositions and the re-refined variants thereof obtained by Phenix. Of note, the results from Phenix equipped with the advanced Amber ff14SB force field [5] have also been included in this comparison. The approach to structure refinement demonstrated in our work has a number of broad advantages. It explicitly models protein-protein interactions in the crystal, as well as protein-water interactions. It also offers a natural way to represent the protein conformational dynamics: multiple protein molecules in the simulated crystal cell (or block of
Language teachers’ and learners’ beliefs about learner autonomy in a secondary school context: A mixed method study

Justifications for promoting learner autonomy are manifold, as it is agreed that learner involvement in decision making concerning the learning process increases motivation and develops students’ critical self-awareness (Benson, 2103). As teachers have a central role in developing learner autonomy by creating a supportive classroom learning environment and given the influence teachers’ beliefs have on their practices (Borg, 2006), it is essential to gain insight into their views regarding learner autonomy (Borg, & Al-Busaidi, 2012). Similarly, learners’ perceptions concerning language learning influence their openness to the ideas presented in the language classroom, especially when these ideas are not in line with learners’ previous experiences (Cotteral, 1995).